A Comparative Study of the Binding Constants of Several Polyphenols with BSA and LDL-VLDL through Fluorescence Quenching: A Potential Tool in the Fight against Atherosclerosis

A thesis presented to the faculty of the Chemistry Department of the University of Scranton as a prerequisite for the degree of Master of Arts in Biochemistry

By: Dana Poloni

Date: June 9, 2015

Table of Contents

Table of Contents………………………………………………………………………...III

List of Figures………………………………………………………………………….VIII

List of Tables………………………………………………………………………...... X

Acknowledgements………………………………………………………………………XI

Abstract…………………………………………………………………………………XII

1.0 Introduction……………………………………………………………………………1

1.1 Phenolic acids: Benzoic Acids and their Derivatives…………………………5

1.2 Phenolic acids: Phenylacetic Acids and their Derivatives…………………...12

1.3 Phenolic acids: Cinnamic Acids and their Derivatives………………………15

1.4 Stilbenoids: Stilbenes………………………………………………………...25

1.5 Flavonoids: Flavones………………………………………………………...28

1.6 Flavonoids: Isoflavones……………………………………………………...30

1.7 Flavonoids: Flavonols………………………………………………………..32

1.8 Flavonoids: Anthocyanidins…………………………………………………34

1.9 Thesis Overview……………………………………………………………..35

2.0 Materials and Methods……………………………………………………………….41

2.1 Reagents……………………………………………………………………...41

2.2 Polyphenols…………………………………………………………………..41

2.3 Materials……………………………………………………………………..42

2.4 PBS Solution Preparation……………………………………………………43

2.5 Polyphenol Standards Preparation…………………………………………...44

2.6 BSA Standard Preparation…………………………………………………...44

2.7 Isolation of Porcine Plasma………………………………………………….44

2.8 Storage of Porcine Plasma…………………………………………………...45

2.9 LDL-VLDL Extraction Method……………………………………………...45

2.10 Column Regeneration………………………………………………………47

2.11.0 Bradford Method – Preparation of Coomassie Reagent………………….47

2.11.1 Stock Reagent…………………………………………………………….47

2.11.2 Assay Reagent…………………………………………………………….48

2.12 Quantitative Determination of Protein in LDL-VLDL from Porcine Plasma via Bradford Method……………………………………………………..48

2.13 FT-IR Spectroscopy………………………………………………………...50

2.14.0 Fluorescence Quenching Method………………………………………...51

2.14.1 Instrumentation and Parameters…………………………………………..51

2.14.2 Procedure…………………………………………………………………51

2.15 Statistical Analysis………………………………………………………….52

3.0 Binding Constant Calculations………………………………………………………53

3.1 Overview……………………………………………………………………..53

3.2 Stern-Volmer Plots…………………………………………………………...56

3.3 Double-Logarithm Plots……………………………………………………...58

3.4 Quadratic Equation…………………………………………………………..59

3.5 Scatchard’s Treatment……………………………………………………….60

3.6 Benesi-Hildebrand’s Treatment……………………………………………...62

4.0 Results and Discussion………………………………………………………………64

4.1 Determination of LDL-VLDL Plasma Source……………………………….64

4.2.0 Incorporation of Polyphenol into BSA and LDL-VLDL…………………..66

4.2.1 Bimolecular Rate Constants (kqs)……...…………………………………..66

4.2.2 Incorporation of Polyphenol into Protein/Lipoprotein via FT-IR………….68

4.3 Binding Constants (Kas).………………………………………………..……69

4.4.0 Correlation between Calculated Binding Constants and Other Theoretical/Calculated Properties and Factors…………………………..80

4.4.1 Polar Surface Area…………………………………………………………81 4.4.2 n (Hill-affinity/binding sites) ……………………………………………...81

4.4.2.1 Outlier- n Value of Ellagic acid, and KDL-BSA, All Polyphenols and PAs……………………………………………………………………….82

4.4.2.2 Outlier- n Value of p-Hydroxyphenylacetic acid, and KDL-LDL-VLDL, All Polyphenols and PAs………………………………………………...82

4.4.3 Hydrogen Bond Acceptors/Donors………………………………………...83

4.4.4 Log P (Partition Coefficient) and Log D (Distribution Coefficient)………83

4.4.5 Log P (Partition Coefficient) and Log D (Distribution Coefficient) vs Log Ka……………………………………………………………………85

4.5.0 Comparison between the Calculated Binding Constants of both the Stern- Volmer and Double-Logarithm Method, for BSA and LDL-VLDL, and the Structural Characteristics of a Given Polyphenol……………………86

4.5.1.0 Comparison of the Stilbenes Resveratrol and Pterostilbene……………..87

4.5.1.1 Resveratrol and Pterostilbene with BSA…………………………………87

4.5.1.2 Resveratrol and Pterostilbene with LDL-VLDL…………………………88

4.5.2.0 Comparison of the Flavonols Quercetin, Quercetin-3-glucuronide, and Quercetin-3-glucoside……………………………………………………89

4.5.2.1 Quercetin, Quercetin-3-glucuronide, and Quercetin-3-glucoside with BSA………………………………………………………………………90

4.5.2.2 Quercetin, Quercetin-3-glucuronide, and Quercetin-3-glucoside with LDL-VLDL………………………………………………………………91

4.5.3.0 Comparison of the Flavones Flavone, Chrysin, Baicalein, and Baicalin…………………………………………………………………..92

4.5.3.1 Flavone, Chrysin, Baicalein, and Baicalin with BSA……………………93

4.5.3.2 Flavone, Chrysin, Baicalein, and Baicalin with LDL-VLDL……………94

4.5.4.0 Comparison of the Phenylacetic acid Derivatives Dopac, m- Hydroxyphenylacetic acid, p-Hydroxyphenylacetic acid, and Homogentisic acid……………………………………………………….95

4.5.4.1 Phenylacetic acid Derivatives Dopac, m- Hydroxyphenylacetic acid, p- Hydroxyphenylacetic acid, and Homogentisic acid with BSA…………..96

4.5.4.2 Phenylacetic acid Derivatives Dopac, m- Hydroxyphenylacetic acid, p- Hydroxyphenylacetic acid, and Homogentisic acid with LDL-VLDL…..97

4.5.5.0 Comparison of the Benzoic acid Derivatives Gallic acid, p- Hydroxysalicylic acid, Protocatechuic acid, m-Hydroxybenzoic acid, and p-Hydroxybenzoic acid…………………………………………………..98

4.5.5.1 Benzoic acid Derivatives Gallic acid, p-Hydroxysalicylic acid, Protocatechuic acid, m-Hydroxybenzoic acid, and p-Hydroxybenzoic acid with BSA……………………………………………………………99

4.5.5.2 Benzoic acid Derivatives Gallic acid, p-Hydroxysalicylic acid, Protocatechuic acid, m-Hydroxybenzoic acid, and p-Hydroxybenzoic acid with LDL-VLDL…………………………………………………..100

4.5.6.0 Comparison of the Benzoic acid Derivatives Gallic acid, Eudesmic acid, Syringic acid, Vanillic acid, and Apocynin…………………………….102

4.5.6.1 Benzoic acid Derivatives Gallic acid, Eudesmic acid, Syringic acid, Vanillic acid, and Apocynin with BSA…………………………………102

4.5.6.2 Benzoic acid Derivatives Gallic acid, Eudesmic acid, Syringic acid, Vanillic acid, and Apocynin with LDL-VLDL…………………………103

4.5.7.0 Comparison of the Cinnamic acid Derivatives Chlorogenic acid, Caffeic acid, Caffeic acid-3-o-glucuronide, and Caffeic acid-4-o- glucuronide…………………………………………………………..…105

4.5.7.1 Cinnamic acid Derivatives Chlorogenic acid, Caffeic acid, Caffeic acid-3- o-glucuronide, and Caffeic acid-4-o-glucuronide with BSA…………...105

4.5.7.2 Cinnamic acid Derivatives Chlorogenic acid, Caffeic acid, Caffeic acid-3- o-glucuronide, and Caffeic acid-4-o-glucuronide with LDL-VLDL…...106

4.5.8.0 Comparison of the Cinnamic acid Derivatives Caffeic acid, Dihydrocaffeic acid, Dihydrocaffeic acid-3-o-glucuronide, and Dihydrocaffeic acid-3-o-sulfate………………………………………...108

4.5.8.1 Cinnamic acid Derivatives Caffeic acid, Dihydrocaffeic acid, Dihydrocaffeic acid-3-o-glucuronide, and Dihydrocaffeic acid-3-o- sulfate with BSA………………………………………………………..108

4.5.8.2 Cinnamic acid Derivatives Caffeic acid, Dihydrocaffeic acid, Dihydrocaffeic acid-3-o-glucuronide, and Dihydrocaffeic acid-3-o- sulfate with LDL-VLDL………………………………………………..109

4.5.9.0 Comparison of the Cinnamic acid Derivatives Caffeic acid, Ferulic acid, Isoferulic acid, Isoferulic acid-3-o-glucuronide, and Dihydroferulic acid……………………………………………………………………...111

4.5.9.1 Cinnamic acid Derivatives Caffeic acid, Ferulic acid, Isoferulic acid, Isoferulic acid-3-o-glucuronide, and Dihydroferulic acid with BSA….111

4.5.9.2 Cinnamic acid Derivatives Caffeic acid, Ferulic acid, Isoferulic acid, Isoferulic acid-3-o-glucuronide, and Dihydroferulic acid with LDL- VLDL…………………………………………………………………...112

4.5.10.0 Comparison of the Cinnamic acid Derivatives o-Coumaric acid and p- Coumaric acid, the Benzoic acid Derivative p-Hydroxybenzoic acid, and the Phenylacetic acid derivative p-Hydroxyphenylacetic acid…………114

4.5.10.1 Cinnamic acid Derivatives o-Coumaric acid and p- Coumaric acid, the Benzoic acid Derivative p-Hydroxybenzoic acid, and the Phenylacetic acid derivative p-Hydroxyphenylacetic acid with BSA………………...114

4.5.10.2 Cinnamic acid Derivatives o-Coumaric acid and p- Coumaric acid, the Benzoic acid Derivative p-Hydroxybenzoic acid, and the Phenylacetic acid derivative p-Hydroxyphenylacetic acid with LDL-VLDL………...115

4.6 Conclusion………………………………………………………………….117

References………………………………………………………………………………123

Appendix A: Ka Statistics and Correlations between Methods………………………...129

Appendix B: Ka Correlations among Other Factors……………………………………138

Appendix C: Ka Plots of BSA…………………………………………………………..280

Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts…………361

List of Figures

Figure 1: Generic phenolic acid structures………………………..………………………5 Figure 2: Ellagic acid………………………………………………………………...……5 Figure 3: Eudesmic acid………………………………………………………...………...6 Figure 4: Syringic acid………………………………………………….………………...7 Figure 5: Gallic acid………………………………………………………………………8 Figure 6: Protocatechuic acid………………………………...…………………………...8 Figure 7: m-Hydroxybenzoic acid…………………………………………….…………..9 Figure 8: p-Hydroxybenzoic acid……………………………..…………………………10 Figure 9: p-Hydroxysalicylic…………………………………….………………………10 Figure 10: Apocynin………………………………………………..……………………11 Figure 11: Vanillic acid…………………………………….……………………………12 Figure 12: Dopac…………………………………………………………………………13 Figure 13: m-Hydroxyphenylacetic acid…………………………………………………13 Figure 14: p-Hydroxyphenylacetic acid…………………………….……………………14 Figure 15: Homogentisic acid……………………………………………………………15 Figure 16: Chlorogenic acid……………………………………………...………………16 Figure 17: Ferulic acid……………………………………………………...……………17 Figure 18: Isoferulic acid……………………………………………………...…………17 Figure 19: Isoferulic acid-3-o-glucuronide………………………………………………18 Figure 20: Dihydroferulic acid………………………………………………………...…19 Figure 21: Caffeic acid…………………………………………………………………...19 Figure 22: Caffeic acid-3-o-glucuronide…………...……………………………………20 Figure 23: Caffeic acid-4-o-glucuronide……………...…………………………………20 Figure 24: Dihydrocaffeic acid………………………..…………………………………21 Figure 25: Dihydrocaffeic acid-3-o-sulfate……………...………………………………22 Figure 26: Dihydrocaffeic acid-3-o-glucuronide…………...……………………………22 Figure 27: Sinapic acid………………………………………..…………………………23 Figure 28: o-Coumaric acid……………………………………...………………………23 Figure 29: p-Coumaric acid…………………………………………...…………………24 Figure 30: Generic stilbene structures…………………………………...………………25 Figure 31: Pterostilbene………………………………………………….………………26 Figure 32: Resveratrol……………………………………………………………………26 Figure 33: Generic flavonoid structures…………………………………………………27 Figure 34: Flavone………………………………………………………….……………28 Figure 35: Chrysin………………………………………………………….……………28 Figure 36: Baicalein…………………………………………………………...…………29 Figure 37: Baicalin…………………………………………………………….…………30 Figure 38: Biochanin A…………………………………………………………..………30 Figure 39: Puerarin………………………………………………………………………31 Figure 40: Quercetin……………………………………………………………..………32 Figure 41: Quercetin-3-glucuronide…………………………………………………..…33 Figure 42: Quercetin-3-glucoside……………………………………………………..…33 Figure 43: Pelargonidin chloride………………………………………………………...34

i

Figure 44: Stern-Volmer plots of apocynin and LDL-VLDL at various days after delivery and use………………………………………………………………….65 Figure 45: Amide I band of BSA and various polyphenols bound to BSA……………...68 Figure 46: Amide I band of LDL-VLDL and various polyphenols bound to LDL- VLDL…………………………………………………………………...... 68 Figure 47: Kas of Section 4.5.1.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………..88 Figure 48: Kas of Section 4.5.1.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods………………………………………………………………89 Figure 49: Kas of Section 4.5.2.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………..91 Figure 50: Kas of Section 4.5.2.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods………………………………………………………………92 Figure 51: Kas of Section 4.5.3.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………..94 Figure 52: Kas of Section 4.5.3.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods………………………………………………………………95 Figure 53: Kas of Section 4.5.4.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………..97 Figure 54: Kas of Section 4.5.4.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods………………………………………………………………98 Figure 55: Kas of Section 4.5.5.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………100 Figure 56: Kas of Section 4.5.5.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods……………………………………………………………..101 Figure 57: Kas of Section 4.5.6.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………103 Figure 58: Kas of Section 4.5.6.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods……………………………………………………………..104 Figure 59: Kas of Section 4.5.7.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………106 Figure 60: Kas of Section 4.5.7.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods……………………………………………………………..107 Figure 61: Kas of Section 4.5.8.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………109 Figure 62: Kas of Section 4.5.8.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods……………………………………………………………..110 Figure 63: Kas of Section 4.5.9.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………112 Figure 64: Kas of Section 4.5.9.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods……………………………………………………………..113 Figure 65: Kas of Section 4.5.10.1 with BSA via the Stern-Volmer and Double-Logarithm methods…………………………………………………………………………115 Figure 66: Kas of Section 4.5.10.2 with LDL-VLDL via the Stern-Volmer and Double- Logarithm methods……………………………………………………………..116

ii

List of Tables

Table 1: Bradford method protein stock concentrations preparation…………………….48 Table 2: Bimolecular rate constants of all polyphenols with BSA and LDL-VLDL via the Stern-Volmer method………………………………………………………...67 Table 3: Stern-Volmer method between Polyphenol and BSA………………………….70 Table 4: Stern-Volmer method between Polyphenol and LDL-VLDL………………….71 Table 5: Double-Logarithm method between Polyphenol and BSA…………………….72 Table 6: Double-Logarithm method between Polyphenol and LDL-VLDL…………….73 Table 7: Scatchard’s method between Polyphenol and BSA…………………………….74 Table 8: Scatchard’s method between Polyphenol and LDL-VLDL…………………….75 Table 9: Quadratic Equation between Polyphenol and BSA…………………………….76 Table 10: Quadratic Equation between Polyphenol and LDL-VLDL…………………...77 Table 11: Benesi-Hildebrand method between Polyphenol and BSA…………………...78 Table 12: Benesi-Hildebrand method between Polyphenol and LDL-VLDL…………...79 Table 13: Binding constant changes from resveratrol to pterostilbene…………………..89 Table 14: Binding constant changes from quercetin, to quercetin-3-glucuronide, to quercetin-3-glucoside…………………………………………………………….92 Table 15: Binding constant changes from flavone, to chrysin, to baicalein, to baicalin...95 Table 16: Binding constant changes from Dopac to m-hydroxyphenylacetic acid, to p- hydroxyphenylacetic acid, to homogentisic acid………………………………...98 Table 17: Binding constant changes from gallic acid, to p-hydrosalicylic acid, to protocatechuic acid, to m-hydroxybenzoic acid, to p-hydroxybenzoic acid……101 Table 18: Binding constant changes from gallic acid, to eudesmic acid, to syringic acid, to vanillic acid, to apocynin…………………………………………………….105 Table 19: Binding constant changes from chlorogenic acid, to caffeic acid, to caffeic acid-3-o-glucuronide, to caffeic acid-4-o-glucuronide…………………………107 Table 20: Binding constant changes from caffeic acid, to dihydrocaffeic acid, to dihydrocaffeic acid-3-o-glucuronide, to dihydrocaffeic acid-3-o-sulfate………110 Table 21: Binding constant changes from caffeic acid, to ferulic acid, to isoferulic acid, to isoferulic acid-3-o-glucuronide, to dihydroferulic acid………………………...113 Table 22: Binding constant changes from o-coumaric acid, to o-coumaric acid, to p- hydroxybenzoic acid, to p-hydroxyphenylacetic acid………………………….117

iii

Acknowledgements

First and most importantly, I would like to thank God. Without Him I would not be where I am today, and I pray I continue to honor and serve him through my future career as a physician.

I would like to express a sincere thank you to my thesis advisor Dr. Joe Vinson.

He has been a tremendous help over the last two years, and I honestly would be lost without him. I wish him the best in his retirement. I would also like to thank Dr. Timothy

Foley and Dr. David Rusak for being on my thesis committee, and for helping to develop my strong interest in biochemistry and analytical chemistry.

I would also like to express my sincere appreciation and gratefulness to my family, particularly my mother Maria, and my father David, for the love, support, and most importantly the patience they have provided me with over these last several years at the University of Scranton. Without them, none of this would have been possible.

Additionally, I am truly grateful to Mrs. Karen Caparo and Mr. Richard Trygar for the help and knowledge they have given me since my start here as a graduate student.

I would also like to thank Dr. Christopher Bauman, Dr. David Marx, and Dr. Art Catino for all that I have learned from them. I am also very grateful to Matt Baer for his advice throughout.

Finally, I would like to thank my amazing girlfriend Rachel. For her constant patience and support over the last three years, I am forever grateful. We did it Rach, now off to Philly!

iv

Abstract

Atherosclerosis is one of the most prevalent diseases in the United States today.

Every year hundreds of thousands of people afflicted by this disease suffer major life- threatening events such as heart attacks and stroke and as a result, many perish. Often times caused by oxidized LDL-VLDL, there is not a lot many people can do to safeguard against this horrible affliction once it has progressed past a certain point without the use of major invasive surgeries. Once foam cell generation becomes prominent in arteries

(the plaque build-up associated with atherosclerosis and its related diseases), life expectancy drops dramatically. Conventional research provides increasing evidence that the best way to combat this disease is through preventative measures.

One important way to help combat atherosclerosis is through a diet rich in antioxidants. This study utilized polyphenols, which have been shown in many studies to exhibit strong antioxidative properties by means of free radical scavenging. In this study, the binding constants of forty different polyphenols with both BSA and LDL-VLDL were measured using the fluorescence quenching method. Through several different methods, static quenching was the mechanism determined to be at play. Calculations were made using the Stern-Volmer, Double-Logarithm, Quadratic Equation, Scatchard’s, and

Benesi-Hildebrand methods. Correlations and comparisons were made among and between the binding constants of these forty polyphenols, and both BSA and LDL-

VLDL, using the Stern-Volmer and Double-Logarithm methods.

Glycosidic metabolites exhibited a lower binding affinity for both BSA and LDL-

VLDL when compared against their parent compounds. The position of a glycoside on a phenolic acid proved to affect its binding capability as well. Hydrogenated cinnamic acid

v

derivatives experienced a decrease in binding also, when paralleled with the binding constant values of their parent cinnamic acid. Additionally, there appears to be an order to which hydroxyl groups either contribute, or detract from the degree of binding with both BSA and LDL-VLDL. Compounds with para hydroxyl groups exhibited lower binding affinities than those polyphenols containing meta hydroxyl groups. Similarly, phenolic acids with ortho hydroxyl groups also appeared to have higher binding constant values then those that contained para hydroxyl groups. Mixed results were obtained with methylated hydroxyl function groups. In larger molecular weight polyphenols (non- phenolic acids) methoxy groups contributed to a higher degree of binding than those without. In the lower molecular weight polyphenols, instances of increased and decreased binding constants were both observed.

This research performed in vitro may provide a basis on the strength of binding affinities for several polyphenols and transport proteins in vivo, as well as potential orders and explanations as to why protein/lipoprotein-polyphenol complexes are formed the way they are. Given the aforementioned information, if polyphenols retain their radical scavenging ability upon binding to BSA, and especially LDL-VLDL, then they may prove as an invaluable tool in our nation’s fight against atherosclerosis.

vi

1.0 Introduction

Today’s society continues to place an increasingly large emphasis on health through diet and nutrition. From a medical view, what one consumes from diet may directly impact one’s health and performance. Many common afflictions and disorders are linked to diet including atherosclerosis, cardiovascular disease, diabetes, rheumatoid arthritis, and multiple types of cancers. Contemporary research continues to provide an increasing amount of evidence that a diet rich in plant sources exhibits a strong correlation with long-term health, and may lead to a reduced risk of some types of disease.

From a biochemical standpoint, many of these disorders that afflict society today result from damage to the cell brought about by some form of oxidative stress. Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are two of the major contributors to oxidative damage in cells. In low to moderate concentrations, they provide a beneficial role in cellular metabolism, however in higher concentrations they produce oxidative stress, which if left unchecked will damage cellular structures and function.[1]

ROS and RNS usually tend to be free radicals, which can be defined as a molecule or molecular fragment which contains at least one unpaired electron in its outer orbit.

.- . . Common examples of ROS include superoxide (O2 ), hydroxyl ( OH), peroxyl (ROO ), lipid peroxyl (LOO.), and alkoxyl (RO.) radicals. Similarly, common examples of RNS

. . include nitric oxide (NO ) and nitrogen oxide (NO2 ) radicals. Albeit, ROS and RNS are not solely defined as radicals, since many of these radicals can be readily converted into non-radical species, and still pose a detrimental effect on health. Some examples of ROS

1

and RNS non-radical species include hydrogen peroxide (H2O2) and nitrous acid (HNO2), respectively.[2]

One of the most effective types of therapeutic response employed by humans to counteract oxidative damage in cells is through the utilization of an antioxidant.

Antioxidants can be defined as the substances, which at low concentrations significantly inhibit or delay the oxidative process. They are extremely effective in counteracting and preventing oxidative stress in cells because they act as free radical scavengers, reducing

ROS and RNS in cells while simultaneously becoming oxidized themselves.[3] To achieve this type of redox balance, humans utilize endogenous and exogenous antioxidants. Some types of endogenous antioxidants include Glutathione, Alpha-lipoic acid, Coenzyme Q,

Bilirubin, and L-carnitine. Exogenous antioxidants are generally collected by humans through diet, especially through a diet rich in plant sources and include Vitamin C,

Vitamin E, carotenoids, and polyphenols.

One of the major diseases that humans are struggling to combat daily is atherosclerosis. Atherosclerosis is a specific form of arteriosclerosis, and results from a thickening and loss of elasticity in the arteriole walls due to the buildup of plaque. This plaque buildup and loss of elasticity limits oxygenated blood flow to the heart and other parts of the body. There are multiple types of atherosclerosis, including coronary heart disease, carotid artery disease, peripheral arterial disease, and chronic kidney disease.

According to the National Heart, Lung, and Blood Institute under the National Institute of

Health for the U.S. Department of Health and Human Services, coronary heart disease is the number one killer of both men and women in the United States.[4] Atherosclerosis can become deadly if arteriole plaque buildup is left unchecked, leading to serious

2

consequences like heart attack and stroke. The plaque buildup process starts with oxidized lipoproteins, especially those in lower density like LDL (low-density lipoprotein) and VLDL (very-low-density lipoprotein). When these lipoproteins become oxidized, they cross the damaged endothelium, causing white blood cells to move in and attempt to digest these low-density lipoproteins. Here, white blood cells are capable of digesting some, but not all of the oxidized lipoproteins. Over the course of years, the accumulation of oxidized lower density lipoproteins results in the buildup of plaque.

Pharmacological treatments such as statins provide one way to combat atherosclerosis, however they are only effective in treating about one third of cardio vascular disease cases, doing so through lowering LDL expression levels.[5,6] Therefore, alternative therapeutics are required to more efficiently limit the effects of the disease.

One of the main ideas behind combating atherosclerosis is to prevent lipoproteins from becoming oxidized. Many endogenous antioxidants, such as vitamin E (α-tocopherol) and tripeptide GSH (L-γ-glutamylcysteinyl-glycine) already achieve this goal in a healthy human subject by acting as free-radical scavengers. The main objective of these antioxidants is to protect membranous lipid material against free-radical-initiated peroxidation reactions.[2] However, in a subject who does not partake in an ideal diet, a certain amount of exogenous antioxidant supplementation may be required to achieve the same outcome. Enter the polyphenol.

Polyphenols are a class of secondary plant metabolites, and generally arise from a common origin: the amino acids phenylalanine and tyrosine. These compounds are formed by plants in situ to protect against photosynthetic stress, viruses, microbes, predators, anthropogenic pressures, and interspecific competition.[7,8,9] These phenolic

3

metabolites can range from simple phenolic molecules with relatively low molecular weights to highly polymerized compounds that have molecular weights of more than 4 kDa. Each polyphenol has at least one phenol unit or building block, which is composed of a six-member hydrocarbon/aromatic ring, and many times, at least one hydroxyl group.

It is no secret that polyphenols provide one of the largest sources of exogenous antioxidants in the human diet. They are of particular interest mainly because of their radical scavenging abilities, which is a result of their molecular structures. The ability to act as efficient radical scavengers allow polyphenols to deliver many beneficial effects to humans such as antiallergenic, antimicrobial, anti-inflamatory, antiviral, and anticarcinogenic actions, all largely due to their antioxidative properties.[10] Applications of substances containing polyphenols are widely used in medicine and the health industry today. They can protect the skin from damage brought about by UV exposure and when consumed, they can help the intestines with the absorption of minerals. Polyphenolic compounds have even been shown to play an auxiliary role in the fight against HIV-1 and several neurological disorders. It would seem that the application of these secondary metabolites is nearly limitless![11] For the purpose of this study, polyphenols can be classified into 3 different classes: Phenolic acids, stilbenes, and flavonoids.

The first major class of polyphenols is the phenolic acid class. Phenolic acids consist of a wide variety of compounds. Many of these compounds exist in their esterified form, and only upon metabolism, is the ester bond cleaved through hydrolysis, and a carboxylic acid functional group is gained. Through biotransformation, other functional groups may be added to phenolic acids, including glycoside, sulfate, methoxy,

4

and hydroxyl groups (for phenolic acids, some research suggests that glucuronidation and glycosylation are favored by intestinal cells, whereas sulfation is favored by liver cells).[12} For the purpose of this study, three different phenolic acid subclasses were examined: Benzoic acid derivatives, cinnamic acid derivatives, and phenylacetic acid derivatives.

a) b) c)

Figure 1: Generic phenolic acid structures of a) Benzoic acids, b) Phenylacetic acids, and c) Cinnamic acids, where R can be a hydrogen, hydroxyl, methoxy, glycoside, or sulfate group.

1.1 Phenolic Acids: Benzoic Acids and their Derivatives

Benzoic acid derivatives consist of a phenolic ring and a carboxylic acid (C6-C1) configuration, and appear to be the simplest type of subclass for phenolic acids. The first benzoic acid mentioned in this study is ellagic acid.

Figure 2: Ellagic acid (2,3,7,8-Tetrahydroxychromeno[5,4,3-cde]chromene-5,10-dione)

5

Ellagic acid (2,3,7,8-Tetrahydroxychromeno[5,4,3-cde]chromene-5,10-dione) is a fused four-ringed polyphenol. In the plant, ellagic acid is produced through the hydrolysis of the tannins ellagitanin and geraniin to aide in protection against microbes.[13] Several in vitro and small animal studies have shown ellagic acid to exhibit strong antiproliferative and antioxidative properties. The antiproliferative properties of ellagic acid arise from the effect it has on the inhibition of the cancer cells’ role in the destruction of the p53 gene, (most likely through inhibition of DNA binding to specific carcinogens like nitrosamines).[14] It has also been shown to enhance the ability of detoxification of certain reactive intermediates in target cells through increasing hepatic phase II enzyme activities, while simultaneously decreasing total hepatic mucosal cytochromes.[15,16] The antioxidative properties of ellagic acid arise from its ability to act as a chemoprotective agent in cellular models through efficient radical scavenging.[17]

Sources of ellagic acid in human diet include red berries like strawberries, raspberries, blackberries, and cranberries, nuts like pecans and walnuts, pomegranate fruit, and beefsteak fungus (ox tongue mushroom).

Figure 3: Eudesmic acid (3,4,5-Trimethoxybenzoic acid)

6

Eudesmic acid (3,4,5-Trimethoxybenzoic acid) is a benzoic acid with three methoxy groups found on the para and both meta positions. Eudesmic acid can act as an intracellular calcium chelator, and in one study, along with N-acetyl-Leu-Leu- norleucinal, inhibited NF-κB (a protein complex responsible for DNA transcription that is involved in cellular responses to ROS/RNS, oxidized LDL, UV radiation, and stress) activation.[18] Eudesmic acid can be found in Eucalyptus.

Figure 4: Syringic acid (4-Hydroxy-3,5-dimethoxybenzoic acid)

Syringic acid (4-Hydroxy-3,5-dimethoxybenzoic acid) is a benzoic acid with a hydroxyl group located on the para position, along with two meta methoxy groups. This phenolic acid possesses strong anticarcinogenic properties through derived proteasome inhibitory activity reported by Orabi et al, specifically, in regards to its anti-mitogenic effect against human malignant melanoma cell lines HTB66 and HTB68 along with an observed minimal level of cytotoxicity on colorectal and breast cancer cells, and normal human fibroblast cells.[19] This polyphenol has also exhibited hepaprotective and antihyperlipidemic activities.[20] Syringic acid can be found in low concentrations in beer, wine, and spirits, moderate concentrations in grains and their by-products, higher

7

concentrations in dates, sage, and thyme, and very high concentrations in black olives and nuts.

Figure 5: Gallic acid (3,4,5-Trihydroxybenzoic acid)

Gallic acid (3,4,5-Trihydroxybenzoic acid) is a benzoic acid with three hydroxyl groups found on the para and both meta positions. This phenolic acid possesses antifungal and anti-viral capabilities, and also acts as an antioxidant, along with proving to be a weak carbonic anhydrase inhibitor.[21] In several studies, gallic acid has shown to inhibit the main suspect in Alzheimer’s and Parkinson’s disease, amyloid fibril formation.[22,23,24] Sources of gallic acid in the human diet can be located in blackberries, raspberries, grape seeds, and white tea.

Figure 6: Protocatechuic acid (3,4-Dihydroxybenzoic acid)

8

Protocatechuic acid (3,4-Dihydroxybenzoic acid) is a benzoic acid that has two hydroxyl groups, one para, and the other meta. Protocatechuic acid imparts various pharmacological activities due not only to its antioxidative properties, but also through other possible enzymatic interactions and anti-inflammatory mechanisms.[25] In addition to its antioxidative and anti-inflammatory properties, this phenolic compound has shown to exhibit anticarcinogenic effects through the destruction of leukemia cells and malignant HSG1 cells via apoptosis.[26] Protocatechuic acid can be found in in acai fruit, roselle, and several species of mushrooms including Agaricus bisporus and Phellinus linteus. It is also a major microbial metabolite of anthocyanidins during digestion.

Figure 7: m-Hydroxybenzoic acid (3-Hydroxybenzoic acid)

m-Hydroxybenzoic acid (3-Hydroxybenzoic acid) is a benzoic acid containing one hydroxyl group on the meta position of the phenyl ring. m-Hydroxybenzoic acid acts as an antioxidant, possessing moderate radical scavenging ability, but it is of more interest in its ability to modify cellular signaling processes. One such process is its ability to activate the Nrf2 pathway, which in turn up-regulates endogenous antioxidant mechanisms.[27] m-Hydroxybenzoic acid can be found in grapefruit, olive oil, and medlar fruit (Mespilus germanica).

9

Figure 8: p-Hydroxybenzoic acid (4-Hydroxybenzoic acid)

p-Hydroxybenzoic acid (4-Hydroxybenzoic acid) is a benzoic acid which has one hydroxyl group in the para position of the phenyl ring. p-Hydroxybenzoic acid possesses similar antioxidant properties, and is also capable of modifying cellular signaling processes via the Nrf2 pathway.[27] p-Hydroxybenzoic acid can be found in tea, wine, vanilla, and the green-cracking mushroom (Russula virescens).

Figure 9: p-Hydroxysalicylic acid (2,4-Dihydroxybenzoic acid)

p-Hydroxysalicylic acid (2,4-Dihydroxybenzoic acid) is a benzoic acid that contains two hydroxyl groups on the phenyl ring; one on the ortho position, the other on the para position. In addition to its antioxidant qualities, p-Hydroxysalicylic acid has shown to improve quinine anti-malarial activity in at least one study.[28] Sources of p-

10

Hydroxysalicylic in the human diet include cranberries, olives, and olive oil.

Figure 10: Apocynin (1-(4-Hydroxy-3-methoxyphenyl)ethanone)

Apocynin (1-(4-Hydroxy-3-methoxyphenyl)ethanone) is a benzoic acid derivative. It has one methoxy group on the meta position of the phenyl ring, and one hydroxyl group para on the phenyl ring. In place of the carboxylic acid functional group, there is an ethanone group. Apocynin possesses strong antioxidant characteristics. In the past, it was thought that apocynin had the ability to prevent O2 from being oxidized to the

-. [29] superoxide radical (O2 ) by inhibiting NADPH oxidase activity. However, current research shows that this is not the case. Apocynin may inhibit some NADPH oxidase activity in leukocytes, but in vascular cells, it acts as a an antioxidant by preventing hydrogen peroxide from activating redox-sensitive kinases like the p38-mitogen-activate protein kinase, protein kinase B (Akt) and extracellular signal-regulated kinase ½ (ERK

½).[30] Apocynin can be found in Canadian hemp (Apocynum cannabinum) and many

Chinese medicinal herbs including Picrorhiza kurroa.

11

Figure 11: Vanillic acid (4-Hydroxy-3-methoxybenzoic acid)

Vanillic acid (4-Hydroxy-3-methoxybenzoic acid) is a benzoic acid and oxidized form of vanillin. This phenolic acid contains one methoxy group on the meta position of the phenyl ring, and one hydroxyl group on the para position. Vanillic acid is an antioxidant that is shown to have beneficial effects on people afflicted by ulcerative colitis, particularly via suppressing both the expression of cyclooxygenase-2 and the activation of NF-κB.[31] Vanillic acid can be found in wine, vinegar, and many Chinese medicinal herbs including Angelica sinensis.

1.2 Phenolic Acids: Phenylacetic Acids and their Derivatives

Phenylacetic acid derivatives are the second subclass of phenolic acids observed, and consist of a phenolic ring and a carboxylic acid (C6-C2) configuration. They vary from benzoic acid derivatives by only one extra carbon in the parent chain linking the carboxylic acid functional group to the phenolic ring. This subclass of phenolic acids can be found in plants, with the highest concentration being in found in the fruits of plants.

Plants use these polyphenols as hormones, and also benefit from their antimicrobial properties.

12

Figure 12: Dopac (2-(3,4-Dihydroxyphenyl)acetic acid)

Dopac (2-(3,4-Dihydroxyphenyl)acetic acid) is a phenylacetic acid with two hydroxyl groups; one para, the other meta on the phenyl ring. In addition to Dopac acting as a strong antioxidant [32], it is used in the treatment of certain neurodegenerative disorders like Parkinson’s disease. Because Dopac is a metabolite of the neurotransmitter dopamine, it is given to those afflicted by Parkinson’s disease in order to shift the equilibrium of the DOPA-Dopac reaction, ensuring more DOPA is converted to dopamine, and less DOPA is metabolized by monoamine oxidases (MAOs). Dopac can be found in the bark of Eucalyptus globulus.

Figure 13: m-Hydroxyphenylacetic acid ((3-Hydroxyphenyl)acetic acid)

13

m-Hydroxyphenylacetic acid ((3-Hydroxyphenyl)acetic acid) is a phenylacetic acid with one hydroxyl group on the meta position of the phenyl ring. It has moderate antioxidant capabilities and is believed to assist in preventing oxidative stress in inner tissues.[33] Sources of m-hydroxyphenylacetic acid in the human diet include black tea, almond skin extracts, cocoa powder, and red wine.

Figure 14: p-Hydroxyphenylacetic acid ((4-Hydroxyphenyl)acetic acid)

p-Hydroxyphenylacetic acid ((4-Hydroxyphenyl)acetic acid) is a phenyl acetic acid with one hydroxyl group on the para position of the phenyl ring. This phenolic acid has moderate antioxidant capabilities, and in one study, it was shown that p- hydroxyphenylacetic acid prevents nitration at acidic cites in the oral cavity where hydrogen peroxide (H2O2) is produced. p-Hydroxyphenylacetic acid can be found in beer.

14

Figure 15: Homogentisic acid (2-(2,5-Dihydroxyphenyl)acetic acid)

Homogentisic acid (2-(2,5-Dihydroxyphenyl)acetic acid) is a phenylacetic acid containing two hydroxyl groups; one on the ortho position, the other on the meta position.

This phenolic acid exhibits strong antioxidant and antiradical activity; homogentisic acid has the ability to protect against thermal-cholesterol degradation, as well as preserve liposomes and LDL from induced oxidative stress brought about by Cu2+.[34]

Homogentisic acid can be found in raisins and strawberry-tree honey.

1.3 Phenolic Acids: Cinnamic Acids and their Derivatives

Finally, the last subclass of phenolic acids is the cinnamic acids. Cinnamic acids consist of a phenolic ring and a carboxylic acid (C6-C3) configuration. Because cinnamic acids have one more carbon in their parent chain than phenylacetic acids, cinnamic acids have the ability to form a double bond entity between C2-C3. This further increases their aromaticity and ability to conjugate, allowing for increased compound stability and the formation of a planar molecule. Through metabolism, some cinnamic acid derivatives undergo hydrogenation at the C2-C3 double bond to produce other, less conjugated and non-planar cinnamic acid derivatives.

15

Figure 16: Chlorogenic acid ((1S,3R,4R,5R)-3-{[(2E)-3-(3,4-Dihydroxyphenyl)prop-2-enoyl]oxy}-1,4,5- trihydroxycyclohexane-1-carboxylic acid)

The first cinnamic acid is chlorogenic acid. Chlorogenic acid ((1S,3R,4R,5R)-3-

{[(2E)-3-(3,4-Dihydroxyphenyl)prop-2-enoyl]oxy}-1,4,5-trihydroxycyclohexane-1- carboxylic acid) is the ester of caffeic acid and (-)-quinic acid. The quinic acid entity is a cyclohexanecarboxylic acid, containing four hydroxyl groups located at the 1, 4, and 5 positions on the cyclohexane ring, and is esterified to the caffeic acid at the 3-position on the cyclohexane ring. The caffeic acid entity contains two hydroxyl groups; one located meta, and the other para on the phenyl ring. The caffeic acid parent chain also contains a

C2-C3 double bond. Chlorogenic acid is a strong antioxidant. This compound has been shown to have a protective effect in neuroinflammatory conditions pertaining to dopaminergic neurons [35], as well as having the ability to slow the release of glucose into the bloodstream following a meal.[36] Chlorogenic acid can be found in peaches and prunes, coffee, and is commonly used as a food additive in chewing gum, coffee products, and breath mints.

16

Figure 17: Ferulic acid ((2E)-3-(4-Hydroxy-3-methoxyphenyl)prop-2-enoic acid)

Ferulic acid ((2E)-3-(4-Hydroxy-3-methoxyphenyl)prop-2-enoic acid) is a cinnamic acid with one methoxy group on the meta position of the phenyl ring, and one hydroxyl on the para position. Several reports show that ferulic acid is a powerful antioxidant, and displays direct antitumor activity against liver [37] and breast cancer.[38]

Sources of ferulic acid in the human diet include apples, artichokes, coffee, oranges, peanuts, and from the hydrolysis of fiber in grains which occurs during digestion.

Figure 18: Isoferulic acid ((2E)-3-(3-Hydroxy-4-methoxyphenyl)prop-2-enoic acid)

Isoferulic acid ((2E)-3-(3-Hydroxy-4-methoxyphenyl)prop-2-enoic acid) is a cinnamic acid with one hydroxyl group on the meta position of the phenyl ring, and one methoxy group on the para position. Isoferulic acid (IFA) has been shown to not only

17

prevent protein oxidation in bovine serum albumin (BSA), but also it has demonstrated the ability to suppress the formation of β-cross amyloid structures of BSA.[39] IFA is a potent inhibitor of interleukin-8, which is a protein that is produced as an inflammatory response designed to serve as a chemoattractant for neutrophils.[40] This polyphenol can be found in coffee, turmeric (Curcuma longa) and black cohosh (Actaea racemosa), a flowering plant used by Native American Indians for medicinal purposes.

Figure 19: Isoferulic acid-3-o-glucuronide ((2S,3S,4S,5R,6S)-6-{5-[(1E)-2-Carboxyeth-1-en-1-yl]-2- methoxyphenoxy}-3,4,5-trihydroxyoxane-2-carboxylic acid)

Isoferulic acid-3-o-glucuronide ((2S,3S,4S,5R,6S)-6-{5-[(1E)-2-Carboxyeth-1- en-1-yl]-2-methoxyphenoxy}-3,4,5-trihydroxyoxane-2-carboxylic acid) is a cinnamic acid derivative and glucuronidated metabolite of isoferulic acid. This compound has one methoxy group on the para position of the phenyl ring, and a glucuronic acid linked to the phenyl ring via a glycosidic bond at the meta position (in place of the meta hydroxyl group in IFA).

18

Figure 20: Dihydroferulic acid (3-(4-Hydroxy-3-methoxyphenyl)propanoic acid)

Dihydroferulic acid (3-(4-Hydroxy-3-methoxyphenyl)propanoic acid) is a cinnamic acid derivative and metabolite of ferulic acid. It has the same structure as ferulic acid, with the exception of the C2-C3 double bond. Aside from its antioxidant properties, this phenolic acid exhibits antifungal properties as well.[41] Dihydroferulic acid can be found in coffee.

Figure 21: Caffeic acid ((2Z)-3-(3,4-Dihydroxyphenyl)prop-2-enoic acid)

Caffeic acid ((2Z)-3-(3,4-Dihydroxyphenyl)prop-2-enoic acid) is a cinnamic acid containing two hydroxyl groups, one on a meta position and the other on the para position of the phenyl ring. This cinnamic acid is a powerful antioxidant [42], and because it exhibits strong antifungal [43] and anticarcinogenic properties [44], it has a variety of

19

potential pharmacological uses. Caffeic acid (CA) is found in coffee, argan oil, nuts, and barley.

Figure 22: Caffeic acid-3-o-glucuronide ((2S,3S,4S,5R,6S)-6-{5-[(1E)-2-Carboxyeth-1-en-1-yl]-2-hydroxyphenoxy}- 3,4,5-trihydroxyoxane-2-carboxylic acid)

Caffeic acid-3-o-glucuronide ((2S,3S,4S,5R,6S)-6-{5-[(1E)-2-Carboxyeth-1-en-1- yl]-2-hydroxyphenoxy}-3,4,5-trihydroxyoxane-2-carboxylic acid) is a cinnamic acid derivative and glucuronidated metabolite of caffeic acid. This compound has one hydroxyl group on the para position of the phenyl ring, and a glucuronic acid linked to the phenyl ring via a glycosidic bond at the meta position (in place of the meta hydroxyl group of CA).

Figure 23: Caffeic acid-4-o-glucuronide ((2S,3S,4S,5R,6S)-6-{4-[(1E)-2-Carboxyeth-1-en-1-yl]-2-hydroxyphenoxy}- 3,4,5-trihydroxyoxane-2-carboxylic acid)

20

Caffeic acid-4-o-glucuronide ((2S,3S,4S,5R,6S)-6-{4-[(1E)-2-Carboxyeth-1-en-1- yl]-2-hydroxyphenoxy}-3,4,5-trihydroxyoxane-2-carboxylic acid) is a cinnamic acid derivative and glucuronidated metabolite of caffeic acid. This compound has one hydroxyl group on the meta position of the phenyl ring, and a glucuronic acid linked to the phenyl ring via a glycosidic bond at the para position (in place of the para hydroxyl group in CA).

Figure 24: Dihydrocaffeic acid (3-(3,4-Dihydroxyphenyl)propanoic acid)

Dihydrocaffeic acid (3-(3,4-Dihydroxyphenyl)propanoic acid) is a cinnamic acid derivative and metabolite of CA. It is structurally identical to CA, with the exception that it lacks a C2-C3 double bond. One study lends support to the antioxidant power of the lipophilized metabolites of this polyphenol, and shows more antioxidant potential (to a cutoff number in the alkyl chain) than when compared to un-lipophilized forms of this cinnamic acid derivative.[45] The main source of dihydrocaffeic acid in the human diet is coffee.

21

Figure 25: Dihydrocaffeic acid-3-o-sulfate (3-[4-hydroxy-3-(sulfooxy)phenyl]propanoic acid)

Dihydrocaffeic acid-3-o-sulfate (3-[4-hydroxy-3-(sulfooxy)phenyl]propanoic acid) is a cinnamic acid derivative and metabolite of dihydrocaffeic acid. It is structurally identical to dihydrocaffeic acid, with the exception that it holds a sulfate group on the phenyl ring in place of the meta hydroxyl group.

Figure 26: Dihydrocaffeic acid-3-o-glucuronide ((2S,3S,4S,5R,6S)-6-[5-(2-Carboxyethyl)-2-hydroxyphenoxy]-3,4,5- trihydroxyoxane-2-carboxylic acid)

Dihydrocaffeic acid-3-o-glucuronide ((2S,3S,4S,5R,6S)-6-[5-(2-Carboxyethyl)-2- hydroxyphenoxy]-3,4,5-trihydroxyoxane-2-carboxylic acid) is a cinnamic acid derivative and glucuronidated metabolite of dihydrocaffeic acid. This compound has one hydroxyl group on the para position of the phenyl ring, and a glucuronic acid linked to the phenyl

22

ring via a glycosidic bond at the meta position (in place of the meta hydroxyl group in the non-glucuronidated form).

Figure 27: Sinapic acid ((2E)-3-(4-Hydroxy-3,5-dimethoxyphenyl)prop-2-enoic acid)

Sinapic acid ((2E)-3-(4-Hydroxy-3,5-dimethoxyphenyl)prop-2-enoic acid) is a cinnamic acid with one para hydroxyl group, and two meta methoxy groups. Sinapic acid exhibits moderate antioxidant activity. It is exceptionally effective in scavenging and reducing hydroxyl radicals, and sinapic acid derivatives have been found to play a role in mRNA expression of adhesion molecules in endothelial cells.[46] Sinapic acid can be found in wine, vinegar, and canola oil.

Figure 28: o-Coumaric acid ((2E)-3-(2-Hydroxyphenyl)prop-2-enoic acid)

23

o-Coumaric acid ((2E)-3-(2-Hydroxyphenyl)prop-2-enoic acid) is a cinnamic acid with one hydroxyl group found on the ortho position of the phenyl ring. This cinnamic acid has been shown to exhibit moderate antioxidant activity.[47] Sources of o-coumaric acid in the human diet include beer, fruits (especially apples) and green olives.

Figure 29: p-Coumaric acid ((2E)-3-(4-Hydroxyphenyl)prop-2-enoic acid)

p-Coumaric acid ((2E)-3-(4-Hydroxyphenyl)prop-2-enoic acid) is a cinnamic acid with one hydroxyl group found on the para position of the phenyl ring. p-Coumaric acid is a strong antioxidant and effective agent in preventing the oxidation of low-density lipoproteins.[48,49] Sources of this cinnamic acid in the human diet can be located in peanuts, wine, vinegar, carrots, tomatoes, and garlic.

In general, cinnamic acids exhibit stronger antioxidant potential than benzoic acids due to the C2-C3 double bond. The conjugated double bond in the side chain has a stabilizing resonance effect on the phenoxyl radical.

24

1.4 Stilbenoids: Stilbenes

The second class of polyphenols is the stilbenoid class, and is mostly constituted of a major subclass called stilbenes. Stilbenes consist of an ethene double bond linking together two phenyl groups attached to each carbon of the double bond (adopting the C6-

C2-C6 configuration). These phenolic compounds can exist in nature as two possible isomers: the (E)-Stilbenes (trans-stilbenes) and (Z)-Stilbenes (cis-stilbenes). However, due to the steric hindrance in cis-stilbenes, conjugation is prevented, and therefore these cis compounds are less stable. Stilbenes undergo biotransformation as well to add additional functional groups to their phenolic rings. Reference to only trans-stilbenes will be made in this study.

a) b)

Figure 30: Generic stilbene structures of a) trans-stilbene and b) cis-stilbene.

The first of two trans-stilbenes used in this study is Pterostilbene.

25

Figure 31: trans-Pterostilbene (4-[(E)-2-(3,5-Dimethoxyphenyl)vinyl]phenol)

trans-Pterostilbene (4-[(E)-2-(3,5-Dimethoxyphenyl)vinyl]phenol) is a trans- stilbene with two meta methoxy groups on one phenyl ring, and one hydroxyl group on the other phenyl ring. This trans-stilbene has been shown to exhibit strong antioxidant properties, along with lowering blood-lipid/cholesterol levels [50] and blood-glucose levels.[51] Pterostilbene is especially prevalent in blueberries and grapes.

Figure 32: trans-Resveratrol (5-[(E)-2-(4-Hydroxyphenyl)vinyl]-1,3-benzenediol))

trans-Resveratrol (5-[(E)-2-(4-Hydroxyphenyl)vinyl]-1,3-benzenediol)) is a trans-stilbene with three hydroxyl groups; one para on one phenyl ring, and the other two both meta on the other phenyl ring. Resveratrol is a powerful antioxidant, and has shown to increase the action of mitochondrial superoxide dismutase (MnSOD [SOD2]), which is

26

an enzyme that decreases the amount of superoxide radicals by converting them to hydrogen peroxide, without increasing total hydrogen peroxide cellular content.[52]

Resveratrol is most commonly found in the skin of grapes, blueberries, raspberries, and mulberries.

The final class of polyphenols is the flavonoid class. This class is made up of a fifteen-carbon skeleton, with two phenyl rings (rings A and B) and a heterocyclic ring (ring C), and can be abbreviated C6-C3-C6. Many types of subclasses exist for flavonoids, and this study will focus on four of them: Flavones, isoflavones, flavonols, and anthocyanidins.

a) b)

c) d)

Figure 32: Generic flavonoid structures of a) Flavones, b) Isoflavones, c) Flavonols, and d) Anthocyanidins

27

1.5 Flavonoids: Flavones

Flavones are a subclass of flavonoids that all have the 2-phenylchromen-4-one (2- phenyl-1-benzopyran-4-one) backbone. Along with exhibiting strong antioxidant activity, flavones deliver multiple beneficial health effects including anti-inflammatory and weight-loss properties, and are commonly used in marketing for the vitamin and supplement industry.

Figure 34: Flavone (2-Phenyl-4H-chromen-4-one)

Flavone (2-Phenyl-4H-chromen-4-one) is the simplest type of flavone. It provides the 2-

Phenyl-4H-chromen-4-one backbone from which all flavones are formed and is the parent compound of this subclass.

Figure 35: Chrysin (5,7-Dihydroxy-2-phenyl-4H-chromen-4-one) is a flavone

28

Chrysin (5,7-Dihydroxy-2-phenyl-4H-chromen-4-one) is a flavone with two hydroxyl groups located on the 5 and 7 positions of Ring A. Chrysin is a polyphenol that exhibits strong antioxidant activity, and delivers anti-inflammatory effects via inhibition of the enzymatic complex cytochrome c oxidase subunit II (COX2) through signaling of interleukin 6 (IL-6).[53] This flavone is commonly found in chamomile, honeycomb, and the edible mushroom Pleurotus ostreatus.

Figure 36: Baicalein (5,6,7-Trihydroxy-2-phenyl-chromen-4-one)

Baicalein (5,6,7-Trihydroxy-2-phenyl-chromen-4-one) is a flavone that has three hydroxyl groups located on the 5, 6, and 7 positions of Ring A. Baicalein has been known to show strong antioxidative properties, along with cancer cell death and proliferation retardation properties.[54] This flavone can be found in the roots of Scutellaria baicalensis, which is used by the Chinese as a medicinal herb.

29

Figure 37: Baicalin ((2S,3S,4S,5R,6R)-6-[(5,6-Dihydroxy-4-oxo-2-phenyl-4H-chromen-7-yl)oxy]-3,4,5- trihydroxyoxane-2-carboxylic acid)

Baicalin ((2S,3S,4S,5R,6R)-6-[(5,6-Dihydroxy-4-oxo-2-phenyl-4H-chromen-7- yl)oxy]-3,4,5-trihydroxyoxane-2-carboxylic acid) is a flavone and metabolite of baicalein, with the difference in structures being the 7-O-glucuronide present on baicalin instead of the third hydroxyl group.

1.6 Flavonoids: Isoflavones

Isoflavones refer to a subclass of flavonoids, many of which act as phytoestrogens in mammals. This subclass of flavonoid differs from the flavone subclass by the location of the phenyl group; they have the 3-Phenyl-4H-chromen-4-one general backbone.

Figure 38: Biochanin A (5,7-Dihydroxy-3-(4-methoxyphenyl)-4H-chromen-4-one)

30

Biochanin A (5,7-Dihydroxy-3-(4-methoxyphenyl)-4H-chromen-4-one) is an isoflavone with two hydroxyl groups located on the positions 6 and 8 of Ring A, and a methoxy group located at the 4’ position of Ring B. Biochanin A has been classified as a phytoestrogen and has been associated with preventing certain types of dietary cancer.[55]

This isoflavone can be commonly found in alfalfa sprouts, peanuts, and soy.

Figure 39: Puerarin (7-Hydroxy-3-(4-hydroxyphenyl)-8-[(3R,4R,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2- yl]chromen-4-one)

Puerarin (7-Hydroxy-3-(4-hydroxyphenyl)-8-[(3R,4R,5S,6R)-3,4,5-trihydroxy-6-

(hydroxymethyl)oxan-2-yl]chromen-4-one) is an isoflavone and the 8-C-glucoside and metabolite of the isoflavone daidzein. Puerarin holds one hydroxyl group on position 7 of

Ring A. At position 8 of Ring A, a glucose molecule is linked. Puerarin also has an additional hydroxyl group located on the 4’ position of Ring B. Aside from its antioxidative properties, puerarin has shown to exhibit a multitude of other beneficial activities including anti-inflammation, anticarcinogenic, neuroprotective, cardioprotective, and pain alleviating properties.[56] Puerarin can be found in the roots of the Chinese kudzu plant (Radix puerariae).

31

1.7 Flavonoids: Flavonols

Flavonols are another subclass of flavonoids. These flavonoids have the 3- hydroxy-2-phenylchromen-4-one general backbone, and can be found in most plant products. It is estimated that the average human consumes between 20-50mg of these flavonoids daily, depending on the type of diet utilized.[57]

Figure 40: Quercetin (2-(3,4-Dihydroxyphenyl)-3,5,7-trihydroxy-4H-chromen-4-one)

Quercetin (2-(3,4-Dihydroxyphenyl)-3,5,7-trihydroxy-4H-chromen-4-one) is a flavonol that has two hydroxyl groups on Ring A at positions 5 and 7, along with two more hydroxyl groups located on the 3’ and 4’ positions of Ring B. Aside from its antioxidative properties, quercetin has also shown some anticarcinogenic benefits.[58]

Sources of quercetin in the human diet come from citrus fruits, apples, dark berries, grapes, onions, parsley, and olive oil.

32

Figure 41: Quercetin-3-glucuronide ((2S,3S,4S,5R,6S)-3,4,5-Trihydroxy-6-[2-hydroxy-5-(3,5,7-trihydroxy-4-oxo-4H- chromen-2-yl)phenoxy]oxane-2-carboxylic acid)

Quercetin-3-glucuronide ((2S,3S,4S,5R,6S)-3,4,5-Trihydroxy-6-[2-hydroxy-5-

(3,5,7-trihydroxy-4-oxo-4H-chromen-2-yl)phenoxy]oxane-2-carboxylic acid) is a flavonol and metabolite of quercetin. It is structurally identical to quercetin, with the exception of the glucuronic acid linked via a glycosidic bond at the 3 position of Ring C

(in place of the hydroxyl group).

Figure 42: Quercetin-3-glucoside (2-(3,4-Dihydroxyphenyl)-5,7-dihydroxy-3-{[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6- (hydroxymethyl)oxan-2-yl]oxy}-4H-chromen-4-one)

Quercetin-3-glucoside (2-(3,4-Dihydroxyphenyl)-5,7-dihydroxy-3-

{[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxy}-4H-chromen-4- one) is a flavonol and metabolite of quercetin. It is structurally identical to quercetin, with

33

the exception of the glucose unit linked via a glycosidic bond at the 3 position of Ring C

(in place of the hydroxyl group). Quercetin-3-glucoside is found primarily in onions.

1.8 Flavonoids: Anthocyanidins

Anthocyanidins are the final subclass of flavonoids that will be discussed in this study. These flavonoids are the aglycones of anthocyanins, and their general backbone is comprised of the flavylium ion (2-phenylchromenylium). A chlorine anion is normally the counterion of the flavylium cation.

Figure 43: Pelargonidin chloride (3,5,7-Trihydroxy-2-(4-hydroxyphenyl)chromenylium chloride)

Pelargonidin chloride (3,5,7-Trihydroxy-2-(4-hydroxyphenyl)chromenylium chloride) is an anthocyanidin that has a hydroxyl group on position 3 of Ring C, two hydroxyl groups on position 5 and 7 of ring A, and one hydroxyl group on the 4’ position of Ring B. In addition, there is also a chlorine anion present to stabilize the oxygen cation. This anthocyanidin is a phytoestrogen that has antioxidative and antigenotoxic properties.[59] Pelargonidin chloride can be found in many types of berries including blueberries, cranberries, raspberries, and strawberries.

34

1.9 Thesis Overview

As the research and studies for the above polyphenols suggest, there is much potential for the application of phenolic compounds in preventing and treating many types of diseases and ailments. However, when looking at the mode of delivery for a phenolic compound in vivo, more is required than simple consumption. Many important interactions take place throughout metabolism in order for a polyphenol to reach a radical, and reduce it. One of these key interactions is between a polyphenol and transport proteins.

Upon digestion, macronutrients and drugs are dispersed throughout the body via transport proteins. A transport protein can be defined as a protein that moves materials throughout an organism. These transporters can range in size from relatively small cell- membrane carrier proteins to large, complex lipoproteins. Here, the degree of binding and unbinding to a transport protein is very important (association and dissociation, respectively). Many factors appear to play a role in compound association/dissociation including size, charge, concentration, structure, environment, competition between other substrates, etc., and it is important to identify these factors in order to ascertain an accurate model for compound delivery. The delivery of polyphenols in vivo is no different from the above mentioned transport method, and it is the hope of this study to identify relative association constants (Kas) in vitro in order for future studies to develop an accurate theory on how polyphenols are actually distributed throughout the human body, and eventually metabolized.

The degree to which a polyphenol binds to a protein can be determined through fluorescence spectroscopy; the technique often employed, and the one that is used in this

35

review is called fluorescence quenching. Fluorescence quenching is the decrease of the quantum yield of fluorescence from a fluorophore induced by a variety of molecular interactions with a quencher molecule.[60] A description of this method is as follows:

When a fluorophore is hit with a beam of ultraviolet light, energy is absorbed, and an electron jumps up from its ground state to an excited state. Eventually, the electron will relax and fall back down to its ground state, while simultaneously emitting light with a longer wavelength and lower energy. This emitted light is called fluorescence. By measuring the decreasing fluorescence of a sample with an increasing quencher

(polyphenol) concentration, one is able to determine the binding constant of a polyphenol to a protein with at least one fluorophore, and hence, the affinity that a protein has towards a given polyphenol. Unless the identification of the exact binding site for a polyphenol to a protein is needed, fluorescence quenching through titration with a ligand is a rapid and facile method for determining the binding affinities of phenolic compounds to proteins.[61]

The total fluorescence of a folded protein is a combination of the individual fluorescence from its aromatic residues (tryptophan [Trp], phenylalanine [Phe], and tyrosine [Tyr]). Generally excited at wavelengths >280 nm, most emissions are due to excitation of Trp residues, with few emissions resulting from Tyr and Phe. This is because Trp has a much stronger fluorescence and higher quantum yield than the other aromatic residues. However, even though Trp makes up the majority of a folded protein’s fluorescence, its own intrinsic fluorescence is heavily influenced by certain factors.

Varying solvents shift Trp residue fluorescence significantly, with more polar solvents shifting it to shorter wavelengths, and higher intensities. The location of the residue

36

within the protein is also an important factor in Trp fluorescence shifting. Trp residues buried in hydrophobic pockets tend to have spectra shifted between 10-20 nm when compared to Trp residues on the surface. Neighboring protonated acidic residues also have a tendency to quench Trp fluorescence, which will result in observed diminished intensity.

When employing fluorescence quenching as a method to determine binding affinities, it is important to note that there are two type of quenching interactions that can occur: static or dynamic. Static quenching results from the formation of a quencher- fluorophore (polyphenol-protein) complex. Dynamic quenching results from collisional encounters between the quencher and fluorophore. Quenching is a result of either one of these types of interactions, or a combination of both, however in any case, molecular contact between the quencher and protein is required.[62] Yet, often times fluorescence quenching alone is not enough to determine which type of quenching interaction is occurring, so other types of analytical techniques (i.e. FTIR, CD) must be utilized to obtain an accurate description of the types of interactions at play. It is important to note that in the case for static and dynamic quenching, the quencher and fluorophore do not necessarily require direct contact. For example, in the case of static quenching for a protein with a polyphenol, the polyphenol need not bond directly to a fluorophore. The polyphenol can bind to any residue, and induce a conformational change in the protein, which will in turn result in a decrease in fluorescence. Likewise for dynamic quenching, a polyphenol may collide with another residue besides Trp, and again, result in a slight conformational change of the protein, yielding a decrease in fluorescence.

37

When polyphenols bind to a protein, they form insoluble protein-polyphenol complexes that are most stable near the specific isoelectric point of that particular protein.[63] In the case of binding between polyphenols and certain transport proteins, this interaction has been shown to be moderated by either hydrogen bonding or hydrophobic interactions, depending on whether the polyphenol is polar or nonpolar, respectively.[64]

Two transport proteins where utilized for this study: the serum albumin protein bovine serum albumin (BSA) and the lipoprotein-superparticle complex low-density lipoprotein and very-low-density lipoprotein (LDL-VLDL superparticle) complex, derived from porcine blood.

BSA is an important serum albumin protein, and is commonly used in many analytical techniques including ELISAs, immunoblots, and Bradford protein assays. The mature BSA protein is a globular protein made up of 583 amino acids, and is 76% homologous to human serum albumin (HSA) in its amino acid sequence. It has a molecular mass of ~66.5 kDa. A deeper look into the BSA particle shows that it is made up of three homologous domains (I, II, and III), and divided into nine loops (L1-L9) by 17 disulfide bonds. These loops in each domain form triplets that are made up of a sequence of large-small-large loops. Delving deeper, each domain in turn is comprised of two subdomains (i.e. IA and IB).[65] Data from X-ray crystallography show that the secondary structure of BSA is predominantly α-helical, and amino acids that are not incorporated into this α-helix occur in-between the regions of the subdomains as extended and flexible turns: BSA contains no β-pleated sheets.[66] BSA contains two tryptophan (Trp) residues, which act as fluorophores due to their intrinsic fluorescence. In reference to fluorescence spectroscopy, and the fluorescence quenching method, the main difference in BSA when

38

compared to HSA, is that BSA contains two fluorophores (Trp134 and Trp213) and three hydrophobic pockets, versus the lone fluorophore (Trp214) and two hydrophobic pockets in HSA.[66]

The tryptophan residues of BSA are vital for the fluorescence quenching method, and knowing their location in the protein is important in understanding how these residues will be affected in the quenching process. The Trp134 residue is the first fluorophore, and is located on a solvent-exposed region of subdomain IB. This fluorophore is highly accessible to a quencher molecule. However, the Trp213 residue is not that easily accessed by a quencher, because it is nestled inside the hydrophobic pocket of subdomain IIA near the Sudlow I site.[66]

The second transport protein, the lipoprotein LDL-VLDL superparticle, is a much more complex transporter and has a fluctuating molecular mass of several million kDa

(2.93 million kDa was the molecular weight used for the LDL-VLDL superparticle). As the primary means of transport for lipids throughout the bloodstream, and as the name implies, this superparticle is comprised of both fats and proteins. This superparticle achieves transport of lipids through emulsification. Its hydrophobic core consists of linoleate (a polyunsaturated fatty acid), a few hundred triglycerides and unesterified cholesterol molecules, and a few thousand esterified cholesterol molecules. This highly hydrophobic core makes it an ideal carrier for hydrophobic compounds like triglycerides, cholesterol, fat-soluble vitamins, phospholipids, and other nonpolar compounds. Its surface monolayer is primarily comprised of a few hundred phospholipids (mostly phosphatidylcholine and sphingomyelin) a few hundred free cholesterol molecules, some very small (low molecular weight) and exchangeable (not always present with the

39

superparticle through transport) ancillary proteins, and a single apolipoprotein (or apoprotein) apo B-100.

Apo B-100 is a non-exchangeable apoprotein (it is always present with the superparticle throughout transport due to its high level of insolubility in aqueous solutions i.e. blood) that consists of 4,536 amino acid residues and has a molecular mass of 512.7 kDa; to date, it is one of the largest monomeric proteins known. Because of its massive size, the exact higher structures of apo B-100 have been difficult to identify.

Several models exist for its secondary and above structure, and strong arguments have been made for each model. Despite this difficulty, a low-resolution model has been identified, with a definitive secondary 5-domain protein-model consisting of 3 α-helices and 2 ß-pleated sheets. Because the primary structure of apo B-100 has been successfully sequenced, it is possible to identify the Trp residues, and thus, the fluorophores. Apo B-

100 has 37 Trp residues, and each one contributes to the total fluorescence of the

[67] apoprotein. The following is a list of the major fluorophores in apo B-100: Trp370,

Trp556, Trp694, Trp936, Trp1114, Trp1140, Trp1151, Trp1210, Trp1342, Trp1434, Trp1893, Trp1954,

Trp2104, Trp2221, Trp2468, Trp2526, Trp2527, Trp2546, Trp2659, Trp2894, Trp2902, Trp2904, Trp3060,

Trp3126, Trp3515, Trp3536, Trp3567, Trp3606, Trp3668, Trp3871, Trp3943, Trp3995, Trp4031, Trp4063,

[68] Trp4087, Trp4117, and Trp4369.

The goal of this study will be to determine and compare the binding constants of the above-mentioned 40 polyphenols between the transport proteins BSA and the LDL-

VLDL superparticle through several different calculations. Data for binding constants will be collected via the fluorescence quenching method. A strong focus will be placed on whether quenching is static or dynamic, and other analytical techniques will be

40

employed to determine whether quenching of a transport protein is a result of mere collisional encounters between the polyphenol and protein, or an incorporation of the polyphenol into the transport protein itself. Several comparisons of important structural and dynamic correlations will be made to determine the reason for different binding affinities.

2.0 Materials and Methods

2.1 Reagents Sigma-Aldrich Lyophilized Bovine Serum Albumin Powder (BSA, ≥98%) Lampire Biological Laboratories Porcine Blood in K2EDTA (Alattoir) Spectrum Quality Products Inc. Urea-carbamide(Crystal Reagent) (≥99.5%) Sigma-Aldrich 0.01M Phosphate Buffered Saline (PBS) pH 7.4 Packets Sigma-Aldrich Methanol Sigma-Aldrich Phosphoric acid Sigma-Aldrich Heparin-Agarose, Type 1 (4%) Reagent Grade Sodium Chloride (NaCl) Sigma-Aldrich Chelex 100 Sodium Form (50-100 mesh [Dry]) Sigma-Aldrich Brilliant Blue G-250 (Powder)

2.2 Polyphenols Ellagic acid (97%) Eudesmic acid (99%) Syringic acid (≥97%) Gallic acid (≥98%) Protocatechuic acid (98%) m-Hydroxybenzoic acid (99%) p-Hydroxybenzoic acid (99%) p-Hydroxysalicylic acid (≥97%) Apocynin (≥98%) Vanillic acid (≥97%) Dopac (98%) m-Hydroxyphenylacetic acid (≥99%) p-Hydroxyphenylacetic acid (98%) Homogentisic acid (97%) Chlorgenic acid (95%) Ferulic acid (99%) Isoferulic acid (97%) Isoferulic acid-3-O-glucuronide (Purity N/A)* Dihydroferulic acid (99%) Caffeic acid (≥98%)

41

Caffeic acid-3-O-glucuronide (Purity N/A)* Caffeic acid-4-O-glucuronide (Purity N/A)* Dihydrocaffeic acid (98%) Dihydrocaffeic acid-3-O-sulfate (Purity N/A)* Dihydrocaffeic acid-3-O-glucuronide (Purity N/A)* Sinapic acid (98%) o-Coumaric acid (97%) p-Coumaric acid (98%) Pterostilbene (≥97%) Resveratrol (≥99%) Flavone (≥99%) Chrysin (97%) Baicalein (95%) Baicalin (98%) Biochanin A (≥97%) Puerarin (≥98%) Quercetin (≥95%) Quercetin-3-glucuronide (Purity N/A)** Quercetin-3-glucoside (≥90%) Pelargonidin Chloride (≥97%) All polyphenols were purchased from Sigma-Aldrich unless otherwise noted. *Generously gifted from the Department of Pharmacy, University of Parma, Parma, Italy ** Generously gifted from the Institute of Food Research, Norwich, UK

2.3 Materials Ice Bath 10 mL Plastic Screw Cap Test Tubes Water and Air Hose Beckman GS-6KR Centrifuge 1.5 mL Plastic Microcentrifuge Tubes Norlake Scientific 4°C Refrigerator Fisher Scientific Isotemp -20°C Freezer So-Low Ultra-Low -80°C Freezer Liquid and Gaseous N2 Metal Tongs Twenty Well Affinity Column Apparatus Plastic Affinity Columns Affinity Column Plastic Caps Affinity Column Frits Distilled Nanopure Water Millipak Gamma Gold Millipore (Direct-Q UV 3) Ring Stand, O-ring, and Column Clamps Plastic Transfer Pipettes Pasteur Pipettes SCILOGEX Micropipette (1000-5000 μL) and Tips SCILOGEX Micropipette (100-1000 μL) and Tips SCILOGEX Micropipette (10-100 μL) and Tips

42

SCILOGEX Micropipette (0.5-10 μL) and Tips 50 mL Graduated Cylinder 50 mL Erlenmeyer Flask 100 mL Erlenmeyer Flask 400 mL Erlenmeyer Flask 30 mL Beakers 50 mL Beakers 100 mL Beakers 200 mL Beakers 400 mL Beaker 600 mL Beaker 500 mL Plastic Bottles 1 L Plastic Bottless 50 mL Volumetric Flasks 100 mL Volumetric Flasks Parafilm M and Dispenser Disposable Gloves Glass Funnel Fisher Brand (P5) Filter Paper Microspatula Macrospatula Denver Instrument Model PI-314 Analytical Balance Scientific Industries Vortex-Genie 2 Thermo Scientific Nicolet-Avatar 320 FT-IR FT-IR EZ OMNIC Software Polymer Solid Films-Polyethylene (FT-IR) Water Resistant CaF2 Plates Thermo Scientific Genesys 20 UV/VIS Spectrophotometer Fisher Scientific Brand two-sided UV/VIS Silica Cuvettes WilMad Glass Co. Inc. Glass Cuvettes KIMAX 3 mL Reaction Vials PerkinElmer LS 45 Luminescence Spectrometer FLWinLab Software Fisher Scientific Temperature Controlled Water Bath/Circulator

2.4 PBS Solution Preparation

A 0.01M PBS solution was prepared by mixing in 1 PBS packet into 1 L of nanopure water, and run through a chelex column.

43

2.5 Polyphenol Standards Preparation

245 μM standards were prepared for each polyphenol by placing the desired amount of polyphenol into a 100ml volumetric flask, and then diluting to the line with methanol.

2.6 BSA Standard Preparation

A 1.03 μM BSA standard was prepared by adding 6.8 mg of BSA into a 100 mL volumetric flask, and dissolving it in PBS up to the line according to the methods of

Amal Alanazi. Aliquots of this standard where then diluted further with more PBS to give optimal intensity (ranging from 900-1000 I.U. on fluorescent spectra), resulting in a final

BSA standard concentration of 0.515 μM. Standards were stored in glass volumetric flasks in the 4°C refrigerator.

2.7 Isolation of Porcine Plasma

Meticulous lengths were taken to prevent/minimize LDL-VLDL oxidation.

Porcine blood ranging in various sitting times from delivery (8 hour, 1 day, and 2 day) was stored in the 4°C refrigerator upon retrieval. 10 mL plastic test tubes were set up in ice water. Porcine blood was removed from the refrigerator source, and 9 mL aliquots were added to 15 plastic test tubes, with each test tube being capped immediately after addition, and submersed in ice water. Upon the completion of the 15th aliquot, the test tubes were then transferred in ice water to the centrifuge, and spun for 7 minutes at 3300

RPMs, at 4°C. The supernatant was the plasma.

44

2.8 Storage of Porcine Plasma

Upon completion of centrifugation, the test tubes were collected, and again immediately submersed in ice water. Each test tube was successively withdrawn from the ice water, opened, and the supernatant was withdrawn with 2.0 mL plastic transfer pipettes. Care was taken not to withdraw the lowest level of supernatant. The plasma aliquots were added to 1.5 mL plastic microcentrifuge tubes, which were previously set up on a stand in ice water. Upon the addition of the plasma into the microcentrifuge tubes, N2 was added. The microcentrifuge tube was immediately capped, then submersed in ice water. After the final microcentrifuge was capped and submersed in ice water, all microcentrifuge tubes were removed from the ice water, and immediately flash frozen with liquid N2. Plasma aliquots were then immediately placed into the -80°C freezer, and stored indefinitely.

2.9 LDL-VLDL Extraction Method

Several empty columns were placed in a plastic column holder, with 10 mL plastic test tubes placed beneath them to collect the waste eluent and eluate. A frit was placed on the bottom of each column using the wide end of a Pasteur pipette to help guide it into place. Next several milliliters of 4% Heparin-agarose was added using a

SCILOGEX micropipette until the total height of Heparin-agarose in the column was above 2.5 cm, but did not exceed 3 cm. Following the addition of the agarose to the columns, a second frit was then added to the column in a sideways manner until it reached the top of the agarose The frit was then gently flipped over with a microspatula so that it laid across the top of the agarose. Next, 5.0 mL of nanopure water was added to

45

the column and allowed to drain. Taking care to never let the column dry out, as soon as the last amount of nanopure water contacted the top edge of the top frit, 4.0 mL of the α-

Fraction Elution Agent (0.9% NaCl) was added to the column and allowed to drain.

Immediately before the last amount of the α-Fraction Elution Agent came into contact with the top frit, the column was capped on both ends. At this time, an aliquot of plasma was removed from the -80°C freezer, and allowed to thaw. Upon completion of thawing, the columns were then uncapped, and allowed to continue draining. When the last amount of α-Fraction Elution Agent came into contact with the second frit, 425 μL of the plasma was then added to each column. Once the entire amount of plasma passed the second frit, the columns were again capped on both ends, and allowed to sit for 3 minutes to ensure plasma absorption into the Heparin-agarose matrix. Afterwards, the top of the column was uncapped, and 2.5 mL of α-Fraction Elution Agent was added to elute the

HDL, albumin, and other proteins present in the plasma. After the elution, the eluate was discarded, and new 10 mL plastic test tubes were placed underneath the columns.

Simultaneously, 1.25 mL of the β-Fraction Elution Agent (2.7% NaCl) was added to the column, which eluted the LDL-VLDL in the plasma. Upon collection of this eluate, bubbling of N2 ensued, followed by capping of the test tubes. Completed columns were administered 5.0mL of PBS, allowed to drain 3.0 mL, then immediately capped on both ends and stored until regeneration and future use. Completed test tubes were immediately bubbled with N2, capped, and then submersed in ice water until the final β-fraction was collected. All β-fractions were then combined, and bubbled with more N2. The combined

β-fractions were then vortexed at the lowest level, which preceded additional N2 addition.

These combined β-fractions were then diluted with PBS to give an optimal initial

46

intensity reading (ranging from 900-1000 I.U. on fluorescent spectra, with dilution concentrations at 9.744E-09 M-1 LDL-VLDL). Following initial fluorescent intensity readings, the combined, and now diluted β-fractions were aliquotted into 1.5 mL plastic microcentrifuge tubes with a 2.0 mL plastic transfer pipette, and submersed in ice water.

Upon the completion of the addition of the final β-fraction into the last 1.5 mL plastic microcentrifuge tube, all β-fraction aliquots were removed from the ice water, flash frozen with liquid N2, and then immediately placed into the -80°C freezer, and stored until use.

*Note: This procedure was performed 2 times in a cold room (4°C) and 2 times in a normal laboratory setting (21°C) to determine the ideal setting. Results show that provided the above method is followed; no observable difference in oxidation has been detected in either method.

2.10 Column Regeneration

Because Heparin-agarose is relatively expensive (~$10.00 USD/mL), it became necessary to develop a method for column regeneration. Previously used columns were uncapped, and the remaining 2.0 mL of PBS were allowed to drain. The column was then washed with 3.0 mL of nanopure H2O, followed by 4.0 mL of urea in nanopure H2O

(1M), 1.0 mL of 1% Triton X-100 diluted with nanopure H2O (v/v), 10 mL of nanopure

H2O, and then 5 mL of PBS. 3.0 ml of PBS were allowed to drain, followed by capping of the column at both ends, and storage on a lab bench until future use.

2.11.0 Bradford Method - Preparation of Coomassie Reagent

2.11.1 Stock Reagent- 100 mg of Sigma-Aldrich Brilliant G-250 was added to 50 mL of methanol in an Erlenmeyer flask. The solution was then gravity filtered through fluted filter paper placed in a glass funnel, supported by an O-ring on a ring stand. The filtrate

47

was collected in a 400 mL Erlenmeyer flask. Next, 100 mL of 85% phosphoric acid

(H3PO4) was added to the flask, followed by 200 mL of nanopure H2O. This stock solution was stored in a brown glass bottle in the 4°C refrigerator until needed (stored indefinitely).

2.11.2 Assay Reagent- In preparation for the assay reagent, 1 part stock reagent was mixed with 4 parts nanopure H2O, and stored in a brown glass bottle in the 4°C refrigerator until use. Storage time for the assay reagent did not exceed one month.

2.12 Quantitative Determination of Protein in LDL-VLDL from Porcine Plasma via

Bradford Method

As per the methods of Mark Romanczyk, a stock solution of BSA with the concentration of 2.0 mg/mL was prepared in a 100 mL volumetric flask, using nanopure

H2O as the diluent. This stock solution was then used to prepare the following standards:

Glass Vial # Volume of Diluent Volume and Source Concentration of (μL) of BSA (μL) BSA in vial (μg/mL) A 0 300 of stock solution 2000 B 125 375 of stock solution 1500 C 325 325 of stock solution 1000 D 175 175 of Vial B 750 E 325 325 of Vial C 500 F 325 325 of Vial E 250 G 325 325 of Vial F 125 H 400 100 of Vial G 25 I (Blank) 400 0 0 Table 1: Bradford method protein stock concentrations determination *Vial solutions were mixed thoroughly via 5 withdraws/aspirations with a 600 μL micropipette before moving on to the next vial. Pipette tips were changed after each solution was mixed.

Once the standards were prepared, one aliquot of the optimized β-fraction containing the diluted LDL-VLDL was removed from the freezer and allowed to thaw.

48

Next, the Genesys 20 spectrophotometer was turned on, and the absorbance wavelength was set for 595 nm. Then, 30 μL of each prepared standard was pipetted into disposable cuvettes, followed by an additional 30 μL of nanopure H2O to serve as the control. Upon completion of thawing, the microcentrifuge tube containing the optimized β-fraction was inverted 10 times. Next, two aliquots of 30 μL each containing the optimized β-fraction was pipetted into disposable cuvettes. After all the cuvettes were filled with the designated solution, 1.5 mL of the Bradford Coomassie Assay Reagent was pipetted into each cuvette. Parafilm “M” was wrapped around the tops of each cuvette, followed by the cuvette being inverted 5 times to ensure proper dispersal of the coomassie reagent. The cuvettes were then allowed to sit for 5 minutes. After the 5-minute interval, Vial I was placed in the spectrophotometer, and used as a blank; its absorbance was marked at 0.

The absorbance of the 10 remaining cuvettes were then measured and recorded. Using

Microsoft Excel 2011, the standard absorbances were then plotted on the y-axis, and the concentrations on the x-axis, followed by the calculation of the linear regression formula.

Finally, the unknown absorbances of the 2 LDL-VLDL samples were entered into the formula to determine their concentrations. These two concentrations were then averaged to obtain the unknown concentration of the LDL-VLDL extracted from the porcine plasma. Assuming the Bradford Assay only detects protein concentration, the results were interpreted as the amount of Apo B-100 in our LDL-VLDL samples, resulting in the working concentration of 55.69 nM Apo B-100, and an overall concentration of 9.744 nM LDL-VLDL.

49

Apo B-100 Calculation: The average concentration of protein detected by the Bradford

Assay was 28.55푢푔 . 푚푙

28.55푢푔 103푚푙 1푔 0.02855푔 푃푟표푡푒푖푛 1. ∗ ∗ = 푚푙 퐿 106푢푔 퐿

0.02855푔 푃푟표푡푒푖푛 1 푚표푙 퐴푝표 퐵−100 2. ∗ = 5.569 ∗ 10−8 M-1 = 55.69 nM Apo B-100 퐿 5.127∗105 푔 퐴푝표 퐵−100

*Apo B-100 exists as a component of both LDL and VLDL in the ratio of 1:1 for each lipoprotein. **Note: Only after this method was it determined which porcine blood was to be used (2-day old, 1-day old, or 8-hour old). Given the considerable degree of oxidation (read as increased protein concentration) observed in the 2-day old porcine blood, as well as the 1- day old porcine blood, all optimized β-fractions used for fluorescent quenching and FTIR spectroscopy were performed with 8-hour old porcine blood.

2.13 FT-IR Spectroscopy:

Due to the aqueous nature of the solvents in the protein standards, traditional salt plates (NaCl) could not be used. Instead, CaF2 plates and polyethylene films were used in place of salt plates. Blanking the instrument with PBS proved futile, since FT-IR spectra with the protein and the protein-polyphenol complex taken thereafter showed little to no intensity within the range of 0-4000 cm-1. Instead, the surrounding media (air) was chosen and set as the blank; the following procedure was performed with both the CaF2 plates, and polymer films. The instrument was turned on, and the FT-IR EZ OMNIC software was opened. The instrument was then blanked. Next, a 50 μL aliquot of the protein standard was applied to the plate/film. Normal practice calls for the drying of a liquid on a plate/film to form a thin film, however, in this procedure, complete drying rendered no spectra. In an attempt to correct for this, most of the liquid was evaporated using N2, with just enough liquid being left on the plate/film to form a small layer. Due to the presence of this liquid, strong, broad peaks were observed at 3000-3300 cm-1

(indicative of water present in the sample), but carbonyl peaks in the 1600-1700 cm-1 range (amide I bands) could still be observed. The intensity of the amide I band was

50

recorded. The plates were then cleaned. Next, a 50 μL aliquot of the protein standard was added to a plastic screw cap test tube, followed by the addition of a 2 mL aliquot of a polyphenol standard (in order to see spectral peak shifts resulting from protein- polyphenol complex formation, polyphenols had to be added in a high molar excess to a protein standard). The test tube was inverted 5 times, and allowed to sit for 5 minutes.

Next, 50 μL of the protein-polyphenol mixture was added to the plate/film, and almost completely dried with N2. The plate was then inserted into the spectrometer, and the shifted intensity of the amide I band was recorded.

2.14.0 Fluorescence Quenching Method:

2.14.1 Instrumentation and Parameters: A PekinElmer LS 45 Luminescence

Spectrometer along with a Fisher Scientific temperature controlled water bath set at 25°C

± 1°C was used to determine fluorescence quenching of BSA and LDL-VLDL.

FLWinLab software was used with instrumentation to interpret fluorescent quenching data. Emission and excitation wavenumbers were set at 342 nm and 280 nm, respectively, for tryptophan in BSA and LDL-VLDL. Emission spectra were acquired in the wavelength range between 300 and 500 nm.

2.14.2 Procedure: The instrument was blanked with 2.7 mL of PBS. Next, 2.7 mL of the optimized BSA or LDL-VLDL β-fraction standard were pipetted into a glass cuvette with a SCILOGEX pipette. The cuvette was placed in the luminescence spectrometer for 5 minutes and then 2 intensity measurements were taken. The intensities were then

51

averaged. The cuvette was then removed from the luminescence spectrometer and 3 μL of the desired 245 μM polyphenolic standard were pipetted into the cuvette using a

SCILOGEX pipette. The cuvette was then placed into the luminescence spectrometer for another 5 minutes to allow for BSA-polyphenol/ LDL-VLDL-polyphenol binding; 2 intensity measurements were then taken and averaged (5 minutes was the time chosen because after this point, there was no change in intensity, and the solution in the cuvette appeared to be at equilibrium). The addition of the polyphenolic standard to BSA was repeated 4 more times, resulting in a final polyphenol concentration of 1.088E-06 M-1 in the cuvette.

2.15 Statistical Analysis: Using Microsoft Excel 2011, along with StatPlus:mac v5, the following statistical analyses were run to interpret and compare the significance of data:

1) Significance of the difference between the binding constants of BSA and LDL-

VLDL – Paired Two-sample T-test (5% alpha value/confidence interval).

2) Significance of correlation coefficients between binding constants and several

potential binding-affecting parameters including:

a. Polar surface area (PSA2)

b. Hill affinity/Stoichiometry (n)

c. Hydrogen Bond Acceptors and Donors

d. Log P/Log D (hydrophobicity index)

e. Log P/Log D vs Log Ka

52

First in total, then by group (split up as phenolic acids [PAs] and non-phenolic

acids [Non-PAs]- Linear Correlation-Pearson Coefficient (2% alpha

value/confidence interval).

3.0 Binding Constant Calculations

3.1 Overview

The quantitative assessment of substrate-protein kinetics is particularly useful in many scientific fields today. There are many ways to interpret data of substrate-protein kinetics, and this next section will attempt to explain how several common methods used were applied to the fluorescence quenching of a protein with a polyphenol.

If the binding of a polyphenol (a quencher, Q) to a protein (P) with N equivalent binding sites is assumed to be occurring, the binding process may be represented by the following equation,

Free sites + QFree ⟷ Occupied sites [Eq. 1]

where QFree is the amount of unbound quencher. When equilibrium is reached, it can be represented by Equation 2:

Kas = [Occupied sites]/([Free sites][QFree]) [Eq. 2]

If the average number of occupied binding sites can be represented by θ, the previous equation can be rewritten to express the binding constant as such:

53

Kas = θ/((1-θ)[QFree]) [Eq. 3]

When utilizing the fluorescent quenching method for obtaining binding constants, it

0 becomes imperative to identify and express θ and [QFree] by their primary data, F , F, [P],

0 and [QTotal]. Here, F is the fluorescence intensity of the protein in the absence of the quencher, F is the fluorescence intensity of the protein in the presence of a given concentration of the quencher, [P] is the total protein concentration, and [QTotal] is the total quencher concentration. If we identify the number of binding sites in the protein as

N, it becomes possible to balance all contributing substituents by the following equation:

[QFree] = [QTotal] - N θ[P] [Eq. 4]

A simple solution from the above equation only results when N = 1. However this is relatively rare, since many factors contribute to the amount of polyphenols binding to a protein, especially in regards to conformational changes resulting in positive or negative cooperativity, leading to an increase or decrease in binding to the protein, respectively.[69,70,71] Because it is impossible to account for all factors that can contribute to polyphenol-protein binding without advanced experimental or theoretical calculations, the assumption will be made that the number of binding sites, N, can always be considered fixed and equivalent.[72,73] Assuming this condition, it is given that,

θ = (F0 – F)/(F0 – F*) [Eq. 5] and

54

θ/(1 – θ) = (F0 – F)/(F – F*) [Eq. 6]

where F* is the fluorescence of the polyphenol saturated protein. By inserting Equations

4, 5, and 6 into Equation 3, the following equation arises to act as the starting point for determining the binding constants of a polyphenol with a protein (Kas).

(퐹0−퐹)/(퐹−퐹∗) 퐾푎푠 = 0 0 ∗ [Eq. 7] ([푄푇표푡푎푙]−푁{(퐹 −퐹)/(퐹 −퐹 )}[푃]

This equation can then be reduced if the following stipulations are assumed:

1) F* ≈ 0

2) [QFree] ≈ [QTotal]

The first stipulation assumes that the emission from a polyphenol-saturated protein is very low, and thus negligible. The second stipulation assumes that the total concentration of quencher present in the solution is very close to the total concentration of unbound quencher in the solution, and can be expressed as [QT]>>N θ [P]. These assumptions are commonly employed by many studies in the evaluation of solute-protein fluorescence changes.[72,73,74] These assumptions are further supported when addition of a polyphenol to BSA or LDL-VLDL quenches protein fluorescence, but the spectral shape remains unchanged. This fact indicates that conformational changes in the Trp microenvironments are relatively negligible. Unless otherwise mentioned, these stipulations prove a necessary condition to evaluate the binding constants of a polyphenol to BSA or LDL-

VLDL through the following methods.

55

3.2 Stern-Volmer Plots

Given that the above assumptions are maintained, Equation 7 can be reduced to

0 F /F = 1 + Kas [QTotal] [Eq. 8.0] or

0 F /F = 1 + KSV [QTotal] [Eq. 8.1] or

0 F /F = 1 + kqτ0 [QTotal] [Eq. 8.2] because

Kas = KSV = kqτ0 [Eq. 9]

Utilization of the Stern-Volmer method has been discussed in many physical and kinetics texts, and is often employed in the discipline of photochemistry. This useful technique assists in the interpretation of the kinetics between a pseudo-first order quenching

[74] 0 reaction and a first order decay process such as fluorescence. Plotting F /F v.s. [QTotal] in a linear regression formula will give KSV as the slope, as well as the binding cooperativity of the polyphenol and protein (n) as the y-intercept. It is important to note

0 that many studies suggest that when plotting F /F v.s. [QTotal] in a linear regression formula the y-intercept (n) represents the total number of binding sites. This however, is an incorrect assumption because the Stern-Volmer equation is merely a modified form of the Hill equation, and thus, n represents the stoichiometry of the binding step. This stoichiometry may be interpreted as the number of polyphenol molecules that simultaneously bind to the protein, or even as the number of binding sites exhibiting

56

infinite cooperativity present in the protein, but never the number of binding sites. This is a slight, but important correction.[75] This idea is in agreement with the data recorded in this and several other studies [69,72,73,76], in that the y-intercept of a Stern-Volmer plot of a protein and quencher is very close to 1, and remains independent of the number of binding sites determined in other procedures.[75] The classic Stern-Volmer model assumes all fluorophores are equally accessible to the quencher.

Taking a deeper look into the primary data that contributes to the Stern-Volmer binding constant, it is apparent that KSV = kqτ0. Here, kq is the bimolecular quenching constant, and τ0 is the native lifetime of a given fluorophore. Rearranging the equation gives

kq = KSV/τ0 [Eq. 10]

The bimolecular rate constant can reflect the efficiency of quenching or the accessibility of the fluorophores to the quencher. Essentially, the bimolecular rate constant is necessary to distinguish whether binding is static or dynamic.[61] The upper limits of dynamic binding (a diffusion-controlled mechanism) tend to be neighboring 1 x 1010 M-1 s-1. Rate limits that are higher suggest static binding, especially if they are at least several orders of magnitude larger.[60]

3.3 Double Logarithm Plots

The binding of a polyphenol to a protein having N independent binding sites can be expressed by

57

N [QFree] + [Free site] ⟷ [Occupied sites] [Eq. 11]

Using the above equilibrium, it becomes possible to express the binding constant as

N Kas = [Occupied sites]/([Free sites][QFree] [Eq.12]

If the assumption of Stipulations 1 and 2 are withheld, it stands to reason that Equation

12 can be rewritten as

0 log{(F – F)/F} = logKas + N log[QTotal] [Eq. 13.1]

For the purpose of this study, we will delegate the title KDL as a replacement for the

Double Logarithm binding constant Kas to avoid confusion between this and other calculated binding constants, where Equation 13.1 can be rewritten as

0 log{(F – F)/F} = logKDL + N log[QTotal] [Eq. 13.2] because

Kas = KDL [Eq. 14]

0 Plotting the log{(F – F)/F} v.s. log[QTotal] in a linear regression formula gives the values

(y-intercept/slope) of N and KDL, where N is the absolute value of the slope, and KDL = 10 .

Again, it is important to note here that N is not the number of equivalent binding sites, but rather the stoichiometry of the binding step.

58

3.4 Quadratic Equation

The quadratic equation is commonly used to quantify the dissociation constant of substrates to enzymes at equilibrium in potentially valid simple systems of enzyme

[77] catalysis. Assuming N = 1, while expressing [QFree] in terms its total concentration, and the total amount of unbound protein [PFree] as [PTotal], Equation 4 can be modified to show

[PFree] = [PTotal](1- θ) [Eq. 15]

Considering the above assumptions, while maintaining the prior two stipulations,

Equation 7 can be modified to show

퐹0−퐹 (푃+푄 +퐾 )−√(푃+ 푄 +퐾 )2−4푃푄 = 푇표푡푎푙 푑 푇표푡푎푙 푑 푇표푡푎푙 [Eq. 16] 퐹0−퐹∗ 2푃

where Kd values are expressed as association constants at equilibrium from the fitting of fluorescent intensities at various quencher and protein concentrations. To avoid confusion, Kas obtained from the quadratic equation will be written as KQu.

3.5 Scatchard’s Treatment

In data analysis of substrate-protein kinetics, Scatchard’s equation provides an excellent starting point for predicting an accurate number of binding sites, as well as being able to predict relatively accurate (within an order of magnitude) binding constants.

Scatchard’s equation is given by

59

푟 = 푁퐾 − 푟퐾 [Eq. 17] 푐 푎 푎

where r is the ratio of the bound substrate to the total amount of available binding sites, c is the concentration of free substrate, and N is number of binding sites per molecule.

When N is the number of equivalent and independent binding sites, Scatchard’s equation reduces to

n/[QFree] = KasN – Kasn [Eq. 18.1]

where n is the average number of bound polyphenols per protein.

For the purpose of this study, we will delegate the title KSc as a replacement for the

Scatchard’s treatment binding constant Kas to avoid confusion between this and other calculated binding constants, where Equation 18.1 can be rewritten as

n/[QFree] = KScN – Kasn [Eq. 18.2]

because

Kas = KSc [Eq. 19]

Plotting n/[QFree] v.s. n in a linear regression formula provides us with the values for N and Kas, where N is represented by the y-intercept, and Kas is represented by the

60

absolute value of the slope. Assessing the slope by its absolute value to determine the binding constant is necessary because a Scatchard plot actually provides the negative reciprocal of the disassociation constant (Kd).

The accuracy of Scatchard plots has come under debate for several reasons.

[75] Primarily, the estimation of n and [QFree] values are not straightforward. These parameters are generally estimated through their relationship with fluorescence intensity,

0 where given Stipulation 1 is maintained, θ = 퐹 −퐹. Remarkably, it is interesting to note 퐹0

퐹0−퐹 that manipulation of Stipulation 1 to F* ≠ 0, which effects a change in θ, (θ = ) 퐹0−퐹∗ results in considerable changes to N, with negligible change to the Kas, and maintenance of linearity.

The second reason Scatchard plots are called into question is due to the fact that the Scatchard equation is assumed by many to only be applicable when N = 1. This renders the use of Equation 18 as a contradiction to the estimation for the value of N.

Despite these shortcomings, Scatchard plots are commonly employed by many studies of substrate-protein activity to assess binding constants.[69]

Ultimately, upon further examination the largest argument made against

Scatchard plots is its accuracy in determining dissociation constants, and thus Kas. At higher concentrations for both substrate and protein, the accuracy is good due to high precision, and high reproducibility under the same experimental conditions. However, under lower concentrations of substrate and protein, accuracy, precision, and overall experimental reproducibility drop off drastically. This reduction in overall experimental accuracy can be attributed to the inability of the linear regression formula to weigh substrate concentration points differently, which ultimately leads to the error associated

61

with this calculation not remaining constant. Nevertheless, provided personal error is kept to a minimum, Scatchard plots are relatively useful in determining an estimate of the association constant, which can later be used in a non-linear fit to extract the best Ka.

3.6 Benesi-Hildebrand’s Treatment

Equating [QTotal] to [QFree], and when N = 1, while disregarding Stipulation 1,

Equation 7 can be rearranged to give the following

1 1 1 0 = 0 ∗ + 0 ∗ [Eq. 20.1] (퐹 −퐹) (퐹 −퐹 ) (퐹 −퐹 )퐾푎푠[푄푇표푡푎푙]

For the purpose of this study, we will delegate the title KBH as a replacement for the

Benesi-Hildebrand treatment binding constant Kas to avoid confusion between this and other calculated binding constants, where Equation 20.1 can be rewritten as

1 1 1 0 = 0 ∗ + 0 ∗ [Eq. 20.2] (퐹 −퐹) (퐹 −퐹 ) (퐹 −퐹 )퐾퐵퐻[푄푇표푡푎푙] because

Kas = KBH [Eq. 21]

Taking the inverse of the ratio of the left hand side of Equation 20 against F0, and

1 1 then plotting it against the total quencher concentration ( (퐹0−퐹) v.s. ) in a linear [푄푇표푡푎푙] 퐹0 regression formula yields KBH as the ratio of the y-intercept to the slope. These Benesi-

Hildebrand plots are commonly referred to as double-reciprocal fits. In regards to the

62

evaluation of F0 – F*, Stipulation 1 is overlooked, and the value obtained from the y- intercept can be looked at as nearly 1 , and thus close to 0. This is an important 퐹0 estimation because although many substrate-protein kinetic studies assume Stipulation 1, in actuality, even at a completely saturated protein where the ratio of substate bound to protein is 1:1, there is still a minor amount of fluorescence intensity observed, albeit very small. The accuracy of Benesi-Hildebrand plots in their assessment of Kas have come under fire as well, for the main reason that certain data points cannot be weighted heavier than others, and thus sources of error do not remain constant. Hence, these double- reciprocal fits have a similar ability to plots of Scatchard’s treatment when it comes to

[75] predicting Kas, and normally are within one order of magnitude as well .

While this study will determine the binding constants of 40 different polyphenols with both BSA and LDL-VLDL using the above five mentioned techniques (Stern-

Volmer, Double Logarithm, Quadratic, Scatchard, and Benesi-Hildebrand), emphasis of interpretation of factors that contribute to calculated binding constants will be placed on the Stern-Volmer and Double Logarithm techniques.

4.0 Results and Discussion

4.1 Determination of LDL-VLDL Plasma Source

Because the basis of this study is to determine the amount of quenching a polyphenol has on BSA and LDL-VLDL, it was necessary to use the least oxidized protein and lipoprotein sources. Since BSA remains fairly un-oxidized in solution, focus shifted toward the LDL-VLDL superparticle. In an effort to determine if time from procurement until storage was a variable, three different samples of porcine blood were

63

acquired; their definition relies on the amount of time they spent in a refrigerator at 4°C after arrival from mailing: the three samples were 48-hour (2-day), 24-hour (1-day), and

8-hour old blood.

Since oxidation is linked to higher absorbance and fluorescence values [78], the

Bradford assay method along with the dilution of the β-fraction via fluorescence spectroscopy was carried out as previously described in order to determine the least oxidized lipoprotein source. Through linear regression, standards were plotted at various concentrations resulting in the linear equation y = 0.00040x + 0.04310. From this equation, concentrations of LDL-VLDL in optimized β-fractions were determined through their Apo B-100 content, resulting in 54.26 μg/ml for 2-day old LDL-VLDL,

34.92 μg/ml for 1-day old LDL-VLDL, and 28.55 μg/ml for 8-hour old LDL-VLDL. As

Figure X shows, higher levels of oxidation greatly affect the binding constant of polyphenols with LDL-VLDL, with the binding constants for 2-day old LDL-VLDL as

8.30880E+04 M-1, 1-day old LDL-VLDL as 1.00368E+05 M-1, and 8-hour old LDL-

VLDL as 1.90588E+05 M-1 (time indicating use after delivery and retrieval).

64

Stern-Volmer Plot - 2-Day Old Plasma (Apocynin-LDL/VLDL)

1.18 1.16 y = 83088x + 1.073 1.14 R² = 0.9972 F0/F 1.12 1.1 1.08 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] a)

Stern-Volmer Plot 1-Day Old Plasma (Apocynin-LDL/VLDL) 1.14 1.12 y = 100368x + 1.0225 1.1 R² = 0.9967 F0/F 1.08 1.06 1.04 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] b)

Stern-Volmer Plot - 8-Hour Old Plasma (Apocynin-LDL/VLDL)

1.25 1.2 y = 190588x + 1.0075 R² = 0.9987 F0/F 1.15 1.1 1.05 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] c) Fig 44: Stern-Volmer plots of apocynin and LDL-VLDL at a) 2 days, b) 1 day, and c) 8 hours after delivery of lipoprotein.

65

It would appear that, in respects to LDL-VLDL aging, more time spent in storage results in higher levels of oxidation, and thus a decreased binding constant via the Stern-

Volmer method. This idea was further supported by the increasing amount of PBS needed to dilute β-fractions in order to normalize them, because oxidation of LDL-VLDL is known to increase fluorescence. As a result, all LDL-VLDL containing samples used in this study were from the 8-hour old source.

4.2.0 Incorporation of Polyphenol into BSA and LDL-VLDL

It is interesting to note that linearity in all plots is maintained, which indicates that there is only one type of quenching mechanism occurring (either static or dynamic).[79] Because this study focuses on binding constants between polyphenols and their respective proteins, it is essential to identify evidence for some degree of static binding (polyphenol-protein complex formation). As mentioned previously, two techniques were utilized to confirm whether a complex was being formed: Calculation of the bimolecular rate constant, and FT-IR spectroscopy.

4.2.1 Bimolecular Rate Constants (kqs)

Bimolecular rate constants (kqs) for each polyphenol and either BSA or LDL-

VLDL were obtained from Equation 10 using the respective calculated KSV values, along with the average literature values for τ0, (~5ns for BSA and ~1.25 ns for LDL). Table X shows that all calculated kqs are several orders of magnitude above the upper limits of diffusion-controlled binding (1 x 1010 M-1 s-1), lending support to the idea that static

66

binding, and therefore the formation of a polyphenol-protein complex, is the mechanism by which polyphenols quench BSA and LDL-VLDL.

Table 2: Bimolecular rate constants of all polyphenols with BSA and LDL-VLDL via the Stern-Volmer method

-1 -1 -1 -1 Polyphenol Kq (PP-BSA) (M s ) Kq (PP-LDL-VLDL) (M s )

Pterostilbene(1,a) 1.16E+14 3.15E+14

Resveratrol(1,a) 6.17E+13 1.99E+14 Quercetin(2,b) 1.39E+14 2.09E+14 Quercetin-3-glucuronide(2,b) 8.05E+13 1.74E+14

Quercetin-3-glucoside(2,b) 4.19E+13 1.48E+14 Biochanin A(2,c) 5.17E+13 2.10E+14 Puerarin(2,c) 4.33E+13 1.51E+14 Chrysin(2,d) 1.01E+14 3.07E+14

Baicalein(2,d) 9.54E+13 2.14E+14

Baicalin(2,d) 7.61E+13 1.72E+14

Flavone(2,d) 5.11E+13 1.33E+14

Pelargonidin Chloride(2,e) 8.41E+13 1.39E+14

Dopac(2,f) 5.62E+13 8.84E+13 m-Hydroxyphenylacteic acid(2,f) 1.50E+13 9.52E+13 p-Hydroxyphenylacteic acid(2,f) 1.25E+13 5.96E+13 Homogentisic acid(2,f) 3.12E+13 7.82E+13

Ellagic acid(2,g) 4.00E+14 2.17E+14

Eudesmic acid(2,g) 4.59E+13 1.59E+14

Syringic acid(2,g) 1.93E+13 7.52E+13

Gallic acid(2,g) 8.91E+13 1.41E+14

Protocatechuic acid(2,g) 3.87E+13 1.30E+14 m-Hydroxybenzoic acid(2,g) 3.50E+13 1.24E+14 p-Hydroxybenzoic acid(2,g) 3.32E+13 1.09E+14 p-Hydroxysalicylic acid(2,g) 2.05E+13 1.06E+14

Apocynin(2,g) 3.17E+13 1.54E+14

Vanillic acid(2,g) 1.86E+13 7.34E+13

Chlorogenic acid(2,h) 1.20E+14 2.17E+14

Ferulic acid(2,h) 5.38E+13 1.72E+14

Isoferulic acid(2,h) 3.38E+13 1.32E+14

Isoferulic acid-3-o-glucuronide(2,h) 3.16E+13 1.22E+14

Dihydroferulic acid(2,h) 2.71E+13 9.16E+13

Caffeic acid(2,h) 4.79E+13 1.65E+14

Caffeic acid-3-o-glucuronide(2,h) 4.46E+13 1.41E+14

Caffeic acid-4-o-glucuronide(2,h) 3.32E+13 1.16E+14 Dihydrocaffeic acid(2,h) 3.19E+13 1.15E+14 Dihydrocaffeic acid-3-o-glucuronide(2,h) 2.44E+13 6.87E+13

Dihydrocaffeic acid-3-o-sulfate(2,h) 2.36E+13 9.25E+13 Sinapic acid(2,h) 3.24E+13 1.04E+14 o-Coumaric acid(2,h) 3.04E+13 8.39E+13 p-Coumaric acid(2,h) 2.71E+13 7.15E+13 *Abbreviations in table: 1) Polyphenol (PP) Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

67

4.2.2 Incorporation of Polyphenol into Protein/Lipoprotein via FT-IR

The second method used to determine the type of quenching mechanism that occurs between a polyphenol and both BSA and LDL-VLDL was FT-IR spectroscopy.

According to Krilov et. al., if static binding is in fact the main quenching mechanism, it will be visible via FT-IR spectroscopy through shifts in certain key bands (both in wavenumber and intensity), in particular the amide I band (~1640-1650 cm-1) for a lipoprotein.[80] Using this method for LDL-VLDL, as well as applying it to BSA, amide I band shifts were observed.

a) b) c) d) Figure 45: Amide I band of a) BSA, b) Pterostilbene-BSA, c) Chrysin-BSA, and d) p-Hydroxybenzoic acid-BSA. (Peaks observed in the 1430-1480 cm-1 regions are a result of the polyethylene films.)

a) b) c) d) Figure 46: Amide I band of a) LDL-VLDL, b) Pterostilbene-LDL-VLDL, c) Chrysin-LDL-VLDL, and d) p-Hydroxybenzoic acid- LDL-VLDL. (Peaks observed in the 1430-1480 cm-1 regions are a result of the polyethylene films.)

68

These FT-IR spectra taken on polyethylene films lend further support that static quenching is the mechanism by which a polyphenol quenches BSA and LDL-VLDL

(Similar results were obtained with CaF2 plates, however amide I band intensities were much smaller, and much of the upper spectrum was distorted by water.)

Additionally, through Stern-Volmer plots, one interesting aspect to note is the high level of protein-quenching occurring given the low [QTotal] values. This observation also lends support to the idea that static binding is the main type of quenching mechanism, because it does not involve multiple binding events of the quencher during the excited Trp fluorophore lifetime.[75]

4.3 Binding Constants (Kas)

The following ten tables list the calculated binding constants between all 40 polyphenols first with BSA, then with LDL-VLDL, per each of the five methods. In each table, the name of the polyphenol, along with its class, subclass, calculated binding constant with the listed protein, calculated Gibbs free energy, standard deviation, and percent standard deviation is provided. Additionally, other pertinent data is provided as well. Stern-Volmer, Double-Logarithm, and Scatchard’s method tables provide n, which is either the affinity in terms of polyphenol/protein ratio as per the Hill equation, for both the Stern-Volmer and Double-Logarithm method, or the number of equivalent and non- equivalent binding sites as per Scatchard’s method. Additionally, the calculated bimolecular rate constant is provided for all Stern-Volmer tables.

69

Table 3: Stern-Volmer method between Polyphenol and BSA Polyphenol Avg.-KSV Kq n ΔG° Std. Deviation % Std. Deviation (M-1) (M-1 s-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 5.81765E+05 1.16E+14 1.0829 -2.76E+03 2.98E+04 5.12 Resveratrol(1,a) 3.08309E+05 6.17E+13 1.0752 -2.63E+03 7.35E+03 2.38 Quercetin(2,b) 6.96324E+05 1.39E+14 0.9853 -2.80E+03 3.14E+04 4.51 Quercetin-3-glucuronide(2,b) 4.02626E+05 8.05E+13 1.1369 -2.68E+03 2.07E+04 5.15 Quercetin-3-glucoside(2,b) 2.09454E+05 4.19E+13 0.9903 -2.55E+03 1.56E+04 7.45 Biochanin A(2,c) 2.58640E+05 5.17E+13 1.0193 -2.59E+03 1.60E+04 6.20 Puerarin(2,c) 2.16250E+05 4.33E+13 1.0367 -2.55E+03 9.68E+03 4.48 Chrysin(2,d) 5.04265E+05 1.01E+14 0.9768 -2.73E+03 2.55E+04 5.07 Baicalein(2,d) 4.76971E+05 9.54E+13 1.1929 -2.72E+03 1.87E+04 3.92 Baicalin(2,d) 3.80551E+05 7.61E+13 1.0113 -2.67E+03 1.34E+04 3.52 Flavone(2,d) 2.55588E+05 5.11E+13 1.0035 -2.59E+03 7.26E+03 2.84 Pelargonidin Chloride(2,e) 4.20588E+05 8.41E+13 0.9823 -2.69E+03 2.33E+04 5.53 Dopac(2,f) 2.80772E+05 5.62E+13 0.9914 -2.61E+03 1.08E+04 3.85 m-Hydroxyphenylacteic acid(2,f) 7.50740E+04 1.50E+13 1.0656 -2.33E+03 2.85E+03 3.79 p-Hydroxyphenylacteic acid(2,f) 6.26470E+04 1.25E+13 1.0453 -2.30E+03 3.54E+03 5.65 Homogentisic acid(2,f) 1.55987E+05 3.12E+13 0.9927 -2.49E+03 3.47E+03 2.23 Ellagic acid(2,g) 2.00000E+06 4.00E+14 1.0090 -3.02E+03 0.00E+00 0.00 Eudesmic acid(2,g) 2.29265E+05 4.59E+13 1.0624 -2.57E+03 1.35E+04 5.90 Syringic acid(2,g) 9.63240E+04 1.93E+13 1.0095 -2.39E+03 6.11E+03 6.34 Gallic acid(2,g) 4.45625E+05 8.91E+13 0.9165 -2.70E+03 2.30E+04 5.17 Protocatechuic acid(2,g) 1.93346E+05 3.87E+13 1.0312 -2.53E+03 8.53E+03 4.41 m-Hydroxybenzoic acid(2,g) 1.75129E+05 3.50E+13 1.0304 -2.51E+03 6.45E+03 3.69 p-Hydroxybenzoic acid(2,g) 1.65956E+05 3.32E+13 1.0474 -2.50E+03 3.46E+03 2.08 p-Hydroxysalicylic acid(2,g) 1.02626E+05 2.05E+13 1.0251 -2.40E+03 1.70E+03 1.66 Apocynin(2,g) 1.58403E+05 3.17E+13 1.0399 -2.49E+03 8.79E+03 5.55 Vanillic acid(2,g) 9.29620E+04 1.86E+13 0.9940 -2.38E+03 5.66E+03 6.09 Chlorogenic acid(2,h) 6.01029E+05 1.20E+14 0.9059 -2.77E+03 1.88E+04 3.13 Ferulic acid(2,h) 2.69154E+05 5.38E+13 0.9480 -2.60E+03 9.60E+03 3.57 Isoferulic acid(2,h) 1.68807E+05 3.38E+13 1.0049 -2.50E+03 5.98E+03 3.54 Isoferulic acid-3-o-glucuronide(2,h) 1.58162E+05 3.16E+13 1.0420 -2.49E+03 5.03E+03 3.18 Dihydroferulic acid(2,h) 1.35662E+05 2.71E+13 1.0093 -2.46E+03 6.84E+02 0.50 Caffeic acid(2,h) 2.39265E+05 4.79E+13 0.9977 -2.57E+03 4.23E+03 1.77 Caffeic acid-3-o-glucuronide(2,h) 2.23214E+05 4.46E+13 1.0543 -2.56E+03 1.11E+04 4.97 Caffeic acid-4-o-glucuronide(2,h) 1.66029E+05 3.32E+13 1.0204 -2.50E+03 7.59E+03 4.57 Dihydrocaffeic acid(2,h) 1.59454E+05 3.19E+13 1.1055 -2.49E+03 1.89E+03 1.19 Dihydrocaffeic acid-3-o- 1.22169E+05 2.44E+13 1.0362 -2.43E+03 4.93E+03 4.04 glucuronide(2,h) Dihydrocaffeic acid-3-o-sulfate(2,h) 1.17962E+05 2.36E+13 0.9992 -2.43E+03 4.73E+03 4.01 Sinapic acid(2,h) 1.62080E+05 3.24E+13 0.9915 -2.49E+03 1.08E+04 6.65 o-Coumaric acid(2,h) 1.52101E+05 3.04E+13 0.9789 -2.48E+03 6.43E+03 4.23 p-Coumaric acid(2,h) 1.35714E+05 2.71E+13 1.0845 -2.46E+03 2.81E+03 2.07 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

70

Table 4: Stern-Volmer method between Polyphenol and LDL-VLDL Polyphenol Avg.-KSV Kq n ΔG° Std. Deviation % Std. Deviation (M-1) (M-1 s-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 3.93676E+05 3.15E+14 1.0501 -2.68E+03 8.94E+03 2.27 Resveratrol(1,a) 2.49154E+05 1.99E+14 1.0273 -2.58E+03 1.16E+04 4.66 Quercetin(2,b) 2.61213E+05 2.09E+14 1.0392 -2.59E+03 7.75E+03 2.97 Quercetin-3-glucuronide(2,b) 2.17353E+05 1.74E+14 1.0606 -2.55E+03 6.39E+03 2.94 Quercetin-3-glucoside(2,b) 1.85184E+05 1.48E+14 1.0376 -2.52E+03 6.13E+03 3.31 Biochanin A(2,c) 2.62132E+05 2.10E+14 1.0125 -2.59E+03 1.10E+04 4.21 Puerarin(2,c) 1.88860E+05 1.51E+14 1.0494 -2.53E+03 7.41E+03 3.92 Chrysin(2,d) 3.84301E+05 3.07E+14 1.0238 -2.67E+03 1.71E+04 4.44 Baicalein(2,d) 2.68051E+05 2.14E+14 1.0382 -2.60E+03 1.42E+04 5.29 Baicalin(2,d) 2.14412E+05 1.72E+14 1.0383 -2.55E+03 1.24E+04 5.80 Flavone(2,d) 1.66581E+05 1.33E+14 1.0452 -2.50E+03 9.13E+03 5.48 Pelargonidin Chloride(2,e) 1.73676E+05 1.39E+14 1.0893 -2.51E+03 1.35E+04 7.77 Dopac(2,f) 1.10515E+05 8.84E+13 1.0228 -2.41E+03 3.47E+03 3.14 m-Hydroxyphenylacteic acid(2,f) 1.19044E+05 9.52E+13 1.0053 -2.43E+03 4.88E+03 4.10 p-Hydroxyphenylacteic acid(2,f) 7.45600E+04 5.96E+13 1.0370 -2.33E+03 3.38E+03 4.54 Homogentisic acid(2,f) 9.77940E+04 7.82E+13 1.0995 -2.39E+03 7.67E+03 7.85 Ellagic acid(2,g) 2.71287E+05 2.17E+14 1.0291 -2.60E+03 2.02E+04 7.45 Eudesmic acid(2,g) 1.98824E+05 1.59E+14 1.0244 -2.54E+03 1.48E+04 7.45 Syringic acid(2,g) 9.39710E+04 7.52E+13 1.0474 -2.38E+03 2.83E+03 3.01 Gallic acid(2,g) 1.76654E+05 1.41E+14 1.0094 -2.51E+03 5.96E+03 3.37 Protocatechuic acid(2,g) 1.62390E+05 1.30E+14 1.0454 -2.49E+03 8.96E+03 5.52 m-Hydroxybenzoic acid(2,g) 1.55147E+05 1.24E+14 1.0404 -2.48E+03 1.73E+03 1.11 p-Hydroxybenzoic acid(2,g) 1.36397E+05 1.09E+14 1.0379 -2.46E+03 7.41E+03 5.43 p-Hydroxysalicylic acid(2,g) 1.32390E+05 1.06E+14 1.0512 -2.45E+03 1.05E+03 0.79 Apocynin(2,g) 1.93015E+05 1.54E+14 1.0430 -2.53E+03 9.32E+03 4.83 Vanillic acid(2,g) 9.17650E+04 7.34E+13 1.0626 -2.38E+03 1.40E+03 1.53 Chlorogenic acid(2,h) 2.71029E+05 2.17E+14 1.0207 -2.60E+03 1.05E+04 3.86 Ferulic acid(2,h) 2.14706E+05 1.72E+14 1.0491 -2.55E+03 7.37E+03 3.43 Isoferulic acid(2,h) 1.65441E+05 1.32E+14 1.0115 -2.50E+03 4.57E+03 2.76 Isoferulic acid-3-o-glucuronide(2,h) 1.52022E+05 1.22E+14 1.0180 -2.48E+03 5.67E+03 3.73 Dihydroferulic acid(2,h) 1.14449E+05 9.16E+13 1.0539 -2.42E+03 8.50E+03 7.43 Caffeic acid(2,h) 2.06544E+05 1.65E+14 1.0582 -2.54E+03 1.36E+04 6.56 Caffeic acid-3-o-glucuronide(2,h) 1.75809E+05 1.41E+14 1.0697 -2.51E+03 1.05E+04 6.00 Caffeic acid-4-o-glucuronide(2,h) 1.44853E+05 1.16E+14 1.0529 -2.47E+03 1.03E+04 7.11 Dihydrocaffeic acid(2,h) 1.43787E+05 1.15E+14 1.0483 -2.47E+03 1.13E+04 7.87 Dihydrocaffeic acid-3-o- 1.15625E+05 9.25E+13 1.0399 -2.42E+03 8.96E+03 7.75 glucuronide(2,h) Dihydrocaffeic acid-3-o-sulfate(2,h) 8.59190E+04 6.87E+13 1.0549 -2.36E+03 4.52E+03 5.26 Sinapic acid(2,h) 1.30515E+05 1.04E+14 1.0185 -2.45E+03 1.78E+03 1.36 o-Coumaric acid(2,h) 1.04890E+05 8.39E+13 1.0384 -2.40E+03 9.26E+03 8.82 p-Coumaric acid(2,h) 8.93380E+04 7.15E+13 1.0705 -2.37E+03 5.66E+03 6.33 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

71

Table 5: Double-Logarithm method between Polyphenol and BSA Polyphenol Avg.-KDL n ΔG° Std. Deviation % Std. Deviation (M-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 6.60426E+05 0.9685 -2.79E+03 2.67E+04 4.04 Resveratrol(1,a) 3.53140E+05 0.5214 -2.66E+03 2.07E+04 5.86 Quercetin(2,b) 6.91400E+05 1.0501 -2.80E+03 3.40E+04 4.92 Quercetin-3-glucuronide(2,b) 5.02384E+05 0.8593 -2.73E+03 2.34E+04 4.66 Quercetin-3-glucoside(2,b) 2.37271E+05 1.1254 -2.57E+03 1.70E+04 7.15 Biochanin A(2,c) 2.56825E+05 0.9318 -2.59E+03 1.42E+04 5.53 Puerarin(2,c) 1.79739E+05 0.7972 -2.51E+03 4.87E+03 2.71 Chrysin(2,d) 5.26141E+05 1.1212 -2.74E+03 1.73E+04 3.29 Baicalein(2,d) 4.65144E+05 0.9413 -2.71E+03 6.07E+03 1.30 Baicalin(2,d) 3.02992E+05 0.8886 -2.62E+03 1.99E+04 6.57 Flavone(2,d) 2.79672E+05 1.0431 -2.61E+03 1.66E+04 5.95 Pelargonidin Chloride(2,e) 3.75650E+05 1.0477 -2.67E+03 6.58E+03 1.75 Dopac(2,f) 2.85125E+05 1.0408 -2.61E+03 1.40E+03 0.49 m-Hydroxyphenylacteic acid(2,f) 7.80400E+03 0.4048 -1.86E+03 7.75E+02 9.93 p-Hydroxyphenylacteic acid(2,f) 7.01200E+03 0.4496 -1.84E+03 5.95E+02 8.49 Homogentisic acid(2,f) 1.53681E+05 1.0224 -2.48E+03 7.75E+03 5.04 Ellagic acid(2,g) 1.58846E+06 1.0663 -2.97E+03 1.13E+05 7.11 Eudesmic acid(2,g) 2.08187E+05 0.7505 -2.55E+03 4.08E+03 1.96 Syringic acid(2,g) 1.00902E+05 0.9743 -2.39E+03 2.19E+03 2.17 Gallic acid(2,g) 4.77312E+05 1.4091 -2.72E+03 1.62E+04 3.39 Protocatechuic acid(2,g) 1.53567E+05 0.7955 -2.48E+03 6.97E+03 4.54 m-Hydroxybenzoic acid(2,g) 1.82885E+05 0.8807 -2.52E+03 5.17E+03 2.83 p-Hydroxybenzoic acid(2,g) 1.22821E+05 0.7281 -2.44E+03 2.04E+03 1.66 p-Hydroxysalicylic acid(2,g) 7.96540E+04 0.8047 -2.35E+03 1.20E+03 1.50 Apocynin(2,g) 1.12104E+05 0.7295 -2.42E+03 2.87E+03 2.56 Vanillic acid(2,g) 1.51633E+05 1.2943 -2.48E+03 6.20E+03 4.09 Chlorogenic acid(2,h) 6.57897E+05 1.5222 -2.78E+03 3.28E+04 4.98 Ferulic acid(2,h) 4.74937E+05 0.9596 -2.72E+03 2.32E+04 4.89 Isoferulic acid(2,h) 1.61208E+05 0.9639 -2.49E+03 7.79E+03 4.83 Isoferulic acid-3-o-glucuronide(2,h) 9.66170E+04 0.6892 -2.39E+03 4.28E+03 4.43 Dihydroferulic acid(2,h) 8.26790E+04 0.7687 -2.35E+03 1.29E+03 1.56 Caffeic acid(2,h) 3.08474E+05 1.1408 -2.63E+03 2.13E+04 6.89 Caffeic acid-3-o-glucuronide(2,h) 1.88169E+05 0.7536 -2.52E+03 8.67E+02 0.46

Caffeic acid-4-o-glucuronide(2,h) 1.25159E+05 0.8116 -2.44E+03 5.78E+03 4.62

Dihydrocaffeic acid(2,h) 1.09963E+05 0.577 -2.41E+03 4.40E+03 4.00

Dihydrocaffeic acid-3-o-glucuronide(2,h) 7.94480E+04 0.7206 -2.35E+03 3.14E+03 3.96

Dihydrocaffeic acid-3-o-sulfate(2,h) 1.04482E+05 0.9506 -2.40E+03 1.62E+03 1.55

Sinapic acid(2,h) 1.78738E+05 1.0939 -2.51E+03 3.45E+03 1.93 o-Coumaric acid(2,h) 2.14378E+05 1.347 -2.55E+03 8.11E+03 3.78 p-Coumaric acid(2,h) 6.38980E+04 0.5393 -2.30E+03 1.90E+03 2.98

Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

72

Table 6: Double-Logarithm method between Polyphenol and LDL-VLDL Polyphenol Avg.-KDL n ΔG° Std. Deviation % Std. Deviation (M-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 3.70553E+05 0.8199 -2.67E+03 2.58E+04 6.97 Resveratrol(1,a) 2.12189E+05 0.8319 -2.55E+03 7.23E+03 3.41 Quercetin(2,b) 2.20924E+05 0.7974 -2.56E+03 1.21E+04 5.47 Quercetin-3-glucuronide(2,b) 1.47041E+05 0.6701 -2.47E+03 8.95E+03 6.09 Quercetin-3-glucoside(2,b) 1.29897E+05 0.7368 -2.45E+03 2.99E+03 2.30 Biochanin A(2,c) 2.54060E+05 0.9339 -2.59E+03 1.05E+04 4.14 Puerarin(2,c) 1.25851E+05 0.6930 -2.44E+03 9.28E+02 0.74 Chrysin(2,d) 3.68845E+05 0.9006 -2.66E+03 2.44E+04 6.62 Baicalein(2,d) 2.33150E+05 0.8114 -2.57E+03 9.25E+03 3.97 Baicalin(2,d) 1.78332E+05 0.7929 -2.51E+03 3.27E+03 1.83 Flavone(2,d) 9.88100E+04 0.6731 -2.39E+03 3.51E+03 3.56 Pelargonidin Chloride(2,e) 7.73850E+04 0.5245 -2.34E+03 1.35E+03 1.74 Dopac(2,f) 5.22800E+04 0.6877 -2.26E+03 2.40E+03 4.59 m-Hydroxyphenylacteic acid(2,f) 4.84710E+04 0.7192 -2.24E+03 2.14E+03 4.42 p-Hydroxyphenylacteic acid(2,f) 1.45980E+04 2.1925 -1.99E+03 1.02E+03 6.96 Homogentisic acid(2,f) 2.00690E+04 0.4512 -2.06E+03 3.31E+02 1.65 Ellagic acid(2,g) 2.10823E+05 0.7860 -2.55E+03 1.12E+04 5.29 Eudesmic acid(2,g) 1.76387E+05 0.8419 -2.51E+03 1.75E+03 0.99 Syringic acid(2,g) 2.70670E+04 0.5425 -2.12E+03 7.78E+02 2.87 Gallic acid(2,g) 1.46939E+05 0.8837 -2.47E+03 4.27E+03 2.91 Protocatechuic acid(2,g) 1.00811E+05 0.6843 -2.39E+03 5.81E+03 5.76 m-Hydroxybenzoic acid(2,g) 9.16920E+04 0.6849 -2.38E+03 4.34E+03 4.73 p-Hydroxybenzoic acid(2,g) 7.49260E+04 0.6756 -2.33E+03 6.43E+03 8.58 p-Hydroxysalicylic acid(2,g) 5.86900E+04 0.5993 -2.28E+03 5.33E+03 9.08 Apocynin(2,g) 1.39137E+05 0.7320 -2.46E+03 7.24E+03 5.20 Vanillic acid(2,g) 1.52640E+04 0.4492 -2.00E+03 6.58E+02 4.31 Chlorogenic acid(2,h) 2.47913E+05 0.8841 -2.58E+03 1.65E+04 6.65 Ferulic acid(2,h) 1.60933E+05 0.7404 -2.49E+03 9.93E+03 6.17 Isoferulic acid(2,h) 1.19218E+05 0.8213 -2.43E+03 5.71E+03 4.79 Isoferulic acid-3-o-glucuronide(2,h) 1.14832E+05 0.8208 -2.42E+03 4.47E+03 3.89 Dihydroferulic acid(2,h) 4.46680E+04 0.5720 -2.23E+03 1.59E+03 3.55 Caffeic acid(2,h) 1.52498E+05 0.7290 -2.48E+03 9.14E+03 5.99 Caffeic acid-3-o-glucuronide(2,h) 1.28712E+05 0.6331 -2.45E+03 4.35E+03 3.38 Caffeic acid-4-o-glucuronide(2,h) 7.61070E+04 0.6283 -2.34E+03 2.97E+03 3.90 Dihydrocaffeic acid(2,h) 7.37570E+04 0.6339 -2.33E+03 7.22E+03 9.79 Dihydrocaffeic acid-3-o-glucuronide(2,h) 4.85870E+04 0.6179 -2.24E+03 2.99E+03 6.16 Dihydrocaffeic acid-3-o-sulfate(2,h) 1.66910E+04 0.4679 -2.02E+03 7.88E+02 4.72 Sinapic acid(2,h) 1.17595E+05 0.8794 -2.43E+03 4.35E+03 3.70 o-Coumaric acid(2,h) 8.74730E+04 0.6985 -2.37E+03 1.50E+03 1.72 p-Coumaric acid(2,h) 6.82660E+04 0.4964 -2.31E+03 2.89E+03 4.24 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

73

Table 7: Scatchard’s method between Polyphenol and BSA Polyphenol Avg.-KSc n ΔG° Std. Deviation % Std. Deviation (M-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 3.29882E+05 0.7507 -2.64E+03 3.13E+04 9.50 Resveratrol(1,a) 1.64963E+05 0.4686 -2.50E+03 1.24E+04 7.54 Quercetin(2,b) 1.58245E+05 0.5732 -2.49E+03 1.19E+04 7.54 Quercetin-3-glucuronide(2,b) 1.95669E+05 0.5764 -2.53E+03 1.89E+04 9.64 Quercetin-3-glucoside(2,b) 1.86430E+04 0.1807 -2.04E+03 2.39E+03 12.81 Biochanin A(2,c) 8.58130E+04 0.3045 -2.36E+03 3.46E+03 4.03 Puerarin(2,c) 1.30301E+05 0.3306 -2.45E+03 1.02E+04 7.86 Chrysin(2,d) 1.40904E+05 0.4818 -2.46E+03 1.37E+04 9.69 Baicalein(2,d) 5.66026E+05 0.9588 -2.75E+03 3.86E+04 6.81 Baicalin(2,d) 1.41603E+05 0.4186 -2.47E+03 1.59E+04 11.23 Flavone(2,d) 1.11923E+05 0.3357 -2.42E+03 1.46E+04 13.07 Pelargonidin Chloride(2,e) 1.31096E+05 0.3869 -2.45E+03 1.62E+04 12.37 Dopac(2,f) 3.99260E+04 0.2548 -2.20E+03 7.75E+02 1.94 m-Hydroxyphenylacteic acid(2,f) 1.96471E+05 0.3134 -2.53E+03 1.42E+04 7.21 p-Hydroxyphenylacteic acid(2,f) 1.38059E+05 0.2311 -2.46E+03 7.14E+03 5.17 Homogentisic acid(2,f) 1.29810E+04 0.1413 -1.97E+03 1.78E+03 13.69 Ellagic acid(2,g) 6.27489E+05 1.2492 -2.77E+03 4.45E+04 7.09 Eudesmic acid(2,g) 2.47816E+05 0.4532 -2.58E+03 3.40E+04 13.73 Syringic acid(2,g) 4.45900E+04 0.1616 -2.23E+03 7.65E+03 17.16 Gallic acid(2,g) 8.60290E+04 0.2965 -2.36E+03 3.22E+03 3.75 Protocatechuic acid(2,g) 1.13610E+05 0.2951 -2.42E+03 9.73E+03 8.56 m-Hydroxybenzoic acid(2,g) 8.04930E+04 0.2620 -2.35E+03 7.70E+03 9.56 p-Hydroxybenzoic acid(2,g) 1.37051E+05 0.3124 -2.46E+03 6.74E+03 4.92 p-Hydroxysalicylic acid(2,g) 4.36690E+04 0.1646 -2.22E+03 7.30E+03 16.71 Apocynin(2,g) 9.01160E+04 0.2711 -2.37E+03 4.89E+03 5.43 Vanillic acid(2,g) 1.52500E+04 0.1125 -2.00E+03 1.64E+03 10.76 Chlorogenic acid(2,h) 1.33195E+05 0.4059 -2.45E+03 1.23E+04 9.25 Ferulic acid(2,h) 2.68496E+05 0.5465 -2.60E+03 4.20E+03 1.56 Isoferulic acid(2,h) 2.85610E+04 0.1772 -2.13E+03 4.29E+03 15.02 Isoferulic acid-3-o-glucuronide(2,h) 7.33090E+04 0.2167 -2.33E+03 6.43E+03 8.78 Dihydroferulic acid(2,h) 1.92610E+04 0.1620 -2.05E+03 1.43E+03 7.45 Caffeic acid(2,h) 6.30810E+04 0.2594 -2.30E+03 7.92E+03 12.55 Caffeic acid-3-o-glucuronide(2,h) 1.22180E+05 0.3596 -2.43E+03 1.41E+03 1.16 Caffeic acid-4-o-glucuronide(2,h) 8.39850E+04 0.2385 -2.36E+03 8.77E+03 10.44 Dihydrocaffeic acid(2,h) 5.77460E+04 0.2089 -2.28E+03 8.67E+03 15.02 Dihydrocaffeic acid-3-o-glucuronide(2,h) 1.02221E+05 0.2386 -2.40E+03 9.16E+03 8.96 Dihydrocaffeic acid-3-o-sulfate(2,h) 2.21570E+04 0.1280 -2.08E+03 1.62E+03 7.29 Sinapic acid(2,h) 8.77800E+03 0.1388 -1.89E+03 2.35E+03 26.73 o-Coumaric acid(2,h) 3.49540E+04 0.1391 -2.17E+03 2.51E+03 7.17 p-Coumaric acid(2,h) 1.58022E+05 0.3687 -2.49E+03 1.27E+04 8.03 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

74

Table 8: Scatchard’s method between Polyphenol and LDL-VLDL Polyphenol Avg.-KSc n ΔG° Std. Deviation % Std. Deviation (M-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 2.66555E+05 0.5660 -2.64E+03 2.56E+04 9.60 Resveratrol(1,a) 1.25629E+05 0.3392 -2.50E+03 9.62E+03 7.65 Quercetin(2,b) 1.57066E+05 0.3849 -2.49E+03 1.41E+04 8.99 Quercetin-3-glucuronide(2,b) 2.08103E+05 0.4198 -2.53E+03 1.83E+04 8.81 Quercetin-3-glucoside(2,b) 1.35912E+05 0.3147 -2.04E+03 1.39E+04 10.19 Biochanin A(2,c) 7.93790E+04 0.2947 -2.36E+03 1.19E+04 14.97 Puerarin(2,c) 1.66735E+05 0.3550 -2.45E+03 1.13E+04 6.78 Chrysin(2,d) 1.59338E+05 0.4467 -2.46E+03 1.15E+04 7.21 Baicalein(2,d) 1.53842E+05 0.3857 -2.75E+03 1.73E+04 11.23 Baicalin(2,d) 1.32136E+05 0.3326 -2.47E+03 1.43E+04 10.80 Flavone(2,d) 1.54882E+05 0.3251 -2.42E+03 1.84E+04 11.89 Pelargonidin Chloride(2,e) 2.77713E+05 0.4768 -2.45E+03 3.62E+04 13.05 Dopac(2,f) 9.06840E+04 0.2047 -2.20E+03 1.42E+04 15.70 m-Hydroxyphenylacteic acid(2,f) 7.34520E+04 0.1726 -2.53E+03 6.03E+03 8.21 p-Hydroxyphenylacteic acid(2,f) 1.38618E+05 0.2257 -2.46E+03 1.42E+04 10.24 Homogentisic acid(2,f) 2.16897E+05 0.3566 -1.97E+03 2.53E+04 11.67 Ellagic acid(2,g) 1.60195E+05 0.3843 -2.77E+03 1.92E+04 11.97 Eudesmic acid(2,g) 1.46026E+05 0.3009 -2.58E+03 1.39E+04 9.53 Syringic acid(2,g) 1.45103E+05 0.2648 -2.23E+03 1.56E+04 10.78 Gallic acid(2,g) 5.98820E+04 0.2145 -2.36E+03 1.07E+04 17.85 Protocatechuic acid(2,g) 1.48129E+05 0.3167 -2.42E+03 6.50E+03 4.39 m-Hydroxybenzoic acid(2,g) 1.37860E+05 0.2975 -2.35E+03 1.41E+04 10.19 p-Hydroxybenzoic acid(2,g) 1.25750E+05 0.2708 -2.46E+03 9.86E+03 7.84 p-Hydroxysalicylic acid(2,g) 1.63283E+05 0.3136 -2.22E+03 1.61E+04 9.84 Apocynin(2,g) 1.47952E+05 0.3354 -2.37E+03 1.33E+04 8.96 Vanillic acid(2,g) 1.95154E+05 0.3218 -2.00E+03 3.04E+04 15.55 Chlorogenic acid(2,h) 1.10169E+05 0.3342 -2.45E+03 1.38E+04 12.52 Ferulic acid(2,h) 1.76581E+05 0.3852 -2.60E+03 2.13E+04 12.04 Isoferulic acid(2,h) 9.90660E+04 0.2309 -2.13E+03 3.41E+03 3.44 Isoferulic acid-3-o-glucuronide(2,h) 7.33680E+04 0.2167 -2.33E+03 9.28E+03 12.64 Dihydroferulic acid(2,h) 1.61246E+05 0.3014 -2.05E+03 1.69E+04 10.51 Caffeic acid(2,h) 2.02092E+05 0.4052 -2.30E+03 2.54E+04 12.59 Caffeic acid-3-o-glucuronide(2,h) 2.05445E+05 0.3989 -2.43E+03 1.98E+04 9.66 Caffeic acid-4-o-glucuronide(2,h) 1.64272E+05 0.3255 -2.36E+03 1.30E+04 7.94 Dihydrocaffeic acid(2,h) 1.56408E+05 0.3132 -2.28E+03 2.07E+04 13.25 Dihydrocaffeic acid-3-o-glucuronide(2,h) 1.30923E+05 0.2613 -2.40E+03 1.26E+04 9.63 Dihydrocaffeic acid-3-o-sulfate(2,h) 1.78643E+05 0.3020 -2.08E+03 2.69E+04 15.06 Sinapic acid(2,h) 5.74300E+04 0.1864 -1.89E+03 1.19E+04 20.69 o-Coumaric acid(2,h) 1.67739E+05 0.3150 -2.17E+03 1.76E+04 10.51 p-Coumaric acid(2,h) 1.75011E+05 0.3498 -2.49E+03 2.02E+04 11.56 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

75

Table 9: Quadratic Equation between Polyphenol and BSA Polyphenol Avg.-KQu ΔG° Std. Deviation % Std. Deviation (M-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 2.45478E+05 -2.58E+03 5.37E+03 2.19 Resveratrol(1,a) 1.52570E+05 -2.48E+03 4.81E+03 3.15 Quercetin(2,b) 2.51105E+05 -2.58E+03 1.35E+04 5.38 Quercetin-3-glucuronide(2,b) 2.28842E+05 -2.57E+03 1.98E+03 0.86 Quercetin-3-glucoside(2,b) 1.06433E+05 -2.41E+03 2.89E+03 2.72 Biochanin A(2,c) 1.31120E+05 -2.45E+03 4.09E+03 3.12 Puerarin(2,c) 1.22953E+05 -2.44E+03 2.33E+03 1.90 Chrysin(2,d) 1.99869E+05 -2.54E+03 3.83E+03 1.91 Baicalein(2,d) 2.48426E+05 -2.58E+03 1.55E+03 0.63 Baicalin(2,d) 1.77478E+05 -2.51E+03 2.36E+03 1.33 Flavone(2,d) 1.25992E+05 -2.44E+03 5.76E+03 4.57 Pelargonidin Chloride(2,e) 2.06322E+05 -2.54E+03 5.27E+03 2.55 Dopac(2,f) 1.34038E+05 -2.45E+03 2.66E+03 1.98 m-Hydroxyphenylacteic acid(2,f) 7.39600E+04 -2.33E+03 1.62E+03 2.19 p-Hydroxyphenylacteic acid(2,f) 5.85980E+04 -2.28E+03 2.40E+03 4.10 Homogentisic acid(2,f) 7.80650E+04 -2.34E+03 3.02E+03 3.87 Ellagic acid(2,g) 3.75235E+05 -2.67E+03 1.35E+04 3.60 Eudesmic acid(2,g) 1.29568E+05 -2.45E+03 1.45E+03 1.12 Syringic acid(2,g) 6.37340E+04 -2.30E+03 7.72E+02 1.21 Gallic acid(2,g) 1.73577E+05 -2.51E+03 1.33E+03 0.77 Protocatechuic acid(2,g) 1.12414E+05 -2.42E+03 1.76E+03 1.56 m-Hydroxybenzoic acid(2,g) 1.11680E+05 -2.42E+03 1.08E+03 0.97 p-Hydroxybenzoic acid(2,g) 1.04846E+05 -2.40E+03 3.12E+03 2.98 p-Hydroxysalicylic acid(2,g) 7.63280E+04 -2.34E+03 9.08E+02 1.19 Apocynin(2,g) 1.06798E+05 -2.41E+03 3.52E+03 3.29 Vanillic acid(2,g) 6.77380E+04 -2.31E+03 1.51E+03 2.23 Chlorogenic acid(2,h) 2.08887E+05 -2.55E+03 9.37E+03 4.49 Ferulic acid(2,h) 1.77997E+05 -2.51E+03 3.38E+03 1.90 Isoferulic acid(2,h) 9.24500E+04 -2.38E+03 1.49E+03 1.62 Isoferulic acid-3-o-glucuronide(2,h) 1.02038E+05 -2.40E+03 2.02E+03 1.98 Dihydroferulic acid(2,h) 1.02304E+05 -2.40E+03 2.40E+03 2.34 Caffeic acid(2,h) 1.24272E+05 -2.44E+03 9.84E+02 0.79 Caffeic acid-3-o-glucuronide(2,h) 1.33768E+05 -2.45E+03 1.71E+03 1.28 Caffeic acid-4-o-glucuronide(2,h) 1.29605E+05 -2.45E+03 2.07E+03 1.60 Dihydrocaffeic acid(2,h) 8.85490E+04 -2.37E+03 1.08E+03 1.22 Dihydrocaffeic acid-3-o-glucuronide(2,h) 8.21300E+04 -2.35E+03 5.81E+02 0.71 Dihydrocaffeic acid-3-o-sulfate(2,h) 6.43110E+04 -2.30E+03 4.07E+02 0.63 Sinapic acid(2,h) 8.35470E+04 -2.36E+03 4.33E+03 5.19 o-Coumaric acid(2,h) 7.85870E+04 -2.34E+03 3.04E+03 3.87 p-Coumaric acid(2,h) 1.26533E+05 -2.44E+03 1.30E+03 1.03 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

76

Table 10: Quadratic Equation between Polyphenol and LDL-VLDL Polyphenol Avg.-KQu ΔG° Std. Deviation % Std. Deviation (M-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 1.79272E+05 -2.51E+03 7.72E+02 0.43 Resveratrol(1,a) 1.28143E+05 -2.44E+03 1.48E+03 1.15 Quercetin(2,b) 1.34300E+05 -2.45E+03 9.74E+02 0.73 Quercetin-3-glucuronide(2,b) 1.26657E+05 -2.44E+03 2.92E+03 2.31 Quercetin-3-glucoside(2,b) 1.07118E+05 -2.41E+03 1.07E+03 1.00 Biochanin A(2,c) 1.26745E+05 -2.44E+03 2.90E+03 2.29 Puerarin(2,c) 1.12034E+05 -2.42E+03 1.48E+03 1.32 Chrysin(2,d) 1.70356E+05 -2.50E+03 4.40E+03 2.58 Baicalein(2,d) 1.15045E+05 -2.42E+03 2.11E+03 1.83 Baicalin(2,d) 1.10207E+05 -2.41E+03 3.95E+03 3.58 Flavone(2,d) 1.02182E+05 -2.40E+03 1.36E+03 1.33 Pelargonidin Chloride(2,e) 1.19742E+05 -2.43E+03 6.58E+02 0.55 Dopac(2,f) 6.66500E+04 -2.31E+03 1.48E+03 2.22 m-Hydroxyphenylacteic acid(2,f) 8.63260E+04 -2.36E+03 9.35E+02 1.08 p-Hydroxyphenylacteic acid(2,f) 7.71540E+04 -2.34E+03 1.96E+03 2.55 Homogentisic acid(2,f) 8.47340E+04 -2.36E+03 1.43E+03 1.69 Ellagic acid(2,g) 1.38648E+05 -2.46E+03 4.41E+03 3.18 Eudesmic acid(2,g) 9.09900E+04 -2.37E+03 2.85E+03 3.13 Syringic acid(2,g) 7.10530E+04 -2.32E+03 7.06E+02 0.99 Gallic acid(2,g) 9.40310E+04 -2.38E+03 1.45E+03 1.55 Protocatechuic acid(2,g) 9.91500E+04 -2.39E+03 1.09E+03 1.10 m-Hydroxybenzoic acid(2,g) 9.55740E+04 -2.38E+03 9.01E+02 0.94 p-Hydroxybenzoic acid(2,g) 8.65410E+04 -2.36E+03 2.11E+03 2.43 p-Hydroxysalicylic acid(2,g) 9.04020E+04 -2.37E+03 2.93E+03 3.24 Apocynin(2,g) 1.11164E+05 -2.42E+03 1.92E+03 1.72 Vanillic acid(2,g) 7.71600E+04 -2.34E+03 2.61E+03 3.38 Chlorogenic acid(2,h) 1.33035E+05 -2.45E+03 3.62E+03 2.72 Ferulic acid(2,h) 1.20306E+05 -2.43E+03 1.16E+03 0.97 Isoferulic acid(2,h) 7.89610E+04 -2.34E+03 7.69E+02 0.97 Isoferulic acid-3-o-glucuronide(2,h) 7.75150E+04 -2.34E+03 2.30E+03 2.96 Dihydroferulic acid(2,h) 8.28590E+04 -2.35E+03 1.30E+03 1.57 Caffeic acid(2,h) 1.22864E+05 -2.44E+03 1.52E+03 1.24 Caffeic acid-3-o-glucuronide(2,h) 1.11130E+05 -2.42E+03 9.05E+02 0.81 Caffeic acid-4-o-glucuronide(2,h) 9.51090E+04 -2.38E+03 2.87E+03 3.02 Dihydrocaffeic acid(2,h) 9.33620E+04 -2.38E+03 1.28E+03 1.37 Dihydrocaffeic acid-3-o-glucuronide(2,h) 7.84470E+04 -2.34E+03 9.70E+02 1.24 Dihydrocaffeic acid-3-o-sulfate(2,h) 7.06360E+04 -2.32E+03 2.34E+03 3.31 Sinapic acid(2,h) 7.50220E+04 -2.33E+03 1.20E+03 1.60 o-Coumaric acid(2,h) 7.26270E+04 -2.33E+03 1.72E+03 2.37 p-Coumaric acid(2,h) 1.05430E+05 -2.40E+03 3.48E+03 3.30 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

77

Table 11: Benesi-Hildebrand method between Polyphenol and BSA Polyphenol Avg.-KBH ΔG° Std. Deviation % Std. Deviation (M-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 1.56790E+06 -2.97E+03 2.97E+05 18.94 Resveratrol(1,a) 8.68250E+05 -2.84E+03 2.21E+05 25.42 Quercetin(2,b) 4.20450E+05 -2.69E+03 1.56E+05 37.17 Quercetin-3-glucuronide(2,b) 5.26800E+05 -2.74E+03 1.33E+05 25.30 Quercetin-3-glucoside(2,b) 9.94500E+04 -2.39E+03 3.89E+03 3.91 Biochanin A(2,c) 4.26000E+05 -2.69E+03 3.89E+04 9.13 Puerarin(2,c) 7.34467E+05 -2.81E+03 3.06E+05 41.60 Chrysin(2,d) 4.63850E+05 -2.71E+03 2.06E+05 44.51 Baicalein(2,d) 2.56629E+06 -3.07E+03 4.44E+05 17.28 Baicalin(2,d) 7.54600E+05 -2.81E+03 2.00E+05 26.52 Flavone(2,d) 5.22000E+05 -2.74E+03 3.25E+04 6.23 Pelargonidin Chloride(2,e) 4.35033E+05 -2.70E+03 9.34E+04 21.47 Dopac(2,f) 1.84300E+05 -2.52E+03 1.39E+04 7.52 m-Hydroxyphenylacteic acid(2,f) 3.20565E+06 -3.11E+03 9.28E+05 28.96 p-Hydroxyphenylacteic acid(2,f) 2.57623E+06 -3.07E+03 9.08E+05 35.24 Homogentisic acid(2,f) 1.43443E+05 -2.47E+03 2.14E+04 14.89 Ellagic acid(2,g) 1.30343E+05 -2.45E+03 1.30E+04 9.99 Eudesmic acid(2,g) 1.62550E+06 -2.97E+03 3.06E+05 18.80 Syringic acid(2,g) 1.49490E+06 -2.96E+03 2.78E+05 18.59 Gallic acid(2,g) 4.83467E+05 -2.72E+03 2.61E+04 5.40 Protocatechuic acid(2,g) 8.08367E+05 -2.83E+03 1.61E+05 19.94 m-Hydroxybenzoic acid(2,g) 4.46950E+05 -2.70E+03 1.90E+05 42.59 p-Hydroxybenzoic acid(2,g) 8.87400E+05 -2.85E+03 2.33E+05 26.30 p-Hydroxysalicylic acid(2,g) 4.93250E+05 -2.72E+03 1.29E+05 26.18 Apocynin(2,g) 1.01707E+06 -2.88E+03 2.29E+05 22.53 Vanillic acid(2,g) 1.41522E+05 -2.47E+03 2.68E+04 18.92 Chlorogenic acid(2,h) 3.45700E+05 -2.65E+03 6.41E+04 18.53 Ferulic acid(2,h) 2.21060E+06 -3.04E+03 3.62E+05 16.38 Isoferulic acid(2,h) 2.70520E+05 -2.60E+03 4.89E+04 18.09 Isoferulic acid-3-o-glucuronide(2,h) 7.14375E+05 -2.80E+03 1.66E+05 23.26 Dihydroferulic acid(2,h) 1.41533E+05 -2.47E+03 2.15E+04 15.19 Caffeic acid(2,h) 4.02600E+05 -2.68E+03 1.70E+05 42.33 Caffeic acid-3-o-glucuronide(2,h) 1.09355E+06 -2.89E+03 3.59E+05 32.85 Caffeic acid-4-o-glucuronide(2,h) 7.06625E+05 -2.80E+03 1.75E+05 24.72 Dihydrocaffeic acid(2,h) 6.47075E+05 -2.78E+03 1.21E+05 18.64 Dihydrocaffeic acid-3-o-glucuronide(2,h) 8.17475E+05 -2.83E+03 1.46E+05 17.87 Dihydrocaffeic acid-3-o-sulfate(2,h) 3.90686E+05 -2.68E+03 6.65E+04 17.03 Sinapic acid(2,h) 1.01800E+05 -2.40E+03 2.69E+04 26.46 o-Coumaric acid(2,h) 3.37914E+05 -2.65E+03 1.21E+05 35.87 p-Coumaric acid(2,h) 1.80715E+06 -2.99E+03 3.11E+05 17.23 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

78

Table 12: Benesi-Hildebrand method between Polyphenol and LDL-VLDL Polyphenol Avg.-KBH ΔG° Std. Deviation % Std. Deviation (M-1) (J*mol-1) (M-1) (%) Pterostilbene(1,a) 1.91690E+06 -3.01E+03 6.45E+05 33.66 Resveratrol(1,a) 6.87333E+05 -2.79E+03 1.70E+05 24.69 Quercetin(2,b) 1.06245E+06 -2.88E+03 2.90E+05 27.29 Quercetin-3-glucuronide(2,b) 1.41900E+06 -2.94E+03 2.34E+05 16.49 Quercetin-3-glucoside(2,b) 9.64667E+05 -2.86E+03 2.06E+05 21.40 Biochanin A(2,c) 4.40200E+05 -2.70E+03 1.45E+05 32.93 Puerarin(2,c) 1.48655E+06 -2.95E+03 3.47E+05 23.36 Chrysin(2,d) 7.20550E+05 -2.80E+03 1.90E+05 26.31 Baicalein(2,d) 9.97350E+05 -2.87E+03 1.41E+05 14.10 Baicalin(2,d) 7.42200E+05 -2.81E+03 2.33E+05 31.44 Flavone(2,d) 1.70605E+06 -2.98E+03 4.28E+05 25.08 Pelargonidin Chloride(2,e) 3.55770E+06 -3.14E+03 1.07E+06 30.05 Dopac(2,f) 1.10378E+06 -2.89E+03 1.94E+05 17.54 m-Hydroxyphenylacteic acid(2,f) 1.13742E+06 -2.90E+03 3.27E+05 28.77 p-Hydroxyphenylacteic acid(2,f) 2.81413E+06 -3.09E+03 6.92E+05 24.58 Homogentisic acid(2,f) 2.65080E+06 -3.07E+03 7.42E+05 28.01 Ellagic acid(2,g) 1.24910E+06 -2.92E+03 2.57E+05 20.61 Eudesmic acid(2,g) 1.22887E+06 -2.91E+03 2.31E+05 18.76 Syringic acid(2,g) 1.83113E+06 -3.00E+03 3.69E+05 20.13 Gallic acid(2,g) 5.87300E+05 -2.76E+03 1.22E+05 20.83 Protocatechuic acid(2,g) 1.09980E+06 -2.89E+03 1.87E+05 16.97 m-Hydroxybenzoic acid(2,g) 1.17407E+06 -2.91E+03 2.97E+05 25.32 p-Hydroxybenzoic acid(2,g) 1.28677E+06 -2.92E+03 1.43E+05 11.09 p-Hydroxysalicylic acid(2,g) 2.08760E+06 -3.02E+03 8.64E+05 41.39 Apocynin(2,g) 9.26933E+05 -2.86E+03 1.71E+05 18.47 Vanillic acid(2,g) 2.92255E+06 -3.09E+03 4.13E+05 14.13 Chlorogenic acid(2,h) 5.65100E+05 -2.75E+03 1.10E+05 19.42 Ferulic acid(2,h) 1.20960E+06 -2.91E+03 2.07E+05 17.15 Isoferulic acid(2,h) 1.00040E+06 -2.87E+03 1.67E+05 16.67 Isoferulic acid-3-o-glucuronide(2,h) 7.15500E+05 -2.80E+03 1.36E+05 18.98 Dihydroferulic acid(2,h) 1.49203E+06 -2.95E+03 2.54E+05 17.00 Caffeic acid(2,h) 1.49825E+06 -2.96E+03 3.41E+05 22.75 Caffeic acid-3-o-glucuronide(2,h) 1.54145E+06 -2.96E+03 3.68E+05 23.90 Caffeic acid-4-o-glucuronide(2,h) 1.84735E+06 -3.00E+03 4.38E+05 23.74 Dihydrocaffeic acid(2,h) 1.92245E+06 -3.01E+03 1.20E+05 6.22 Dihydrocaffeic acid-3-o-glucuronide(2,h) 1.57490E+06 -2.97E+03 3.80E+05 24.16 Dihydrocaffeic acid-3-o-sulfate(2,h) 2.77685E+06 -3.08E+03 1.77E+05 6.37 Sinapic acid(2,h) 4.66100E+05 -2.71E+03 8.07E+04 17.31 o-Coumaric acid(2,h) 2.27080E+06 -3.04E+03 6.02E+05 26.53 p-Coumaric acid(2,h) 1.73235E+06 -2.99E+03 4.87E+05 28.11 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

79

According to statistical analysis, all binding constants between BSA and LDL-

VLDL, per each method, are significantly different. Statistical analysis via Stern-Volmer,

Double-Logarithm, and Quadratic Equation methods shows that the calculated binding constants are significantly higher for a given polyphenol with BSA, than they are for

LDL-VLDL. Statistical analysis via Scatchard’s and the Benesi-Hildebrand methods shows that the binding constants are significantly higher for a polyphenol with LDL-

VLDL, than they are for BSA. However, as previously mentioned, these two methods were only used as a source of estimation, since sources of error for these two methods remain inconsistent. Additionally, statistical analysis for the Stern-Volmer, Double-

Logarithm, and Quadratic Equation methods shows that the correlation coefficient for a polyphenol and its recorded binding constant for both BSA and LDL-VLDL is significant. Again, this was not the case for the binding constants calculated by

Scatchard’s or the Benesi-Hildebrand method. All statistical data can be found in

Appendix A.

4.4.0 Correlation between Calculated Binding Constants and Other

Theoretical/Calculated Properties and Factors

In an effort to understand what contributes to the binding constant between a certain polyphenol, and a given protein, several theoretical and calculated properties and factors associated with polyphenols were investigated. All properties were obtained at

ChemSpider at www.chemspider.com, or if unavailable there, then at The Human

Metabalome Database (HMDB) at www.hmbd.ca.

80

4.4.1 Polar Surface Area (PSA)

The polar surface area of a given polyphenol, and its calculated binding constant, per each method, with either BSA or LDL-VLDL, was first compared as a whole with all forty polyphenols, and then split up into groups: Non-phenolic acids (Non-PAs) and phenolic acids (PAs), using linear regression analysis. Statistical analysis via the Pearson coefficient was then applied to all cases to determine whether or not the correlation coefficient of the linear regression formula was statistically significant. It was determined that in no case, was the correlation coefficient statistically significant between the binding constant of any polyphenol, any protein, with any method, and the polar surface area of that polyphenol, both in total and then by group. All statistical data can be found in Appendix B.

4.4.2 n (Hill-affinity/binding sites)

The n value of a given polyphenol, and its calculated binding constant, per each of the applicable methods, with either BSA or LDL-VLDL, was first compared as a whole with all forty polyphenols, and then split up into groups: Non-phenolic acids (Non-PAs) and phenolic acids (PAs), using linear regression analysis. Statistical analysis via the

Pearson coefficient was then applied to all cases to determine whether or not the correlation coefficient of the linear regression formula was statistically significant. It was determined that several cases proved of statistical significance and are listed as follows:

2 1. All polyphenols, n and KDL-BSA, R = 0.18825 2 2. All polyphenols, n and KSC-BSA, R = 0.91836 2 3. All polyphenols, n and KSC-LDL-VLDL, R = 0.70772 2 4. PAs, n and KDL-BSA, R = 0.21152 2 5. Non-PAs, n and KSC-BSA, R = 0.90301 2 6. PAs, n and KSC-BSA, R = 0.94842

81

2 7. Non-PAs, n and KDL-LDL-VLDL, R = 0.63812 2 8. Non-PAs, n and KSC-LDL-VLDL, R = 0.77430 2 9. PAs, n and KSC-LDL-VLDL, R = 0.73631

It is important to note here 2 outliers when determining the significance of the correlation coefficient between n, and the calculated binding constant.

4.4.2.1 Outlier- n Value of Ellagic acid, and KDL-BSA, All Polyphenols and PAs

The first outlier was the n value of Ellagic acid for BSA, in the Double-Logarithm method, for both groups: All polyphenols and PAs. Looking at the statistical data for all

2 2 polyphenols, n and KDL-BSA, the R = 0.18825. As mentioned above, R is statistically significant. However, if we remove the n value for Ellagic acid, and then determine the statistical significance of R2, a new value for R2 is increased by 1.62 times its previous, which now = 0.30452. Similarly, if the n value of Ellagic acid is removed from the PAs group, the R2 is increased 2.64 times from 0.21152 to 0.55898. All statistical data can be found in Appendix B.

4.4.2.2 Outlier- n Value of p-Hydroxyphenylacetic acid, and KDL-LDL-VLDL, All

Polyphenols and PAs

The second outlier was the n value of p-Hydroxyphenylacetic acid for LDL-

VLDL, in the Double-Logarithm method, for both groups: All polyphenols and PAs.

2 Looking at the statistical data for all polyphenols, n and KDL-LDL-VLDL, the R =

0.03310. This R2 value is not statistically significant. However, if we remove the n value for p-Hydroxyphenylacetic acid, and then determine the statistical significance of R2, a new value for R2 is increased by 18.17 times its previous, which now = 0.60153, and is statistically significant. Similarly, if the n value of p-Hydroxyphenylacetic acid is

82

removed from the PAs group, the R2, which was previously not statistically significant, it is increased 93.33 times from 0.00690 to 0.64396. All statistical data can be found in

Appendix B.

4.4.3 Hydrogen Bond Acceptors/Donors

The number of hydrogen bond acceptors/donors of a given polyphenol, and its calculated binding constant, per each method, with either BSA or LDL-VLDL, was first compared as a whole with all forty polyphenols, and then split up into groups: Non- phenolic acids (Non-PAs) and phenolic acids (PAs), using linear regression analysis.

Statistical analysis via the Pearson coefficient was then applied to all cases to determine whether or not the correlation coefficient of the linear regression formula was statistically significant. It was determined that in no case, was the correlation coefficient statistically significant between the binding constant of any polyphenol, with any protein, any method, and the number of hydrogen bond acceptors/donors of that polyphenol, both in total and then by group. All statistical data can be found in Appendix B.

4.4.4 Log P (Partition Coefficient) and Log D (Distribution Coefficient)

The partition coefficient (log P) is the ratio of un-ionized concentrations obtained from a compound at equilibrium in a mixture of two immiscible phases. The two immiscible phases normally used are octanol and water. The partition coefficient is generally used as a measure of lipophilicity of a compound in the physical sciences, and can be described by the following equation:

83

log Poctanol/water = log ([solute]octanol/[solute]un-ionized water) [Eq. 22]

In certain cases involving ionizable systems, the distribution coefficient (log D) must be used instead of the partition coefficient to measure the degree of lipophilicity of a compound. The distribution coefficient can be defined as the ratio of the sum of the concentration of all forms of the compound (both ionized and un-ionized) in a mixture of two immiscible phases. The distribution coefficient can be described by the following equation:

log Doctanol/water = log ([solute]octanol/[solute]ionized water + [solute]neutral water) [Eq. 23]

In this study, fluorescence quenching of BSA was carried out at a pH of 7.4. A pH of 7.4 is of particular interest because it is the physiological pH of blood serum and plasma. At this particular pH, the partition coefficient can be used to describe the lipophilicity of flavonoids and stilbenes because there is no appreciable ionization of these polyphenols at this particular pH since they are phenols. However, the partition coefficient cannot be used for phenolic acids at a pH of 7.4 because phenolic acids are completely ionized, and thus, the distribution coefficient must be used to measure the degree of lipophilicity for these polyphenols.

The partition coefficient for Non-PAs and the distribution coefficient for PAs, the calculated binding constant, per each method, with either BSA or LDL-VLDL, was first compared as a whole with all forty polyphenols, and then split up into groups: Non- phenolic acids (Non-PAs) and phenolic acids (PAs), using linear regression analysis.

84

Statistical analysis via the Pearson coefficient was then applied to all cases to determine whether or not the correlation coefficient of the linear regression formula was statistically significant. It was determined that several cases proved of statistical significance and are listed as follows:

2 1. All polyphenols, Log P/D and KQu-BSA, R = 0.14880 2 2. All polyphenols, Log P/D and KSV-LDL-VLDL, R = 0.31597 2 3. All polyphenols, Log P/D and KDL-LDL-VLDL, R = 0.27842 2 4. All polyphenols, Log P/D and KQu-LDL-VLDL, R = 0.33274

It is interesting to note that the only time a statistically significant R2 value is observed occurred when all forty polyphenols were compared, and when the above four cases are separated by group (i.e., Non-PAs and PAs), no statistical significance of the R2 value is observed. There did not appear to be any outliers either. All statistical data can be found in Appendix B.

4.4.5 Log P (Partition Coefficient) and Log D (Distribution Coefficient) vs Log Ka

In an attempt to exhaust all options, log vs log plots were developed to examine if there was a stronger correlation between the binding constant of a given polyphenol, and its Log P/D value. The partition coefficient for Non-PAs and the distribution coefficient for PAs, the logarithm of the calculated binding constant for each polyphenol, per each method, with either BSA or LDL-VLDL, was first compared as a whole with all 40 polyphenols, and then split up into groups: Non-phenolic acids (Non-PAs) and phenolic acids (PAs), using linear regression analysis. Statistical analysis via the Pearson coefficient was then applied to all cases to determine whether or not the correlation coefficient of the linear regression formula was statistically significant. It was determined that several cases proved of statistical significance and are listed as follows:

85

2 1. All polyphenols, Log P/D and Log KSV-BSA, R = 0.15153 2 2. All polyphenols, Log P/D and Log KDL-BSA, R = 0.13674 2 3. All polyphenols, Log P/D and Log KQu-BSA, R = 0.18660 2 4. All polyphenols, Log P/D and Log KSV-LDL-VLDL, R = 0.29712 2 5. All polyphenols, Log P/D and Log KDL-LDL-VLDL, R = 0.22209 2 6. All polyphenols, Log P/D and Log KQu-LDL-VLDL, R = 0.33482

Again, it is interesting to note that in cases only with all forty polyphenols, is there any statistical significance of the R2 value, and when the above six cases are separated by group (i.e., Non-PAs and PAs), no statistical significance of the R2 value is observed.

Again, there did not appear to be any outliers present. All statistical data can be found in

Appendix B.

4.5.0 Comparison between the Calculated Binding Constants of both the Stern-

Volmer and Double-Logarithm Method, for BSA and LDL-VLDL, and the

Structural Characteristics of a Given Polyphenol

While attempting to understand what contributes to a given polyphenol’s binding constant, it appears that there are more contributing factors then those previously mentioned. In the following section, several comparisons will be made amongst derived arbitrary groups between the most basic structures of the polyphenols investigated and similar polyphenols with varying functional groups at various positions. Unfortunately, some of the most basic polyphenols were not tested (i.e. cinnamic acid, benzoic acid, etc.), so other compounds with the next level of basic structure were used as a baseline for comparison.

86

4.5.1.0 Comparison of the Stilbenes Resveratrol and Pterostilbene

Resveratrol is a tri-hydroxylated trans-stilbene, containing one hydroxyl group on the 4 position of one phenyl ring, and two hydroxyl groups on the 3 and 5 positions on the other phenyl ring. Pterostilbene is similar in structure, with the exception that the hydroxyl groups on the 3 and 5 positions are methylated. This difference in structure exemplifies a large difference in the observed binding constants between these polyphenols for both BSA and LDL-VLDL.

4.5.1.1 Resveratrol and Pterostilbene with BSA

Binding constants for resveratrol with BSA via the Stern-Volmer and Double-

Logarithm methods measured 3.08309E+05 M-1 and 3.53140E+05 M-1, respectively. The binding constants for pterostilbene with BSA via the Stern-Volmer and Double-

Logarithm methods measured 5.81765E+05 M-1 and 6.60426E+05 M-1, respectively.

These results show that via the Stern-Volmer method, the binding constant of pterostilbene and BSA is 1.89 times larger than that of resveratrol. Similarly, via the

Double-Logarithm method, the binding constant of pterostilbeneand BSA is 1.87 times greater than the calculated binding constant of resveratrol.

87

7.00E+05

6.00E+05

5.00E+05

4.00E+05 Ka (M-1) KSV-BSA 3.00E+05 KDL-BSA

2.00E+05

1.00E+05

0.00E+00 Resveratrol Pterostilbene

Fig 47: Binding constants for resveratrol and pterostilbene with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.1.2 Resveratrol and Pterostilbene with LDL-VLDL

Similar increases in magnitude were observed between the binding constants of resveratrol and pterostilbene with LDL-VLDL. The binding constants for resveratrol and

LDL-VLDL measured 2.49154E+05 M-1 and 2.12189E+05 M-1 for the Stern-Volmer and

Double-Logarithm methods, respectively. The binding constants for Pterostilbene and

LDL-VLDL then increased by 1.58 times and 1.75 times, to 3.93676E+05 M-1 and

3.70553E+05 M-1, for the Stern-Volmer and Double-Logarithm methods, respectively.

88

4.50E+05 4.00E+05 3.50E+05 3.00E+05 2.50E+05 Ka (M-1) KSV-LDL 2.00E+05 KDL-LDL 1.50E+05 1.00E+05 5.00E+04 0.00E+00 Resveratrol Pterostilbene

Fig 48: Binding constants for resveratrol and pterostilbene with LDL-VLDL via the Stern-Volmer and Double-Logarithm methods.

Section 4.5.1 Summary:

Ka Resveratrol  Pterostilbene

KSV-BSA 3.08309E+05 + 1.89 X

KDL-BSA 3.53140E+05 + 1.87 X

KSV-LDL-VLDL 2.49154E+05 + 1.58 X

KDL-LDL-VLDL 2.12189E+05 + 1.75 X Table 13: Binding constant changes from resveratrol to pterostilbene (M-1).

4.5.2.0 Comparison of the Flavonols Quercetin, Quercetin-3-glucuronide, and

Quercetin-3-glucoside

Quercetin is a tetra-hydroxylated flavonol. It contains hydroxyl groups located on the 7 and 5 positions of ring A, 3’ and 4’ positions of ring B, as well as one hydroxyl group located at the 3 position of ring C (the hydroxyl group responsible for making it a flavonol). Quercetin-3-glucuronide replaces the fifth hydroxyl group at the 3 position of ring C with glucuronic acid linked via a glycosidic bond. Similarly, quercetin-3-glucoside replaces its fifth hydroxyl group at the 3 position of ring C with a glucose molecule,

89

again linked via a glycosidic bond. When comparing the binding constants of these three compounds, it is apparent that structure is one of the large determining factors in the degree of binding. Hydrophobic and hydrophilic forces do not appear to contribute to the same degree of binding for these three larger polyphenols, as they do for smaller polyphenols. Because the glycosidic derivatives of quercetin possess a greater amount of hydrogen bond donors and acceptors, and yet a decrease in the magnitude of their binding constants when compared to their parent compound quercetin, it would appear that some other factor (probably steric) is responsible for the degree of binding with these polyphenols.

4.5.2.1 Quercetin, Quercetin-3-glucuronide, and Quercetin-3-glucoside with BSA

Binding constants for quercetin with BSA via the Stern-Volmer and Double-

Logarithm methods measured 6.96324E+05 M-1 and 6.91400E+05 M-1, respectively. The binding constants for quercetin-3-glucuronide with BSA via the Stern-Volmer and

Double-Logarithm methods measured 4.02626E+05 M-1 and 5.02384E+05 M-1, respectively. The binding constants for quercetin-3-glucoside via the Stern-Volmer and

Double-Logarithm methods are 2.09454E+05 M-1 and 2.37271E+05 M-1, respectively.

The overall order of binding constants with BSA for these three polyphenols from largest to smallest is as follows: Quercetin > quercetin-3-glucuronide > quercetin-3-glucoside.

90

8.00E+05 7.00E+05 6.00E+05 5.00E+05 Ka (M-1) 4.00E+05 3.00E+05 2.00E+05 1.00E+05 KSV-BSA 0.00E+00 KDL-BSA

Fig 49: Binding constants for quercetin, quercetin-3-glucuronide, and quercetin-3-glucoside with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.2.2 Quercetin, Quercetin-3-glucuronide, and Quercetin-3-glucoside with LDL-

VLDL

Similar increases in magnitude were observed between the binding constants of these three flavonols with LDL-VLDL. The binding constants for quercetin and LDL-

VLDL measured 2.61213E+05 M-1 and 2.20924E+05 M-1 for the Stern-Volmer and

Double-Logarithm methods, respectively. The binding constants for quercetin-3- glucuronide then decreased to 2.17353E+05 M-1 and 1.47041E+05 M-1 with LDL-VLDL for the Stern-Volmer and Double-Logarithm methods, respectively. When glucuronic acid is replaced with glucose, forming quercetin-3-glucoside, again the binding constants dropped to 1.85184E+05 M-1 and 1.29897+05 M-1 for the Stern-Volmer and Double-

Logarithm methods, respectively. The same order for the binding constants of these three flavonols with BSA can be observed with LDL-VLDL, and the order from largest to smallest is as follows: Quercetin > quercetin-3-glucuronide > quercetin-3-glucoside.

91

3.00E+05 2.50E+05 2.00E+05 Ka (M-1) 1.50E+05 1.00E+05 5.00E+04 KSV-LDL 0.00E+00 KDL-LDL

Fig 50: Binding constants for quercetin, quercetin-3-glucuronide, and quercetin-3-glucoside with LDL-VLDL via the Stern-Volmer and Double-Logarithm methods.

Section 4.5.2 Summary:

Ka Quercetin Quercetin-3- Quercetin-3-glucoside  glucuronide  KSV-BSA 6.96324E+05 - 1.73 X - 1.92 X

KDL-BSA 6.91400E+05 - 1.38 X - 2.12 X

KSV-LDL-VLDL 2.61213E+05 - 1.20 X - 1.17 X

KDL-LDL-VLDL 2.20924E+05 - 1.50 X - 1.13 X Table 14: Binding constant changes from quercetin, to quercetin-3-glucuronide, to quercetin-3-glucoside (M-1).

4.5.3.0 Comparison of the Flavones Flavone, Chrysin, Baicalein, and Baicalin

Flavone is the parent compound for this subclass of polyphenols. Chrysin is a flavone with two hydroxyl groups on the 5 and 7 positions of ring A. Baicalein has an additional third hydroxyl group located at the 6 position of ring A. Baicalin is similar in structure to baicalein, with the exception that at the 7 position of ring A, there is a glcyosidic bond linking a glucuronic acid to the polyphenol. A similar pattern with the flavonol subclass and their structures related to their binding constants can be observed with this flavone subclass. Polyphenols with glycosides attached to a parent compound appear to have lower binding constants than those identical compounds without

92

glycosides. The phenolic group increases the binding compared to the parent compound without a phenolic group (flavone).

4.5.3.1 Flavone, Chrysin, Baicalein, and Baicalin with BSA

Binding constants for flavone with BSA via the Stern-Volmer and Double-

Logarithm methods measured 2.55588E+05 M-1 and 2.79672E+05 M-1, respectively.

When two hydroxyl groups are attached to the 5 and 7 positions of flavone’s ring A to form chrysin, the observed binding constant increases to 5.04265E+05 M-1 and

5.26141E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively.

Adding an additional hydroxyl group to the 6 position of ring A forms baicalein, which has observed binding constants measured at 4.76971E+05 M-1 and 4.65144E+05 M-1 for the Stern-Volmer and Double-Logarithm methods, respectively. Linking glucuronic acid to baicalein at the 7 position of ring A with a glycosidic bond produces baicalin, which possess binding constants measured at 3.80551E+05 M-1 and 3.02992E+05 M-1 via the

Stern-Volmer and Double-Logarithm methods, respectively. The order of binding constants from largest to smallest in the flavone subclass is as follows: Chrysin > baicalein > baicalin > flavone.

93

6.00E+05

5.00E+05

4.00E+05

Ka (M-1) 3.00E+05 KSV-BSA KDL-BSA 2.00E+05

1.00E+05

0.00E+00 Flavone Chrysin Baicalein Baicalin

Fig 51: Binding constants for flavone, chrysin, baicalein, and baicalin with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.3.2 Flavone, Chrysin, Baicalein, and Baicalin with LDL-VLDL

Again, a similar pattern of binding constants with this subclass can be observed with LDL-VLDL as was observed with BSA. Flavone possessed the lowest binding constant, measuring at 1.66581E+05 M-1 and 9.88100E+04 M-1 via the Stern-Volmer and

Double-Logarithm methods, respectively. Chrysin’s binding constant then measured a large increase at 3.84301E+05 M-1 and 3.68845E+05 M-1 via the Stern-Volmer and

Double-Logarithm methods, respectively. A decrease in the binding constant from

-1 chrysin to baicalein was observed, with Kas being measured 2.68051E+05 M by the

Stern-Volmer method, and 2.33150E+05 M-1 for the Double-Logarithm method. Finally, the observed binding constants of baicalin were measured at 2.14412E+05 M-1 and

1.78332E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively.

The same order of binding constants from largest to smallest that was observed for BSA can be observed for LDL-VLDL as well.

94

4.50E+05 4.00E+05 3.50E+05 3.00E+05 2.50E+05 Ka (M-1) KSV-LDL 2.00E+05 KDL-LDL 1.50E+05 1.00E+05 5.00E+04 0.00E+00 Flavone Chrysin Baicalein Baicalin

Fig 52: Binding constants for flavone, chrysin, baicalein, and baicalin with LDL-VLDL via the Stern-Volmer and Double-Logarithm methods.

Section 4.5.3 Summary:

Ka Flavone  Chrysin  Baicalein  Baicalin

KSV-BSA 2.55588E+05 + 1.97 X - 1.06 X - 1.25 X

KDL-BSA 2.79672E+05 +1.88 X -1.13 X -1.54 X

KSV-LDL-VLDL 1.66581E+05 + 2.31 X - 1.43 X - 1.25 X

KDL-LDL-VLDL 9.88100E+04 + 3.73 X - 1.58 X - 1.31 X

Table 15: Binding constant changes from flavone, to chrysin, to baicalein, to baicalin (M-1).

4.5.4.0 Comparison of the Phenylacetic acid Derivatives Dopac, m-

Hydroxyphenylacetic acid, p-Hydroxyphenylacetic acid, and Homogentisic acid

Dopac is a phenylacetic acid derivative that contains two hydroxyl groups on the

3 and 4 positions of its aromatic ring. m-Hydroxyphenylacetic acid contains only one hydroxyl group at the 3 position of its aromatic ring. Similarly, p-Hydroxyphenylacetic acid contains a single hydroxyl group on the 4 position of its aromatic ring. Homogentisic acid contains two hydroxyl groups on its aromatic ring, however these OH groups are located at the 2 and 5 positions.

95

4.5.4.1 Dopac, m-Hydroxyphenylacetic acid, p-Hydroxyphenylacetic acid, and

Homogentisic acid with BSA

The binding constant for Dopac with BSA measured using the Stern-Volmer and

Double-Logarithm possessed a value of 2.80772E+05 M-1 and 2.85125E+05 M-1, respectively. There was a large drop in the binding constant value if one hydroxyl group was removed. Particularly, the binding constant of m-hydroxyphenylacetic acid was measured at 7.50740E+04 M-1 via the Stern-Volmer method, and 7.80400E+03 M-1 via the Double-Logarithm method. The binding constant for p-hydroxyphenylacetic acid was measured at 6.26470E+04 M-1 via the Stern-Volmer method, and 7.01200E+03 M-1 via the Double-Logarithm method. Transitioning to homogentisic acid, a polyphenol with two hydroxyl groups, the binding constant increased to 1.55987E+05 M-1 and

1.53681E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. It appears that phenylacetic acid derivatives containing two hydroxyl groups posses much larger binding constants than those with only one. The order of binding constants for this subclass of phenylacetic acid derivatives from largest to smallest is as follows: Dopac > homogentisic acid > m-hydroxyphenylacetic acid > p-hydroxyphenylacetic acid.

96

3.00E+05 2.50E+05 2.00E+05 Ka (M-1) 1.50E+05 1.00E+05 5.00E+04 KSV-BSA 0.00E+00 KDL-BSA

Fig 53: Binding constants for Dopac, m-hydroxyphenylacetic acid, p-hydroxyphenylacetic acid, and homogentisic acid with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.4.2 Dopac, m-Hydroxyphenylacetic acid, p-Hydroxyphenylacetic acid, and

Homogentisic acid with LDL-VLDL

Transitioning to LDL-VLDL, the binding constants for the phenylacetic acid derivatives and this lipoprotein varied somewhat, but for the most part the same pattern that was observed with BSA was observed here. The binding constant of Dopac was measured at 1.10515E+05 M-1 and 5.22800E+04 M-1 via the Stern-Volmer and Double-

Logarithm methods, respectively. The binding constant of m-hydroxyphenylacetic acid via the Stern-Volmer and Double-Logarithm methods was found to be 1.19044E+05 M-1 and 4.84710E+05 M-1, respectively. For the phenylacetic acid derivative p- hydroxyphenylacetic acid, the binding constant was calculated to be 7.45600E+04 M-1 and 1.45980E+04 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. The value of the binding constant for homogentisic acid then increased to

9.77940E+04 and 2.00690E+04 via the Stern-Volmer and Double-Logarithm methods, respectively. The order of binding constants calculated via the Stern-Volmer method, from largest to smallest was m-hydroxyphenylacetic acid > Dopac > homogentisic acid >

97

p-hydroxyphenylacetic acid. The order of binding constants calculated via the Double-

Logarithm method, from largest to smallest was found to be Dopac > homogentisic acid

> m-hydroxyphenylacetic acid > p-hydroxyphenylacetic acid. This was the same order of binding for both methods with BSA.

1.40E+05 1.20E+05 1.00E+05 8.00E+04 Ka (M-1) 6.00E+04 4.00E+04 2.00E+04 KSV-LDL 0.00E+00 KDL-LDL

Fig 54: Binding constants for Dopac, m-hydroxyphenylacetic acid, p-hydroxyphenylacetic acid, and homogentisic acid with LDL- VLDL via the Stern-Volmer and Double-Logarithm methods.

Section 4.5.4 Summary:

Ka Dopac m- p- Homogentisic acid Hydroxyphenylacetic Hydroxyphenylacetic  acid  acid  KSV-BSA 2.80772E+05 - 3.74 X - 1.20 X + 2.49 X

KDL-BSA 2.85125E+05 - 36.54 X - 1.11 X + 21.92 X

KSV-LDL-VLDL 1.10515E+05 + 1.08 X - 1.60 X + 1.31 X

KDL-LDL-VLDL 5.22800E+04 - 1.08 X - 3.32 X + 1.37 X Table 16: Binding constant changes from Dopac to m-hydroxyphenylacetic acid, to p-hydroxyphenylacetic acid, to homogentisic acid (M-1).

4.5.5.0 Comparison of the Benzoic acid Derivatives Gallic acid, p-Hydroxysalicylic acid, Protocatechuic acid, m-Hydroxybenzoic acid, and p-Hydroxybenzoic acid

Gallic acid is a tri-hydroxylated benzoic acid, containing hydroxyl groups on the

3, 4, and 5 positions of its aromatic ring. p-hydroxysalicylic acid is a di-hydroxylated

98

benzoic acid with hydroxyl groups on both the 2 and 4 positions of its aromatic ring.

Protocatechuic acid is also a di-hydroxylated benzoic acid with hydroxyl groups on both

3 and 4 positions of its aromatic ring. m-hydroxybenzoic acid only contains one hydroxyl group at the 3 position of its aromatic ring. p-hydroxybenzoic acid also only contains one hydroxyl group, which is found on the 4 position of its aromatic ring.

4.5.5.1 Gallic acid, p-Hydroxysalicylic acid, Protocatechuic acid, m-Hydroxybenzoic acid, and p-Hydroxybenzoic acid with BSA

In both the Stern-Volmer and Double-Logarithm methods, the binding constant for the sole tri-hydroxylated benzoic acid derivative gallic acid was found to be

4.45625E+05 M-1 and 4.77312E+05 M-1, respectively. Next, the binding constant for the di-hydroxylated benzoic acid derivative p-Hydroxysalicylic acid was measured at

1.02626E+05 M-1 and 7.96540E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. The binding constant for the other di-hydroxylated benzoic acid derivative protocatechuic acid was found to be 1.93346E+05 M-1 and 1.53567E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. Finally, the binding constants of the mono-hydroxylated benzoic acid derivatives m-hydroxybenzoic acid and p-hydroxybenzoic acid were recorded. The binding constant of m-hydroxybenzoic acid was calculated at 1.75129E+05 M-1 and 1.82885E+05 M-1 via the Stern-Volmer and

Double-Logarithm methods, respectively. The binding constant of p-hydroxybenzoic acid was measured at 1.65956E+05 M-1 and 1.22821E+05 M-1 via the Stern-Volmer and

Double-Logarithm methods, respectively. The order of binding constants from largest to smallest in this benzoic acid derivative subclass via the Stern-Volmer method is as

99

follows: Gallic acid > protocatechuic acid > m-hydroxybenzoic acid > p-hydroxybenzoic acid > p-hydrosalicylic acid. The order of binding constants from largest to smallest in this benzoic acid derivative subclass via the Double-Logarithm method is as follows:

Gallic acid > m-hydroxybenzoic acid > protocatechuic acid > p-hydroxybenzoic acid > p- hydrosalicylic acid.

6.00E+05 5.00E+05 4.00E+05 Ka (M-1) 3.00E+05 2.00E+05 1.00E+05 KSV-BSA 0.00E+00 KDL-BSA

Fig 55: Binding constants for gallic acid, p-hydrosalicylic acid, protocatechuic acid, m-hydroxybenzoic acid, and p-hydroxybenzoic acid with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.5.2 Gallic acid, p-Hydroxysalicylic acid, Protocatechuic acid, m-Hydroxybenzoic acid, and p-Hydroxybenzoic acid with LDL-VLDL

The pattern of binding constants with these five polyphenols and LDL-VLDL is similar to that observed with these five polyphenols and BSA. With LDL-VLDL, the binding constant of gallic acid via the Stern-Volmer and Double-Logarithm methods was found to be 1.76654E+05 M-1 and 1.46939E+05 M-1, respectively. The binding constant of p-hydroxysalicylic acid via the Stern-Volmer and Double-Logarithm methods was found to be 1.32390E+05 M-1 and 5.86900E+04 M-1, respectively. The binding constant for protocatechuic acid was found to be 1.62390E+05 M-1 and 1.00811E+05 M-1 via the

100

Stern-Volmer and Double-Logarithm methods, respectively. For the mono-hydroxylated benzoic acid derivative m-hydroxybenzoic acid, the binding constant was measured at

1.55147E+05 M-1 and 9.16920E+04 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. For the other mono-hydroxylated benzoic acid derivative p- hydroxybenzoic acid, the binding constant was measured at 1.36397E+05 M-1 and

7.49260E+04 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively.

The order of binding constants from largest to smallest in this benzoic acid derivative subclass with LDL-VLDL is as follows: Gallic acid > protocatechuic acid > m- hydroxybenzoic acid > p-hydroxybenzoic acid > p-hydrosalicylic acid.

2.00E+05 1.80E+05 1.60E+05 1.40E+05 1.20E+05 Ka (M-1) 1.00E+05 8.00E+04 6.00E+04 4.00E+04 KSV-LDL 2.00E+04 0.00E+00 KDL-LDL

Fig 56: Binding constants for gallic acid, p-hydrosalicylic acid, protocatechuic acid, m-hydroxybenzoic acid, and p-hydroxybenzoic acid with LDL-VLDL via the Stern-Volmer and Double-Logarithm methods.

Section 4.5.5 Summary:

Ka Gallic acid p-Hydrosalicylic Protocatechuic m- p- acid acid Hydroxybenzoic Hydroxybenzoic    acid  acid KSV-BSA 4.45625E+05 - 4.34 X + 1.88 X - 1.10 X - 1.06 X

KDL-BSA 4.77312E+05 - 5.99 X + 1.93 X + 1.19 X - 1.49 X

KSV-LDL-VLDL 1.76654E+05 - 1.33 X + 1.23 X - 1.05 X - 1.14 X

KDL-LDL-VLDL 1.46939E+05 - 2.50 X + 1.72 X - 1.10 X - 1.22 X Table 17: Binding constant changes from gallic acid, to p-hydrosalicylic acid, to protocatechuic acid, to m-hydroxybenzoic acid, to p- hydroxybenzoic acid (M-1).

101

4.5.6.0 Comparison of the Benzoic acid Derivatives Gallic acid, Eudesmic acid,

Syringic acid, Vanillic acid, and Apocynin

Gallic acid, as mentioned previously, is a tri-hydroxylated benzoic acid derivative, containing a hydroxyl group on the 3, 4, and 5 positions of its aromatic ring.

Eudesmic acid is a benzoic acid derivative that possesses three methoxy groups; one the

3, 4, and 5 positions of its aromatic ring. Syringic acid is another benzoic acid derivative that contains a methoxy group on both the 3 and 5 positions of its aromatic ring, as well as a single hydroxyl group on the 4 position. Vanillic acid, another benzoic acid derivative, contains a single methoxy group on the 3 position, and a single hydroxyl group on the 4 position of its aromatic ring. Apocynin, the final benzoic acid derivative in this group comparison, is identical to vanillic acid with the exception that this polyphenol is a ketone, and it contains a ketone in place of a carboxylic acid group.

4.5.6.1 Gallic acid, Eudesmic acid, Syringic acid, Vanillic acid, and Apocynin with

BSA

In both the Stern-Volmer and Double-Logarithm methods, the binding constant for the sole tri-hydroxylated benzoic acid derivative gallic acid was found to be

4.45625E+05 M-1 and 4.77312E+05 M-1, respectively. Next, the binding constant for the only tri-methoxylated benzoic acid derivative eudesmic acid was found to be

2.29265E+05 M-1 and 2.08187E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. The binding constant of syringic acid, via the Stern-Volmer and

Double-Logarithm methods, was found to be 9.63240E+04 M-1 and 1.00902E+05 M-1, respectively. Next, the binding constant of vanillic acid, via the Stern-Volmer and

102

Double-Logarithm methods, was measured at 9.29620E+04 M-1 and 1.51633E+05 M-1, respectively. Finally, the binding constant for apocynin was measured at 1.58403E+05

M-1 and 1.12104E+05 M-1, respectively. In regards to the Stern-Volmer method, the order of largest to smallest binding constant is as follows: Gallic acid > eudesmic acid > apocynin > syringic acid > vanillic acid. For the Double-Logarithm method, the order of largest to smallest binding constant is as follows: Gallic acid > eudesmic acid > vanillic acid > apocynin > syringic acid.

6.00E+05

5.00E+05

4.00E+05

-1 Ka (M ) 3.00E+05 KSV-BSA KDL-BSA 2.00E+05

1.00E+05

0.00E+00 Gallic Acid Eudesmic Syringic Vanillic Apocynin Acid Acid Acid

Fig 57: Binding constants for gallic acid, eudesmic acid, syringic acid, vanillic acid, and apocynin with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.6.2 Gallic acid, Eudesmic acid, Syringic acid, Vanillic acid, and Apocynin with

LDL-VLDL

The order of binding constants for these five benzoic acid derivatives appeared to differ with LDL-VLDL when compared against the binding constants of BSA. With

LDL-VLDL, the binding constant of gallic acid was found to be 1.76654E+05 M-1 and

1.46939E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively.

The binding constant of eudsemic acid was measured at 1.98824E+05 M-1 and

103

1.76387E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively.

Next, the binding constant of syringic acid was found to be 9.39710E+04 M-1 and

2.70670E+04 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively.

The binding constant of vanillic acid, via the Stern-Volmer and Double-Logarithm methods, was found to be 9.17650E+04 M-1 and 1.52640E+04 M-1, respectively. Finally, the binding constant of apocynin was measured at 1.93015E+05 M-1 and 1.39137E+05

M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. In regards to the

Stern-Volmer method, the order of largest to smallest binding constant is as follows:

Eudesmic acid > apocynin > gallic acid > syringic acid > vanillic acid. For the Double-

Logarithm method, the order of largest to smallest binding constant is as follows:

Eudesmic acid > gallic acid > apocynin > syringic acid > vanillic acid.

2.50E+05

2.00E+05

1.50E+05 -1 Ka (M ) KSV-LDL 1.00E+05 KDL-LDL

5.00E+04

0.00E+00 Gallic Acid Eudesmic Syringic Vanillic Apocynin Acid Acid Acid

Fig 58: Binding constants for gallic acid, eudesmic acid, syringic acid, vanillic acid, and apocynin with LDL-VLDL via the Stern- Volmer and Double-Logarithm methods.

104

Section 4.5.6 Summary:

Ka Gallic acid Eudesmic acid Syringic acid Vanillic acid Apocynin

    KSV-BSA 4.45625E+05 - 1.94 X - 2.38 X - 1.04 X + 1.70 X

KDL-BSA 4.77312E+05 - 2.29 X - 2.06 X + 1.50 X - 1.35 X

KSV-LDL-VLDL 1.76654E+05 + 1.13 X - 2.12 X - 1.02 X + 2.10 X

KDL-LDL-VLDL 1.46939E+05 + 1.20 X - 6.52 X - 1.77X + 9.12 X Table 18: Binding constant changes from gallic acid, to eudesmic acid, to syringic acid, to vanillic acid, to apocynin (M-1).

4.5.7.0 Comparison of the Cinnamic acid Derivatives Chlorogenic acid, Caffeic acid,

Caffeic acid-3-o-glucuronide, and Caffeic acid-4-o-glucuronide

Caffeic acid is a di-hydroxylated cinnamic acid derivative that contains a hydroxyl group on both the 3 and 4 positions of its aromatic ring. The glycosylated caffeic acid derivatives caffeic acid-3-o-glucuronide and caffeic acid-4-o-glucuronide used in this study contain glucuronic acid groups linked to caffeic acid via a glycosidic bond at the 3 and 4 positions of its aromatic ring, respectively. Chlorogenic acid was the most complex cinnamic acid derivative used in this study, and is the only ester. It is derived from a quinic acid molecule that has been esterified to a caffeic acid molecule.

4.5.7.1 Chlorogenic acid, Caffeic acid, Caffeic acid-3-o-glucuronide, and Caffeic acid-4-o-glucuronide with BSA

The binding constant of caffeic acid via the Stern-Volmer and Double-Logarithm methods was found to be 2.39265E+05 M-1 and 3.08474E+05 M-1, respectively. The binding constant for caffeic acid-3-o-glucuronide was found to be 2.23214E+05 M-1 and

1.88169E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively.

Next, the binding constant for caffeic acid-4-o-glucuronide was found to be 1.66029E+05

105

M-1 and 1.25159E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. Finally, the binding constant of chlorogenic acid was found to be

6.01029E+05 M-1 and 6.57897E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. The order of binding constants from largest to smallest for these four cinnamic acid derivatives is as follows: Chlorogenic acid > caffeic acid > caffeic acid-3-o-glucuronide > caffeic acid-4-o-glucuronide.

7.00E+05 6.00E+05 5.00E+05 4.00E+05 Ka (M-1) 3.00E+05 2.00E+05 KSV-BSA 1.00E+05 KDL-BSA 0.00E+00

Fig 59: Binding constants for chlorogenic acid, caffeic acid, caffeic acid-3-o-glucuronide, and caffeic acid-4-o-glucuronide with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.7.2 Chlorogenic acid, Caffeic acid, Caffeic acid-3-o-glucuronide, and Caffeic acid-4-o-glucuronide with LDL-VLDL

The binding constants for these four cinnamic acid derivatives shared a similar pattern with LDL-VLDL as the one they shared with BSA. The binding constant of caffeic acid via the Stern-Volmer and Double-Logarithm methods was found to be

2.06544E+05 M-1 and 1.52498E+05 M-1, respectively. The binding constant for caffeic acid-3-o-glucuronide was found to be 1.75809E+05 M-1 and 1.28712E+05 M-1 via the

Stern-Volmer and Double-Logarithm methods, respectively. Next, the binding constant

106

for caffeic acid-4-o-glucuronide was found to be 1.44853E+05 M-1 and 7.61070E+04 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. Finally, the binding constant of chlorogenic acid was found to be 2.71029E+05 M-1 and 2.47913E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. The order of binding constants from largest to smallest for these four cinnamic acid derivatives is as follows:

Chlorogenic acid > caffeic acid > caffeic acid-3-o-glucuronide > caffeic acid-4-o- glucuronide.

3.00E+05

2.50E+05

2.00E+05

Ka (M-1) 1.50E+05 1.00E+05 KSV-LDL 5.00E+04 KDL-LDL 0.00E+00

Fig 60: Binding constants for chlorogenic acid, caffeic acid, caffeic acid-3-o-glucuronide, and caffeic acid-4-o-glucuronide with LDL- VLDL via the Stern-Volmer and Double-Logarithm methods.

Section 4.5.7 Summary:

Ka Chlorogenic acid Caffeic acid Caffeic acid-3-o- Caffeic acid-4-o- glucuronide glucuronide    KSV-BSA 6.01029E+05 - 2.51 X - 1.07 X - 1.34 X

KDL-BSA 6.57897E+05 - 2.13 X - 1.64 X - 1.50 X

KSV-LDL-VLDL 2.71029E+05 - 1.31 X - 1.17 X - 1.21 X

KDL-LDL-VLDL 2.47913E+05 - 1.63 X - 1.18 X - 1.69 X Table 19: Binding constant changes from chlorogenic acid, to caffeic acid, to caffeic acid-3-o-glucuronide, to caffeic acid-4-o- glucuronide (M-1).

107

4.5.8.0 Comparison of the Cinnamic acid Derivatives Caffeic acid, Dihydrocaffeic acid, Dihydrocaffeic acid-3-o-glucuronide, and Dihydrocaffeic acid-3-o-sulfate

As mentioned previously, caffeic acid is a di-hydroxylated cinnamic acid derivative that contains a hydroxyl group on both the 3 and 4 positions of its aromatic ring. Dihydrocaffeic acid is similar in structure to caffeic acid, with the exception that its

C2-C3 double bond is hydrogenated. Dihydrocaffeic acid-3-o-glucuronide is a glycosylated version of dihydrocaffeic acid at the 3 position of its aromatic ring. Here, a glucuronic acid is linked via a glycosidic bond. Dihydrocaffeic acid-3-o-sulfate is the final dihydrocaffeic acid derivative used in this study, and contains a sulfate group linked to dihydrocaffeic acid at the 3 position of its aromatic ring.

4.5.8.1 Caffeic acid, Dihydrocaffeic acid, Dihydrocaffeic acid-3-o-glucuronide, and

Dihydrocaffeic acid-3-o-sulfate with BSA

As mentioned previously, the binding constant of caffeic acid with BSA was found to 2.39265E+05 M-1 and 3.08474E+05 M-1 via the Stern-Volmer and Double

Logarithm methods, respectively. The binding constant of dihydrocaffeic acid was measured to be 1.59454E+05 M-1 and 1.09963E+05 M-1 when calculated via the Stern-

Volmer and Double-Logarithm methods, respectively. The binding constant of the glycosylated cinnamic acid derivative, dihydrocaffeic acid-3-o-glucuronide was found to be 1.22169E+05 M-1 and 7.94480E+04 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. Finally, the binding constant for dihydrocaffeic acid-3-o-sulfate was measured to be 1.17962E+05 M-1 and 1.04482E+05 M-1 via the Stern-Volmer and

Double-Logarithm methods, respectively. For the Stern-Volmer method, the order of

108

largest to smallest binding constant is as follows: Caffeic acid > dihydrocaffeic acid > dihydrocaffeic acid-3-o-glucuronide > dihydrocaffeic acid-3-o-sulfate. With respect to the Double-Logarithm method, the order of largest to smallest binding constant is as follows: Caffeic acid > dihydrocaffeic acid > dihydrocaffeic acid-3-o-sulfate > dihydrocaffeic acid-3-o-glucuronide.

3.50E+05 3.00E+05 2.50E+05 2.00E+05 Ka (M-1) 1.50E+05 1.00E+05 KSV-BSA 5.00E+04 KDL-BSA 0.00E+00

Fig 61: Binding constants for caffeic acid, dihydrocaffeic acid, dihydrocaffeic acid-3-o-glucuronide, and dihydrocaffeic acid-3-o- sulfate with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.8.2 Caffeic acid, Dihydrocaffeic acid, Dihydrocaffeic acid-3-o-glucuronide, and

Dihydrocaffeic acid-3-o-sulfate with LDL-VLDL

As with BSA, the binding constant with caffeic acid and LDL-VLDL proved to be the largest in this group, comparatively. The binding constant for caffeic acid was found to be 2.06544E+05 M-1 and 1.52498E+05 M-1 via the Stern-Volmer and Double-

Logarithm methods, respectively. Next, the binding constant for dihydrocaffeic acid was measured to be 1.43787E+05 M-1 and 7.37570E+04 M-1 via the Stern-Volmer and

Double-Logarithm methods, respectively. The binding constant of dihydrocaffeic acid-3- o-glucuronide, when measured via the Stern-Volmer and Double-Logarithm methods,

109

was found to be 8.59190E+04 M-1 and 1.66910E+04 M-1, respectively. Finally, the binding constant of dihydrocaffeic acid-3-o-sulfate was found to be 1.15625E+05 M-1 and 4.85870E+04 M-1 when calculated via the Stern-Volmer and Double-Logarithm methods, respectively. The order of largest to smallest binding constant for these four cinnamic acids is as follows: Caffeic acid > dihydrocaffeic acid > dihydrocaffeic acid-3- o-sulfate > dihydrocaffeic acid-3-o-glucuronide.

2.50E+05

2.00E+05

1.50E+05 Ka (M-1) 1.00E+05

5.00E+04 KSV-LDL KDL-LDL 0.00E+00

Fig 62: Binding constants for caffeic acid, dihydrocaffeic acid, dihydrocaffeic acid-3-o-glucuronide, and dihydrocaffeic acid-3-o- sulfate with LDL-VLDL via the Stern-Volmer and Double-Logarithm methods.

Section 4.5.8 Summary:

Ka Caffeic acid Dihydrocaffeic Dihydrocaffeic Dihydrocaffeic acid acid-3-o- acid-3-o-sulfate   glucuronide  KSV-BSA 2.39265E+05 - 1.50 X - 1 .31 X - 1.04 X

KDL-BSA 3.08474E+05 - 2.81 X - 1.38 X + 1.32 X

KSV-LDL-VLDL 2.06544E+05 - 1.44 X - 1.67 X + 1.35 X

KDL-LDL-VLDL 1.52498E+05 - 2.07 X - 4.42 X + 2.91 X Table 20: Binding constant changes from caffeic acid, to dihydrocaffeic acid, to dihydrocaffeic acid-3-o-glucuronide, to dihydrocaffeic acid-3-o-sulfate (M-1).

110

4.5.9.0 Comparison of the Cinnamic acid Derivatives Caffeic acid, Ferulic acid,

Isoferulic acid, Isoferulic acid-3-o-glucuronide, and Dihydroferulic acid

Again, as mentioned previously, caffeic acid is a di-hydroxylated cinnamic acid derivative that contains a hydroxyl group on both the 3 and 4 positions of its aromatic ring. Ferulic acid is similar to caffeic acid, with the exception that in place of the second hydroxyl group on the 3 position of the aromatic ring of caffeic acid, lies a methoxy group. Isoferulic acid resembles ferulic acid, with the exception that its aromatic substituents are switched, containing a hydroxyl group on the 3 position and a methoxy group on the 4 position of its aromatic ring. Isoferulic acid-3-o-glucuronide is a glycosylated version of isoferulic acid, and possesses a glucuronic acid linked to the aromatic ring at the 3 position via a glycosidic bond. Finally, dihydroferulic acid resembles ferulic acid, with the exception that its C2-C3 double bond has been hydrogenated.

4.5.9.1 Caffeic acid, Ferulic acid, Isoferulic acid, Isoferulic acid-3-o-glucuronide, and Dihydroferulic acid with BSA

Under the Stern-Volmer and Double-Logarithm methods, the binding constant of caffeic acid was found to be 2.39265E+05 M-1 and 3.08474E+05 M-1, respectively. The binding constant of ferulic acid was measured to be 2.69154E+05 M-1 and 4.74937E+05

M-1 via the Stern-Volmer and Double Logarithm methods, respectively. For isoferulic acid, the binding constant was found to be 1.68807E+05 M-1 and 1.61208E+05 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. Next, the binding constant of the glycosylated cinnamic acid derivative isoferulic acid-3-o-glucuronide via

111

the Stern-Volmer and Double-Logarithm methods was found to be 1.58162E+05 M-1 and

9.66170E+04 M-1, respectively. Finally, the binding constant of dihydroferulic acid was measured at 1.35662E+05 M-1 and 8.26790E+04 M-1 via the Stern-Volmer and Double-

Logarithm methods, respectively. The order of binding constants from largest to smallest is as follows: Ferulic acid > caffeic acid > isoferulic acid > isoferulic acid-3-o- glucuronide > dihydroferulic acid.

5.00E+05 4.50E+05 4.00E+05 3.50E+05 3.00E+05 Ka (M-1) 2.50E+05 2.00E+05 1.50E+05 KSV-BSA 1.00E+05 5.00E+04 KDL-BSA 0.00E+00

Fig 63: Binding constants for caffeic acid, ferulic acid, isoferulic acid, isoferulic acid acid-3-o-glucuronide, and dihydroferulic acid with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.9.2 Caffeic acid, Ferulic acid, Isoferulic acid, Isoferulic acid-3-o-glucuronide, and Dihydroferulic acid with LDL-VLDL

The values of the binding constants for these five cinnamic acid derivatives with

LDL-VLDL proved to be similar to the values with BSA. The binding constant of caffeic acid via the Stern-Volmer and Double-Logarithm methods was found to be 2.06544E+05

M-1 and 1.52498E+05 M-1, respectively. Next, the binding constant of ferulic acid was found to be 2.14706E+05 M-1 and 1.60933E+05 M-1 via the Stern-Volmer and Double-

Logarithm methods, respectively. The binding constant of isoferulic acid, calculated via

112

the Stern-Volmer and Double-Logarithm methods, was measured to be 1.65441E+05 M-1 and 1.19218E+05 M-1, respectively. Next, the binding constant of the glycosylated cinnamic acid derivative isoferulic acid-3-o-glucuronide via the Stern-Volmer and

Double-Logarithm methods was found to be 1.52022E+05 M-1 and 1.14832E+05 M-1, respectively. Finally, the binding constant of dihydroferulic acid was found to be

1.14449E+05 M-1 and 4.46680E+04 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. The order of binding constants from largest to smallest is as follows: Ferulic acid > caffeic acid > isoferulic acid > isoferulic acid-3-o-glucuronide > dihydroferulic acid.

2.50E+05

2.00E+05

1.50E+05 Ka (M-1) 1.00E+05 KSV-LDL 5.00E+04 KDL-LDL 0.00E+00

Fig 64: Binding constants for caffeic acid, ferulic acid, isoferulic acid, isoferulic acid acid-3-o-glucuronide, and dihydroferulic acid with LDL-VLDL via the Stern-Volmer and Double-Logarithm methods.

Section 4.5.9 Summary:

Ka Caffeic acid Ferulic acid Isoferulic acid Isoferulic acid-3- Dihydroferulic o-glucuronide acid     KSV-BSA 2.39265E+05 + 1.12 X - 1.59 X - 1.07 X - 1.17 X

KDL-BSA 3.08474E+05 + 1.54 X - 2.95 X - 1.67 X - 1.17 X

KSV-LDL-VLDL 2.06544E+05 + 1.04 X - 1.30 X - 1.09 X - 1.33 X

KDL-LDL-VLDL 1.52498E+05 + 1.06 X - 1.35 X - 1.04 X - 2.57 X Table 21: Binding constant changes from caffeic acid, to ferulic acid, to isoferulic acid, to isoferulic acid-3-o-glucuronide, to dihydroferulic acid (M-1).

113

4.5.10.0 Comparison of the Cinnamic acid Derivatives o-Coumaric acid and p-

Coumaric acid, the Benzoic acid Derivative p-Hydroxybenzoic acid, and the

Phenylacetic acid derivative p-Hydroxyphenylacetic acid

The final comparison will be made between three different types of phenolic acids: Cinnamic acid derivatives, a benzoic acid derivative, and a phenylacetic acid derivative. This section will hopefully make evident the difference in the effect the parent compounds themselves have on binding with both BSA and LDL-VLDL. o-Coumaric acid is a cinnamic acid derivative, which has one hydroxyl group attached to its aromatic ring at the 2 position. p-Coumaric acid is a structural isomer of o-coumaric acid, and has one hydroxyl group attached to its aromatic ring at the 4 position. Next, the lone benzoic acid derivative in this comparative group, p-hydroxybenzoic acid, possesses one hydroxyl group attached to its aromatic ring at the 4 position. Finally, the only phenylacetic acid derivative, p-hydroxyphenylacetic acid, also possesses a single hydroxyl group at the 4 position of its aromatic ring.

4.5.10.1 Cinnamic acid Derivatives o-Coumaric acid and p-Coumaric acid, the

Benzoic acid Derivative p-Hydroxybenzoic acid, and the Phenylacetic acid derivative p-Hydroxyphenylacetic acid with BSA

The binding constant of o-coumaric acid was calculated via the Stern-Volmer and

Double-Logarithm methods, and was found to be 1.52101E+05 M-1 and 2.14378E+05

M-1, respectively. Next, the binding constant of p-coumaric acid was found to be

1.35714E+05 M-1 and 6.38980E+04 M-1 via the Stern-Volmer and Double-Logarithm methods, respectively. Next, the binding constant of p-hydroxybenzoic acid was

114

measured to be 1.65956E+05 and 1.22821E+05 via the Stern-Volmer and Double-

Logarithm methods, respectively. Lastly, the binding constant of p-hydroxyphenylacetic acid calculated via the Stern-Volmer and Double-Logarithm methods, was found to be

6.26470E+04 M-1 and 7.01200E+03 M-1, respectively. With respect to the Stern-Volmer method, the order of binding constants from largest to smallest is as follows: p-

Hydroxybenzoic acid > o-coumaric acid > p-coumaric acid > p-hydroxyphenylacetic acid. For the Double-Logarithm method, the order of binding constants from largest to smallest is as follows: o-Coumaric acid > p-hydroxybenzoic acid > p-coumaric acid > p- hydroxyphenylacetic acid.

2.50E+05 2.00E+05 1.50E+05 Ka (M-1) 1.00E+05 5.00E+04 KSV-BSA 0.00E+00 KDL-BSA

Fig 65: Binding constants for o-coumaric acid, p-coumaric acid, p-hydroxybenzoic acid, and p-hydroxyphenylacetic acid with BSA via the Stern-Volmer and Double-Logarithm methods.

4.5.10.2 Cinnamic acid Derivatives o-Coumaric acid and p-Coumaric acid, the

Benzoic acid Derivative p-Hydroxybenzoic acid, and the Phenylacetic acid derivative p-Hydroxyphenylacetic acid with LDL-VLDL

The value of the binding constant of o-coumaric acid, calculated via the Stern-

Volmer and Double-Logarithm methods, was found to be 1.04890E+05 M-1 and

115

8.74730E+04 M-1, respectively. Next, the binding constant of p-coumaric acid was measured to be 8.93380E+04 M-1 and 6.82660E+04 M-1 via the Stern-Volmer and

Double-Logarithm methods, respectively. The binding constant of p-hydroxybenzoic acid was found to be 1.36397E+05 M-1 and 7.49260E+04 M-1 via the Stern-Volmer and

Double-Logarithm methods, respectively. Finally, the binding constant of p- hydroxyphenylacetic acid calculated via the Stern-Volmer and Double-Logarithm methods, was found to be 7.45600E+04 M-1 and 1.45980E+04 M-1, respectively. For the

Stern-Volmer method, the order of binding constants from largest to smallest is as follows: p-Hydroxybenzoic acid > o-coumaric acid > p-coumaric acid > p- hydroxyphenylacetic acid. For the Double-Logarithm method, the order of binding constants from largest to smallest is as follows: o-Coumaric acid > p-hydroxybenzoic acid > p-coumaric acid > p-hydroxyphenylacetic acid.

1.60E+05 1.40E+05 1.20E+05 1.00E+05 Ka (M-1) 8.00E+04 6.00E+04 4.00E+04 KSV-LDL 2.00E+04 0.00E+00 KDL-LDL

Fig 66: Binding constants for o-coumaric acid, p-coumaric acid, p-hydroxybenzoic acid, and p-hydroxyphenylacetic acid with LDL- VLDL via the Stern-Volmer and Double-Logarithm methods.

116

Section 4.5.10 Summary:

Ka o-Coumaric acid p-Coumaric acid p-Hydroxybenzoic p-Hydroxyphenylacetic acid acid   

KSV-BSA 1.52101E+05 - 1.12 X + 1.22 X - 2.65 X

KDL-BSA 2.14378E+05 - 3.36 X + 1.92 X - 17.52 X

KSV-LDL-VLDL 1.04890E+05 - 1.17 X + 1.53 X - 1.88 X

KDL-LDL-VLDL 8.74730E+04 - 1.28 X + 1.10 X - 5.13 X Table 22: Binding constant changes from o-coumaric acid, to o-coumaric acid, to p-hydroxybenzoic acid, to p-hydroxyphenylacetic acid (M-1).

4.6 Conclusion

As this research suggests, several conclusions can be drawn from the data obtained from this study. Starting with the quenching mechanism, evidence suggests that the mechanism of fluorescence quenching with BSA and LDL-VLDL is purely static, with this idea being supported by three main points. First, all plots maintained a linear slope starting with a protein or lipoprotein molar excess, and finishing with a polyphenol molar excess. Curvature of said plots would offer support for both, a static and dynamic quenching mechanism. Secondly, the calculated bimolecular rate constant for any of the forty polyphenols used in this study, with either BSA or LDL-VLDL, exceeds the limit set forth by the rate of diffusion by several orders of magnitude. This observation eliminates the idea that dynamic binding could be a potential mechanism for fluorescence quenching. Finally, FT-IR spectroscopy reveals a shift in the amide I bands of BSA and

LDL-VLDL, indicating an incorporation of the polyphenol into the protein/lipoprotein.

This amide I band shift provides evidence that a conformational change in the protein/lipoprotein is being observed, and a protein/lipoprotein-polyphenol complex is being formed. Additionally, calculated Gibbs free energy values, via all methods, for all polyphenols with both BSA and LDL-VLDL fell within the range of -1.80 and -3.10

117

kJM-1, indicating a large degree of spontaneity in protein/lipoprotein-polyphenol complex formation.

Next, the difference between the binding constants of all forty polyphenols and

BSA, and the binding constants of all forty polyphenols and LDL-VLDL, are statistically significant. Statistical analysis shows that the more reliable Stern-Volmer, Double-

Logarithm, and Quadratic methods possess higher mean values of binding constants with

BSA than they do for LDL-VLDL. While this may be surprising, one possible explanation may account for such results. When a polyphenol binds to BSA, it induces a conformational change in the upper levels of its protein structure that respond with positive cooperativity. Alternatively, when a polyphenol binds with LDL-VLDL, it may induce a conformation change in the upper levels of its protein structure that is governed by negative cooperativity. While the protein portion of LDL-VLDL may be less inclined to further form more protein-polyphenol complexes, the lipid portion of this lipoprotein is still available to form complexes with a polyphenol, especially if the polyphenol is a nonpolar compound. Ultimately, BSA may not exhibit positive cooperativity, and in reality, when compared to LDL-VLDL, it is more probable that BSA experiences a lesser degree of negative cooperativity (the average n value is slightly lower than 1). This is one potential theory that could help explain why the average binding constant of a polyphenol and BSA is higher than the binding constant of said polyphenol and LDL-VLDL, while still being sustained by evidence from other non-fluorescence quenching studies that support the idea why LDL-VLDL has a higher n value than BSA. Alternatively, statistical analysis shows that for the less reliable Scatchard and Benesi-Hildebrand

118

methods, the mean value of binding constants between these forty polyphenols and LDL-

VLDL is higher than that of the polyphenols and BSA.

Another idea supported by this study is that there are several statistically significant correlations between the binding constants of all forty polyphenols calculated by one of the five methods, and either BSA or LDL-VLDL. Among all five outside factors measured to determine if linear correlations were significant, the n value ranked the highest, and possessed nine cases of statistical significance. Next, Log P/D vs Log Ka correlation coefficients ranked second, containing six statistically significant cases. This was followed up by the Log P/D value, which was comprised of four statistically significant cases. All correlations between the binding constants of these forty polyphenols and both polar surface area and the number of hydrogen bond donors and acceptors proved to be statistically insignificant.

Finally, the last and potentially most important idea this study puts forth is the notion that the degree of binding between a polyphenol and both BSA and LDL-VLDL, given the parameters utilized in this study, is primarily dictated by polyphenol structure

(in regards to the Stern-Volmer and Double-Logarithm methods). Parent compounds exhibit higher binding constants with BSA and LDL-VLDL than their glycoside metabolites, with glucuronide metabolites exhibiting higher binding constants than glucoside metabolites (i.e., 1) quercetin > quercetin-3-glucuronide > quercetin-3- glucoside, 2) caffeic acid > both caffeic acid glycosides, and 3) isoferulic acid > isoferulic acid-3-o-glucuronide). Also, in the cases involving phenolic acids and their glycoside metabolites, phenolic acids with glucuronic acid on the 3 position of the aromatic ring displayed higher binding constant values than their structural isomers

119

containing glucuronic acid at the 4 position (i.e. caffeic acid-3-o-glucuronide > caffeic acid-4-o-glucuronide).

Similarly, the C2-C3 double bond of cinnamic acids appears to play an important role in determining the degree of binding between a polyphenol and BSA or LDL-VLDL.

Cinnamic acids with the C2-C3 double bond were found to have higher binding constant values when compared to their derivatives that lacked this double bond (i.e., 1) ferulic acid > dihydroferulic acid and 2) caffeic acid > dihydrocaffeic acid).

Phenylacetic acid derivatives containing two hydroxyl groups exhibited a much higher degree of binding with BSA than those that only contained one hydroxyl group.

Alternatively, there was no difference in the degree of binding between phenylacetic acid derivatives containing two hydroxyl groups and those that possessed only one hydroxyl group, with LDL-VLDL.

Benzoic acids with three hydroxyl groups exhibited higher degrees of binding than those with two or one hydroxyl groups. However, it was not the case that benzoic acid derivatives containing two hydroxyl groups exhibited higher binding constants than those that possessed only one hydroxyl group. It seems that the position of the hydroxyl group on the aromatic ring of the benzoic acid derivative plays a key role in determining the degree of binding, with hydroxyl groups ortho and meta on the ring appearing to contribute to higher binding constant values, and those para seemingly help contribute to a decrease in the degree of binding with both BSA and LDL-VLDL. This idea is further supported by the observed binding constants of cinnamic acid derivatives (i.e. o-coumaric acid > p-coumaric acid).

120

Once methylated hydroxyl groups are included, the notion mentioned above does not appear to be maintained. Ferulic acid contains a methoxy group meta, and a hydroxyl group para to its aromatic ring. Isoferulic acid has these two functional groups reversed, and yet still experiences a much lower binding constant than ferulic acid in all cases. In situations where hydroxyl groups became methylated, mixed results were obtained. In the instance of stilbenes, methylated hydroxyl groups seemed to act favorably in increasing the binding constant of the polyphenol (i.e. pterostilbene > resveratrol). Additionally, the tri-methoxy benzoic acid derivative eudesmic acid exhibited a higher binding constant with LDL-VLDL, than that of the tri-hydroxylated benzoic acid derivative gallic acid.

However, in binding with BSA, eudesmic acid exhibited a lower binding constant than that of gallic acid. It appears that that some other factor is at play, potentially sterics, which may interrupt hydrogen binding between lower molecular weight polyphenols and transport proteins.

Finally, in an attempt to compare all three types of phenolic acids utilized by this study, three polyphenols were chosen: p-Coumaric acid, p-hydroxybenzoic acid, and p- hydroxyphenylacetic acid. These three compounds were selected because they all possess equivalent substituents at the same position of their aromatic rings. It was found that in all cases, the benzoic acid derivative possessed the largest binding constant, followed closely by the cinnamic acid derivative. The phenylacetic acid derivative proved to exhibit the smallest binding constant at a much greater degree.

Overall, there are an infinite amount of parameters that can be utilized when performing the fluorescence quenching method. The goal of this study was to employ one set of parameters, and then apply them to all forty polyphenols utilized in an attempt to

121

measure the degree of binding with BSA and LDL-VLDL through various methods.

Given the results, it appears that as a whole, non-phenolic acids have a much higher average binding constant value when than that of phenolic acids. While this study did not investigate the radical scavenging ability of these polyphenols, and hence their level of effectiveness as antioxidants, it does exemplify the affinity these polyphenols have for transport proteins in vitro. This research supports many studies that have been performed on the binding of polyphenols with BSA.[81,82] This study also supports the little research done on in vivo binding of polyphenols with LDL-VLDL, which have shown that the relationship between the concentration of oxidized LDL-VLDL in plasma and the concentration of polyphenols and their metabolites are inversely proportional.[83]

Because an increased concentration of oxidized LDL-VLDL is a biomarker for disease, this research may help to diminish, and even more importantly, potentially negate the destructive impact brought about by oxidized LDL-VLDL. If in vivo binding constants are similar to those calculated in vitro, than it goes to say that these forty polyphenols bind spontaneously with both BSA and LDL-VLDL to form a polyphenol-protein complex. This antioxidative complex may not only prove as an effective means in supplying antioxidants throughout the body, but also may be a crucial component in the fight against atherosclerosis.

122

References:

1. Sen, S., and Chakraborty, R. “Chapter 1: The Role of Antioxidants in Human Health.” Oxidative Stress: Diagnostics, Prevention, and Therapy. By Silvana Andreescu and Maria Hepel. Washington, DC: American Chemical Society, 2011. 1-37. Print. 2. Yu, M.; Tsunoda, H.; and Tsunoda, M. Environmental Toxicology: Biological and Health Effects of Pollutants. Boca Raton: CRC, 2005. Print. 3. Marian, V.; Leibfritz D.; Moncol, J.; Cronin, M.T.D.; Mazur, M.; and Telser, J. “Free radicals and antioxidants in normal physiological functions and human disease." The International Journal of Biochemistry & Cell Biology. (2007) 39.1: 44-84. Web. 10 Feb. 2015. 4. National Institute of Health. “What Is Atherosclerosis?”. Department of Health and Human Services. 4 Aug. 2014. Web. 11 Feb. 2015. 5. Law, M.R.; Wald, N.J.; Rudnicka, A. “Quantifying effect of statins on low density lipoprotein cholesterol, ischaemic heart disease, and stroke: systematic review and meta-analysis”. Br. Med. J. (2003) 326; 7404: 1423. 6. Unit, E.S. “Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins”. Lancet (2005) 366: 1267−1278. 7. Pereira, D.M.; Valentão, P.; Pereira, A.; Andrade, P.B. “Phenolics: from chemistry to biology” Molecules. (2010) 14: 2202-2211. 8. Awstini, S; Dmommt, J.; Perwnt, G. “Distribution of phenolic compounds in the seagrass Posidonia oceanica” Phytochemistry. (1998) 48: 611-617. 9. Dumay, O.; Coata, J.; Desjorbert, J; Pergent, G. “Variations in the concentration of phenolic compounds in the seagrass Posidonia oceanica under conditions of competition” Phytochemistry. (2004) 65: 3211-3220. 10. Silva, F.; Borges, F.; Guimarães, C.; Lima, J.L.F.C.; Matos,C.; and Reis, S. “Phenolic acids and derivatives: Studies on the relationship among structure, radical scavenging activity, and physiochemical parameters." J. Agric. Food Chem. (2000) 48: 2122-126. Print 11. Fraga, C.G.; Galleano, M.; Verstraeten, S.V.; and Oteiza, P.I. “Basic biochemical mechanisms behind the health benefits of polyphenols”. Mol. Aspects Med. (2010) 31.6: 435-445. 12. Poquet, L.; Clifford, M.N.; and Williamson, G. “Investigation of the metabolic fate of dihydrocaffeic acid”. Biochemical Pharmacology. (2008) 75.5: 1218-1229. 13. "Ellagic Acid." Ellagic Acid. Phytochemicals, n.d. Web. 19 Feb. 2015. . 14. Mandal, Shivappurkar, Galati, and Stoner. "Inhibition of N- nitrosobenzymethylamine metabolism and DNA binding in cultured rat sophagus by ellagic acid". Carcinogenesis. (1988) 9.7: 1313–1316

123

15. Seeram, N.P.; Adams, L.S.; Henning, S.M. et al. "In vitro antiproliferative, apoptotic and antioxidant activities of punicalagin, ellagic acid and a total pomegranate tannin extract are enhanced in combination with other polyphenols as found in pomegranate juice". J. Nutr. Biochem. (1999) 16.6: 360–67. 16. Narayanan, B.A.; Geoffroy, O.; Willingham, M.C.; Re, G.G.; Nixon, D.W. “p53/p21 (WAF1/CIP1) expression and its possible role in G1 arrest and apoptosis in ellagic acid treated cancer cells”. Cancer Lett. (1999) 136.2: 215–221. 17. Vattem, D.A. and Shetty, K. "Biological Function of Ellagic Acid: A Review". Journal of Food Biochemistry. (2005) 29.3: 234–266. 18. Donelly, M,I. and Dagley, S. "Production of Methanol from Aromatic Acids by Pseudomonas Putida." J. Bacteriol. (1980) 142.3: 916-24. PubMed.gov. Web. 20 Feb. 2015. 19. Orabi, K.Y. et. al. "Selective growth inhibition of human malignant melanoma cells by syringic acid-derived proteasome inhibitors." Cancer Cell International. (2013)13.1: 82-87. Web. 20. Ramachandran, V. "Preventive Effect of Syringic Acid on Hepatic Marker Enzymes and Lipid Profile Against Acetaminophen-Induced Hepatotoxicity Rats." Inter. J. of Pharm. & Bio Archives. (2010) 1.4: 393- 398. Web. 12 Feb. 2015. 21. Satomi, H; Umemura, K; Ueno, A; Hatano, T; Okuda, T; Noro, T. "Carbonic anhydrase inhibitors from the pericarps of Punica granatum L". Biological & Pharmaceutical Bulletin. (1993) 16.8: 787–790. 22. Liu, Y; Pukala, T. L.; Musgrave, I. F.; Williams, D. M.; Dehle, F. C.; Carver, J. A. "Gallic acid is the major component of grape seed extract that inhibits amyloid fibril formation". Bioorganic & Medicinal Chemistry Letters. (2013) 23.23: 6336–6340 23. Liu, Y; Carver, J. A.; Calabrese, A. N.; Pukala, T. L. "Gallic acid interacts with α- synuclein to prevent the structural collapse necessary for its aggregation". Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. (2014) 1844.9: 1481–1485. 24. Wang, Y. J.; Thomas, P; Zhong, J. H.; Bi, F. F.; Kosaraju, S; Pollard, A; Fenech, M; Zhou, X. F. "Consumption of grape seed extract prevents amyloid-beta deposition and attenuates inflammation in brain of an Alzheimer's disease mouse". Neurotoxicity Research. (2009) 15.1: 3–14. 25. Kakkar, S. and Bais, S. “A review on protocatechuic acid and its pharmacological potential”. ISRN Pharmacology (2014): pp1-9 26. Babich, H.; Sedletcaia, A.; Kenigsberg, B. (November 2002). "In vitro cytotoxicity of protocatechuic acid to cultured human cells from oral tissue: involvement in oxidative stress". Pharmacol. Toxicol. (2002) 91.5: 245–253. 27. Juurlink, B.H.J.; Azouz, H.J.; Aldalati, A.M.Z.; Altinawi, B.M.H.; Ganguly, P. “Hydroxybenzoic acid isomers and the cardiovascular system.” Nutrition Journal. (2014) 13.63: 1-10. Web. 22 Feb. 2015.

124

28. Loiseau, P. M. and Nguyen, D.X. "Plasmodium berghei mouse model: antimalarial activity of new alkaloid salts and of thiosemicarbazone and acridine derivatives." Tropical Medicine and International Health. (1996) 1.3: 379-84. Web. 22 Feb. 2015. 29. Li, N.; Zhang, G.; Yi, F.X.; Zou, A.P.; and Li, P.L. “Activation of NAD(P)H oxidase by outward movements of H+ ions in renal medullary thick ascending limb of Henle.” American Journal of Physiology-Renal Physiology. (2005) 289.5: 1048–1056. 30. Heumüller,S.; Wind, S.; Barbosa-Sicard, E.; Schmidt, H.H.; Busse, R.; Schröder, K.; and Brandes, R.P. “Apocynin is not an inhibitor of vascular NADPH oxidases but an antioxidant.” Hypertension. (2008) 51.2: 211-217. 31. Kim, S.J.; Kim, M.C.; Um, J.Y.; and Hong, S.H. “The beneficial effect of vanillic acid on ulcerative colitis.” Molecules. (2010) 15: 7208-7217. 32. Raneva, V.; Shimasaki, H.; Ishida, Y.; Ueta, N.; and Niki, E. “Antioxidative activity of 3,4-dihydroxyphenylacetic acid and caffeic acid in rat plasma.” Lipids. (2001) 10: 1111-1116 33. Gonthier, M.P.; Cheynier, V.; Donovan, J.L.; Manach, C.; Morand, C.; Mila, I.; Lapierre, C.; Rémésy, C.; and Scalbert, A. “Microbial aromatic acid metabolites formed in the gut account for a major fraction of the polyphenols excreted in urine of rats fed red wine polyphenols.” J. Nutrition. (2003) 133.2: 461-467. 34. Rosa, A.; Tuberoso, C.I.G.; Atzeri, A.; Melis, M.P.; Bifulco, E.; and Dessi, M.A. “Antioxidant profile of strawberry tree honey and its marker homogentisic acid in several models of oxidative stress”. Food Chem. (2011) 129.3: 1045-1053. 35. Ohnishi, R.; Ito, H.; Iguchi, A.; Shinomiya, K.; Kamei, C.; Hatano, T.; and Yoshida, T. “Effects of chlorogenic acid and its metabolites on spontaneous locomotor activity in mice.” Bioscic Biotechnol. Biochem. (2006) 10: 2560-2563. 36. Johnston, K. L.; Clifford, M. N.; Morgan, L. M. “Coffee acutely modifies gastrointestinal hormone secretion and glucose tolerance in humans: glycemic effects of chlorogenic acid and caffeine”. Am. J. Clin. Nutr. (2003) 78.4: 728–733. 37. Gelinas, P. and McKinnon, C.M. “Effect of wheat variety, farming site, and bread-baking on total phenolics”. International Journal of Food Science and Technology. (2006) 41.3: 329-332. 38. Ibtissem, B.; Abdelly, C.; and Sfar, S. “Antioxidant and antibacterial properties of Mesembryanthemum crystallinum and Carpobrotus edulis extracts.” Advances in Chemical Engineering and Science. (2012) 2.3: 359-365. 39. Meeprom, A.; Weerachat, S.; Chan, C.B.; and Adisakwattana, S. “Isoferulic acid, a new anti-glycation agent, inhibits fructose- and glucose-mediated protein glycation in vitro.” Molecules. (2013) 18: 6439-6454. 40. Köhidai L. and Csaba G. “Chemotaxis and chemotactic selection induced with cytokines (IL-8, RANTES and TNF-alpha) in the unicellular Tetrahymena pyriformis”. Cytokine. (1998) 10.7: 481–486.

125

41. Beck, J.J.; Kim, J.H.; Campbell, B.C.; and Chou, S.C. “Fungicidal activities of dihydroferulic acid alkyl ester analogues”. Journal of Natural Products. (2007) 70.5: 779-782. 42. Olthof, M.R.; Hollman, P.C.; and Katan, M.B.; “Chlorogenic acid and caffeic acid are absorbed in humans”. J. Nutr. (2001) 131.1: 66–71. 43. Agricultural Research Service. “Nuts' New Aflatoxin Fighter: Caffeic Acid?” www.ars.usda.gov. United States Department of Agriculture, 4 Oct. 2006. Web. 24 Feb. 2015. . 44. Rajendra, P.N; Karthikeyan, A.; Karthikeyan, S.; and Reddy, B.V. “Inhibitory effect of caffeic acid on cancer cell proliferation by oxidative mechanism in human HT-1080 fibrosarcoma cell line”. Mol Cell Biochem. (2011) 1.2: 11-19. 45. Sørensen, A.D.M.; Nielsen, N.S.; Yang, Z.; Xu, X.; and Jacobsen, C. “Lipophilization of dihydrocaffeic acid affects its antioxidative properties in fish-oil-enriched emulsions”. European. J. of Lipid Sci. and Tech. (2012) 114.2: 134-145. 46. Zeng, X.; Zheng, J.; Fu, C.; Su, H.; Sun, X.; Zhang, X.; Hou, Y.; and Zhu, Y. “A newly synthesized sinapic acid derivative inhibits endothelial activation in vitro and in vivo”. Mol. Phar. (2013) 83.5: 1099-1108. 47. Foti, M.; Piattelli, M.; Baratta, M.T.; and Ruberto, G. “Flavonoids, coumarins, and cinnamic acids as antioxidants in a micellar system. Structure-activity relationship.” J. Agric. Food Chem. (1996) 44.2: 497-501. 48. Zang, L.Y.; Cosma, G.; Gardner, H.; Shi, X.; Castranova, V.; and Vallyathan, V. “Effect of antioxidant protection by p-coumaric acid on low-density lipoprotein cholesterol oxidation”. Am. J. Physiol. Cell. Physiol. (2000) 279.4: 954-960. 49. Yildiz, F. “Food Acids: Organic Acids, Volatile Organic Acids, and Phenolic Acids.” Advances in Food Biochemistry. Boca Raton: CRC, 2010. 332-34. Print. 50. Agricultural Research Service. “Pterostilbene’s Healthy Potential” www.ars.usda.gov. United States Department of Agriculture, 4 Oct. 2006. Web. 27 Feb. 2015. . 51. Pari, L. and Satheesh, M.A. “Effect of pterostilbene on hepatic key enzymes of glucose metabolism in streptozotocin- and nicotinamide-induced diabetic rats”. Life Sciences. (2006) 79.7: 641–645. 52. Robb, E.L.; Page, M.M.; Wiens, B.E.; and Stuart, J.A. “Molecular mechanisms of oxidative stress resistance induced by resveratrol: Specific and progressive induction of MnSOD”. Biochem. Biophys. Res. Commun. (2008) 367.2: 406–412. 53. Woo, K.J.; Jeong, Y.J.; Inoue, H.; Park, J.W.; and Kwon, T.K. “Chrysin suppresses lipopolysaccharide-induced cyclooxygenase-2 expression through the inhibition of nuclear factor for IL-6 (NF-IL6) DNA-binding activity”. FEBS Lett. (2005) 579.3: 705–711.

126

54. Chao, J.I.; Su, W.C.; and Liu, H.F. “ Baicalein induces cancer cell death and proliferation retardation by the inhibition of CDC2 kinase and surviving associated with opposite role of p38 mitogen-activated protein kinase in AKT”. Mol. Cancer Ther. (2007) 6: 3039-3049. 55. Thors, L.; Burston, J.J.; Alter, B.J.; McKinney, M.K.; Cravatt, B.F.; Ross, R.A.; Pertwee, R.G.; Gereau, R.W. 4th; Wiley, J.L.; and Fowler, C.J. “Biochanin A, a naturally occurring inhibitor of fatty acid amide hydrolase”. British Journal of Pharmacology. (2010) 160.3: 549–560. 56. Zhou, Y.X.; Zhang, H.; and Peng, C. “Puerarin: a review of pharmacological effects”. Phytother. Res. (2014) 28.7: 961-975. 57. Cermak, R. and Wolffram, S. “The potential of flavonoids to influence drug metabolism and pharmacokinetics by local gastrointestinal mechanisms”. Curr. Drug Metab. (2006) 7.7: 729–44. 58. Wang, G.; Song, L.; Wang, H.; and Xing, N. “Quercetin synergizes with 2- methoxyestradiol inhibiting cell growth and inducing apoptosis in human prostate cancer cells”. Oncol. Rep. (2013) 1: 357-363. 59. Abraham, S.K.; Schupp, N.; Schmid, U.; and Stopper, H. “Antigenotoxic effects of the phytoestrogen pelargonidin chloride and the polyphenol chlorogenic acid”. Mol. Nutr. Food. Res. (2007) 51.7: 880-887. 60. Lakowicz, J.R. Principles of Fluorescence Spectroscopy. New York: Springer, 2006. Print. 61. Soares, S.; Mateus, N.; and De Freitas, V. “Interaction of different polyphenols with bovine serum albumin (BSA) and human salivary α-amylase (HSA) by fluorescent quenching”. J. Agric. Food. Chem. (2007) 55.6: 6726-6735. 62. Rawel, H.M.; Meidtner, K.; and Kroll, J. “Binding of selected phenolic compounds to proteins”. J. Agric. Food Chem. (2005) 53.10: 4228-4235. 63. Hagerman, A.E. and Butler, L.G. “Protein precipitation method for the quantitative determination of tannins”. J. Agric. Food. Chem. (1978) 26.4: 809-812. 64. Hagerman, A.E.; Rice, M.E.; and Ritchard, N.T. “Mechanisms of protein p precipitation for two tannins, pentagalloyl glucose and epicatechin16 (4→8) Catechin (Procyanidin)”. J. Agric. Food. Chem. (1998) 46.7: 2590- 2595. 65. Peters, T. All about Albumin: Biochemistry, Genetics, and Medical Applications. San Diego: Academic, 1996. Print. 66. Majorek, K.A.; Porebski, P.J.; Dayal, A.; Zimmerman, M.D.; Jablonska, K.; Stewart, A.J.; Chruszcz, M.; and Minor, W. “Structural and immunologic characterization of bovine, horse, and rabbit serum albumins”. Mol. Immunol. (2012) 52:174-182. 67. Segrest, J.P.; Jones, M.K.; Loof, H.D.; and Dashti, N. “Structure of apolipoprotein B-100 in low density lipoproteins”. Journal of Lipid Research. (2001) 42: 1346-1367. 68. Law, S.W.; Grant, S.M.; Higuchi, K.; Hospattankar, A.; Lackner, K.; Lee, N.; and Brewer, H.B. Jr. “Human liver apolipoprotein B-100 cDNA: Complete nucleic acid and derived amino acid sequence”. Proc. Natl. Acad. Sci. USA. (1986) 83: 8142-8146.

127

69. Alarcón, E.; Aspée, A.; Albuin, E.B.; and Lissi, E.A. “Evaluation of solute binding to proteins and intra-protein distances from steady state fluorescence measurements”. J. Photochem. Photobiol. (2012) B106: 1- 17. 70. Ward, L.D. “Measurement of ligand binding to proteins by fluorescence spectroscopy”. Methods Enzymol. (1985) 117: 400-414. 71. Wei, X.L.; Xiao, J.B.; Wang, Y.; and Bai, Y. “Which model based on fluorescence quenching is suitable to study the interaction between trans- resveratrol and BSA?” Spectrochim. Acta. (2010) A75: 299-304. 72. Van de Weert, M. “Fluorescence quenching to study protein-ligand binding: Common errors”. J. Fluoresc. (2010) 20: 625-629. 73. Van de Weert, M. and Stella, L. “Fluorescence quenching and ligand binding: A critical discussion of a popular methodology”. J. Molec. Struct. (2011) 998: 144-150. 74. Green, N.J.B.; Pimblott, S.M.; and Tachiya, M. “Generalizations of the Stern- Volmer Relation”. J. Phys. Chem. (1993) 97: 196-202. 75. Encinas, M.V.; Lissi, E.; and Vergara, C. “Association of valdecoxib, a nonsteroidal anti-inflammatory drug, with human serum albumin”. Photochem. and Photobio. (2013) 89: 1399-1405. 76. Lissi, E. and Abuin, E. “On the evaluation of the number of binding sites in proteins from steady state fluorescence measurements”. J. Fluoresc. (2011) 21: 1831-1833. 77. Beckett, D. “Chapter one-measurement and analysis of equilibrium binding titrations: a beginners guide”. Methods Enzymol. (2011) 488: 1-16. 78. Chao, C.C.; Ma, Y.S.; and Stadtman, E. R. “Modification of protein surface hydrophobicity and methionine oxidation by oxidative systems”. Proc. Natl. Acad. Sci. USA. (1997) 94.7: 2969-2974. 79. Papadopoulou, A.; Green, R.J.; and Frazier, R. A. “Interaction of flavonoids with bovine serum albumin: a fluorescence quenching study”. J. Agric. Food Chem. (2005) 53: 158-163. 80. Krilov, D; Balarin, M.; Kosović, M.; Gamulin, O.; and Brnjas-Kraljević, J. “FT- IR spectroscopy of lipoproteins—a comparative study”. Spectrochim. Acta. A. Mol. Biomol. Spectrosc. (2009) 73.4: 701-706. 81. Xiao, J.; Zhao, Y.; Wang, H.; Yuan, Y.; Yang, F.; Zhang, C.; and Yamamoto, K. “Noncovalent interaction of dietary polyphenols with common human plasma proteins”. J. Agric. Food. Chem. (2011) 59.1: 10747-10754. 82. Xiao, J. and Kai, G. “A review of dietary polyphenol-plasma interactions: Characterization, influence on the bioactivity, and structure-affinity relationship”. Critical Reviews in Food Science and Nutrition. (2012) 52.1: 85-101. 83. Cotrim, B.A.; Joglar, J.; Rojas, M.J.L.; Decara del Olmo, J.M.; Macias-González, M.; Cuevas, M.R.; Fitó, M. Muñoz-Aguayo, D.; Covas Planells, M.I.; Farré, M.; Rodríguez de Fonseca, F.; and de la Torre, R. “Unsaturated fatty alcohol derivatives of olive oil phenolic compounds with potential low-density lipoprotein (LDL) antioxidant and antiobesity properties”. J. Agric. Food. Chem. (2012) 60.1: 1067-1074.

128 Appendix A: Ka Statistics and Correlations between Methods

Appendix A: Statistical Analysis of the Significance of the Binding Constants for 40 Polyphenols between BSA and LDL-VLDL

Table A1: KSV-BSA and KSV-LDL/VLDL – Paired two-sample t-test

Comparing Means [ Paired two-sample t-test ] (KSV-BSA and KSV-LDL/VLDL) Descriptive Statistics Sample VAR size Mean Variance

Ksv-BSA 40 2.93906E+05 1.00700E+11 Ksv-LDL/VLDL 40 1.77332E+05 5.61074E+09

Summary Degrees Of Freedom 39 Hypothesized Mean Difference 0.E+0 Test Statistics 2.616 Pooled Variance 5.31500E+10

Two-tailed distribution p-level 0.013 t Critical Value (5%) 2.02439

One-tailed distribution p-level 0.006 t Critical Value (5%) 1.685 Pearson Correlation Coefficient 0.565

G-criterion Test Statistics 0.103 p-level 0.084 Critical Value (5%) 0.184

Pagurova criterion Test Statistics 2.261 p-level 0.971 Ratio of variances parameter 0.947 Critical Value (5%) 0.025

Table A2: KSV-BSA and KSV-LDL/VLDL – Paired two-sample t-test – Statistics STATISTIC VALUE Mean Difference 1.22762E+05 Std. Dev of Difference 2.79142E+05 Standard Error of Difference 4.41363E+04 T-Alpha half 95% Conf. Interval 2.02439 Lower Conf. Interval 3.34127E+04 Higher Conf. Interval 2.12111E+05

RESULT: The difference between the binding constants of BSA and LDL-VLDL using the Stern-Volmer method is statistically significant.

128 Appendix A: Ka Statistics and Correlations between Methods

Figure A1: KSV-BSA vs KSV-LDL-VLDL

KSV-BSA vs KSV-LDL/VLDL

4.50E+05 4.00E+05 3.50E+05 3.00E+05 2.50E+05 K -LDL/VLDL SV 2.00E+05 1.50E+05 1.00E+05 5.00E+04 0.00E+00 0.00E+00 1.00E+06 2.00E+06 3.00E+06 y = 0.1334x + 138128 KSV-BSA R² = 0.3193

Table A3: Correlation Coefficient Matrix KSV-BSA vs KSV-LDL-VLDL Correlation Coefficients Matrix (KSV-BSA vs KSV-LDL-VLDL) Critical value Sample size 40 (2%) 2.431

5.81765E+05 3.93676E+05 581765 Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) 393676 Pearson Correlation Coefficient 0.568 1. R Standard Error 0.018 t 4.195 p-value 0. H0 (2%) rejected

R Variable vs. Variable R 393676 vs. 581765 0.568

RESULT: The correlation coefficient of the linear regression formula of KSV-BSA vs KSV-LDL-VLDL is statistically significant.

129 Appendix A: Ka Statistics and Correlations between Methods

Table A4: KDL-BSA and KDL-LDL/VLDL – Paired two-sample t-test

Comparing Means [ Paired two-sample t-test ] (KDL-BSA and KDL-LDL/VLDL) Descriptive Statistics Sample VAR size Mean Variance

KDL-BSA 40 2.82699E+05 7.78229E+10

KDL-LDL/VLDL 40 1.26286E+05 7.62679E+09

Summary Degrees Of Freedom 39 Hypothesized Mean Difference 0.E+0 Test Statistics 4.20946 Pooled Variance 4.27249E+10

Two-tailed distribution p-level 0.00015 t Critical Value (5%) 2.02269

One-tailed distribution p-level 0.00007 t Critical Value (5%) 1.68488 Pearson Correlation Coefficient 0.62026

G-criterion Test Statistics 0.16147 p-level 0.03408 Critical Value (5%) 0.18367

Pagurova criterion Test Statistics 3.38414 p-level 0.99853 Ratio of variances parameter 0.91075 Critical Value (5%) 0.0252

Table A5: KDL-BSA and KDL-LDL/VLDL – Paired two-sample t-test – Statistics STATISTIC VALUE Mean Difference 1.61307E+05 Std. Dev of Difference 2.31588E+05 Standard Error of Difference 3.66173E+04 T-Alpha half 95% Conf. Interval 2.02269 Lower Conf. Interval 8.72414E+04 Higher Conf. Interval 2.35372E+05

RESULT: The difference between the binding constants of BSA and LDL-VLDL using the Double-Logarithm method is statistically significant.

130 Appendix A: Ka Statistics and Correlations between Methods

Figure A2: KDL-BSA vs KDL-LDL-VLDL

KDL-BSA vs KDL-LDL/VLDL

4.00E+05 3.50E+05 3.00E+05 2.50E+05 2.00E+05 KDL- LDL/VLDL 1.50E+05 1.00E+05 5.00E+04 0.00E+00 0.00E+00 5.00E+05 1.00E+06 1.50E+06 2.00E+06 y = 0.1942x + 71394 KDL-BSA R² = 0.3847

Table A6: Correlation Coefficient Matrix KDL-BSA vs KDL-LDL-VLDL Correlation Coefficients Matrix (KDL-BSA vs KDL-LDL-VLDL) Critical value Sample size 40 (2%) 2.431

6.60426E+05 3.70553E+05 660426 Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) 370553 Pearson Correlation Coefficient 0.599 1. R Standard Error 0.017 t 4.548 p-value 0. H0 (2%) rejected

R Variable vs. Variable R 370553 vs. 660426 0.599

RESULT: The correlation coefficient of the linear regression formula of KDL-BSA vs KDL-LDL-VLDL is statistically significant.

131 Appendix A: Ka Statistics and Correlations between Methods

Table A7: KSc-BSA and KSc-LDL/VLDL – Paired two-sample t-test

Comparing Means [ Paired two-sample t-test ] (KSc-BSA and KSc-LDL/VLDL) Descriptive Statistics Sample VAR size Mean Variance

KSc-BSA 40 1.30614E+05 1.71013E+10

KSc-LDL/VLDL 40 1.50617E+05 2.37512E+09

Summary Degrees Of Freedom 39 Hypothesized Mean Difference 0.E+0 Test Statistics 0.96227 Pooled Variance 9.73820E+09

Two-tailed distribution p-level 0.34185 t Critical Value (5%) 2.02269

One-tailed distribution p-level 0.17092 t Critical Value (5%) 1.68488 Pearson Correlation Coefficient 0.172

G-criterion Test Statistics 0.04768 p-level 0.13217 Critical Value (5%) 0.18367

Pagurova criterion Test Statistics 0.90649 p-level 0.6309 Ratio of variances parameter 0.87805 Critical Value (5%) 0.0252

Table A8: KSc-BSA and KSc-LDL/VLDL – Paired two-sample t-test – Statistics STATISTIC VALUE Mean Difference 8.88235E+04 Std. Dev of Difference 9.79920E+04 Standard Error of Difference 1.54939E+04 T-Alpha half 95% Conf. Interval 2.02269 Lower Conf. Interval 5.74841E+04 Higher Conf. Interval 1.20163E+05

RESULT: The difference between the binding constants of BSA and LDL-VLDL using Scatchard’s method is statistically significant.

132 Appendix A: Ka Statistics and Correlations between Methods

Figure A3: KSc-BSA vs KSc-LDL-VLDL

KSc-BSA vs KSc-LDL/VLDL

3.00E+05 2.50E+05 2.00E+05

KSc-LDL/VLDL 1.50E+05 1.00E+05 5.00E+04 0.00E+00 0.00E+00 2.00E+05 4.00E+05 6.00E+05 8.00E+05

y = 0.0641x + 142244 KSc-BSA R² = 0.0296

Table A9: Correlation Coefficient Matrix KSc-BSA vs KSc-LDL-VLDL Correlation Coefficients Matrix (KSc-BSA vs KSc-LDL-VLDL) Critical value Sample size 40 (2%) 2.431

3.29882E+05 2.66555E+05 329882 Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) 266555 Pearson Correlation Coefficient 0.086 1. R Standard Error 0.027 t 0.524 p-value 0.604 H0 (2%) accepted

R Variable vs. Variable R 266555 vs. 329882 0.086

RESULT: The correlation coefficient of the linear regression formula of KSc-BSA vs KSc-LDL-VLDL is not statistically significant.

133 Appendix A: Ka Statistics and Correlations between Methods

Table A10: KQu-BSA and KQu-LDL/VLDL – Paired two-sample t-test Comparing Means [ Paired two-sample t-test ] (KQu-BSA and KQu-LDL/VLDL) Descriptive Statistics Sample VAR size Mean Variance

KQu-BSA 40 1.36454E+05 4.48333E+09

KQu-LDL/VLDL 40 1.02967E+05 6.87924E+08

Summary Degrees Of Freedom 39 Hypothesized Mean Difference 0.E+0 Test Statistics 4.221 Pooled Variance 2.58562E+09

Two-tailed distribution p-level 0.00010 t Critical Value (5%) 2.023

One-tailed distribution p-level 0.00005 t Critical Value (5%) 1.685 Pearson Correlation Coefficient 0.756

G-criterion Test Statistics 0.156 p-level 0.039 Critical Value (5%) 0.184

Pagurova criterion Test Statistics 2.945 p-level 0.995 Ratio of variances parameter 0.867 Critical Value (5%) 0.025

Table A11: KQu-BSA and KQu-LDL/VLDL – Paired two-sample t-test – Statistics STATISTIC VALUE Mean Difference 3.77164E+04 Std. Dev of Difference 4.69950E+04 Standard Error of Difference 7.43057E+03 T-Alpha half 95% Conf. Interval 2.023 Lower Conf. Interval 2.26866E+04 Higher Conf. Interval 5.27461E+04

RESULT: The difference between the binding constants of BSA and LDL-VLDL using the Quadratic Equation is statistically significant.

134 Appendix A: Ka Statistics and Correlations between Methods

Figure A4: KQu-BSA vs KQu-LDL-VLDL

KQu-BSA vs KQu-LDL/VLDL 2.00E+05

1.60E+05

1.20E+05

KQu-LDL/VLDL 8.00E+04

4.00E+04

0.00E+00 0.00E+00 1.00E+05 2.00E+05 3.00E+05 4.00E+05 y = 0.296x + 62581 KQu-BSA R² = 0.5709

Table A12: Correlation Coefficient Matrix KQu-BSA vs KQu-LDL-VLDL Correlation Coefficients Matrix (KQu-BSA vs KQu-LDL-VLDL) Critical value Sample size 40 (2%) 2.431

2.45478E+05 1.79272E+05 245478 Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) 179272 Pearson Correlation Coefficient 0.742 1. R Standard Error 0.012 t 6.732 p-value 0. H0 (2%) rejected

R Variable vs. Variable R 179272 vs. 245478 0.742

RESULT: The correlation coefficient of the linear regression formula of KQu-BSA vs KQu-LDL-VLDL is statistically significant.

135 Appendix A: Ka Statistics and Correlations between Methods

Table A13: KBH-BSA and KBH-LDL/VLDL – Paired two-sample t-test

Comparing Means [ Paired two-sample t-test ] (KBH-BSA and KBH-LDL/VLDL) Descriptive Statistics Sample VAR size Mean Variance

KBH-BSA 40 8.25277E+05 5.67103E+11

KBH-LDL/VLDL 40 1.46036E+06 5.38353E+11

Summary Degrees Of Freedom 39 Hypothesized Mean Difference 0.E+0 Test Statistics 3.86321 Pooled Variance 5.52728E+11

Two-tailed distribution p-level 0.00041 t Critical Value (5%) 2.02269

One-tailed distribution p-level 0.00021 t Critical Value (5%) 1.68488 Pearson Correlation Coefficient 0.02214

G-criterion Test Statistics 0.20408 p-level 0.01125 Critical Value (5%) 0.18367

Pagurova criterion Test Statistics 3.82022 p-level 0.99973 Ratio of variances parameter 0.513 Critical Value (5%) 0.02515

Table A14: KBH-BSA and KBH-LDL/VLDL – Paired two-sample t-test – Statistics STATISTIC VALUE Mean Difference 9.04734E+05 Std. Dev of Difference 8.09400E+05 Standard Error of Difference 1.27977E+05 T-Alpha half 95% Conf. Interval 2.02269 Lower Conf. Interval 6.45875E+05 Higher Conf. Interval 1.16359E+06

RESULT: The difference between the binding constants of BSA and LDL-VLDL using the Benesi-Hildebrand method is statistically significant.

136 Appendix A: Ka Statistics and Correlations between Methods

Figure A5: KBH-BSA vs KBH-LDL-VLDL

KBH-BSA vs KBH-LDL/VLDL

4.00E+06 3.50E+06 3.00E+06 2.50E+06

KBH- 2.00E+06 LDL/VLDL 1.50E+06 1.00E+06 5.00E+05 0.00E+00 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 y = 0.0216x + 1E+06 KBH-BSA R² = 0.0005

Table A15: Correlation Coefficient Matrix KBH-BSA vs KBH-LDL-VLDL Correlation Coefficients Matrix (KBH-BSA vs KBH-LDL-VLDL) Critical value Sample size 40 (2%) 2.431

1.56790E+06 1.91690E+06 1567900 Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) 1916900 Pearson Correlation Coefficient 0.006 1. R Standard Error 0.027 t 0.037 p-value 0.971 H0 (2%) accepted

R Variable vs. Variable R 1916900 vs. 1567900 0.006

RESULT: The correlation coefficient of the linear regression formula of KBH-BSA vs KBH-LDL-VLDL is not statistically significant.

137 Appendix B: Ka Correlations among Other Factors Appendix B: Correlation Coefficient Matrices of the Linear Regression Formula between the Binding Constants of 40 Polyphenols, and either Polar Surface Area (PSA), the number of binding sites (n), Log P and/or Log D, Hydrogen Bond Donors, and Hydrogen Bond Acceptors (First for all PPs, then by group [ie phenolic acids (PAs) and non-phenolic acids (Non-PAs)]).

Figure B1

All PPs Polar Surface Area vs Ksv-BSA 25

20 y = 0.0126x + 1.7184 15 5 -1 R² = 0.0411 Ksv (10 M ) 10

5

0 0 50 100 150 200 250 PSA (A°2)

Table B1 Correlation Coefficients Matrix (Polar Surface Area and Ksv-BSA) Sample size 40 Critical value (2%) 2.429

Polar Surface Area (A?2) Stern-Volmer PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.203 1. R Standard Error 0.025 t 1.276 p-value 0.21 H0 (2%) accepted

R Variable vs. Variable R Ksv vs. Polar Surface Area (A?2) 0.203

138 Appendix B: Ka Correlations among Other Factors Figure B2

All PPs Polar Surface Area vs KDL-BSA 20

15 y = 0.0114x + 1.7257 5 -1 KDL (10 M ) 10 R² = 0.0433

5

0 0 50 100 150 200 250 PSA (A°2)

Table B2

Correlation Coefficients Matrix (Polar Surface Area and KDL-BSA) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Double Log PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.208 1. R Standard Error 0.025 t 1.311 p-value 0.198 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. PSA (A^2) 0.208

139 Appendix B: Ka Correlations among Other Factors Figure B3

All PPs Polar Surface Area vs KSc-BSA

7 6 5 y = 0.0042x + 0.8964 4 K (105 M-1) R² = 0.0273 SC 3 2 1 0 0 50 100 150 200 250 PSA (A°2)

Table B3 Correlation Coefficients Matrix (Polar Surface Area and KSc-BSA) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Scatchard PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.165 1. R Standard Error 0.026 t 1.032 p-value 0.309 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. PSA (A^2) 0.165

140 Appendix B: Ka Correlations among Other Factors Figure B4

All PPs Polar Surface Area vs KQu-BSA 4 3.5 3 y = 0.0036x + 1.0152 2.5 R² = 0.0756 5 -1 KQu (10 M ) 2 1.5 1 0.5 0 0 50 100 150 200 250 PSA (A°2)

Table B4 Correlation Coefficients Matrix (Polar Surface Area and KQu-BSA) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Quadratic PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.275 1. R Standard Error 0.024 t 1.763 p-value 0.086 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. PSA (A^2) 0.275

141 Appendix B: Ka Correlations among Other Factors Figure B5

All PPs Polar Surface Area vs KBH-BSA 35 30 25 y = -0.0213x + 10.313 20 R² = 0.0208 K (105 M-1) BH 15 10 5 0 0 50 100 150 200 250 PSA (A°2)

Table B5 Correlation Coefficients Matrix (Polar Surface Area and KBH-BSA) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Benesi-Hildibrand PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildibrand Pearson Correlation Coefficient -0.144 1. R Standard Error 0.026 t -0.898 p-value 0.375 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. PSA (A^2) -0.144

142 Appendix B: Ka Correlations among Other Factors Figure B6

All PPs Polar Surface Area vs Ksv-LDL/VLDL 4.5 4 3.5 3 y = 0.0014x + 1.6385 2.5 K (105 M-1) R² = 0.009 sv 2 1.5 1 0.5 0 0 50 100 150 200 250 PSA (A°2)

Table B6 Correlation Coefficients Matrix (Polar Surface Area and KSV-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Stern-Volmer PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.095 1. R Standard Error 0.026 t 0.587 p-value 0.561 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. PSA (A^2) 0.095

143 Appendix B: Ka Correlations among Other Factors Figure B7

All PPs Polar Surface Area vs KDL-LDL/VLDL

4 3.5 3 2.5 y = 0.001x + 1.1704 5 -1 R² = 0.0031 KDL (10 M ) 2 1.5 1 0.5 0 0 50 100 150 200 250 PSA (A°2)

Table B7 Correlation Coefficients Matrix (Polar Surface Area and KDL-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Double Log PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.056 1. R Standard Error 0.026 t 0.345 p-value 0.732 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. PSA (A^2) 0.056

144 Appendix B: Ka Correlations among Other Factors Figure B8

All PPs Polar Surface Area vs KSc-LDL/VLDL

3 2.5

2 y = 0.0005x + 1.4555 5 -1 R² = 0.003 KSC (10 M ) 1.5 1 0.5 0 0 50 100 150 200 250 PSA (A°2)

Table B8 Correlation Coefficients Matrix (Polar Surface Area and KSc-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Scatchard PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.055 1. R Standard Error 0.026 t 0.338 p-value 0.737 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. PSA (A^2) 0.055

145 Appendix B: Ka Correlations among Other Factors Figure B9

All PPs Polar Surface Area vs KQu-LDL/VLDL

2

1.5 y = 0.0004x + 0.9906 5 -1 R² = 0.0061 KQu (10 M ) 1

0.5

0 0 50 100 150 200 250 PSA (A°2)

Table B9 Correlation Coefficients Matrix (Polar Surface Area and KQu-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Quadratic PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.078 1. R Standard Error 0.026 t 0.485 p-value 0.631 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. PSA (A^2) 0.078

146 Appendix B: Ka Correlations among Other Factors Figure B10

All PPs Polar Surface Area vs KBH-LDL/VLDL

40 35 30 y = -0.011x + 16.053 25 R² = 0.006 5 -1 KBH (10 M ) 20 15 10 5 0 0 50 100 150 200 250 PSA (A°2)

Table B10 Correlation Coefficients Matrix (Polar Surface Area and KBH-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

PSA (A^2) Benesi-Hildebrand PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient -0.075 1. R Standard Error 0.026 t -0.464 p-value 0.645 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. PSA (A^2) -0.075

147 Appendix B: Ka Correlations among Other Factors Figure B11

All PPs n vs Ksv-BSA

25

20

15 y = -5.402x + 8.4669 5 -1 R² = 0.0082 Ksv (10 M ) 10

5

0 0 0.5 1 1.5 n

Table B11 Correlation Coefficients Matrix (n and KSV-BSA) Sample size 40 Critical value (2%) 2.429

SV n Stern-Volmer SV n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.091 1. R Standard Error 0.026 t -0.561 p-value 0.578 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. SV n -0.091

148 Appendix B: Ka Correlations among Other Factors Figure B12

All PPs n vs KDL-BSA 18 16 14 12 y = 4.875x - 1.6195 10 K (105 M-1) R² = 0.1883 DL 8 6 4 2 0 0 0.5 1 1.5 2 n

Table B12 Correlation Coefficients Matrix (n and KDL-BSA) Sample size 40 Critical value (2%) 2.429

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.434 1. R Standard Error 0.021 t 2.969 p-value 0.005 H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.434

149 Appendix B: Ka Correlations among Other Factors Figure B13

All PPs n vs KSc-BSA 7 6 5 y = 5.4634x - 0.5887 4 R² = 0.9184 K (105 M-1) SC 3 2 1 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 n

Table B13 Correlation Coefficients Matrix (n and KSc-BSA) Sample size 40 Critical value (2%) 2.429

Scatch n Scatchard Scatch n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.958 1. R Standard Error 0.002 t 20.675 p-value 0.E+0 H0 (2%) rejected

R Variable vs. Variable R Scatchard vs. Scatch n 0.958

150 Appendix B: Ka Correlations among Other Factors Figure B14

All PPs n vs Ksv-LDL/VLDL 4.5 4 3.5 3 y = -8.7521x + 10.891 2.5 K (105 M-1) R² = 0.0568 sv 2 1.5 1 0.5 0 1 1.02 1.04 1.06 1.08 1.1 1.12 n

Table B14 Correlation Coefficients Matrix (n and KSV-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

n Stern-Volmer n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.238 1. R Standard Error 0.025 t -1.513 p-value 0.139 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. n -0.238

151 Appendix B: Ka Correlations among Other Factors Figure B15

All PPs n vs KDL-LDL/VLDL

4 3.5 3 y = 0.5933x + 0.8218 2.5 R² = 0.0331 5 -1 KDL (10 M ) 2 1.5 1 0.5 0 0 0.5 1 1.5 2 2.5 n

Table B15 Correlation Coefficients Matrix (n and KDL-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.182 1. R Standard Error 0.025 t 1.14 p-value 0.261 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. DL n 0.182

152 Appendix B: Ka Correlations among Other Factors Figure B16

All PPs n vs KSc-LDL/VLDL 3 2.5

2 y = 5.1393x - 0.1573 5 -1 R² = 0.7077 KSC (10 M ) 1.5 1 0.5 0 0 0.1 0.2 0.3 0.4 0.5 0.6 n

Table B16 Correlation Coefficients Matrix (n and KSc-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

Scatch n Scatchard Scatch n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.841 1. R Standard Error 0.008 t 9.592 p-value 1.071E-11 H0 (2%) rejected

R Variable vs. Variable R Scatchard vs. Scatch n 0.841

153 Appendix B: Ka Correlations among Other Factors Figure B17

All PPs H-bond Acceptors/Donors vs Ksv-BSA

14 y = 0.1827x + 4.888 12 R² = 0.0423 10 Acceptors H-bond 8 Acceptors/Donors 6 Donors 4 Linear (Acceptors) 2 Linear (Donors) 0 y = 0.0967x + 3.0157 0 5 10 15 20 25 R² = 0.0258 5 -1 Ksv (10 M )

Table B17a

Correlation Coefficients Matrix (H-bond Acceptors and KSV-BSA) Sample size 40 Critical value (2%) 2.429

Stern-Volmer H Bond Acceptors Stern-Volmer Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.206 1. R Standard Error 0.025 t 1.296 p-value 0.203 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Stern-Volmer 0.206 Table B17b Correlation Coefficients Matrix (H-bond Donors and KSV-BSA) Sample size 40 Critical value (2%) 2.429

H Bond Donors Stern-Volmer H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.161 1. R Standard Error 0.026 t 1.003 p-value 0.322 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. H Bond Donors 0.161 154 Appendix B: Ka Correlations among Other Factors Figure B18

All PPs H-bond Acceptors/Donors vs KDL-BSA y = 0.2056x + 4.8439 14 R² = 0.0414 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 0 5 10 15 20 y = 0.1138x + 2.9782 5 -1 R² = 0.0276 KDL (10 M )

Table B18a Correlation Coefficients Matrix (H-bond Acceptors and KDL-BSA) Sample size 40 Critical value (2%) 2.429

Double Log H Bond Acceptors Double Log Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.203 1. R Standard Error 0.025 t 1.281 p-value 0.208 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Double Log 0.203 Table B18b Correlation Coefficients Matrix (H-bond Donors and KDL-BSA) Sample size 40 Critical value (2%) 2.429

H Bond Donors Double Log H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.166 1. R Standard Error 0.026 t 1.039 p-value 0.305 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. H Bond Donors 0.166

155 Appendix B: Ka Correlations among Other Factors Figure B19

All PPs H-bond Acceptors/Donors vs KSc-BSA y = 0.1941x + 5.1715 14 R² = 0.00811 12 Acceptors 10 Donors H-bond 8 Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 y = 0.0439x + 3.2427 0 R² = 0.0009 0 2 4 6 8 5 -1 KSC (10 M )

Table B19a Correlation Coefficients Matrix (H-bond Acceptors and KSc-BSA) Sample size 40 Critical value (2%) 2.429

Scatchard H Bond Acceptors Scatchard Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.09 1. R Standard Error 0.026 t 0.557 p-value 0.58 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Scatchard 0.09 Table B19b Correlation Coefficients Matrix (H-bond Donors and KSc-BSA) Sample size 40 Critical value (2%) 2.429

H Bond Donors Scatchard H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.03 1. R Standard Error 0.026 t 0.185 p-value 0.854 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. H Bond Donors 0.03 156 Appendix B: Ka Correlations among Other Factors Figure B20

All PPs H-bond Acceptors/Donors vs KQu-BSA y = 1.0325x + 4.0161 14 R² = 0.0602 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = 0.6812x + 2.3705 0 1 2 3 4 R² = 0.057 5 -1 KQu (10 M )

Table B20a Correlation Coefficients Matrix (H-bond Acceptors and KQu-BSA) Sample size 40 Critical value (2%) 2.429

Quadratic H Bond Acceptors Quadratic Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.245 1. R Standard Error 0.025 t 1.56 p-value 0.127 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Quadratic 0.245 Table B20b

Correlation Coefficients Matrix (H-bond Donors and KQu-BSA) Sample size 40 Critical value (2%) 2.429

H Bond Donors Quadratic H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.239 1. R Standard Error 0.025 t 1.515 p-value 0.138 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. H Bond Donors 0.239 157 Appendix B: Ka Correlations among Other Factors Figure B21

All PPs H-bond Acceptors/Donors vs KBH-BSA y = -0.0782x + 6.07 14 R² = 0.0436 12 Acceptors 10 Donors H-bond 8 Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = -0.0573x + 3.773 0 10 20 30 40 R² = 0.051 5 -1 KBH (10 M )

Table B21a Correlation Coefficients Matrix (H-bond Acceptors and KBH-BSA) Sample size 40 Critical value (2%) 2.429

Benesi-Hildibrand H Bond Acceptors Benesi-Hildibrand Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.209 1. R Standard Error 0.025 t -1.316 p-value 0.196 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Benesi-Hildibrand -0.209 Table B21b Correlation Coefficients Matrix (H-bond Donors and KBH-BSA) Sample size 40 Critical value (2%) 2.429

H Bond Donors Benesi-Hildibrand H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildibrand Pearson Correlation Coefficient -0.226 1. R Standard Error 0.025 t -1.429 p-value 0.161 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. H Bond Donors -0.226

158 Appendix B: Ka Correlations among Other Factors Figure B22

All PPs H-bond Acceptors/Donors vs Ksv-LDL/VLDL

14 y = 0.4405x + 4.6439 R² = 0.0137 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 0 1 2 3 4 5 y = 0.1859x + 2.9704 R² = 0.0053 5 -1 Ksv (10 M )

Table B22a Correlation Coefficients Matrix (H-bond Acceptors and KSV-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

Stern-Volmer H Bond Acceptors Stern-Volmer Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.117 1. R Standard Error 0.026 t 0.727 p-value 0.472 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Stern-Volmer 0.117 Table B22b Correlation Coefficients Matrix (H-bond Donors and KSV-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

H Bond Donors Stern-Volmer H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.073 1. R Standard Error 0.026 t 0.45 p-value 0.655 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. H Bond Donors 0.073

159 Appendix B: Ka Correlations among Other Factors Figure B23

All PPs H-bond Acceptors/Donors vs KDL-LDL/VLDL

14 y = 0.2836x + 5.0668 R² = 0.0077 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = 0.0439x + 3.2446 0 1 2 3 4 R² = 0.0004 5 -1 KDL (10 M )

Table B23a Correlation Coefficients Matrix (H-bond Acceptors and KDL-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

Double Log H Bond Acceptors Double Log Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.088 1. R Standard Error 0.026 t 0.544 p-value 0.59 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Double Log 0.088 Table B23b Correlation Coefficients Matrix (H-bond Donors and KDL-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

H Bond Donors Double Log H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.02 1. R Standard Error 0.026 t 0.124 p-value 0.902 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. H Bond Donors 0.02

160 Appendix B: Ka Correlations among Other Factors Figure B24

All PPs H-bond Acceptors/Donors vs KSc-LDL/VLDL y = -0.0732x + 5.5352 14 R² = 0.0002 12 Acceptors 10 Donors H-bond 8 Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = 0.1907x + 3.0128 0 0.5 1 1.5 2 2.5 3 R² = 0.0024 5 -1 KSC (10 M )

Table B24a Correlation Coefficients Matrix (H-bond Acceptors and KSc-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

Scatchard H Bond Acceptors Scatchard Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.013 1. R Standard Error 0.026 t -0.078 p-value 0.938 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Scatchard -0.013 Table B24b

Correlation Coefficients Matrix (H-bond Donors and KSc-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

H Bond Donors Scatchard H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.049 1. R Standard Error 0.026 t 0.3 p-value 0.766 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. H Bond Donors 0.049

161 Appendix B: Ka Correlations among Other Factors Figure B25

All PPs H-bond Acceptors/Donors vs KQu-LDL/VLDL y = 1.031x + 4.3635 14 R² = 0.0092 12 Acceptors 10 H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = 0.8067x + 2.4694 0 0.5 1 1.5 2 R² = 0.0123 5 -1 KQu (10 M )

Table B25a Correlation Coefficients Matrix (H-bond Acceptors and KQu-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

Quadratic H Bond Acceptors Quadratic Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.096 1. R Standard Error 0.026 t 0.594 p-value 0.556 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Quadratic 0.096 Table B25b Correlation Coefficients Matrix (H-bond Donors and KQu-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

H Bond Donors Quadratic H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.111 1. R Standard Error 0.026 t 0.687 p-value 0.496 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. H Bond Donors 0.111

162 Appendix B: Ka Correlations among Other Factors Figure B26

All PPs H-bond Acceptors/Donors vs KBH-LDL/VLDL y = -0.0702x + 6.4509 14 R² = 0.0334 12 Acceptors 10 Donors H-bond 8 Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = -0.0294x + 3.7295 0 10 20 30 40 R² = 0.0128 5 -1 KBH (10 M )

Table B26a Correlation Coefficients Matrix (H-bond Acceptors and KBH-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

Benesi-Hildebrand H Bond Acceptors Benesi-Hildebrand Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.183 1. R Standard Error 0.025 t -1.147 p-value 0.259 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Benesi-Hildebrand -0.183 Table B26b Correlation Coefficients Matrix (H-bond Donors and KBH-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

H Bond Donors Benesi-Hildebrand H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient -0.113 1. R Standard Error 0.026 t -0.701 p-value 0.488 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. H Bond Donors -0.113

163 Appendix B: Ka Correlations among Other Factors Figure B27

All PPs Log P/D vs Ksv-BSA 25

20 y = 0.1963x + 3.1256 15 R² = 0.0324 5 -1 Ksv (10 M ) 10

5

0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B27 Correlation Coefficients Matrix (LogP/D and KSV-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D Stern-Volmer LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.18 1. R Standard Error 0.025 t 1.128 p-value 0.267 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. LogP/D 0.18

164 Appendix B: Ka Correlations among Other Factors Figure B28

All PPs Log P/D vs KDL-BSA 18 16 14 12 y = 0.2549x + 3.0692 10 K (105 M-1) R² = 0.0706 DL 8 6 4 2 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B28 Correlation Coefficients Matrix (LogP/D and KDL-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D Double Log LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.266 1. R Standard Error 0.024 t 1.699 p-value 0.097 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. LogP/D 0.266

165 Appendix B: Ka Correlations among Other Factors Figure B29

All PPs Log P/D vs KSc-BSA

7 6 5 y = 0.1262x + 1.4261 4 R² = 0.0788 K (105 M-1) SC 3 2 1 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B29 Correlation Coefficients Matrix (LogP/D and KSc-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D Scatchard LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.281 1. R Standard Error 0.024 t 1.803 p-value 0.079 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. LogP/D 0.281

166 Appendix B: Ka Correlations among Other Factors Figure B30

All PPs Log P/D vs KQu-BSA

4 3.5 3 2.5 y = 0.0888x + 1.4489 5 -1 KQu (10 M ) 2 R² = 0.1488 1.5 1 0.5 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B30 Correlation Coefficients Matrix (LogP/D and KQu-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D Quadratic LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.386 1. R Standard Error 0.022 t 2.577 p-value 0.014 H0 (2%) rejected

R Variable vs. Variable R Quadratic vs. LogP/D 0.386

167 Appendix B: Ka Correlations among Other Factors Figure B31

All PPs Log P/D vs KBH-BSA 35 30 25 20 K (105 M-1) y = 0.1393x + 8.3851 BH 15 R² = 0.0029 10 5 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B31 Correlation Coefficients Matrix (LogP/D and KBH-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D Benesi-Hildibrand LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildibrand Pearson Correlation Coefficient 0.054 1. R Standard Error 0.026 t 0.332 p-value 0.742 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. LogP/D 0.054

168 Appendix B: Ka Correlations among Other Factors Figure B32

All PPs Log P/D vs Ksv-LDL/VLDL 4.5 4 3.5 3 y = 0.1448x + 1.9109 2.5 K (105 M-1) R² = 0.316 sv 2 1.5 1 0.5 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B32 Correlation Coefficients Matrix (LogP/D and KSV-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D Stern-Volmer LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.562 1. R Standard Error 0.018 t 4.19 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Stern-Volmer vs. LogP/D 0.562

169 Appendix B: Ka Correlations among Other Factors Figure B33

All PPs Log P/D vs KDL-LDL/VLDL 4 3.5 3 2.5 y = 0.1584x + 1.4134 5 -1 KDL (10 M ) 2 R² = 0.2784 1.5 1 0.5 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B33 Correlation Coefficients Matrix (LogP/D and KDL-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D Double Log LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.528 1. R Standard Error 0.019 t 3.829 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Double Log vs. LogP/D 0.528

170 Appendix B: Ka Correlations among Other Factors Figure B34

All PPs Log P/D vs Ksc-LDL/VLDL 3 2.5 2 y = 0.0379x + 1.5422 5 -1 KSC (10 M ) 1.5 R² = 0.0512 1 0.5 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B34 Correlation Coefficients Matrix (LogP/D and KSc-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D Scatchard LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.226 1. R Standard Error 0.025 t 1.432 p-value 0.16 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. LogP/D 0.226

171 Appendix B: Ka Correlations among Other Factors Figure B35

All PPs Log P/D vs KQu-LDL/VLDL

2

1.5 y = 0.052x + 1.0791 5 -1 R² = 0.3327 KQu (10 M ) 1

0.5

0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B35 Correlation Coefficients Matrix (LogP/D and KQu-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D Quadratic LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.577 1. R Standard Error 0.018 t 4.353 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Quadratic vs. LogP/D 0.577

172 Appendix B: Ka Correlations among Other Factors Figure B36

All PPs Log P/D vs KBH-LDL/VLDL

40 35 30 25 y = -0.2994x + 14.319 5 -1 KBH (10 M ) 20 R² = 0.0141 15 10 5 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B36 Correlation Coefficients Matrix (LogP/D and KBH-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D Benesi-Hildebrand LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient -0.119 1. R Standard Error 0.026 t -0.737 p-value 0.466 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. LogP/D -0.119

173 Appendix B: Ka Correlations among Other Factors Figure B37

All PPs Log P/D vs Log Ksv-BSA

7 6 5 y = 0.0397x + 5.3853 Log K (M-1) 4 SV R² = 0.1515 3 2 1 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B37 Correlation Coefficients Matrix (LogP/D and Log-KSV-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-Ksv LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Ksv Pearson Correlation Coefficient 0.389 1. R Standard Error 0.022 t 2.605 p-value 0.013 H0 (2%) rejected

R Variable vs. Variable R LOG-Ksv vs. LogP/D 0.389

174 Appendix B: Ka Correlations among Other Factors Figure B38

All PPs Log P/D vs Log KDL-BSA

7 6 5 4 y = 0.0575x + 5.3273 Log K (M-1) R² = 0.1367 DL 3 2 1 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B38 Correlation Coefficients Matrix (LogP/D and Log-KDL-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-KDL LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KDL Pearson Correlation Coefficient 0.37 1. R Standard Error 0.023 t 2.453 p-value 0.019 H0 (2%) rejected

R Variable vs. Variable R LOG-KDL vs. LogP/D 0.37

175 Appendix B: Ka Correlations among Other Factors Figure B39

All PPs Log P/D vs Log KSc-BSA

7 6 5 y = 0.0439x + 4.9752 4 Log K (M-1) R² = 0.0888 Sc 3 2 1 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B39 Correlation Coefficients Matrix (LogP/D and Log-KSc-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-KSc LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KSc Pearson Correlation Coefficient 0.298 1. R Standard Error 0.024 t 1.924 p-value 0.062 H0 (2%) accepted

R Variable vs. Variable R LOG-KSc vs. LogP/D 0.298

176 Appendix B: Ka Correlations among Other Factors Figure B40

All PPs Log P/D vs Log KQu-BSA 5.7 5.6 5.5 5.4 y = 0.0286x + 5.1185 5.3 -1 R² = 0.1866 Log KBH (M ) 5.2 5.1 5 4.9 4.8 4.7 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B40 Correlation Coefficients Matrix (LogP/D and Log-KQu-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-Kqu LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Kqu Pearson Correlation Coefficient 0.432 1. R Standard Error 0.021 t 2.953 p-value 0.005 H0 (2%) rejected

R Variable vs. Variable R LOG-Kqu vs. LogP/D 0.432

177 Appendix B: Ka Correlations among Other Factors Figure B41

All PPs Log P/D vs Log KBH-BSA

7 6 5 4 y = 0.008x + 5.7597 Log K (M-1) R² = 0.0035 Qu 3 2 1 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B41 Correlation Coefficients Matrix (LogP/D and Log-KBH-BSA) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-KBH LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KBH Pearson Correlation Coefficient 0.059 1. R Standard Error 0.026 t 0.363 p-value 0.718 H0 (2%) accepted

R Variable vs. Variable R LOG-KBH vs. LogP/D 0.059

178 Appendix B: Ka Correlations among Other Factors Figure B42

All PPs Log P/D vs Log-KSV-LDL/VLDL

5.7 5.6 5.5 5.4 y = 0.0331x + 5.245 5.3 R² = 0.2971 Log K (M-1) SV 5.2 5.1 5 4.9 4.8 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B42 Correlation Coefficients Matrix (LogP/D and Log-KSV-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-Ksv LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Ksv Pearson Correlation Coefficient 0.545 1. R Standard Error 0.018 t 4.008 p-value 0. H0 (2%) rejected

R Variable vs. Variable R LOG-Ksv vs. LogP/D 0.545

179 Appendix B: Ka Correlations among Other Factors Figure B43

All PPs Log P/D vs Log-KDL-LDL/VLDL

6 5

4 y = 0.0584x + 5.0369 -1 R² = 0.2221 Log KDL (M ) 3 2 1 0 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B43 Correlation Coefficients Matrix (LogP/D and Log-KDL-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-KDL LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KDL Pearson Correlation Coefficient 0.471 1. R Standard Error 0.02 t 3.294 p-value 0.002 H0 (2%) rejected

R Variable vs. Variable R LOG-KDL vs. LogP/D 0.471

180 Appendix B: Ka Correlations among Other Factors Figure B44

All PPs Log P/D vs Log-KSc-LDL/VLDL 5.5 5.4 5.3 y = 0.0112x + 5.1634 5.2 R² = 0.0429 -1 Log KSc (M ) 5.1 5 4.9 4.8 4.7 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B44 Correlation Coefficients Matrix (LogP/D and Log-KSc-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-KSc LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KSc Pearson Correlation Coefficient 0.207 1. R Standard Error 0.025 t 1.306 p-value 0.2 H0 (2%) accepted

R Variable vs. Variable R LOG-KSc vs. LogP/D 0.207

181 Appendix B: Ka Correlations among Other Factors Figure B45

All PPs Log P/D vs Log-KQu-LDL/VLDL 5.3

5.2 y = 0.021x + 5.0198 5.1 R² = 0.3348 -1 Log KQu (M ) 5

4.9

4.8 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B45 Correlation Coefficients Matrix (LogP/D and Log-KQu-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-Kqu LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Kqu Pearson Correlation Coefficient 0.579 1. R Standard Error 0.018 t 4.374 p-value 0. H0 (2%) rejected

R Variable vs. Variable R LOG-Kqu vs. LogP/D 0.579

182 Appendix B: Ka Correlations among Other Factors Figure B46

All PPs Log P/D vs Log-KBH-LDL/VLDL

6.6 6.4 6.2 y = -0.0111x + 6.1008 R² = 0.0212 -1 Log KBH (M ) 6 5.8 5.6 5.4 -8 -6 -4 -2 0 2 4 6 Log P/D

Table B46 Correlation Coefficients Matrix (LogP/D and Log-KBH-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

LogP/D LOG-KBH LogP/D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KBH Pearson Correlation Coefficient -0.146 1. R Standard Error 0.026 t -0.907 p-value 0.37 H0 (2%) accepted

R Variable vs. Variable R LOG-KBH vs. LogP/D -0.146

183 Appendix B: Ka Correlations among Other Factors Figure B47

Non-PAs Polar Surface Area vs Ksv-BSA

8 7 6 5 y = -0.0022x + 4.1699 5 -1 R² = 0.0098 Ksv (10 M ) 4 3 2 1 0 0 50 100 150 200 250 PSA (A°2)

Table B47 Correlation Coefficients Matrix (Non-PAs-PSA and KSV-BSA) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Stern-Volmer PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.099 1. R Standard Error 0.099 t -0.314 p-value 0.76 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. PSA (A^2) -0.099

184 Appendix B: Ka Correlations among Other Factors Figure B48

PAs Polar Surface Area vs Ksv-BSA 25

20 y = 0.0247x + 0.27 15 5 -1 R² = 0.0823 Ksv (10 M ) 10

5

0 0 50 100 150 200 PSA (A°2)

Table B48 Correlation Coefficients Matrix (PAs-PSA and KSV-BSA) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Stern-Volmer PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.287 1. R Standard Error 0.035 t 1.527 p-value 0.139 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. PSA (A^2) 0.287

185 Appendix B: Ka Correlations among Other Factors Figure B49

Non-PAs Polar Surface Area vs KDL-BSA

8 7 6 y = -0.0011x + 4.1496 5 5 -1 R² = 0.0021 KDL (10 M ) 4 3 2 1 0 0 50 100 150 200 250 PSA (A°2)

Table B49 Correlation Coefficients Matrix (Non-PAs-PSA and KDL-BSA) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Double Log PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient -0.046 1. R Standard Error 0.1 t -0.146 p-value 0.887 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. PSA (A^2) -0.046

186 Appendix B: Ka Correlations among Other Factors Figure B50

PAs Polar Surface Area vs KDL-BSA 18 16 14 12 y = 0.0199x + 0.5063 10 K (105 M-1) R² = 0.0751 DL 8 6 4 2 0 0 50 100 150 200 PSA (A°2)

Table B50 Correlation Coefficients Matrix (PAs-PSA and KDL-BSA) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Double Log PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.274 1. R Standard Error 0.036 t 1.453 p-value 0.158 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. PSA (A^2) 0.274

187 Appendix B: Ka Correlations among Other Factors Figure B51

Non-PAs Polar Surface Area vs KSc-BSA

6 5 y = 0.003x + 1.4835 4 R² = 0.0208 5 -1 KSC (10 M ) 3 2 1 0 0 50 100 150 200 250 PSA (A°2)

Table B51 Correlation Coefficients Matrix (Non-PAs-PSA and KSc-BSA) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Scatchard PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.144 1. R Standard Error 0.098 t 0.461 p-value 0.655 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. PSA (A^2) 0.144

188 Appendix B: Ka Correlations among Other Factors Figure B52

PAs Polar Surface Area vs KSc-BSA 7 6 5 y = 0.0034x + 0.7772 4 R² = 0.0138 K (105 M-1) SC 3 2 1 0 0 50 100 150 200 PSA (A°2)

Table B52 Correlation Coefficients Matrix (PAs-PSA and KSc-BSA) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Scatchard PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.117 1. R Standard Error 0.038 t 0.603 p-value 0.552 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. PSA (A^2) 0.117

189 Appendix B: Ka Correlations among Other Factors Figure B53

Non-PAs Polar Surface Area vs KQu-BSA

3 2.5 y = 0.0007x + 1.7494 2 R² = 0.0086 5 -1 KQu (10 M ) 1.5 1 0.5 0 0 50 100 150 200 250 PSA (A°2)

Table B53 Correlation Coefficients Matrix (Non-PAs-PSA and KQu-BSA) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Quadratic PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.093 1. R Standard Error 0.099 t 0.295 p-value 0.774 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. PSA (A^2) 0.093

190 Appendix B: Ka Correlations among Other Factors Figure B54

PAs Polar Surface Area vs KQu-BSA 4 3.5 3 y = 0.0047x + 0.7362 2.5 R² = 0.0995 5 -1 KQu (10 M ) 2 1.5 1 0.5 0 0 50 100 150 200 PSA (A°2)

Table B54 Correlation Coefficients Matrix (PAs-PSA and KQu-BSA) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Scatchard PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.117 1. R Standard Error 0.038 t 0.603 p-value 0.552 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. PSA (A^2) 0.117

191 Appendix B: Ka Correlations among Other Factors Figure B55

Non-PAs Polar Surface Area vs KBH-BSA

30

25 y = 0.0042x + 7.3569 20 R² = 0.0019

5 -1 KBH (10 M ) 15 10 5 0 0 50 100 150 200 250 PSA (A°2)

Table B55 Correlation Coefficients Matrix (Non-PAs-PSA and KBH-BSA) Sample size 12 Critical value (2%) 2.764

Polar Surface Area Benesi- (A?2) Hildibrand Pearson Correlation Polar Surface Area (A?2) Coefficient 1. R Standard Error t p-value H0 (2%) Pearson Correlation Benesi-Hildibrand Coefficient 0.043 1. R Standard Error 0.1 t 0.136 p-value 0.894 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. Polar Surface Area (A?2) 0.043

192 Appendix B: Ka Correlations among Other Factors Figure B56

PAs Polar Surface Area vs KBH-BSA 35 30 25 y = -0.0481x + 12.81 20 R² = 0.0635 K (105 M-1) BH 15 10 5 0 0 50 100 150 200 PSA (A°2)

Table B56 Correlation Coefficients Matrix (PAs-PSA and KBH-BSA) Sample size 28 Critical value (2%) 2.479

Polar Surface Area Benesi- (A?2) Hildibrand Pearson Correlation Polar Surface Area (A?2) Coefficient 1. R Standard Error t p-value H0 (2%) Pearson Correlation Benesi-Hildibrand Coefficient -0.252 1. R Standard Error 0.036 t -1.328 p-value 0.196 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. Polar Surface Area (A?2) -0.252

193 Appendix B: Ka Correlations among Other Factors Figure B57

Non-PAs Polar Surface Area vs Ksv-LDL/VLDL

4.5 4 3.5 3 y = -0.0035x + 2.8518 2.5 R² = 0.0986 K (105 M-1) sv 2 1.5 1 0.5 0 0 50 100 150 200 250 PSA (A°2)

Table B57 Correlation Coefficients Matrix (Non-PAs-PSA and KSV-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Stern-Volmer PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.314 1. R Standard Error 0.09 t -1.046 p-value 0.32 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. PSA (A^2) -0.314

194 Appendix B: Ka Correlations among Other Factors Figure B58

PAs Polar Surface Area vs Ksv-LDL/VLDL

3 2.5

2 y = 0.0034x + 1.1661 5 -1 Ksv (10 M ) 1.5 R² = 0.0742 1 0.5 0 0 50 100 150 200 PSA (A°2)

Table B58 Correlation Coefficients Matrix (PAs-PSA and KSV-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Stern-Volmer PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.272 1. R Standard Error 0.036 t 1.443 p-value 0.161 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. PSA (A^2) 0.272

195 Appendix B: Ka Correlations among Other Factors Figure B59

Non-PAs Polar Surface Area vs KDL-LDL/VLDL

4 3.5 3 y = -0.0047x + 2.5282 2.5 R² = 0.1102 5 -1 KDL (10 M ) 2 1.5 1 0.5 0 0 50 100 150 200 250 PSA (A°2)

Table B59 Correlation Coefficients Matrix (Non-PAs-PSA and KDL-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Double Log PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient -0.332 1. R Standard Error 0.089 t -1.113 p-value 0.292 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. PSA (A^2) -0.332

196 Appendix B: Ka Correlations among Other Factors Figure B60

PAs Polar Surface Area vs KDL-LDL/VLDL

3 2.5 y = 0.0035x + 0.6229 2 R² = 0.058 5 -1 KDL (10 M ) 1.5 1 0.5 0 0 50 100 150 200 PSA (A°2)

Table B60 Correlation Coefficients Matrix (PAs-PSA and KDL-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Double Log PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.241 1. R Standard Error 0.036 t 1.265 p-value 0.217 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. PSA (A^2) 0.241

197 Appendix B: Ka Correlations among Other Factors Figure B61

Non-PAs Polar Surface Area vs KSc-LDL/VLDL

3 2.5 y = -2E-05x + 1.6834 2 R² = 6E-06 5 -1 KSC (10 M ) 1.5 1 0.5 0 0 50 100 150 200 250 PSA (A°2)

Table B61 Correlation Coefficients Matrix (Non-PAs-PSA and KSc-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Scatchard PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient -0.002 1. R Standard Error 0.1 t -0.008 p-value 0.994 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. PSA (A^2) -0.002

198 Appendix B: Ka Correlations among Other Factors Figure B62

PAs Polar Surface Area vs KSc-LDL/VLDL

2.5

2 y = 0.0003x + 1.4031 1.5 R² = 0.0009 5 -1 KSC (10 M ) 1

0.5

0 0 50 100 150 200 PSA (A°2)

Table B62 Correlation Coefficients Matrix (PAs-PSA and KSc-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Scatchard PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.03 1. R Standard Error 0.038 t 0.151 p-value 0.881 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. PSA (A^2) 0.03

199 Appendix B: Ka Correlations among Other Factors Figure B63

Non-PAs Polar Surface Area vs KQu-LDL/VLDL

2

1.5 y = -0.0012x + 1.4053 R² = 0.1099 5 -1 KQu (10 M ) 1

0.5

0 0 50 100 150 200 250 PSA (A°2)

Table B63 Correlation Coefficients Matrix (Non-PAs-PSA and KQu-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Quadratic PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient -0.331 1. R Standard Error 0.089 t -1.111 p-value 0.293 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. PSA (A^2) -0.331

200 Appendix B: Ka Correlations among Other Factors Figure B64

PAs Polar Surface Area vs KQu-LDL/VLDL

1.6 1.4 1.2 y = 0.0009x + 0.8377 1 R² = 0.0424 5 -1 KQu (10 M ) 0.8 0.6 0.4 0.2 0 0 50 100 150 200 PSA (A°2)

Table B64 Correlation Coefficients Matrix (PAs-PSA and KQu-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Quadratic PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.206 1. R Standard Error 0.037 t 1.073 p-value 0.293 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. PSA (A^2) 0.206

201 Appendix B: Ka Correlations among Other Factors Figure B65

Non-PAs Polar Surface Area vs KBH-LDL/VLDL

40 35 30 25 y = -0.0071x + 13.861 5 -1 KBH (10 M ) 20 R² = 0.0033 15 10 5 0 0 50 100 150 200 250 PSA (A°2)

Table B65 Correlation Coefficients Matrix (Non-PAs-PSA and KBH-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

PSA (A^2) Benesi-Hildebrand PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient -0.057 1. R Standard Error 0.1 t -0.182 p-value 0.859 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. PSA (A^2) -0.057

202 Appendix B: Ka Correlations among Other Factors Figure B66

PAs Polar Surface Area vs KBH-LDL/VLDL

35 30 25 y = -0.0083x + 16.009 20 K (105 M-1) R² = 0.0025 BH 15 10 5 0 0 50 100 150 200 PSA (A°2)

Table B66 Correlation Coefficients Matrix (PAs-PSA and KBH-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

PSA (A^2) Benesi-Hildebrand PSA (A^2) Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient -0.05 1. R Standard Error 0.038 t -0.256 p-value 0.8 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. PSA (A^2) -0.05

203 Appendix B: Ka Correlations among Other Factors Figure B67

Non-PAs n vs Ksv-BSA 8 7 6 5 y = 2.2529x + 1.5806 5 -1 Ksv (10 M ) 4 R² = 0.0101 3 2 1 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 n

Table B67 Correlation Coefficients Matrix (Non-PAs-n and KSV-BSA) Sample size 12 Critical value (2%) 2.764

SV n Stern-Volmer SV n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.101 1. R Standard Error 0.099 t 0.32 p-value 0.756 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. SV n 0.101

204 Appendix B: Ka Correlations among Other Factors Figure B68

PAs n vs Ksv-BSA

25

20 y = -18.8x + 21.611 15 R² = 0.0544 5 -1 Ksv (10 M ) 10

5

0 0.8 0.85 0.9 0.95 1 1.05 1.1 1.15 n

Table B68 Correlation Coefficients Matrix (PAs-n and KSV-BSA) Sample size 28 Critical value (2%) 2.479

SV n Stern-Volmer SV n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.233 1. R Standard Error 0.036 t -1.223 p-value 0.232 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. SV n -0.233

205 Appendix B: Ka Correlations among Other Factors Figure B69

Non-PAs n vs KDL-BSA 8 7 6 5 y = 2.1542x + 1.9979 5 -1 KDL (10 M ) 4 R² = 0.0467 3 2 1 0 0 0.2 0.4 0.6 0.8 1 1.2 n

Table B69 Correlation Coefficients Matrix (Non-PAs-n and KDL-BSA) Sample size 12 Critical value (2%) 2.764

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.216 1. R Standard Error 0.095 t 0.7 p-value 0.5 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. DL n 0.216

206 Appendix B: Ka Correlations among Other Factors Figure B70

PAs n vs KDL-BSA

18 16 14 12 y = 5.0225x - 2.2049 10 R² = 0.2115 5 -1 KDL (10 M ) 8 6 4 2 0 -2 0 0.5 1 1.5 2 n

Table B70 Correlation Coefficients Matrix (PAs-n and KDL-BSA) Sample size 28 Critical value (2%) 2.479

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.46 1. R Standard Error 0.03 t 2.641 p-value 0.014 H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.46

207 Appendix B: Ka Correlations among Other Factors Figure B71

Non-PAs n vs KSc-BSA 6 5 4 y = 6.3222x - 1.2255 5 -1 KSC (10 M ) 3 R² = 0.903 2 1 0 0 0.2 0.4 0.6 0.8 1 1.2 n

Table B71 Correlation Coefficients Matrix (Non-PAs-n and KSc-BSA) Sample size 12 Critical value (2%) 2.764

Scatch n Scatchard Scatch n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.95 1. R Standard Error 0.01 t 9.649 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Scatchard vs. Scatch n 0.95

208 Appendix B: Ka Correlations among Other Factors Figure B72

PAs n vs KSc-BSA 7 6 5 y = 5.5332x - 0.5129 4 R² = 0.9484 K (105 M-1) SC 3 2 1 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 n

Table B72 Correlation Coefficients Matrix (PAs-n and KSc-BSA) Sample size 28 Critical value (2%) 2.479

Scatch n Scatchard Scatch n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.974 1. R Standard Error 0.002 t 21.865 p-value 0.E+0 H0 (2%) rejected

R Variable vs. Variable R Scatchard vs. Scatch n 0.974

209 Appendix B: Ka Correlations among Other Factors Figure B73

Non-PAs n vs Ksv-LDL/VLDL

4.5 4 3.5 3 2.5 y = -14.882x + 17.987 K (105 M-1) sv 2 R² = 0.1488 1.5 1 0.5 0 1 1.02 1.04 1.06 1.08 1.1 n

Table B73 Correlation Coefficients Matrix (Non-PAs-n and KSV-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

n Stern-Volmer n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.386 1. R Standard Error 0.085 t -1.322 p-value 0.215 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. n -0.386

210 Appendix B: Ka Correlations among Other Factors Figure B74

PAs n vs Ksv-LDL/VLDL 3 2.5 2 y = 8.1268x - 6.9147

5 -1 R² = 0.0737 Ksv (10 M ) 1.5 1 0.5 0 1 1.02 1.04 1.06 1.08 n

Table B74 Correlation Coefficients Matrix (PAs-n and KSV-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

n Stern-Volmer n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.303 1. R Standard Error 0.035 t -1.619 p-value 0.118 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. n -0.303

211 Appendix B: Ka Correlations among Other Factors Figure B75

Non-PAs n vs KDL-LDL/VLDL 4 3.5 3 2.5 y = 6.7981x - 3.1895 5 -1 KDL (10 M ) 2 R² = 0.6381 1.5 1 0.5 0 0 0.2 0.4 0.6 0.8 1 n

Table B75 Correlation Coefficients Matrix (Non-PAs-n and KDL-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.799 1. R Standard Error 0.036 t 4.199 p-value 0.002 H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.799

212 Appendix B: Ka Correlations among Other Factors Figure B76

PAs n vs KDL-LDL/VLDL 3 2.5 2 y = 0.1611x + 0.8226 5 -1 KDL (10 M ) 1.5 R² = 0.0069 1 0.5 0 0 0.5 1 1.5 2 2.5 n

Table B76 Correlation Coefficients Matrix (PAs-n and KDL-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.083 1. R Standard Error 0.038 t 0.425 p-value 0.674 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. DL n 0.083

213 Appendix B: Ka Correlations among Other Factors Figure B77

Non-PAs n vs KSc-LDL/VLDL

3 2.5 2 y = 6.365x - 0.7807 5 -1 KSC (10 M ) 1.5 R² = 0.7743 1 0.5 0 0 0.1 0.2 0.3 0.4 0.5 0.6 n

Table B77 Correlation Coefficients Matrix (Non-PAs-n and KSc-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

Scatch n Scatchard Scatch n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.88 1. R Standard Error 0.023 t 5.857 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Scatchard vs. Scatch n 0.88

214 Appendix B: Ka Correlations among Other Factors Figure B78

PAs n vs KSc-LDL/VLDL 2.5

2 y = 5.8351x - 0.2997 1.5 R² = 0.7363 5 -1 KSC (10 M ) 1

0.5

0 0 0.1 0.2 0.3 0.4 0.5 n

Table B78 Correlation Coefficients Matrix (PAs-n and KSc-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Scatch n Scatchard Scatch n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.858 1. R Standard Error 0.01 t 8.521 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Scatchard vs. Scatch n 0.858

215 Appendix B: Ka Correlations among Other Factors Figure B79

Non-PAs H-bond Acceptors/Donors vs Ksv-BSA

14 y = -0.4488x + 7.8453 12 R² = 0.0373 10 Acceptors 8 H-bond Donors Acceptors/Donors 6 4 Linear (Acceptors) 2 Linear (Donors) 0 0 2 4 6 8 y = -0.2411x + 4.78 R² = 0.0209 5 -1 Ksv (10 M )

Table B79a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KSV-BSA) Sample size 12 Critical value (2%) 2.764

Stern-Volmer H Bond Acceptors Stern-Volmer Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.193 1. R Standard Error 0.096 t -0.622 p-value 0.548 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Stern-Volmer -0.193 Table B79b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KSV-BSA) Sample size 12 Critical value (2%) 2.764

H Bond Donors Stern-Volmer H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.144 1. R Standard Error 0.098 t -0.462 p-value 0.654 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. H Bond Donors -0.144

216 Appendix B: Ka Correlations among Other Factors Figure B80

PAs H-bond Acceptors/Donors vs Ksv-BSA

12 y = 0.206x + 4.6246 R² = 0.0909 10 8 Acceptors H-bond 6 Donors Acceptors/Donors 4 Linear (Acceptors) 2 Linear (Donors)

0 y = 0.1004x + 2.8189 0 5 10 15 20 25 R² = 0.0536 5 -1 Ksv (10 M )

Table B80a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KSV-BSA) Sample size 28 Critical value (2%) 2.479

Stern-Volmer H Bond Acceptors Stern-Volmer Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.302 1. R Standard Error 0.035 t 1.613 p-value 0.119 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Stern-Volmer 0.302 Table B80b

Correlation Coefficients Matrix (PAs-H-bond Donors and KSV-BSA) Sample size 28 Critical value (2%) 2.479

H Bond Donors Stern-Volmer H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.231 1. R Standard Error 0.036 t 1.213 p-value 0.236 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. H Bond Donors 0.231

217 Appendix B: Ka Correlations among Other Factors Figure B81

Non-PAs H-bond Acceptors/Donors vs KDL-BSA

y = -0.247x + 7.0776 14 R² = 0.0134 12 Acceptors 10 H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = -0.1661x + 4.502 0 2 4 6 8 R² = 0.0118 5 -1 KDL (10 M )

Table B81a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KDL-BSA) Sample size 12 Critical value (2%) 2.764

Double Log H Bond Acceptors Double Log Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.116 1. R Standard Error 0.099 t -0.369 p-value 0.72 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Double Log -0.116 Table B81b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KDL-BSA) Sample size 12 Critical value (2%) 2.764

H Bond Donors Double Log H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient -0.108 1. R Standard Error 0.099 t -0.345 p-value 0.737 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. H Bond Donors -0.108

218 Appendix B: Ka Correlations among Other Factors Figure B82

PAs H-bond Acceptors/Donors vs KDL-BSA

12 y = 0.2271x + 4.6174 R² = 0.0784 10 8 Acceptors H-bond 6 Donors Acceptors/Donors 4 Linear (Acceptors) 2 Linear (Donors)

0 y = 0.1154x + 2.8045 0 5 10 15 20 R² = 0.0502 5 -1 KDL (10 M )

Table B82a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KDL-BSA) Sample size 28 Critical value (2%) 2.479

Double Log H Bond Acceptors Double Log Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.28 1. R Standard Error 0.035 t 1.487 p-value 0.149 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Double Log 0.28 Table B82b Correlation Coefficients Matrix (PAs-H-bond Donors and KDL-BSA) Sample size 28 Critical value (2%) 2.479

H Bond Donors Double Log H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.224 1. R Standard Error 0.037 t 1.173 p-value 0.252 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. H Bond Donors 0.224

219 Appendix B: Ka Correlations among Other Factors Figure B83

Non-PAs H-bond Acceptors/Donors vs KSc-BSA y = -0.3886x + 6.7877 14 R² = 0.0239 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = -0.2542x + 4.2941 0 1 2 3 4 5 6 R² = 0.0198 5 -1 KSC (10 M )

Table B83a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KSc-BSA) Sample size 12 Critical value (2%) 2.764

Scatchard H Bond Acceptors Scatchard Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.155 1. R Standard Error 0.098 t -0.495 p-value 0.631 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Scatchard -0.155 Table B83b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KSc-BSA) Sample size 12 Critical value (2%) 2.764

H Bond Donors Scatchard H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient -0.141 1. R Standard Error 0.098 t -0.45 p-value 0.663 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. H Bond Donors -0.141

220 Appendix B: Ka Correlations among Other Factors Figure B84

PAs H-bond Acceptors/Donors vs KSc-BSA

12 y = 0.3912x + 4.7168 R² = 0.0378 10 Acceptors 8 H-bond Donors 6 Acceptors/Donors Linear (Acceptors) 4 Linear (Donors) 2 0 y = 0.0963x + 2.9665 0 2 4 6 8 R² = 0.0057 5 -1 KSC (10 M )

Table B84a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KSc-BSA) Sample size 28 Critical value (2%) 2.479

Scatchard H Bond Acceptors Scatchard Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.194 1. R Standard Error 0.037 t 1.01 p-value 0.322 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Scatchard 0.194 Table B84b Correlation Coefficients Matrix (PAs-H-bond Donors and KSc-BSA) Sample size 28 Critical value (2%) 2.479

H Bond Donors Scatchard H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.075 1. R Standard Error 0.038 t 0.385 p-value 0.703 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. H Bond Donors 0.075

221 Appendix B: Ka Correlations among Other Factors Figure B85

Non-PAs H-bond Acceptors/Donors vs KQu-BSA y = -0.4411x + 6.8908 14 R² = 0.0045 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 0 0.5 1 1.5 2 2.5 3 y = -0.0879x + 3.9942 R² = 0.0003 5 -1 KQu (10 M )

Table B85a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KQu-BSA) Sample size 12 Critical value (2%) 2.764

Quadratic H Bond Acceptors Quadratic Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.067 1. R Standard Error 0.1 t -0.213 p-value 0.836 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Quadratic -0.067 Table B85b

Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KQu-BSA) Sample size 12 Critical value (2%) 2.764

H Bond Donors Quadratic H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient -0.019 1. R Standard Error 0.1 t -0.059 p-value 0.954 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. H Bond Donors -0.019

222 Appendix B: Ka Correlations among Other Factors Figure B86

PAs H-bond Acceptors/Donors vs KQu-BSA y = 1.3469x + 3.5739 12 R² = 0.1171 10 Acceptors 8 H-bond Donors 6 Acceptors/Donors Linear (Acceptors) 4 Linear (Donors) 2 0 y = 0.7518x + 2.1957 0 1 2 3 4 R² = 0.0905 5 -1 KQu (10 M )

Table B86a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KQu-BSA) Sample size 28 Critical value (2%) 2.479

Quadratic H Bond Acceptors Quadratic Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.342 1. R Standard Error 0.034 t 1.857 p-value 0.075 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Quadratic 0.342 Table B86b Correlation Coefficients Matrix (PAs-H-bond Donors and KQu-BSA) Sample size 28 Critical value (2%) 2.479

H Bond Donors Quadratic H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.301 1. R Standard Error 0.035 t 1.609 p-value 0.12 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. H Bond Donors 0.301

223 Appendix B: Ka Correlations among Other Factors Figure B87

Non-PAs H-bond Acceptors/Donors vs KBH-BSA y = -0.1278x + 7.0829 14 R² = 0.0575 12 Acceptors 10 H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = -0.0866x + 4.5109 0 5 10 15 20 25 30 R² = 0.0512 5 -1 KBH (10 M )

Table B87a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KBH-BSA) Sample size 12 Critical value (2%) 2.764

Benesi-Hildibrand H Bond Acceptors Benesi-Hildibrand Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.24 1. R Standard Error 0.094 t -0.781 p-value 0.453 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Benesi-Hildibrand -0.24 Table B87b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KBH-BSA) Sample size 12 Critical value (2%) 2.764

H Bond Donors Benesi-Hildibrand H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildibrand Pearson Correlation Coefficient -0.226 1. R Standard Error 0.095 t -0.735 p-value 0.479 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. H Bond Donors -0.226

224 Appendix B: Ka Correlations among Other Factors Figure B88

PAs H-bond Acceptors/Donors vs KBH-BSA

12 y = -0.0614x + 5.6612 R² = 0.0398 10 8 Acceptors H-bond 6 Donors Acceptors/Donors 4 Linear (Acceptors) 2 Linear (Donors)

0 y = -0.0467x + 3.4662 0 10 20 30 40 R² = 0.0572 5 -1 KBH (10 M )

Table B88a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KBH-BSA) Sample size 28 Critical value (2%) 2.479

Benesi-Hildibrand H Bond Acceptors Benesi-Hildibrand Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.199 1. R Standard Error 0.037 t -1.038 p-value 0.309 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Benesi-Hildibrand -0.199 Table B88b Correlation Coefficients Matrix (PAs-H-bond Donors and KBH-BSA) Sample size 28 Critical value (2%) 2.479

H Bond Donors Benesi-Hildibrand H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildibrand Pearson Correlation Coefficient -0.239 1. R Standard Error 0.036 t -1.257 p-value 0.22 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. H Bond Donors -0.239

225 Appendix B: Ka Correlations among Other Factors Figure B89

Non-PAs H-bond Acceptors/Donors vs Ksv-LDL/VLDL

14 y = -1.5651x + 9.95 R² = 0.1097 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 2 Linear (Donors) 0 y = -1.3829x + 7.2499 0 1 2 3 4 5 R² = 0.1661 5 -1 Ksv (10 M )

Table B89a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KSV-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

Stern-Volmer H Bond Acceptors Stern-Volmer Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.331 1. R Standard Error 0.089 t -1.11 p-value 0.293 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Stern-Volmer -0.331 Table B89b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KSV-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

H Bond Donors Stern-Volmer H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient -0.408 1. R Standard Error 0.083 t -1.411 p-value 0.189 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. H Bond Donors -0.408

226 Appendix B: Ka Correlations among Other Factors Figure B90

PAs H-bond Acceptors/Donors vs Ksv-LDL/VLDL

12 y = 1.5711x + 2.8262 R² = 0.1107 10 8 Acceptors H-bond 6 Donors Acceptors/Donors 4 Linear (Acceptors) 2 Linear (Donors)

0 y = 0.8598x + 1.8037 0 0.5 1 1.5 2 2.5 3 R² = 0.0822 5 -1 Ksv (10 M )

Table B90a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KSV-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Stern-Volmer H Bond Acceptors Stern-Volmer Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.333 1. R Standard Error 0.034 t 1.799 p-value 0.084 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Stern-Volmer 0.333 Table B90b

Correlation Coefficients Matrix (PAs-H-bond Donors and KSV-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

H Bond Donors Stern-Volmer H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.287 1. R Standard Error 0.035 t 1.526 p-value 0.139 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. H Bond Donors 0.287

227 Appendix B: Ka Correlations among Other Factors Figure B91

Non-PAs H-bond Acceptors/Donors vs KDL-LDL/VLDL y = -1.2483x + 8.5978 14 R² = 0.1135 12 Acceptors 10 Donors H-bond 8 Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = -1.1469x + 6.1435 0 1 2 3 4 R² = 0.1856 5 -1 KDL (10 M )

Table B91a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KDL-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

Double Log H Bond Acceptors Double Log Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.337 1. R Standard Error 0.089 t -1.131 p-value 0.284 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Double Log -0.337 Table B91b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KDL-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

H Bond Donors Double Log H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient -0.431 1. R Standard Error 0.081 t -1.51 p-value 0.162 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. H Bond Donors -0.431

228 Appendix B: Ka Correlations among Other Factors Figure B92

PAs H-bond Acceptors/Donors vs KDL-LDL/VLDL

y = 1.2643x + 3.9534 12 R² = 0.0973 10 Acceptors 8 H-bond Donors 6 Acceptors/Donors Linear (Acceptors) 4 Linear (Donors) 2 0 y = 0.6065x + 2.5008 0 0.5 1 1.5 2 2.5 3 R² = 0.0556 5 -1 KDL (10 M )

Table B92a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KDL-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Double Log H Bond Acceptors Double Log Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.312 1. R Standard Error 0.035 t 1.674 p-value 0.106 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Double Log 0.312 Table B92b Correlation Coefficients Matrix (PAs-H-bond Donors and KDL-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

H Bond Donors Double Log H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.236 1. R Standard Error 0.036 t 1.237 p-value 0.227 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. H Bond Donors 0.236

229 Appendix B: Ka Correlations among Other Factors Figure B93

Non-PAs H-bond Acceptors/Donors vs KSc-LDL/VLDL

14 y = -0.3353x + 6.647 R² = 0.0029 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = 0.1349x + 3.6066 0 0.5 1 1.5 2 2.5 3 R² = 0.0009 5 -1 KSC (10 M )

Table B93a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KSc-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

Scatchard H Bond Acceptors Scatchard Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.054 1. R Standard Error 0.1 t -0.171 p-value 0.868 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Scatchard -0.054 Table B93b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KSc-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

H Bond Donors Scatchard H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.03 1. R Standard Error 0.1 t 0.096 p-value 0.926 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. H Bond Donors 0.03

230 Appendix B: Ka Correlations among Other Factors Figure B94

PAs H-bond Acceptors/Donors vs KSc-LDL/VLDL y = -0.2813x + 5.5454 12 R² = 0.0025 10 Acceptors 8 H-bond Donors 6 Acceptors/Donors Linear (Acceptors) 4 Linear (Donors) 2

0 y = -0.0616x + 3.1596 0 0.5 1 1.5 2 2.5 R² = 0.0003 5 -1 KSC (10 M )

Table B94a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KSc-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Scatchard H Bond Acceptors Scatchard Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.05 1. R Standard Error 0.038 t -0.255 p-value 0.801 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Scatchard -0.05 Table B94b Correlation Coefficients Matrix (PAs-H-bond Donors and KSc-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

H Bond Donors Scatchard H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient -0.017 1. R Standard Error 0.038 t -0.088 p-value 0.931 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. H Bond Donors -0.017

231 Appendix B: Ka Correlations among Other Factors Figure B95

Non-PAs H-bond Acceptors/Donors vs KQu-LDL/VLDL y = -4.3306x + 11.611 14 R² = 0.0861 12 10 Acceptors H-bond 8 Donors Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = -3.6132x + 8.4456 0 0.5 1 1.5 2 R² = 0.1161 5 -1 KQu (10 M )

Table B95a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KQu-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

Quadratic H Bond Acceptors Quadratic Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.293 1. R Standard Error 0.091 t -0.97 p-value 0.355 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Quadratic -0.293 Table B95b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KQu-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

H Bond Donors Quadratic H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient -0.341 1. R Standard Error 0.088 t -1.146 p-value 0.278 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. H Bond Donors -0.341

232 Appendix B: Ka Correlations among Other Factors Figure B96

PAs H-bond Acceptors/Donors vs KQu-LDL/VLDL y = 2.7382x + 2.6131 12 R² = 0.0459 10 Acceptors 8 H-bond Donors 6 Acceptors/Donors 4 Linear (Acceptors) 2 Linear (Donors) 0 y = 2.2085x + 1.031 0 0.5 1 1.5 R² = 0.0741 5 -1 KQu (10 M )

Table B96a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KQu-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Quadratic H Bond Acceptors Quadratic Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient 0.214 1. R Standard Error 0.037 t 1.119 p-value 0.274 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Quadratic 0.214 Table B96b Correlation Coefficients Matrix (PAs-H-bond Donors and KQu-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

H Bond Donors Quadratic H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.272 1. R Standard Error 0.036 t 1.443 p-value 0.161 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. H Bond Donors 0.272

233 Appendix B: Ka Correlations among Other Factors Figure B97

Non-PAs H-bond Acceptors/Donors vs KBH-LDL/VLDL

y = -0.0576x + 6.8367 14 R² = 0.0184 12 Acceptors 10 Donors H-bond 8 Acceptors/Donors 6 Linear (Acceptors) 4 Linear (Donors) 2 0 y = -0.0018x + 3.8569 0 10 20 30 40 R² = 3E-05 5 -1 KBH (10 M )

Table B97a Correlation Coefficients Matrix (Non-PAs-H-bond Acceptors and KBH-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

Benesi-Hildebrand H Bond Acceptors Benesi-Hildebrand Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.136 1. R Standard Error 0.098 t -0.433 p-value 0.674 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Benesi-Hildebrand -0.136 Table B97b Correlation Coefficients Matrix (Non-PAs-H-bond Donors and KBH-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

H Bond Donors Benesi-Hildebrand H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient -0.006 1. R Standard Error 0.1 t -0.019 p-value 0.985 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. H Bond Donors -0.006

234 Appendix B: Ka Correlations among Other Factors Figure B98

PAs H-bond Acceptors/Donors vs KBH-LDL/VLDL y = -0.0667x + 6.1601 12 R² = 0.0351 10 Acceptors 8 H-bond Donors 6 Acceptors/Donors Linear (Acceptors) 4 Linear (Donors) 2 0 y = -0.0361x + 3.6214 0 10 20 30 40 R² = 0.0254 5 -1 KBH (10 M )

Table B98a Correlation Coefficients Matrix (PAs-H-bond Acceptors and KBH-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Benesi-Hildebrand H Bond Acceptors Benesi-Hildebrand Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) H Bond Acceptors Pearson Correlation Coefficient -0.187 1. R Standard Error 0.037 t -0.972 p-value 0.34 H0 (2%) accepted

R Variable vs. Variable R H Bond Acceptors vs. Benesi-Hildebrand -0.187 Table B98b Correlation Coefficients Matrix (PAs-H-bond Donors and KBH-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

H Bond Donors Benesi-Hildebrand H Bond Donors Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient -0.159 1. R Standard Error 0.037 t -0.824 p-value 0.418 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. H Bond Donors -0.159

235 Appendix B: Ka Correlations among Other Factors Figure B99

Non-PAs Log P vs Ksv-BSA

8 7 6 5 y = 0.2407x + 3.2985 5 -1 R² = 0.0258 Ksv (10 M ) 4 3 2 1 0 0 1 2 3 4 5 Log P

Table B99 Correlation Coefficients Matrix (Non-PAs-Log P and KSV-BSA) Sample size 11 Critical value (2%) 2.821

4.13 5.81765 4.13 Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) 5.81765 Pearson Correlation Coefficient -0.028 1. R Standard Error 0.111 t -0.083 p-value 0.936 H0 (2%) accepted

R Variable vs. Variable R 5.81765 vs. 4.13 -0.028

236 Appendix B: Ka Correlations among Other Factors Figure B100

PAs Log D vs Ksv-BSA

25

20 y = 0.0179x + 2.5604 R² = 9E-05 15 5 -1 Ksv (10 M ) 10

5

0 -8 -6 -4 -2 0 2 Log D

Table B100 Correlation Coefficients Matrix (PAs-Log D and KSV-BSA) Sample size 28 Critical value (2%) 2.479

Log D Stern-Volmer Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.01 1. R Standard Error 0.038 t 0.049 p-value 0.961 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. Log D 0.01

237 Appendix B: Ka Correlations among Other Factors Figure B101

Non-PAs Log P vs KDL-BSA

8 7 6 y = 0.484x + 2.7636 5 R² = 0.0878 5 -1 KDL (10 M ) 4 3 2 1 0 0 1 2 3 4 5 Log P

Table B101 Correlation Coefficients Matrix (Non-PAs-Log P and KDL-BSA) Sample size 12 Critical value (2%) 2.764

LogP Double Log LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.296 1. R Standard Error 0.091 t 0.981 p-value 0.35 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. LogP 0.296

238 Appendix B: Ka Correlations among Other Factors Figure B102

PAs Log D vs KDL-BSA 18 16 14 12 y = 0.0536x + 2.446 10 R² = 0.0012 K (105 M-1) DL 8 6 4 2 0 -8 -6 -4 -2 0 2 Log D

Table B102 Correlation Coefficients Matrix (PAs-Log D and KDL-BSA) Sample size 28 Critical value (2%) 2.479

Log D Double Log Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.034 1. R Standard Error 0.038 t 0.175 p-value 0.862 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. Log D 0.034

239 Appendix B: Ka Correlations among Other Factors Figure B103

Non-PAs Log P vs KSc-BSA 6 5

4 y = 0.5346x + 0.4186 5 -1 R² = 0.1489 KSC (10 M ) 3 2 1 0 0 1 2 3 4 5 Log P

Table B103 Correlation Coefficients Matrix (Non-PAs-Log P and KSc-BSA) Sample size 12 Critical value (2%) 2.764

LogP Scatchard LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.386 1. R Standard Error 0.085 t 1.323 p-value 0.215 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. LogP 0.386

240 Appendix B: Ka Correlations among Other Factors Figure B104

PAs Log D vs KSc-BSA 7 6 5 y = 0.0457x + 1.2021 4 R² = 0.0052 K (105 M-1) SC 3 2 1 0 -8 -6 -4 -2 0 2 Log D

Table B104 Correlation Coefficients Matrix (PAs-Log D and KSc-BSA) Sample size 28 Critical value (2%) 2.479

Log D Scatchard Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.072 1. R Standard Error 0.038 t 0.37 p-value 0.714 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. Log D 0.072

241 Appendix B: Ka Correlations among Other Factors Figure B105

Non-PAs Log P vs KQu-BSA 3 2.5 2 y = 0.0995x + 1.5711 5 -1 R² = 0.0353 KQu (10 M ) 1.5 1 0.5 0 0 1 2 3 4 5 Log P

Table B105 Correlation Coefficients Matrix (Non-PAs-Log P and KQu-BSA) Sample size 12 Critical value (2%) 2.764

LogP Quadratic LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.188 1. R Standard Error 0.096 t 0.605 p-value 0.559 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. LogP 0.188

242 Appendix B: Ka Correlations among Other Factors Table B106

PAs Log D vs KQu-BSA

4 3.5 3 y = -0.0026x + 1.1585 2.5 R² = 6E-05 5 -1 KQu (10 M ) 2 1.5 1 0.5 0 -8 -6 -4 -2 0 2 Log D

Table B106 Correlation Coefficients Matrix (PAs-Log D and KQu-BSA) Sample size 28 Critical value (2%) 2.479

Log D Quadratic Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient -0.008 1. R Standard Error 0.038 t -0.04 p-value 0.968 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. Log D -0.008

243 Appendix B: Ka Correlations among Other Factors Figure B107

Non-PAs Log P vs KBH-BSA

30 25 20 y = 2.4941x + 1.3176 5 -1 KBH (10 M ) 15 R² = 0.1457 10 5 0 0 1 2 3 4 5 Log P

Table B107 Correlation Coefficients Matrix (Non-PAs-Log P and KBH-BSA) Sample size 12 Critical value (2%) 2.764

LogP Benesi-Hildibrand LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildibrand Pearson Correlation Coefficient 0.382 1. R Standard Error 0.085 t 1.306 p-value 0.221 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. LogP 0.382

244 Appendix B: Ka Correlations among Other Factors Figure B108

PAs Log D vs KBH-BSA

35 30 25 y = 0.4319x + 9.5131 20 R² = 0.011 K (105 M-1) BH 15 10 5 0 -8 -6 -4 -2 0 2 Log D

Table B108 Correlation Coefficients Matrix (PAs-Log D and KBH-BSA) Sample size 28 Critical value (2%) 2.479

Log D Benesi-Hildibrand Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildibrand Pearson Correlation Coefficient 0.105 1. R Standard Error 0.038 t 0.537 p-value 0.596 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildibrand vs. Log D 0.105

245 Appendix B: Ka Correlations among Other Factors Figure B109

Non-PAs Log P vs Ksv-LDL/VLDL 4.5 4 3.5 3 y = 0.3121x + 1.6568 2.5 K (105 M-1) R² = 0.1792 sv 2 1.5 1 0.5 0 0 1 2 3 4 5 Log P

Table B109 Correlation Coefficients Matrix (Non-PAs-Log P and KSV-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP Stern-Volmer LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.423 1. R Standard Error 0.082 t 1.478 p-value 0.17 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. LogP 0.423

246 Appendix B: Ka Correlations among Other Factors Figure B110

PAs Log D vs Ksv-LDL/VLDL 3 2.5 2 y = 0.0164x + 1.5152 5 -1 Ksv (10 M ) 1.5 R² = 0.0037 1 0.5 0 -8 -6 -4 -2 0 2 Log D

Table B110 Correlation Coefficients Matrix (PAs-Log D and KSV-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Log D Stern-Volmer Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Stern-Volmer Pearson Correlation Coefficient 0.061 1. R Standard Error 0.038 t 0.312 p-value 0.757 H0 (2%) accepted

R Variable vs. Variable R Stern-Volmer vs. Log D 0.061

247 Appendix B: Ka Correlations among Other Factors Figure B111

Non-PAs Log P vs KDL-LDL/VLDL

4 3.5 3 y = 0.3506x + 1.0999 2.5 R² = 0.1392 5 -1 KDL (10 M ) 2 1.5 1 0.5 0 0 1 2 3 4 5 Log P

Table B111 Correlation Coefficients Matrix (Non-PAs-Log P and KDL-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP Double Log LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.373 1. R Standard Error 0.086 t 1.272 p-value 0.232 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. LogP 0.373

248 Appendix B: Ka Correlations among Other Factors Figure B112

PAs Log D vs KDL-LDL/VLDL 3 2.5

2 y = 0.024x + 1.0001 5 -1 R² = 0.0059 KDL (10 M ) 1.5 1 0.5 0 -8 -6 -4 -2 0 2 Log D

Table B112 Correlation Coefficients Matrix (PAs-Log D and KDL-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Log D Double Log Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.076 1. R Standard Error 0.038 t 0.391 p-value 0.699 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. Log D 0.076

249 Appendix B: Ka Correlations among Other Factors Figure B113

Non-PAs Log P vs KSc-LDL/VLDL

3 2.5 2 y = 0.1643x + 1.2527 5 -1 KSC (10 M ) 1.5 R² = 0.0861 1 0.5 0 0 1 2 3 4 5 Log P

Table B113 Correlation Coefficients Matrix (Non-PAs-Log P and KSc-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP Scatchard LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient 0.293 1. R Standard Error 0.091 t 0.971 p-value 0.355 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. LogP 0.293

250 Appendix B: Ka Correlations among Other Factors Figure B114

PAs Log D vs KSc-LDL/VLDL

2.5

2 y = -0.0004x + 1.4302 1.5 R² = 3E-06 5 -1 KSC (10 M ) 1

0.5

0 -8 -6 -4 -2 0 2 Log D

Table B114 Correlation Coefficients Matrix (PAs-Log D and KSc-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Log D Scatchard Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Scatchard Pearson Correlation Coefficient -0.002 1. R Standard Error 0.038 t -0.009 p-value 0.993 H0 (2%) accepted

R Variable vs. Variable R Scatchard vs. Log D -0.002

251 Appendix B: Ka Correlations among Other Factors Figure B115

Non-PAs Log P vs KQu-LDL/VLDL 2

1.5 y = 0.1041x + 1.0051 5 -1 R² = 0.1947 KQu (10 M ) 1

0.5

0 0 1 2 3 4 5 Log P

Table B115 Correlation Coefficients Matrix (Non-PAs-Log P and KQu-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP Quadratic LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.441 1. R Standard Error 0.081 t 1.555 p-value 0.151 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. LogP 0.441

252 Appendix B: Ka Correlations among Other Factors Figure B116

PAs Log D vs KQu-LDL/VLDL

1.6 1.4 1.2 1 y = 0.009x + 0.9462 5 -1 R² = 0.0082 KQu (10 M ) 0.8 0.6 0.4 0.2 0 -8 -6 -4 -2 0 2 Log D

Table B116 Correlation Coefficients Matrix (PAs-Log D and KQu-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Log D Quadratic Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Quadratic Pearson Correlation Coefficient 0.091 1. R Standard Error 0.038 t 0.465 p-value 0.646 H0 (2%) accepted

R Variable vs. Variable R Quadratic vs. Log D 0.091

253 Appendix B: Ka Correlations among Other Factors Figure B117

Non-PAs Log P vs KBH-LDL/VLDL 40 35 30 25 y = 2.1248x + 7.5438 5 -1 KBH (10 M ) 20 R² = 0.067 15 10 5 0 0 1 2 3 4 5 Log P

Table B117 Correlation Coefficients Matrix (Non-PAs-Log P and KBH-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP Benesi-Hildebrand LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient 0.259 1. R Standard Error 0.093 t 0.848 p-value 0.416 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. LogP 0.259

254 Appendix B: Ka Correlations among Other Factors Figure B118

PAs Log D vs KBH-LDL/VLDL 35 30 25 y = -0.2999x + 14.513 20 K (105 M-1) R² = 0.0071 BH 15 10 5 0 -8 -6 -4 -2 0 2 Log D

Table B118 Correlation Coefficients Matrix (PAs-Log D and KBH-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

Log D Benesi-Hildebrand Log D Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Benesi-Hildebrand Pearson Correlation Coefficient -0.084 1. R Standard Error 0.038 t -0.431 p-value 0.67 H0 (2%) accepted

R Variable vs. Variable R Benesi-Hildebrand vs. Log D -0.084

255 Appendix B: Ka Correlations among Other Factors Figure B119

Non-PAs Log P vs Log-KSV-BSA

5.9 5.8 5.7 y = 0.0286x + 5.489 5.6 Log K (M-1) R² = 0.0292 SV 5.5 5.4 5.3 5.2 0 1 2 3 4 5 Log P

Table B119 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KSV-BSA) Sample size 12 Critical value (2%) 2.764

LogP LOG-Ksv LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Ksv Pearson Correlation Coefficient 0.171 1. R Standard Error 0.097 t 0.549 p-value 0.595 H0 (2%) accepted

R Variable vs. Variable R LOG-Ksv vs. LogP 0.171

256 Appendix B: Ka Correlations among Other Factors Figure B120

PAs Log D vs Log-KSV-BSA

7 6 5 y = -0.004x + 5.2451 4 R² = 0.0007 Log K (M-1) SV 3 2 1 0 -8 -6 -4 -2 0 2 Log D

Table B120 Correlation Coefficients Matrix (PAs-Log D and Log-KSV-BSA) Sample size 28 Critical value (2%) 2.479

LogP LOG-Ksv LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Ksv Pearson Correlation Coefficient -0.026 1. R Standard Error 0.038 t -0.135 p-value 0.894 H0 (2%) accepted

R Variable vs. Variable R LOG-Ksv vs. LogP -0.026

257 Appendix B: Ka Correlations among Other Factors Figure B121

Non-PAs Log P vs Log-KDL-BSA 5.9 5.8 5.7 y = 0.0564x + 5.4229 5.6 Log K (M-1) R² = 0.0982 DL 5.5 5.4 5.3 5.2 0 1 2 3 4 5 Log P

Table B121 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KDL-BSA) Sample size 12 Critical value (2%) 2.764

LogP LOG-KDL LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KDL Pearson Correlation Coefficient 0.313 1. R Standard Error 0.09 t 1.043 p-value 0.321 H0 (2%) accepted

R Variable vs. Variable R LOG-KDL vs. LogP 0.313

258 Appendix B: Ka Correlations among Other Factors Figure B122

PAs Log D vs Log-KDL-BSA 7 6 5 y = 0.0019x + 5.15 4 Log K (M-1) R² = 6E-05 DL 3 2 1 0 -8 -6 -4 -2 0 2 Log D

Table B122 Correlation Coefficients Matrix (PAs-Log D and Log-KDL-BSA) Sample size 28 Critical value (2%) 2.479

LogP LOG-KDL LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KDL Pearson Correlation Coefficient 0.008 1. R Standard Error 0.038 t 0.04 p-value 0.968 H0 (2%) accepted

R Variable vs. Variable R LOG-KDL vs. LogP 0.008

259 Appendix B: Ka Correlations among Other Factors Figure B123

Non-PAs Log P vs Log-KSc-BSA 7 6 5 4 y = 0.1287x + 4.8114 Log K (M-1) R² = 0.1397 Sc 3 2 1 0 0 1 2 3 4 5 Log P

Table B123 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KSc-BSA) Sample size 12 Critical value (2%) 2.764

LogP LOG-KSc LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KSc Pearson Correlation Coefficient 0.374 1. R Standard Error 0.086 t 1.274 p-value 0.231 H0 (2%) accepted

R Variable vs. Variable R LOG-KSc vs. LogP 0.374

260 Appendix B: Ka Correlations among Other Factors Figure B124

PAs Log D vs Log-KSc-BSA

7 6 5 y = -0.0002x + 4.8415 4 R² = 5E-07 Log K (M-1) Sc 3 2 1 0 -8 -6 -4 -2 0 2 Log D

Table B124 Correlation Coefficients Matrix (PAs-Log D and Log-KSc-BSA) Sample size 28 Critical value (2%) 2.479

LogP LOG-KSc LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KSc Pearson Correlation Coefficient -0.001 1. R Standard Error 0.038 t -0.004 p-value 0.997 H0 (2%) accepted

R Variable vs. Variable R LOG-KSc vs. LogP -0.001

261 Appendix B: Ka Correlations among Other Factors Figure B125

Non-PAs Log P vs Log-KQu-BSA

5.45 5.4 5.35 5.3 y = 0.0232x + 5.1834 5.25 Log K (M-1) R² = 0.0307 Qu 5.2 5.15 5.1 5.05 5 0 1 2 3 4 5 Log P

Table B125 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KQu-BSA) Sample size 12 Critical value (2%) 2.764

LogP LOG-Kqu LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Kqu Pearson Correlation Coefficient 0.175 1. R Standard Error 0.097 t 0.563 p-value 0.586 H0 (2%) accepted

R Variable vs. Variable R LOG-Kqu vs. LogP 0.175

262 Appendix B: Ka Correlations among Other Factors Figure B126

PAs Log D vs Log-KQu-BSA

5.7 5.6 5.5 5.4 y = -0.0014x + 5.0225 5.3 R² = 0.0002 -1 Log KQu (M ) 5.2 5.1 5 4.9 4.8 4.7 -8 -6 -4 -2 0 2 Log D

Table B126 Correlation Coefficients Matrix (PAs-Log D and Log-KQu-BSA) Sample size 28 Critical value (2%) 2.479

LogP LOG-Kqu LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Kqu Pearson Correlation Coefficient -0.015 1. R Standard Error 0.038 t -0.077 p-value 0.939 H0 (2%) accepted

R Variable vs. Variable R LOG-Kqu vs. LogP -0.015

263 Appendix B: Ka Correlations among Other Factors Figure B127

Non-PAs Log P vs Log-KBH-BSA

7 6 5 y = 0.126x + 5.4449 4 R² = 0.1389 Log K (M-1) BH 3 2 1 0 0 1 2 3 4 5 Log P

Table B127 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KBH-BSA) Sample size 12 Critical value (2%) 2.764

LogP LOG-KBH LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KBH Pearson Correlation Coefficient 0.373 1. R Standard Error 0.086 t 1.27 p-value 0.233 H0 (2%) accepted

R Variable vs. Variable R LOG-KBH vs. LogP 0.373

264 Appendix B: Ka Correlations among Other Factors Figure B128

PAs Log D vs Log-KBH-BSA

7 6 5 y = -0.001x + 5.7404 4 R² = 2E-05 Log K (M-1) BH 3 2 1 0 -8 -6 -4 -2 0 2 Log D

Table B128 Correlation Coefficients Matrix (PAs-Log D and Log-KBH-BSA) Sample size 28 Critical value (2%) 2.479

LogP LOG-KBH LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KBH Pearson Correlation Coefficient -0.005 1. R Standard Error 0.038 t -0.024 p-value 0.981 H0 (2%) accepted

R Variable vs. Variable R LOG-KBH vs. LogP -0.005

265 Appendix B: Ka Correlations among Other Factors Figure B129

Non-PAs Log P vs Log-KSV-LDL/VLDL

5.65 5.6 5.55 5.5 y = 0.0461x + 5.2559 5.45 Log K (M-1) R² = 0.1467 SV 5.4 5.35 5.3 5.25 5.2 0 1 2 3 4 5 Log P

Table B129 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KSV-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP LOG-Ksv LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Ksv Pearson Correlation Coefficient 0.383 1. R Standard Error 0.085 t 1.311 p-value 0.219 H0 (2%) accepted

R Variable vs. Variable R LOG-Ksv vs. LogP 0.383

266 Appendix B: Ka Correlations among Other Factors Figure B130

PAs Log D vs Log-KSV-LDL/VLDL

5.5 5.4 5.3 y = 0.0046x + 5.1553 5.2 R² = 0.0037 Log K (M-1) SV 5.1 5 4.9 4.8 -8 -6 -4 -2 0 2 Log D

Table B130 Correlation Coefficients Matrix (PAs-Log D and Log-KSV-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

LogP LOG-Ksv LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Ksv Pearson Correlation Coefficient 0.061 1. R Standard Error 0.038 t 0.31 p-value 0.759 H0 (2%) accepted

R Variable vs. Variable R LOG-Ksv vs. LogP 0.061

267 Appendix B: Ka Correlations among Other Factors Figure B131

Non-PAs Log P vs Log-KDL-LDL/VLDL

5.7 5.6 5.5 5.4 5.3 y = 0.0541x + 5.1168 Log K (M-1) R² = 0.0674 DL 5.2 5.1 5 4.9 4.8 0 1 2 3 4 5 Log P

Table B131 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KDL-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP LOG-KDL LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KDL Pearson Correlation Coefficient 0.26 1. R Standard Error 0.093 t 0.85 p-value 0.415 H0 (2%) accepted

R Variable vs. Variable R LOG-KDL vs. LogP 0.26

268 Appendix B: Ka Correlations among Other Factors Figure B132

PAs Log D vs Log-KDL-LDL/VLDL

6 5

4 y = 0.0175x + 4.9063 -1 R² = 0.0096 Log KDL (M ) 3 2 1 0 -8 -6 -4 -2 0 2 Log D

Table B132 Correlation Coefficients Matrix (PAs-Log D and Log-KDL-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

LogP LOG-KDL LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KDL Pearson Correlation Coefficient 0.098 1. R Standard Error 0.038 t 0.502 p-value 0.62 H0 (2%) accepted

R Variable vs. Variable R LOG-KDL vs. LogP 0.098

269 Appendix B: Ka Correlations among Other Factors Figure B133

Non-PAs Log P vs Log-KSc-LDL/VLDL

5.5 5.4 5.3 y = 0.0314x + 5.1214 5.2 Log K (M-1) R² = 0.0478 Sc 5.1 5 4.9 4.8 0 1 2 3 4 5 Log P

Table B133 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KSc-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP LOG-KSc LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KSc Pearson Correlation Coefficient 0.219 1. R Standard Error 0.095 t 0.708 p-value 0.495 H0 (2%) accepted

R Variable vs. Variable R LOG-KSc vs. LogP 0.219

270 Appendix B: Ka Correlations among Other Factors Figure B134

PAs Log D vs Log-KSc-LDL/VLDL

5.4 5.3 5.2 y = 0.0024x + 5.1373 5.1 R² = 0.0009 Log K (M-1) Sc 5 4.9 4.8 4.7 -8 -6 -4 -2 0 2 Log D

Table B134 Correlation Coefficients Matrix (PAs-Log D and Log-KSc-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

LogP LOG-KSc LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KSc Pearson Correlation Coefficient 0.03 1. R Standard Error 0.038 t 0.153 p-value 0.88 H0 (2%) accepted

R Variable vs. Variable R LOG-KSc vs. LogP 0.03

271 Appendix B: Ka Correlations among Other Factors Figure B135

Non-PAs Log P vs Log-KQu-LDL/VLDL

5.3 5.25 5.2 y = 0.0318x + 5.0168 5.15 R² = 0.1847 Log K (M-1) Qu 5.1 5.05 5 4.95 0 1 2 3 4 5 Log P

Table B135 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KQu-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP LOG-Kqu LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Kqu Pearson Correlation Coefficient 0.43 1. R Standard Error 0.082 t 1.505 p-value 0.163 H0 (2%) accepted

R Variable vs. Variable R LOG-Kqu vs. LogP 0.43

272 Appendix B: Ka Correlations among Other Factors Figure B136

PAs Log D vs Log-KQu-LDL/VLDL

5.2 5.15 5.1 y = 0.0046x + 4.9685 5.05 R² = 0.0106 -1 Log KQu (M ) 5 4.95 4.9 4.85 4.8 -8 -6 -4 -2 0 2 Log D

Table B136 Correlation Coefficients Matrix (PAs-Log D and Log-KQu-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

LogP LOG-Kqu LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-Kqu Pearson Correlation Coefficient 0.103 1. R Standard Error 0.038 t 0.529 p-value 0.601 H0 (2%) accepted

R Variable vs. Variable R LOG-Kqu vs. LogP 0.103

273 Appendix B: Ka Correlations among Other Factors Figure B137

Non-PAs Log P vs Log-KBH-LDL/VLDL

6.6 6.4

6.2 y = 0.0546x + 5.9084 -1 R² = 0.0524 Log KBH (M ) 6 5.8 5.6 5.4 0 1 2 3 4 5 Log P

Table B137 Correlation Coefficients Matrix (Non-PAs-Log P and Log-KBH-LDL/VLDL) Sample size 12 Critical value (2%) 2.764

LogP LOG-KBH LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KBH Pearson Correlation Coefficient 0.229 1. R Standard Error 0.095 t 0.744 p-value 0.474 H0 (2%) accepted

R Variable vs. Variable R LOG-KBH vs. LogP 0.229

274 Appendix B: Ka Correlations among Other Factors Figure B138

PAs Log D vs Log-KBH-LDL/VLDL

6.6 6.5 6.4 6.3 y = -0.0058x + 6.1228 6.2 R² = 0.0029 -1 Log KBH (M ) 6.1 6 5.9 5.8 5.7 5.6 -8 -6 -4 -2 0 2 Log D

Table B138 Correlation Coefficients Matrix (PAs-Log D and Log-KBH-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

LogP LOG-KBH LogP Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) LOG-KBH Pearson Correlation Coefficient -0.054 1. R Standard Error 0.038 t -0.274 p-value 0.787 H0 (2%) accepted

R Variable vs. Variable R LOG-KBH vs. LogP -0.054

275 Appendix B: Ka Correlations among Other Factors Figure B139a Figure B139b

All PPs n vs KDL-BSA All PPs (w/o Ellagic acid) n vs KDL-BSA 20 8 15 6

5 - KDL (10 M10 K (105 M-1) 4 1) DL 5 2 0 0 0 0.5 1 1.5 2 0 0.5 1 1.5 2 n n y = 4.875x - 1.6195 y = 4.0572x - 1.1924 R² = 0.1883 R² = 0.3045 Table B139a Correlation Coefficients Matrix (All PPs-n and KDL-BSA) Sample size 40 Critical value (2%) 2.429

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.434 1. R Standard Error 0.021 t 2.969 p-value 0.005 H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.434 Table B139b

Correlation Coefficients Matrix (PAs {w/o Ellagic acid}-n and KDL-BSA) Sample size 39 Critical value (2%) 2.431

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.552 1. R Standard Error 0.019 t 4.025 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.552

276 Appendix B: Ka Correlations among Other Factors Figure B140a Figure B140b

All PPs n vs KDL-LDL/VLDL All PPs (w/o p-Hydroxyphenylacetic acid) n vs K -LDL/VLDL 4 DL 3 4 5 - KDL (10 M 1) 2 2 5 -1 1 KDL (10 M ) 0 0 0 0.5 1 0 1 2 3 -2 n y = 0.5933x + 0.8218 n y = 5.1585x - 2.352 R² = 0.6015 R² = 0.0331 Table B140a Correlation Coefficients Matrix (All PPs-n and KDL-LDL/VLDL) Sample size 40 Critical value (2%) 2.429

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.182 1. R Standard Error 0.025 t 1.14 p-value 0.261 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. DL n 0.182 Table B140b Correlation Coefficients Matrix (PAs {w/o p-Hydroxyphenylacetic acid}-n and KDL-LDL/VLDL) Sample size 39 Critical value (2%) 2.431

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.776 1. R Standard Error 0.011 t 7.474 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.776

277 Appendix B: Ka Correlations among Other Factors Figure B141a Figure B141b

PAs n vs KDL-BSA PAs (w/o Ellagic acid) n vs KDL-BSA 20 8 15 6 K (105 M- 5 - 10 DL 4 KDL (10 M 1) 1 ) 5 2 0 0 -5 0 0.5 1 1.5 2 0 1 2 y = 5.0225x - 2.2049 n y = 3.9504x - 1.7188 n R² = 0.559 R² = 0.2115 Table B141a Correlation Coefficients Matrix (PAs-n and KDL-BSA) Sample size 28 Critical value (2%) 2.479

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.46 1. R Standard Error 0.03 t 2.641 p-value 0.014 H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.46 Table B141b Correlation Coefficients Matrix (PAs {w/o Ellagic acid}-n and KDL-BSA) Sample size 27 Critical value (2%) 2.485

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.748 1. R Standard Error 0.018 t 5.629 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.748

278 Appendix B: Ka Correlations among Other Factors Figure B142a Figure B142b PAs (w/o p-Hydroxyphenylacetic PAs n vs KDL-LDL/VLDL 3 acid) n vs KDL-LDL/VLDL 2.5 3 2 5 - KDL (10 M 2 1.5 5 - 1) KDL (10 M 1 1) 0.5 1 0 0 0 1 2 3 0 0.5 1 n y = 0.1611x + 0.8226 y = 3.6757x - 1.5293 n R² = 0.0069 R² = 0.644

Table B142a Correlation Coefficients Matrix (PAs-n and KDL-LDL/VLDL) Sample size 28 Critical value (2%) 2.479

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.083 1. R Standard Error 0.038 t 0.425 p-value 0.674 H0 (2%) accepted

R Variable vs. Variable R Double Log vs. DL n 0.083 Table B142b

Correlation Coefficients Matrix (PAs {w/o p-Hydroxyphenylacetic acid}-n and KDL-LDL/VLDL) Sample size 27 Critical value (2%) 2.485

DL n Double Log DL n Pearson Correlation Coefficient 1. R Standard Error t p-value H0 (2%) Double Log Pearson Correlation Coefficient 0.802 1. R Standard Error 0.014 t 6.724 p-value 0. H0 (2%) rejected

R Variable vs. Variable R Double Log vs. DL n 0.802

279 Appendix C: Ka Plots of BSA

Appendix C: All Polyphenols with BSA - Method Plots

Polyphenol Page #

Pterostilbene(1,a) 281 Resveratrol(1,a) 283 Quercetin(2,b) 285 Quercetin-3-glucuronide(2,b) 287 Quercetin-3-glucoside(2,b) 289 Biochanin A(2,c) 291 Puerarin(2,c) 293 Chrysin(2,d) 295 Baicalein(2,d) 297 Baicalin(2,d) 299 Flavone(2,d) 301 Pelargonidin Chloride(2,e) 303 Dopac(2,f) 305 m-Hydroxyphenylacteic acid(2,f) 307 p-Hydroxyphenylacteic acid(2,f) 309 Homogentisic acid(2,f) 311 Ellagic acid(2,g) 313 Eudesmic acid(2,g) 315 Syringic acid(2,g) 317 Gallic acid(2,g) 319 Protocatechuic acid(2,g) 321 m-Hydroxybenzoic acid(2,g) 323 p-Hydroxybenzoic acid(2,g) 325 p-Hydroxysalicylic acid(2,g) 327 Apocynin(2,g) 329 Vanillic acid(2,g) 331 Chlorogenic acid(2,h) 333 Ferulic acid(2,h) 335 Isoferulic acid(2,h) 337 Isoferulic acid-3-o-glucuronide(2,h) 339 Dihydroferulic acid(2,h) 341 Caffeic acid(2,h) 343 Caffeic acid-3-o-glucuronide(2,h) 345 Caffeic acid-4-o-glucuronide(2,h) 347 Dihydrocaffeic acid(2,h) 349 Dihydrocaffeic acid-3-o-glucuronide(2,h) 351 Dihydrocaffeic acid-3-o-sulfate(2,h) 353 Sinapic acid(2,h) 355 o-Coumaric acid(2,h) 357 p-Coumaric acid(2,h) 359 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

280 Appendix C: Ka Plots of BSA

Pterostilbene

Figure C1a: Stern-Volmer Plot of Pterostilbene and BSA Stern-Volmer Plot (Pterostilbene-BSA) 2

1.8

1.6 y = 581765x + 1.0829 F0/F R² = 0.9931 (A.U.) 1.4

1.2

1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C1b: Double Logarithm Plot of Pterostilbene and BSA Double Logarithm Plot (Pterostilbene-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -0.1-5.8 -0.2 y = 0.9685x + 5.6365 -0.3 log {(F0-F)/F} R² = 0.9964 -0.4 (A.U.) -0.5 -0.6 -0.7 -0.8 log [Q] (M)

281 Appendix C: Ka Plots of BSA

Figure C1c: Scatchard’s Plot of Pterostilbene and BSA Scatchard's Plot (Pterostilbene-BSA) 0.8 0.7 0.6 {(F0-F)/F0}/ 0.5 y = -329882x + 0.7507 [Q] 0.4 R² = 0.8558 (A.U. x μM-1) 0.3 0.2 0.1 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C1d: Benesi-Hildebrand Plot of Pterostilbene and BSA Benesi-Hildabrand Plot (Pterostilbene-BSA) 6 5 4 1/{(F0-F)/F0} y = 1E-06x + 1.5679 3 (A.U.-1) R² = 0.9698 2 1 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

282 Appendix C: Ka Plots of BSA

Resveratrol

Figure C2a: Stern-Volmer Plot of Resveratrol and BSA Stern-Volmer Plot (Resveratrol-BSA) 1.7 1.6 1.5 F0/F 1.4 y = 308309x + 1.0752 (A.U.) 1.3 R² = 0.9896 1.2 1.1 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C2b: Double Logarithm Plot of Resveratrol and BSA Double Logarithm Plot (Resveratrol-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -5.6 -0.1

-0.2 y = 0.5214x + 2.8927 log {(F0-F)/F} R² = 0.9928 -0.3 (A.U.) -0.4

-0.5

-0.6 log [Q] (M)

283 Appendix C: Ka Plots of BSA

Figure C2c: Scatchard’s Plot of Resveratrol and BSA Scatchard's Plot (Resveratrol-BSA) 0.5

0.4

{(F0-F)/F0}/ 0.3 y = -164963x + 0.4686 [Q] R² = 0.9446 (A.U. x μM-1) 0.2

0.1

0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C2d: Benesi-Hildebrand Plot of Resveratrol and BSA Benesi-Hildebrand Plot (Resveratrol-BSA) 9 8 7 6 y = 2E-06x + 1.7365 0 0 1/{(F -F)/F } 5 R² = 0.9988 (A.U.-1) 4 3 2 1 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

284 Appendix C: Ka Plots of BSA

Quercetin

Figure C3a: Stern-Volmer Plot of Quercetin and BSA Stern-Volmer Plot (Quercetin-BSA) 2.2 2 1.8 y = 696324x + 0.9853 F0/F 1.6 R² = 0.9997 (A.U.) 1.4 1.2 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C3b: Double Logarithm Plot of Quercetin and BSA Double Logarithm Plot (Quercetin-BSA) 0.2

0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -5.6 -0.2 y = 1.0501x + 6.1323 log {(F0-F)/F} R² = 0.9994 -0.4 (A.U.) -0.6

-0.8

-1 log [Q] (M)

285 Appendix C: Ka Plots of BSA

Figure C3c: Scatchard’s Plot of Quercetin and BSA Scatchard's Plot (Quercetin-BSA) 0.6 0.5 0.4 {(F0-F)/F0}/ y = -158245x + 0.5732 [Q] 0.3 R² = 0.9949 (A.U. x μM-1) 0.2 0.1 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C3d: Benesi-Hildebrand Plot of Quercetin and BSA Benesi-Hildebrand Plot (Quercetin-BSA) 8 7 6 5 y = 2E-06x + 0.8409 1/{(F0-F)/F0} 4 R² = 0.9992 (A.U.-1) 3 2 1 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

286 Appendix C: Ka Plots of BSA

Quercetin-3-glucuronide

Figure C4a: Stern-Volmer Plot of Quercetin-3-glucuronide and BSA Stern-Volmer Plot (Quercetin-3-glucuronide-BSA) 1.9 1.8 1.7 y = 402626x + 1.1369 1.6 R² = 0.8794 F0/F 1.5 (A.U.) 1.4 1.3 1.2 1.1 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C4b: Double Logarithm Plot of Quercetin-3-glucuronide and BSA Double Logarithm Plot (Quercetin-3-glucuronide-BSA)

0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.1-5.6 -0.2 y = 0.8593x + 4.8989 -0.3 R² = 0.9388 log {(F0-F)/F} -0.4 (A.U.) -0.5 -0.6 -0.7 -0.8 -0.9 log [Q] (M)

287 Appendix C: Ka Plots of BSA

Figure C4c: Scatchard’s Plot of Quercetin-3-glucuronide and BSA Scatchard's Plot (Quercetin-3-glucuronide-BSA) 0.6 0.5 0.4 y = -195669x + 0.5764 {(F0-F)/F0}/ R² = 0.9627 [Q] 0.3 (A.U. x μM-1) 0.2 0.1 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C4d: Benesi-Hildebrand Plot of Quercetin-3-glucuronide and BSA Benesi-Hildebrand Plot (Quercetin-3-glucuronide-BSA) 8 7 6 y = 2E-06x + 1.0536 R² = 0.978 5 1/{(F0-F)/F0} 4 (A.U.-1) 3 2 1 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

288 Appendix C: Ka Plots of BSA

Quercetin-3-glucoside

Figure C5a: Stern-Volmer Plot of Quercetin-3-glucoside and BSA Stern-Volmer Plot (Quercetin-3-glucoside-BSA) 1.35 1.3 1.25 y = 209454x + 0.9903 F0/F 1.2 R² = 0.9991 (A.U.) 1.15 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C5b: Double Logarithm Plot of Quercetin-3-glucoside and BSA Double Logarithm Plot (Quercetin-3-glucoside-BSA)

0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.2-5.6 -0.4 y = 1.1254x + 6.0493 -0.6 R² = 0.9969 log {(F0-F)/F} -0.8 (A.U.) -1 -1.2 -1.4 -1.6 log [Q] (M)

289 Appendix C: Ka Plots of BSA

Figure C5c: Scatchard’s Plot of Quercetin-3-glucoside and BSA Scatchard's Plot (Quercetin-3-glucoside-BSA) 0.18 0.175 0.17 0 0 y = -18643x + 0.1807 {(F -F)/F }/ 0.165 [Q] R² = 0.9657 (A.U. x μM-1) 0.16 0.155 0.15 0.145 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C5d: Benesi-Hildebrand Plot of Quercetin-3-glucoside and BSA Benesi-Hildebrand Plot (Quercetin-3-glucoside-BSA) 25

20 y = 6E-06x + 0.5967 R² = 0.9997 15 1/{(F0-F)/F0} -1 (A.U. ) 10

5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

290 Appendix C: Ka Plots of BSA

Biochanin A

Figure C6a: Stern-Volmer Plot of Biochanin A and BSA Stern-Volmer Plot (Biochanin A-BSA) 1.35 1.3 1.25 y = 258640x + 1.0193 F0/F 1.2 R² = 0.9814 (A.U.) 1.15 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C6b: Double Logarithm Plot of Biochanin A and BSA Double Logarithm Plot (Biochanin A-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

y-0.4 = 0.9318x + 5.0407 log {(F0-F)/F} R² = 0.9927 -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

291 Appendix C: Ka Plots of BSA

Figure C6c: Scatchard’s Plot of Biochanin A and BSA Scatchard's Plot (Biochanin A-BSA) 0.3 0.25 0.2 {(F0-F)/F0}/ y = -85813x + 0.3045 [Q] 0.15 R² = 0.9666 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C6d: Benesi-Hildebrand Plot of Biochanin A and BSA Benesi-Hildebrand Plot (Biochanin A-BSA) 14 12 10 y = 3E-06x + 1.278 0 0 8 1/{(F -F)/F } R² = 0.9982 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

292 Appendix C: Ka Plots of BSA

Puerarin

Figure C7a: Stern-Volmer Plot of Puerarin and BSA Stern-Volmer Plot (Puerarin-BSA) 1.3 1.25 1.2 y = 216250x + 1.0367 F0/F 1.15 R² = 0.99 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C7b: Double Logarithm Plot of Puerarin and BSA Double Logarithm Plot (Puerarin-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

y-0.4 = 0.7972x + 4.189 R² = 0.9967 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

293 Appendix C: Ka Plots of BSA

Figure C7c: Scatchard’s Plot of Puerarin and BSA Scatchard's Plot (Puerarin-BSA) 0.35 0.3 0.25 0 0 {(F -F)/F }/ 0.2 y = -130301x + 0.3306 [Q] R² = 0.99 (A.U. x μM-1) 0.15 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C7d: Benesi-Hildebrand Plot of Puerarin and BSA Benesi-Hildebrand Plot (Puerarin-BSA) 14 12 10 y = 3E-06x + 2.2034 1/{(F0-F)/F0} 8 R² = 0.9997 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

294 Appendix C: Ka Plots of BSA

Chrysin

Figure C8a: Stern-Volmer Plot of Chrysin and BSA Stern-Volmer Plot (Chrysin-BSA) 1.6 1.5 1.4 F0/F y = 504265x + 0.9768 1.3 (A.U.) R² = 0.9981 1.2 1.1 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C8b: Double Logarithm Plot of Chrysin and BSA Double Logarithm Plot (Chrysin-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4y = 1.1212x + 6.4145 log {(F0-F)/F} R² = 0.9984 (A.U.) -0.6

-0.8

-1 log [Q] (M)

295 Appendix C: Ka Plots of BSA

Figure C8c: Scatchard’s Plot of Chrysin and BSA Scatchard's Plot (Chrysin-BSA) 0.5

0.4

{(F0-F)/F0}/ 0.3 y = -140904x + 0.4818 [Q] R² = 0.9955 (A.U. x μM-1) 0.2

0.1

0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C8d: Benesi-Hildebrand Plot of Chrysin and BSA Benesi-Hildebrand Plot (Chrysin-BSA) 9 8 7 6 y = 2E-06x + 0.9277 0 0 1/{(F -F)/F } 5 R² = 0.9997 (A.U.-1) 4 3 2 1 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

296 Appendix C: Ka Plots of BSA

Baicalein

Figure C9a: Stern-Volmer Plot of Baicalein and BSA Stern-Volmer Plot (Baicalein-BSA) 1.8 1.7 1.6 1.5 y = 476971x + 1.1929 F0/F 1.4 R² = 0.9782 (A.U.) 1.3 1.2 1.1 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C9b: Double Logarithm Plot of Baicalein and BSA Double Logarithm Plot (Baicalein-BSA) 0 -6.6 -6.4 -6.2 -6 -0.1-5.8 -0.2 -0.3 y = 0.9413x + 5.3349 log {(F0-F)/F} -0.4 R² = 0.9914 (A.U.) -0.5 -0.6 -0.7 -0.8 -0.9 log [Q] (M)

297 Appendix C: Ka Plots of BSA

Figure C9c: Scatchard’s Plot of Baicalein and BSA Scatchard's Plot (Baicalein-BSA) 0.9 0.8 0.7 0.6 {(F0-F)/F0}/ y = -566026x + 0.9588 0.5 [Q] R² = 0.9288 0.4 (A.U. x μM-1) 0.3 0.2 0.1 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C9d: Benesi-Hildebrand Plot of Baicalein and BSA Benesi-Hildebrand Plot (Baicalein-BSA) 5

4 y = 7E-07x + 1.7964 3 1/{(F0-F)/F0} R² = 0.9943 -1 (A.U. ) 2

1

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

298 Appendix C: Ka Plots of BSA

Baicalin

Figure C10a: Stern-Volmer Plot of Baicalin and BSA Stern-Volmer Plot (Baicalin-BSA) 1.5 1.45 1.4 1.35 1.3 F0/F y = 380551x + 1.0113 1.25 (A.U.) R² = 0.9934 1.2 1.15 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C10b: Double Logarithm Plot of Baicalin and BSA Double Logarithm Plot (Baicalin-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4 y = 0.8886x + 4.8708 log {(F0-F)/F} -0.6 R² = 0.9961 (A.U.) -0.8

-1

-1.2 log [Q] (M)

299 Appendix C: Ka Plots of BSA

Figure C10c: Scatchard’s Plot of Baicalin and BSA Scatchard's Plot (Baicalin-BSA) 0.45 0.4 0.35 0.3 0 0 {(F -F)/F }/ 0.25 y = -141603x + 0.4186 [Q] 0.2 R² = 0.9077 (A.U. x μM-1) 0.15 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C10d: Benesi-Hildebrand Plot of Baicalin and BSA Benesi-Hildebrand Plot (Baicalin-BSA) 10

8 y = 2E-06x + 1.5092 6 1/{(F0-F)/F0} R² = 0.9969 -1 (A.U. ) 4

2

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

300 Appendix C: Ka Plots of BSA

Flavone

Figure C11a: Stern-Volmer Plot of Flavone and BSA Stern-Volmer Plot (Flavone-BSA) 1.3 1.25 y = 255588x + 1.0035 1.2 R² = 0.9911 F0/F 1.15 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C11b: Double Logarithm Plot of Flavone and BSA Double Logarithm Plot (Flavone-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4 y = 1.0431x + 5.6814 log {(F0-F)/F} -0.6 R² = 0.9919 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

301 Appendix C: Ka Plots of BSA

Figure C11c: Scatchard’s Plot of Flavone and BSA Scatchard's Plot (Flavone-BSA) 0.35 0.3 0.25 0 0 y = -111923x + 0.3357 {(F -F)/F }/ 0.2 [Q] R² = 0.9984 (A.U. x μM-1) 0.15 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C11d: Benesi-Hildebrand Plot of Flavone and BSA Bensesi-Hildebrand Plot (Flavone-BSA) 14 12 10 y = 3E-06x + 1.566 1/{(F0-F)/F0} 8 R² = 0.999 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

302 Appendix C: Ka Plots of BSA

Pelargonidin Chloride

Figure C12a: Stern-Volmer Plot of Pelargonidin Chloride and BSA Stern-Volmer Plot (Pelargonidin Chloride-BSA) 1.5

1.4

y = 420588x + 0.9823 0 1.3 F /F R² = 0.9859 (A.U.) 1.2

1.1

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C12b: Double Logarithm Plot of Pelargonidin Chloride and BSA Double Logarithm Plot (Pelargonidin Chloride-BSA)

0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 1.0477x + 5.8407 -0.4 R² = 0.9891 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

303 Appendix C: Ka Plots of BSA

Figure C12c: Scatchard’s Plot of Pelargonidin Chloride and BSA Scatchard's Plot (Pelargonidin Chloride-BSA) 0.4 0.35 0.3 {(F0-F)/F0}/ 0.25 y = -131096x + 0.3869 [Q] 0.2 R² = 0.9814 (A.U. x μM-1) 0.15 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C12d: Benesi-Hildebrand Plot of Pelargonidin Chloride and BSA Benesi-Hildebrand Plot (Pelargonidin Chloride-BSA)

12 10 y = 3E-06x + 1.3051 8 R² = 0.996 1/{(F0-F)/F0} 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

304 Appendix C: Ka Plots of BSA

Dopac

Figure C13a: Stern-Volmer Plot of Dopac and BSA Stern-Volmer Plot (Dopac-BSA) 1.35 1.3 1.25 F0/F 1.2 y = 280772x + 0.9914 R² = 0.998 (A.U.) 1.15 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C13b: Double Logarithm Plot of Dopac and BSA Double Logarithm Plot (Dopac-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4 y = 1.0408x + 5.6776 log {(F0-F)/F} -0.6R² = 0.998 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

305 Appendix C: Ka Plots of BSA

Figure C13c: Scatchard’s Plot of Dopac and BSA Scatchard's Plot (Dopac-BSA) 0.3 0.25 0.2 {(F0-F)/F0}/ y = -39926x + 0.2548 [Q] 0.15 R² = 0.995 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C13d: Benesi-Hildebrand Plot of Dopac and BSA Benesi-Hildebrand Plot (Dopac-BSA) 16 14 12 10 y = 4E-06x + 0.7372 1/{(F0-F)/F0} 8 R² = 0.9999 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

306 Appendix C: Ka Plots of BSA m-Hydroxyphenylacetic acid

Figure C14a: Stern-Volmer Plot of m-Hydroxyphenylacetic acid and BSA Stern-Volmer Plot (m-Hydroxyphenylacetic acid-BSA)

1.16 1.14 1.12 y = 75074x + 1.0656 1.1 R² = 0.9772 F0/F 1.08 (A.U.) 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C14b: Double Logarithm Plot of m-Hydroxyphenylacetic acid and BSA Double Logarithm Plot (m-Hydroxyphenylacetic acid-BSA)

0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.4048x + 1.5756 -0.4 R² = 0.9978 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 log [Q] (M)

307 Appendix C: Ka Plots of BSA

Figure C14c: Scatchard’s Plot of m-Hydroxyphenylacetic acid and BSA Scatchard's Plot (m-Hydroxyphenylacetic acid-BSA)

0.3 0.25 0.2 y = -196471x + 0.3134 {(F0-F)/F0}/ R² = 0.9149 [Q] 0.15 -1 (A.U. x μM ) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C14d: Benesi-Hildebrand Plot of m-Hydroxyphenylacetic acid and BSA Benesi-Hildebrand Plot (m-Hydroxyphenylacetic acid-BSA)

14 12 y = 2E-06x + 6.4113 10 R² = 0.9948 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

308 Appendix C: Ka Plots of BSA p-Hydroxyphenylacetic acid

Figure C15a: Stern-Volmer Plot of p-Hydroxyphenylacetic acid and BSA Stern-Volmer Plot (p-Hydroxyphenylacetic acid-BSA)

1.12 1.1 y = 62647x + 1.0453 1.08 R² = 0.9836 F0/F 1.06 (A.U.) 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C15b: Double Logarithm Plot of p-Hydroxyphenylacetic acid and BSA Double Logarithm Plot (p-Hydroxyphenylacetic acid-BSA)

0 -6.6 -6.4 -6.2 -6 -0.2-5.8 y = 0.4496x + 1.7291 -0.4 R² = 0.9995 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

309 Appendix C: Ka Plots of BSA

Figure C15c: Scatchard’s Plot of p-Hydroxyphenylacetic acid and BSA Scatchard's Plot (p-Hydroxyphenylacetic acid-BSA)

0.25 0.2 y = -138059x + 0.2311 {(F0-F)/F0}/ 0.15 R² = 0.9173 [Q] (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C15d: Benesi-Hildebrand Plot of p-Hydroxyphenylacetic acid and BSA Benesi-Hildebrand Plot (p-Hydroxyphenylacetic acid-BSA)

20

15 y = 3E-06x + 7.7287 1/{(F0-F)/F0} R² = 0.9944 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

310 Appendix C: Ka Plots of BSA

Homogentisic acid

Figure C16a: Stern-Volmer Plot of Homogentisic acid and BSA Stern-Volmer Plot (Homogentisic acid-BSA) 1.3 1.25 1.2 F0/F 1.15 y = 155987x + 0.9927 (A.U.) R² = 0.9953 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C16b: Double Logarithm Plot of Homogentisic acid and BSA Double Logarithm Plot (Homogentisic acid-BSA)

0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.2-5.6 -0.4 y = 1.0224x + 5.3028 -0.6 R² = 0.9979 log {(F0-F)/F} -0.8 (A.U.) -1 -1.2 -1.4 -1.6 log [Q] (M)

311 Appendix C: Ka Plots of BSA

Figure C16c: Scatchard’s Plot of Homogentisic acid and BSA Scatchard's Plot (Homogentisic acid-BSA) 0.145 0.14 0.135 {(F0-F)/F0}/ y = -12981x + 0.1413 [Q] 0.13 R² = 0.8793 (A.U. x μM-1) 0.125 0.12 0.115 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C16d: Benesi-Hildebrand Plot of Homogentisic acid and BSA Benesi-Hildebrand Plot (Homogentisic acid-BSA) 30 25 y = 7E-06x + 1.0041 20 R² = 0.9996 1/{(F0-F)/F0} 15 (A.U.-1) 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

312 Appendix C: Ka Plots of BSA

Ellagic acid

Figure C17a: Stern-Volmer Plot of Ellagic acid and BSA Stern-Volmer Plot (Ellagic acid-BSA) 3

2.5

F0/F y = 2E+06x + 1.009 2 (A.U.) R² = 0.9959

1.5

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C17b: Double Logarithm Plot of Ellagic acid and BSA Double Logarithm Plot (Ellagic acid-BSA) 0.3 0.2 0.1 y =0 1.0663x + 6.6121 log {(F0-F)/F} R² = 0.9913 -6.6 -6.4 -6.2 -6 -0.1-5.8 (A.U.) -0.2 -0.3 -0.4 -0.5 log [Q] (M)

313 Appendix C: Ka Plots of BSA

Figure C17c: Scatchard’s Plot of Ellagic acid and BSA Scatchard's Plot (Ellagic acid-BSA) 1.2 1 0.8 {(F0-F)/F0}/ y = -627489x + 1.2492 [Q] 0.6 R² = 0.9881 (A.U. x μM-1) 0.4 0.2 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C17d: Benesi-Hildebrand Plot of Ellagic acid and BSA Benesi-Hildebrand Plot (Ellagic acid-BSA) 4 3.5 3 2.5 y = 7E-07x + 0.9124 1/{(F0-F)/F0} 2 R² = 0.9955 (A.U.-1) 1.5 1 0.5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

314 Appendix C: Ka Plots of BSA

Eudesmic acid

Figure C18a: Stern-Volmer Plot of Eudesmic acid and BSA Stern-Volmer Plot (Eudesmic acid-BSA) 1.35 1.3 1.25 y = 229265x + 1.0624 F0/F 1.2 R² = 0.9997 (A.U.) 1.15 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C18b: Double Logarithm Plot of Eudesmic acid and BSA Double Logarithm Plot (Eudesmic acid-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.7505x + 3.9915 -0.4 R² = 0.992 log {(F0-F)/F} (A.U.) -0.6

-0.8

-1 log [Q] (M)

315 Appendix C: Ka Plots of BSA

Figure C18c: Scatchard’s Plot of Eudesmic acid and BSA Scatchard's Plot (Eudesmic acid-BSA) 0.45 0.4 0.35 0.3 {(F0-F)/F0}/ y = -247816x + 0.4532 0.25 [Q] R² = 0.9101 0.2 (A.U. x μM-1) 0.15 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C18d: Benesi-Hildebrand Plot of Eudesmic acid and BSA Benesi-Hildebrand Plot (Eudesmic acid-BSA) 10

8 y = 2E-06x + 3.251 R² = 0.9902 6 1/{(F0-F)/F0} -1 (A.U. ) 4

2

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

316 Appendix C: Ka Plots of BSA

Syringic acid

Figure C19a: Stern-Volmer Plot of Syringic acid and BSA Stern-Volmer Plot (Syringic acid-BSA) 1.18 1.16 1.14 1.12 y = 96324x + 1.0095 0 F /F 1.1 R² = 0.9826 (A.U.) 1.08 1.06 1.04 1.02 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C19b: Double Logarithm Plot of Syringic acid and BSA Double Logarithm Plot (Syringic acid-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.2-5.6 -0.4 -0.6 y = 0.9743x + 4.8753 log {(F0-F)/F} -0.8 R² = 0.9794 (A.U.) -1 -1.2 -1.4 -1.6 -1.8 log [Q] (M)

317 Appendix C: Ka Plots of BSA

Figure C19c: Scatchard’s Plot of Syringic acid and BSA Scatchard's Plot (Syringic acid-BSA) 0.16 0.14 0.12 {(F0-F)/F0}/ 0.1 y = -44590x + 0.1616 [Q] 0.08 R² = 0.9432 (A.U. x μM-1) 0.06 0.04 0.02 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C19d: Benesi-Hildebrand Plot of Syringic acid and BSA Benesi-Hildebrand Plot (Syringic acid-BSA) 30 25 20 y = 6E-06x + 2.9898 1/{(F0-F)/F0} 15 R² = 0.9951 (A.U.-1) 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

318 Appendix C: Ka Plots of BSA

Gallic acid

Figure C20a: Stern-Volmer Plot of Gallic acid and BSA Stern-Volmer Plot (Gallic acid-BSA) 1.45 1.4 1.35 1.3 y = 445625x + 0.9165 F0/F 1.25 R² = 0.9764 (A.U.) 1.2 1.15 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C20b: Double Logarithm Plot of Gallic acid and BSA Double Logarithm Plot (Gallic acid-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4 y = 1.4091x + 8.002 log {(F0-F)/F} -0.6R² = 0.9931 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

319 Appendix C: Ka Plots of BSA

Figure C20c: Scatchard’s Plot of Gallic acid and BSA Scatchard's Plot (Gallic acid-BSA) 0.3 0.25 0.2 {(F0-F)/F0}/ y = -86029x + 0.2965 [Q] 0.15 R² = 0.9806 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C20d: Benesi-Hildebrand Plot of Gallic acid and BSA Benesi-Hildebrand Plot (Gallic acid-BSA) 16 14 12 10 1/{(F0-F)/F0} y = 3E-06x + 1.4504 8 (A.U.-1) R² = 0.999 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

320 Appendix C: Ka Plots of BSA

Protocatechuic acid

Figure C21a: Stern-Volmer Plot of Protocatechuic acid and BSA Stern-Volmer Plot (Protocatechuic acid-BSA) 1.3 1.25 y = 193346x + 1.0312 1.2 R² = 0.9943 F0/F 1.15 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C21b: Double Logarithm Plot of Protocatechuic acid and BSA Double Logarithm Plot (Protocatechuic acid-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.7955x + 4.1257 -0.4 R² = 0.9986 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

321 Appendix C: Ka Plots of BSA

Figure C21c: Scatchard’s Plot of Protocatechuic acid and BSA Scatchard's Plot (Protocatechuic acid-BSA) 0.3 0.25 y = -113610x + 0.2951 0 0 0.2 {(F -F)/F }/ R² = 0.9801 [Q] 0.15 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C21d: Benesi-Hildebrand Plot of Protocatechuic acid and BSA Benesi-Hildebrand Plot (Protocatechuic acid-BSA) 16 14 12 y = 3E-06x + 2.4251 10 R² = 0.9999 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 Axis 1/[Q] (M-1)

322 Appendix C: Ka Plots of BSA m-Hydroxybenzoic acid

Figure C22a: Stern-Volmer Plot of m-Hydroxybenzoic acid and BSA Stern-Volmer Plot (m-Hydroxybenzoic acid-BSA) 1.25

1.2 y = 175129x + 1.0304 R² = 0.9797 1.15 F0/F (A.U.) 1.1

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C22b: Double Logarithm Plot of m-Hydroxybenzoic acid and BSA Double Logarithm Plot (m-Hydroxybenzoic acid-BSA)

0 -6.6 -6.4 -6.2 -6 -0.2-5.8

-0.4y = 0.8807x + 4.6344 R² = 0.9975 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

323 Appendix C: Ka Plots of BSA

Figure C22c: Scatchard’s Plot of m-Hydroxybenzoic acid and BSA Scatchard's Plot (m-Hydroxybenzoic acid-BSA) 0.3 0.25 0.2 y = -80493x + 0.262 {(F0-F)/F0}/ R² = 0.997 [Q] 0.15 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C22d: Benesi-Hildebrand Plot of m-Hydroxybenzoic acid and BSA Benesi-Hildebrand Plot (m-Hydroxybenzoic acid-BSA) 18 16 14 y = 4E-06x + 1.7878 12 R² = 0.9994 1/{(F0-F)/F0} 10 (A.U.-1) 8 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

324 Appendix C: Ka Plots of BSA p-Hydroxybenzoic acid

Figure C23a: Stern-Volmer Plot of p-Hydroxybenzoic acid and BSA Stern-Volmer Plot (p-Hydroxybenzoic acid-BSA) 1.24 1.22 1.2 y = 165956x + 1.0474 1.18 R² = 0.9514 F0/F 1.16 (A.U.) 1.14 1.12 1.1 1.08 1.06 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C23b: Double Logarithm Plot of p-Hydroxybenzoic acid and BSA Double Logarithm Plot (p-Hydroxybenzoic acid-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.7281x + 3.7055 -0.4 R² = 0.9762 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

325 Appendix C: Ka Plots of BSA

Figure C23c: Scatchard’s Plot of p-Hydroxybenzoic acid and BSA Scatchard's Plot (p-Hydroxybenzoic acid-BSA) 0.3 0.25 y = -137051x + 0.3124 0.2 {(F0-F)/F0}/ R² = 0.9907 [Q] 0.15 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C23d: Benesi-Hildebrand Plot of p-Hydroxybenzoic acid and BSA Benesi-Hildebrand Plot (p-Hydroxybenzoic acid-BSA) 16 14 y = 3E-06x + 2.6622 12 R² = 0.9926 10 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

326 Appendix C: Ka Plots of BSA p-Hydrosalicylic acid

Figure C24a: Stern-Volmer Plot of p-Hydrosalicylic acid and BSA Stern-Volmer Plot (p-Hydrosalicylic acid-BSA) 1.2 1.18 1.16 y = 102626x + 1.0251 1.14 R² = 0.9697 F0/F 1.12 (A.U.) 1.1 1.08 1.06 1.04 1.02 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C24b: Double Logarithm Plot of p-Hydrosalicylic acid and BSA Double Logarithm Plot (p-Hydrosalicylic acid-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.2-5.6 -0.4 y = 0.8047x + 3.944 -0.6 R² = 0.9908 log {(F0-F)/F} -0.8 (A.U.) -1 -1.2 -1.4 -1.6 log [Q] (M)

327 Appendix C: Ka Plots of BSA

Figure C24c: Scatchard’s Plot of p-Hydrosalicylic acid and BSA Scatchard's Plot (p-Hydrosalicylic acid-BSA) 0.18 0.16 0.14 0.12 {(F0-F)/F0}/ y = -43669x + 0.1646 0.1 [Q] R² = 0.9569 0.08 (A.U. x μM-1) 0.06 0.04 0.02 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C24d: Benesi-Hildebrand Plot of p-Hydrosalicylic acid and BSA Benesi-Hildebrand Plot (p-Hydrosalicylic acid-BSA) 25

20 y = 6E-06x + 2.9595 R² = 0.9965 1/{(F0-F)/F0} 15 -1 (A.U. ) 10

5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

328 Appendix C: Ka Plots of BSA

Apocynin

Figure C25a: Stern-Volmer Plot of Apocynin and BSA Stern-Volmer Plot (Apocynin-BSA) 1.35 1.3 1.25 y = 158403x + 1.0399 F0/F 1.2 R² = 0.9943 (A.U.) 1.15 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C25b: Double Logarithm Plot of Apocynin and BSA Double Logarithm Plot (Apocynin-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -5.6 -0.2 y = 0.7295x + 3.6837 -0.4 R² = 0.9921 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

329 Appendix C: Ka Plots of BSA

Figure C25c: Scatchard’s Plot of Apocynin and BSA Scatchard's Plot (Apocynin-BSA) 0.3 0.25 0.2 {(F0-F)/F0}/ y = -90116x + 0.2711 [Q] 0.15 R² = 0.8259 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C25d: Benesi-Hildebrand Plot of Apocynin and BSA Benesi-Hildebrand Plot (Apocynin-BSA) 16 14 12 10 y = 3E-06x + 3.0512 1/{(F0-F)/F0} 8 R² = 0.9749 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

330 Appendix C: Ka Plots of BSA

Vanillic acid

Figure C26a: Stern-Volmer Plot of Vanillic acid and BSA Stern-Volmer Plot (Vanillic acid-BSA) 1.16 1.14 1.12 1.1 F0/F y = 92962x + 0.994 1.08 (A.U.) R² = 0.9909 1.06 1.04 1.02 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C26b: Double Logarithm Plot of Vanillic acid and BSA Double Logarithm Plot (Vanillic acid-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -5.6

-0.5 y = 1.2943x + 6.7055 R² = 0.9419 log {(F0-F)/F} -1 (A.U.)

-1.5

-2 log [Q] (M)

331 Appendix C: Ka Plots of BSA

Figure C26c: Scatchard’s Plot of Vanillic acid and BSA Scatchard's Plot (Vanillic acid-BSA) 0.12 0.1 0.08 {(F0-F)/F0}/ y = -15250x + 0.1125 [Q] 0.06 R² = 0.9548 (A.U. x μM-1) 0.04 0.02 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C26d: Benesi-Hildebrand Plot of Vanillic acid and BSA Benesi-Hildebrand Plot (Vanillic acid-BSA) 40 35 30 25 1/{(F0-F)/F0} y = 9E-06x + 1.2737 20 (A.U.-1) R² = 0.9994 15 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

332 Appendix C: Ka Plots of BSA

Chlorogenic acid

Figure C27a: Stern-Volmer Plot of Chlorogenic acid and BSA Stern-Volmer Plot (Chlorogenic acid-BSA) 1.6 1.5

1.4 y = 601029x + 0.9059 F0/F 1.3 R² = 0.9991 (A.U.) 1.2 1.1 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C27b: Double Logarithm Plot of Chlorogenic acid and BSA Double Logarithm Plot (Chlorogenic acid-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4y = 1.5222x + 8.8564 R² = 0.9924 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

333 Appendix C: Ka Plots of BSA

Figure C27c: Scatchard’s Plot of Chlorogenic acid and BSA Scatchard's Plot (Chlorogenic acid-BSA) 0.4 0.35 0.3 {(F0-F)/F0}/ 0.25 y = -133195x + 0.4059 [Q] 0.2 R² = 0.7794 (A.U. x μM-1) 0.15 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C27d: Benesi-Hildebrand Plot of Chlorogenic acid and BSA Benesi-Hildebrand Plot (Chlorogenic acid-BSA) 12 10 y = 3E-06x + 1.0371 8 R² = 0.9823 1/{(F0-F)/F0} 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

334 Appendix C: Ka Plots of BSA

Ferulic acid

Figure C28a: Stern-Volmer Plot of Ferulic acid and BSA Stern-Volmer Plot (Ferulic acid-BSA) 1.35 1.3 1.25 F0/F 1.2 y = 269154x + 0.948 (A.U.) 1.15 R² = 0.9803 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C28b: Double Logarithm Plot of Ferulic acid and BSA Double Logarithm Plot (Ferulic acid-BSA) 0 -6.6 -6.4 -6.2 -6 -0.1-5.8 -0.2 y = 0.9596x + 5.4473 -0.3 R² = 0.9888 log {(F0-F)/F} -0.4 (A.U.) -0.5 -0.6 -0.7 -0.8 -0.9 log [Q] (M)

335 Appendix C: Ka Plots of BSA

Figure C28c: Scatchard’s Plot of Ferulic acid and BSA Scatchard's Plot (Ferulic acid-BSA) 0.6 0.5 0.4 {(F0-F)/F0}/ y = -268496x + 0.5465 [Q] 0.3 R² = 0.8883 (A.U. x μM-1) 0.2 0.1 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C28d: Benesi-Hildebrand Plot of Ferulic acid and BSA Benesi-Hildebrand Plot (Ferulic acid-BSA) 8 7 6 5 y = 1E-06x + 2.2106 1/{(F0-F)/F0} 4 R² = 0.9862 (A.U.-1) 3 2 1 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

336 Appendix C: Ka Plots of BSA

Isoferulic acid

Figure C29a: Stern-Volmer Plot of Isoferulic acid and BSA Stern-Volmer Plot (Isoferulic acid-BSA) 1.3 1.25 1.2 y = 166807x + 1.0049 F0/F 1.15 R² = 0.9989 (A.U.) 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C29b: Double Logarithm Plot of Isoferulic acid and BSA Double Logarithm Plot (Isoferulic acid-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -5.6 -0.2

-0.4 y = 0.9639x + 5.0194 R² = 0.9989 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

337 Appendix C: Ka Plots of BSA

Figure C29c: Scatchard’s Plot of Isoferulic acid and BSA Scatchard's Plot (Isoferulic acid-BSA) 0.2

0.15 {(F0-F)/F0}/ y = -28561x + 0.1772 [Q] 0.1 R² = 0.9561 (A.U. x μM-1) 0.05

0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C29d: Benesi-Hildebrand Plot of Isoferulic acid and BSA Benesi-Hildebrand Plot (Isoferulic acid-BSA) 25

20

15 y = 5E-06x + 1.3526 1/{(F0-F)/F0} -1 R² = 0.999 (A.U. ) 10

5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

338 Appendix C: Ka Plots of BSA

Isoferulic acid-3-o-glucuronide

Figure C30a: Stern-Volmer Plot of Isoferulic acid-3-o-glucuronide and BSA Stern-Volmer Plot (Isoferulic acid-3-o-glucuronide-BSA) 1.25

1.2 y = 158162x + 1.042 R² = 0.9944 1.15 F0/F (A.U.) 1.1

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C30b: Double Logarithm Plot of Isoferulic acid-3-o-glucuronide and BSA Double Logarithm Plot (Isoferulic acid-3-o-glucuronide-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.6892x + 3.4357 -0.4 R² = 0.9996 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

339 Appendix C: Ka Plots of BSA

Figure C30c: Scatchard’s Plot of Isoferulic acid-3-o-glucuronide and BSA Scatchard's Plot (Isoferulic acid-3-o-glucuronide-BSA) 0.25

0.2 y = -73309x + 0.2167 {(F0-F)/F0}/ 0.15 R² = 0.9391 [Q] (A.U. x μM-1) 0.1 0.05

0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C30d: Benesi-Hildebrand Plot of Isoferulic acid-3-o-glucuronide and BSA Benesi-Hildebrand Plot (Isoferulic acid-3-o-glucuronide-BSA) 20

y = 4E-06x + 2.8575 15 R² = 0.998 1/{(F0-F)/F0} 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

340 Appendix C: Ka Plots of BSA

Dihydroferulic acid

Figure C31a: Stern-Volmer Plot of Dihydroferulic acid and BSA Stern-Volmer Plot (Dihydroferulic acid-BSA) 1.18 1.16 1.14 y = 135662x + 1.0093 1.12 R² = 0.9973 F0/F 1.1 (A.U.) 1.08 1.06 1.04 1.02 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C31b: Double Logarithm Plot of Dihydroferulic acid and BSA Double Logarithm Plot (Dihydroferulic acid-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4y = 0.7687x + 3.78 R² = 0.9798 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

341 Appendix C: Ka Plots of BSA

Figure C31c: Scatchard’s Plot of Dihydroferulic acid and BSA Scatchard's Plot (Dihydroferulic acid-BSA) 0.158 0.156 0.154 0.152 {(F0-F)/F0}/ y = -19261x + 0.162 0.15 [Q] R² = 0.8997 0.148 (A.U. x μM-1) 0.146 0.144 0.142 0.14 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C31d: Benesi-Hildebrand Plot of Dihydroferulic acid and BSA Benesi-Hildebrand Plot (Dihydroferulic acid-BSA) 25

20 y = 6E-06x + 0.8492 R² = 0.9996 15 1/{(F0-F)/F0} -1 (A.U. ) 10

5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

342 Appendix C: Ka Plots of BSA

Caffeic acid

Figure C32a: Stern-Volmer Plot of Caffeic acid and BSA Stern-Volmer Plot (Caffeic acid-BSA) 1.3 1.25 1.2 y = 239265x + 0.9977 F0/F 1.15 R² = 0.9974 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C32b: Double Logarithm Plot of Caffeic acid and BSA Double Logarithm Plot (Caffeic acid-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4y = 1.1408x + 6.2621 R² = 0.9965 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

343 Appendix C: Ka Plots of BSA

Figure C32c: Scatchard’s Plot of Caffeic acid and BSA Scatchard's Plot (Caffeic acid-BSA) 0.3 0.25 0.2 {(F0-F)/F0}/ y = -63081x + 0.2594 [Q] 0.15 R² = 0.8591 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C32d: Benesi-Hildebrand Plot of Caffeic acid and BSA Benesi-Hildebrand Plot (Caffeic acid-BSA) 16 14 12 10 y = 4E-06x + 1.6104 1/{(F0-F)/F0} 8 R² = 0.9957 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

344 Appendix C: Ka Plots of BSA

Caffeic acid-3-o-glucuronide

Figure C33a: Stern-Volmer Plot of Caffeic acid-3-o-glucuronide and BSA Stern-Volmer Plot (Caffeic acid-3-o-glucuronide-BSA) 1.45 1.4 1.35 y = 223214x + 1.0543 1.3 R² = 0.9913 F0/F 1.25 (A.U.) 1.2 1.15 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C33b: Double Logarithm Plot of Caffeic acid-3-o-glucuronide and BSA Double Logarithm Plot (Caffeic acid-3-o-glucuronide-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -5.6 -0.2 y = 0.7536x + 3.9749 -0.4 R² = 0.9966 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

345 Appendix C: Ka Plots of BSA

Figure C33c: Scatchard’s Plot of Caffeic acid-3-o-glucuronide and BSA Scatchard's Plot (Caffeic acid-3-o-glucuronide-BSA) 0.4 0.35 0.3 y = -122180x + 0.3596 0 0 0.25 {(F -F)/F }/ R² = 0.9189 [Q] 0.2 (A.U. x μM-1) 0.15 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C33d: Benesi-Hildebrand Plot of Caffeic acid-3-o-glucuronide and BSA Benesi-Hildebrand Plot (Caffeic acid-3-o-glucuronide-BSA) 12

10 y = 2E-06x + 2.1871 8 R² = 0.9978 1/{(F0-F)/F0} 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

346 Appendix C: Ka Plots of BSA

Caffeic acid-4-o-glucuronide

Figure C34a: Stern-Volmer Plot of Caffeic acid-4-o-glucuronide and BSA Stern-Volmer Plot (Caffeic acid-4-o-glucuronide-BSA) 1.25

1.2 y = 166029x + 1.0204 1.15 R² = 0.9999 F0/F (A.U.) 1.1

1.05

1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C34b: Double Logarithm Plot of Caffeic acid-4-o-glucuronide and BSA Double Logarithm Plot (Caffeic acid-4-o-glucuronide-BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y-0.4 = 0.8116x + 4.1371 R² = 0.9995 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

347 Appendix C: Ka Plots of BSA

Figure C34c: Scatchard’s Plot of Caffeic acid-4-o-glucuronide and BSA Scatchard's Plot (Caffeic acid-4-o-glucuronide-BSA) 0.25

0.2 y = -83985x + 0.2385 {(F0-F)/F0}/ 0.15 R² = 0.9155 [Q] (A.U. x μM-1) 0.1

0.05

0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C34d: Benesi-Hildebrand Plot of Caffeic acid-4-o-glucuronide and BSA Benesi-Hildebrand Plot Caffeic acid-4-o-glucuronide-BSA) 18 16 14 y = 4E-06x + 2.8265 12 R² = 0.9961 1/{(F0-F)/F0} 10 (A.U.-1) 8 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

348 Appendix C: Ka Plots of BSA

Dihydrocaffeic acid

Figure C35a: Stern-Volmer Plot of Dihydrocaffeic acid and BSA Stern-Volmer Plot (Dihydrocaffeic acid-BSA) 1.4 1.35 1.3 y = 159454x + 1.1055 1.25 R² = 0.9753 F0/F 1.2 (A.U.) 1.15 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C35b: Double Logarithm Plot of Dihydrocaffeic acid and BSA Double Logarithm Plot (Dihydrocaffeic acid-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.1-5.6 -0.2 y = 0.577x + 2.9088 -0.3 R² = 0.9984 -0.4 log {(F0-F)/F} -0.5 (A.U.) -0.6 -0.7 -0.8 -0.9 -1 log [Q] (M)

349 Appendix C: Ka Plots of BSA

Figure C35c: Scatchard’s Plot of Dihydrocaffeic acid and BSA Scatchard's Plot (Dihydrocaffeic acid-BSA) 0.25

0.2

{(F0-F)/F0}/ 0.15 y = -57746x + 0.2089 [Q] R² = 0.9299 (A.U. x μM-1) 0.1

0.05

0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C35d: Benesi-Hildebrand Plot of Dihydrocaffeic acid and BSA Benesi-Hildebrand Plot (Dihydrocaffeic acid-BSA) 20

15 y = 4E-06x + 2.5883 R² = 0.9987 1/{(F0-F)/F0} 10 (A.U.-1)

5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

350 Appendix C: Ka Plots of BSA

Dihydrocaffeic acid-3-o-glucuronide

Figure C36a: Stern-Volmer Plot of Dihydrocaffeic acid-3-o-glucuronide and BSA Stern-Volmer Plot (Dihydrocaffeic acid-3-o-glucuronide- 1.2 BSA)

1.15 y = 122169x + 1.0362 R² = 0.9466 F0/F 1.1 (A.U.)

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

Figure C36b: Double Logarithm Plot of Dihydrocaffeic acid-3-o-glucuronide and BSA Double Logarithm Plot (Dihydrocaffeic acid-3-o-glucuronide- BSA) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4y = 0.7206x + 3.531 R² = 0.9699 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

351 Appendix C: Ka Plots of BSA

Figure C36c: Scatchard’s Plot of Dihydrocaffeic acid-3-o-glucuronide and BSA Scatchard's Plot (Dihydrocaffeic acid-3-o-glucuronide- 0.25 BSA) 0.2 y = -102221x + 0.2386 {(F0-F)/F0}/ 0.15 R² = 0.9684 [Q] (A.U. x μM-1) 0.1 0.05

0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

Figure C36d: Benesi-Hildebrand Plot of Dihydrocaffeic acid-3-o-glucuronide and BSA Benesi-Hildebrand Plot (Dihydrocaffeic acid-3-o-glucuronide- 20 BSA) y = 4E-06x + 3.2699 15 R² = 0.9886 1/{(F0-F)/F0} 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

352 Appendix C: Ka Plots of BSA

Dihydrocaffeic acid-3-o-sulfate

Figure C37a: Stern-Volmer Plot of Dihydrocaffeic acid-3-o-sulfate and BSA Stern-Volmer Plot (Dihydrocaffeic acid-3-o-sulfate-BSA)

1.25

1.2 y = 117962x + 0.9992 F0/F 1.15 R² = 0.9918 (A.U.) 1.1

1.05

1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C37b: Double Logarithm Plot of Dihydrocaffeic acid-3-o-sulfate and BSA Double Logarithm Plot (Dihydrocaffeic acid-3-o-sulfate-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.2-5.6 -0.4 y = 0.9506x + 4.7711 -0.6 R² = 0.9802 log {(F0-F)/F} -0.8 (A.U.) -1 -1.2 -1.4 -1.6 log [Q] (M)

353 Appendix C: Ka Plots of BSA

Figure C37c: Scatchard’s Plot of Dihydrocaffeic acid-3-o-sulfate and BSA Scatchard's Plot (Dihydrocaffeic acid-3-o-sulfate-BSA) 0.14 0.12 0.1 y = -22157x + 0.128 0 0 {(F -F)/F }/ 0.08 R² = 0.7399 [Q] (A.U. x μM-1) 0.06 0.04 0.02 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C37d: Benesi-Hildebrand Plot of Dihydrocaffeic acid-3-o-sulfate and BSA Benesi-Hildebrand Plot (Dihydrocaffeic acid-3-o-sulfate-BSA) 30

25 y = 7E-06x + 2.7348 20 R² = 0.9925 1/{(F0-F)/F0} 15 (A.U.-1) 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

354 Appendix C: Ka Plots of BSA

Sinapic acid

Figure C38a: Stern-Volmer Plot of Sinapic acid and BSA Stern-Volmer Plot (Sinapic acid-BSA) 1.3 1.25 1.2 y = 162080x + 0.9915 F0/F 1.15 R² = 0.9987 (A.U.) 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C38b: Double Logarithm Plot of Sinapic acid and BSA Double Logarithm Plot (Sinapic acid-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.2-5.6 -0.4 -0.6 y = 1.0939x + 5.7454 log {(F0-F)/F} R² = 0.9982 -0.8 (A.U.) -1 -1.2 -1.4 -1.6 log [Q] (M)

355 Appendix C: Ka Plots of BSA

Figure C38c: Scatchard’s Plot of Sinapic acid and BSA Scatchard's Plot (Sinapic acid-BSA) 0.14 0.138 0.136 0.134 y = -8778.4x + 0.1388 {(F0-F)/F0}/ 0.132 R² = 0.8317 [Q] 0.13 (A.U. x μM-1) 0.128 0.126 0.124 0.122 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C38d: Benesi-Hildebrand Plot of Sinapic acid and BSA Benesi-Hildebrand Plot (Sinapic acid-BSA) 30 25 20 y = 7E-06x + 0.7126 1/{(F0-F)/F0} 15 R² = 0.9994 (A.U.-1) 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

356 Appendix C: Ka Plots of BSA o-Coumaric acid

Figure C39a: Stern-Volmer Plot of o-Coumaric acid and BSA Stern-Volmer Plot (o-Coumaric acid-BSA) 1.25

1.2

1.15 F0/F y = 152101x + 0.9789 R² = 0.9895 (A.U.) 1.1

1.05

1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C39b: Double Logarithm Plot of o-Coumaric acid and BSA Double Logarithm Plot (o-Coumaric acid-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.2-5.6 -0.4 y = 1.347x + 7.1811 -0.6 R² = 0.9879 log {(F0-F)/F} -0.8 (A.U.) -1 -1.2 -1.4 -1.6 -1.8 log [Q] (M)

357 Appendix C: Ka Plots of BSA

Figure C39c: Scatchard’s Plot of o-Coumaric acid and BSA Scatchard's Plot (o-Coumaric acid-BSA) 0.14 0.12 0.1 0 0 {(F -F)/F }/ 0.08 y = -34954x + 0.1391 [Q] R² = 0.8873 (A.U. x μM-1) 0.06 0.04 0.02 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C39d: Benesi-Hildebrand Plot of o-Coumaric acid and BSA Benesi-Hildebrand Plot (o-Coumaric acid-BSA) 35 30 y = 7E-06x + 2.3654 25 R² = 0.9909 1/{(F0-F)/F0} 20 (A.U.-1) 15 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

358 Appendix C: Ka Plots of BSA p-Coumaric acid

Figure C40a: Stern-Volmer Plot of p-Coumaric acid and BSA Stern-Volmer Plot (p-Coumaric acid-BSA) 1.35 1.3 1.25 y = 135714x + 1.0845 F0/F 1.2 R² = 0.9832 (A.U.) 1.15 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q] (M)

Figure C40b: Double Logarithm Plot of p-Coumaric acid and BSA Double Logarithm Plot (p-Coumaric acid-BSA) 0 -6.8 -6.6 -6.4 -6.2 -6 -5.8 -0.1-5.6 -0.2 -0.3 y = 0.5393x + 2.5916 R² = 0.986 -0.4 log {(F0-F)/F} -0.5 (A.U.) -0.6 -0.7 -0.8 -0.9 -1 log [Q] (M)

359 Appendix C: Ka Plots of BSA

Figure C40c: Scatchard’s Plot of p-Coumaric acid and BSA Scatchard's Plot (p-Coumaric acid-BSA) 0.4 0.35 0.3 {(F0-F)/F0}/ 0.25 y = -158022x + 0.3687 [Q] 0.2 R² = 0.8379 (A.U. x μM-1) 0.15 0.1 0.05 0 0.00E+00 5.00E-07 1.00E-06 1.50E-06 2.00E-06 [Q} (M)

Figure C40d: Benesi-Hildebrand Plot of p-Coumaric acid and BSA Benesi-Hildebrand Plot (p-Coumaric acid-BSA) 12 10 y = 2E-06x + 3.6143 8 R² = 0.9702 1/{(F0-F)/F0} 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

360 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Appendix D: All Polyphenols with LDL-VLDL - Spectra and Method Plots

Polyphenol Observed Spectral Page # Shifts of λmax Pterostilbene(1,a) Red 362 Resveratrol(1,a) Red 364 Quercetin(2,b) None 366 Quercetin-3-glucuronide(2,b) None 368 Quercetin-3-glucoside(2,b) Blue 370 Biochanin A(2,c) None 372 Puerarin(2,c) None 374 Chrysin(2,d) None 376 Baicalein(2,d) None 378 Baicalin(2,d) None 380 Flavone(2,d) None 382 Pelargonidin Chloride(2,e) None 384 Dopac(2,f) Blue 386 m-Hydroxyphenylacteic acid(2,f) None 388 p-Hydroxyphenylacteic acid(2,f) Red 390 Homogentisic acid(2,f) Blue 392 Ellagic acid(2,g) None 394 Eudesmic acid(2,g) None 396 Syringic acid(2,g) None 398 Gallic acid(2,g) None 400 Protocatechuic acid(2,g) Blue 402 m-Hydroxybenzoic acid(2,g) None 404 p-Hydroxybenzoic acid(2,g) Blue 406 p-Hydroxysalicylic acid(2,g) None 408 Apocynin(2,g) Blue 410 Vanillic acid(2,g) None 412 Chlorogenic acid(2,h) None 414 Ferulic acid(2,h) None 416 Isoferulic acid(2,h) None 418 Isoferulic acid-3-o-glucuronide(2,h) None 420 Dihydroferulic acid(2,h) Blue 422 Caffeic acid(2,h) None 424 Caffeic acid-3-o-glucuronide(2,h) None 426 Caffeic acid-4-o-glucuronide(2,h) None 428 Dihydrocaffeic acid(2,h) None 430 Dihydrocaffeic acid-3-o-sulfate(2,h) None 432 Dihydrocaffeic acid-3-o-glucuronide(2,h) Blue 434 Sinapic acid(2,h) None 436 o-Coumaric acid(2,h) Blue 438 p-Coumaric acid(2,h) None 440 Key: CLASS - Stilbenoid = 1, Flavonoid = 2, Phenolic acid = 3. SUBCLASS – Stilbene = a, Flavonol = b, Isoflavone = c, Flavone = d, Anthocyanidin = e, Phenylacetic acid derivative = f, Benzoic acid derivative = g, Cinnamic acid derivative = h.

361 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Pterostilbene

Figure D1a: Fluorescence Quenching Spectrum of Pterostilbene and LDL-VLDL

Figure D1b: Stern-Volmer Plot of Pterostilbene and LDL-VLDL Stern-Volmer Plot (Pterostilbene-LDL/VLDL) 1.6 1.5 1.4 F0/F 1.3 y = 393676x + 1.0501 (A.U.) R² = 0.9984 1.2 1.1 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

362 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D1c: Double Logarithm Plot of Pterostilbene and LDL-VLDL Double Logarithm Plot (Pterostilbene-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.8199x + 4.5659 R² = 0.9999 -0.4 log {(F0-F)/F} (A.U.) -0.6

-0.8

-1 log [Q] (M)

Figure D1d: Scatchard’s Plot of Pterostilbene and LDL-VLDL Scatchard's Plot (Pterostilbene-LDL/VLDL) 0.6 0.5 0.4 {(F0-F)/F0}/ y = -266555x + 0.566 0.3 [Q] R² = 0.9266 (A.U. x μM-1)0.2 0.1 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D1e: Benesi-Hildebrand Plot of Pterostilbene and LDL-VLDL Benesi-Hildebrand Plot (Pterostilbene-LDL/VLDL) 8

6 y = 1E-06x + 1.9169 1/{(F0-F)/F0} R² = 0.9954 4 (A.U.-1) 2

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

363 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Resveratrol

Figure D2a: Fluorescence Quenching Spectrum of Resveratrol and LDL-VLDL

Figure D2b: Stern-Volmer Plot of Resveratrol and LDL-VLDL Stern-Volmer Plot (Resveratrol-LDL/VLDL) 1.35 1.3 1.25 y = 249154x + 1.0273 F0/F 1.2 R² = 0.999 (A.U.) 1.15 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

364 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D2c: Double Logarithm Plot of Resveratrol and LDL-VLDL Double Logarithm Plot (Resveratrol-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.8319x + 4.4313 -0.4 R² = 0.9993 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D2d: Scatchard’s Plot of Resveratrol and LDL-VLDL Scatchard's Plot

0.4 (Resveratrol-LDL/VLDL)

0.3 0 0 {(F -F)/F }/ y = -125629x + 0.3392 0.2 [Q] R² = 0.9503 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D2e: Benesi-Hildebrand Plot of Resveratrol and LDL-VLDL Benesi-Hildebrand Plot

15 (Resveratrol-LDL/VLDL)

y = 3E-06x + 2.062 10 1/{(F0-F)/F0} R² = 0.9988 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

365 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Quercetin

Figure D3a: Fluorescence Quenching Spectrum of Quercetin and LDL-VLDL

Figure D3b: Stern-Volmer Plot of Quercetin and LDL-VLDL Stern-Volmer Plot (Quercetin-LDL/VLDL) 1.35 1.3 1.25

0 1.2 F /F y = 261213x + 1.0392 (A.U.) 1.15 R² = 0.9957 1.1 1.05 1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

366 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D3c: Double Logarithm Plot of Quercetin and LDL-VLDL Double Logarithm Plot (Quercetin-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4y = 0.7974x + 4.2615 R² = 0.9993 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D3d: Scatchard’s Plot of Quercetin and LDL-VLDL Scatchard's Plot

0.4 (Quercetin-LDL/VLDL)

0.3 {(F0-F)/F0}/ y = -157066x + 0.3849 [Q] 0.2 R² = 0.9576 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D3e: Benesi-Hildebrand Plot of Quercetin and LDL-VLDL Benesi-Hildebrand Plot (Quercetin-LDL/VLDL) 12 10 8 y = 2E-06x + 2.1249 1/{(F0-F)/F0} R² = 0.9986 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

367 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Quercetin-3-glucuronide

Figure D4a: Fluorescence Quenching Spectrum of Quercetin-3-glucuronide and LDL- VLDL

Figure D4b: Stern-Volmer Plot of Quercetin-3-glucuronide and LDL-VLDL Stern-Volmer Plot (Quercetin-3-glucuronide-LDL/VLDL) 1.35 1.3 1.25 y = 217353x + 1.0606 F0/F 1.2 R² = 0.9971 (A.U.) 1.15 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

368 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D4c: Double Logarithm Plot of Quercetin-3-glucuronide and LDL-VLDL Double Logarithm Plot (Quercetin-3-glucuronide-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.6701x + 3.4627 -0.4 R² = 0.9999 log {(F0-F)/F} (A.U.) -0.6

-0.8

-1 log [Q] (M)

Figure D4d: Scatchard’s Plot of Quercetin-3-glucuronide and LDL-VLDL Scatchard's Plot (Quercetin-3-glucuronide-LDL/VLDL) 0.5 0.4 {(F0-F)/F0}/ 0.3 y = -208103x + 0.4198 [Q] R² = 0.9306 (A.U. x μM-1) 0.2 0.1 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D4e: Benesi-Hildebrand Plot of Quercetin-3-glucuronide and LDL-VLDL Benesi-Hildebrand Plot (Quercetin-3-glucuronide-LDL/VLDL) 12 10 y = 2E-06x + 2.838 8 1/{(F0-F)/F0} R² = 0.9963 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

369 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Quercetin-3-glucoside

Figure D5a: Fluorescence Quenching Spectrum of Quercetin-3-glucoside and LDL- VLDL

Figure D5b: Stern-Volmer Plot of Quercetin-3-glucoside and LDL-VLDL Stern-Volmer Plot (Quercetin-3-glucoside-LDL/VLDL) 1.3 1.25 1.2 y = 185184x + 1.0376 F0/F 1.15 R² = 0.9972 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

370 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D5c: Double Logarithm Plot of Quercetin-3-glucoside and LDL-VLDL Double Logarithm Plot (Quercetin-3-glucoside-LDL/VLDL)

0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4y = 0.7368x + 3.7677 R² = 0.9994 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D5d: Scatchard’s Plot of Quercetin-3-glucoside and LDL-VLDL Scatchard's Plot (Quercetin-3-glucoside-LDL/VLDL) 0.4

0.3 {(F0-F)/F0}/ y = -135912x + 0.3147 [Q] 0.2 R² = 0.9446 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D5e: Benesi-Hildebrand Plot of Quercetin-3-glucoside and LDL-VLDL Benesi-Hildebrand Plot (Quercetin-3-glucoside-LDL/VLDL) 15

10 y = 3E-06x + 2.894 1/{(F0-F)/F0} R² = 0.9982 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

371 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Biochanin A

Figure D6a: Fluorescence Quenching Spectrum of Biochanin A and LDL-VLDL

Figure D6b: Stern-Volmer Plot of Biochanin A and LDL-VLDL Stern-Volmer Plot (Biochanin A-LDL/VLDL) 1.35 1.3 1.25 F0/F 1.2 y = 262132x + 1.0125 (A.U.) 1.15 R² = 0.9982 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

372 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D6c: Double Logarithm Plot of Biochanin A and LDL-VLDL Double Logarithm Plot (Biochanin A-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.9399x + 5.0801 -0.4 R² = 0.9992 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D6d: Scatchard’s Plot of Biochanin A and LDL-VLDL Scatchard's Plot (Biochanin A-LDL/VLDL) 0.3 0.25 {(F0-F)/F0}/ 0.2 y = -79379x + 0.2947 [Q] 0.15 R² = 0.9989 -1 (A.U. x μM ) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D6e: Benesi-Hildebrand Plot of Biochanin A and LDL-VLDL Benesi-Hildebrand Plot (Biochanin A-LDL/VLDL) 15

y = 3E-06x + 1.3206 10 1/{(F0-F)/F0} R² = 0.9998 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

373 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Puerarin

Figure D7a: Fluorescence Quenching Spectrum of Puerarin and LDL-VLDL

Figure D7b: Stern-Volmer Plot of Puerarin and LDL-VLDL Stern-Volmer Plot (Puerarin-LDL/VLDL) 1.3 1.25 1.2 F0/F y = 188860x + 1.0494 1.15 (A.U.) R² = 0.9942 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

374 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D7c: Double Logarithm Plot of Puerarin and LDL-VLDL Double Logarithm Plot (Puerarin-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.693x + 3.5342 -0.4 R² = 0.9993 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D7d: Scatchard’s Plot of Puerarin and LDL-VLDL Scatchard's Plot (Puerarin-LDL/VLDL) 0.4

0.3 0 0 {(F -F)/F }/ y = -166735x + 0.355 [Q] 0.2 R² = 0.95 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D7e: Benesi-Hildebrand Plot of Puerarin and LDL-VLDL Benesi-Hildebrand Plot (Puerarin-LDL/VLDL) 14 12 10 y = 2E-06x + 2.9731 R² = 0.9988 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

375 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Chrysin

Figure D8a: Fluorescence Quenching Spectrum of Chrysin and LDL-VLDL

Figure D8b: Stern-Volmer Plot of Chrysin and LDL-VLDL Stern-Volmer Plot (Chrysin-LDL/VLDL) 1.5

1.4

1.3 F0/F y = 384301x + 1.0238 R² = 0.9997 (A.U.) 1.2

1.1

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

376 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D8c: Double Logarithm Plot of Chrysin and LDL-VLDL Double Logarithm Plot (Chrysin-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.9006x + 5.0135 -0.4 R² = 1 log {(F0-F)/F} (A.U.) -0.6

-0.8

-1 log [Q] (M)

Figure D8d: Scatchard’s Plot of Chrysin and LDL-VLDL Scatchard's Plot

0.5 (Chrysin-LDL/VLDL) 0.4

0 0 {(F -F)/F }/ 0.3 y = -159338x + 0.4467 [Q] R² = 0.9721 (A.U. x μM-1) 0.2 0.1 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D8e: Benesi-Hildebrand Plot of Chrysin and LDL-VLDL Benesi-Hildebrand Plot (Chrysin-LDL/VLDL) 10

8 y = 2E-06x + 1.4411 R² = 0.9997 1/{(F0-F)/F0} 6 -1 (A.U. ) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

377 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Baicalein

Figure D9a: Fluorescence Quenching Spectrum of Baicalein and LDL-VLDL

Figure D9b: Stern-Volmer Plot of Baicalein and LDL-VLDL Stern-Volmer Plot (Baicalein-LDL/VLDL) 1.35 1.3 1.25 F0/F 1.2 y = 268051x + 1.0382 R² = 0.996 (A.U.) 1.15 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

378 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D9c: Double Logarithm Plot of Baicalein and LDL-VLDL Double Logarithm Plot (Baicalein-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.8114x + 4.3553 -0.4 R² = 0.9995 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D9d: Scatchard’s Plot of Baicalein and LDL-VLDL Scatchard's Plot

0.4 (Baicalein-LDL/VLDL)

0.3 {(F0-F)/F0}/ y = -153842x + 0.3857 [Q] 0.2 R² = 0.9743 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D9e: Benesi-Hildebrand Plot of Baicalein and LDL-VLDL Benesi-Hildebrand Plot (Baicalein-LDL/VLDL) 12 10 y = 2E-06x + 1.9947 8 1/{(F0-F)/F0} R² = 0.9999 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

379 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Baicalin

Figure D10a: Fluorescence Quenching Spectrum of Baicalin and LDL-VLDL

Figure D10b: Stern-Volmer Plot of Baicalin and LDL-VLDL Stern-Volmer Plot (Baicalin-LDL/VLDL) 1.3 1.25 1.2 F0/F y = 214412x + 1.0383 1.15 (A.U.) R² = 0.9834 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

380 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D10c: Double Logarithm Plot of Baicalin and LDL-VLDL Double Logarithm Plot (Baicalin-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

y -0.4= 0.7929x + 4.1637 log {(F0-F)/F} R² = 0.9952 -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D10d: Scatchard’s Plot of Baicalin and LDL-VLDL Scatchard's Plot

0.4 (Baicalin-LDL/VLDL)

0.3 {(F0-F)/F0}/ [Q] 0.2 y = -132136x + 0.3326 (A.U. x μM-1) R² = 0.9912 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D10e: Benesi-Hildebrand Plot of Baicalin and LDL-VLDL Benesi-Hildebrand Plot (Baicalin-LDL/VLDL) 14 12 10 y = 3E-06x + 2.2266 R² = 0.9995 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

381 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Flavone

Figure D11a: Fluorescence Quenching Spectrum of Flavone and LDL-VLDL

Figure D11b: Stern-Volmer Plot of Flavone and LDL-VLDL Stern-Volmer Plot (Flavone-LDL/VLDL) 1.25

1.2

1.15 F0/F y = 166581x + 1.0452 R² = 0.9979 (A.U.) 1.1

1.05

1 0.00E+00 5.00E-07 1.00E-06 1.50E-06 [Q] (M)

382 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D11c: Double Logarithm Plot of Flavone and LDL-VLDL Double Logarithm Plot (Flavone-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

y-0.4 = 0.6731x + 3.362 log {(F0-F)/F} R² = 0.9997 -0.6 (A.U.) -0.8

-1

-1.2 log [Q} (M)

Figure D11d: Scatchard’s Plot of Flavone and LDL-VLDL Scatchard's Plot (Flavone-LDL/VLDL) 0.4

0.3 {(F0-F)/F0}/ y = -154882x + 0.3251 [Q] 0.2 R² = 0.9257 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D11e: Benesi-Hildebrand Plot of Flavone and LDL-VLDL Benesi-Hildebrand Plot

14 (Flavone-LDL/VLDL) 12 10 y = 2E-06x + 3.4121 1/{(F0-F)/F0} 8 R² = 0.9955 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

383 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Pelargonidin Chloride

Figure D12a: Fluorescence Quenching Spectrum of Pelargonidin Chloride and LDL- VLDL

Figure D12b: Stern-Volmer Plot of Pelargonidin Chloride and LDL-VLDL Stern-Volmer Plot (Pelargonidin Chloride-LDL/VLDL) 1.3 1.25 1.2 y = 173676x + 1.0893 F0/F 1.15 R² = 0.9939 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

384 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D12c: Double Logarithm Plot of Pelargonidin Chloride and LDL-VLDL Double Logarithm Plot (Pelargonidin Chloride-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.5245x + 2.5641 -0.4R² = 0.9988 log {(F0-F)/F} (A.U.) -0.6

-0.8

-1 log [Q] (M)

Figure D12d: Scatchard’s Plot of Pelargonidin Chloride and LDL-VLDL Scatchard's Plot (Pelargonidin Chloride-LDL/VLDL) 0.5 0.4 y = -277713x + 0.4768 0 0 {(F -F)/F }/ 0.3 R² = 0.9048 [Q] (A.U. x μM-1) 0.2 0.1 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D12e: Benesi-Hildebrand Plot of Pelargonidin Chloride and LDL-VLDL Benesi-Hildebrand Plot (Pelargonidin Chloride-LDL/VLDL) 10

8 y = 1E-06x + 3.5577 R² = 0.9876 1/{(F0-F)/F0} 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

385 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Dopac

Figure D13a: Fluorescence Quenching Spectrum of Dopac and LDL-VLDL

Figure D13b: Stern-Volmer Plot of Dopac and LDL-VLDL Stern-Volmer Plot (Dopac-LDL/VLDL) 1.16 1.14 1.12 1.1 y = 110515x + 1.0228 F0/F 1.08 R² = 0.9994 (A.U.) 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

386 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D13c: Double Logarithm Plot of Dopac and LDL-VLDL Double Logarithm Plot (Dopac-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4 y = 0.6877x + 3.2448 log {(F0-F)/F} -0.6 R² = 0.9926 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

Figure D13d: Scatchard’s Plot of Dopac and LDL-VLDL Scatchard's Plot

0.2 (Dopac-LDL/VLDL)

0.15 {(F0-F)/F0}/ y = -90684x + 0.2047 [Q] 0.1 R² = 0.9828 (A.U. x μM-1) 0.05

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D13e: Benesi-Hildebrand Plot of Dopac and LDL-VLDL Benesi-Hildebrand Plot (Dopac-LDL/VLDL) 25 20 y = 4E-06x + 4.4151 1/{(F0-F)/F0} 15 -1 R² = 0.9991 (A.U. ) 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

387 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts m-Hydroxyphenylacetic acid

Figure D14a: Fluorescence Quenching Spectrum of m-Hydroxyphenylacetic acid and LDL-VLDL

Figure D14b: Stern-Volmer Plot of m-Hydroxyphenylacetic acid and LDL-VLDL Stern-Volmer Plot (m-Hydroxyphenylacetic acid- LDL/VLDL) 1.16 1.14 1.12 y = 119044x + 1.0053 1.1 R² = 0.9538 F0/F 1.08 (A.U.) 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

388 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D14c: Double Logarithm Plot of m-Hydroxyphenylacetic acid and LDL-VLDL Double Logarithm Plot (m-Hydroxyphenylacetic acid-

LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 y = 0.7192x + 3.3698 -0.5R² = 0.9614 log {(F0-F)/F} (A.U.) -1

-1.5 log [Q] (M)

Figure D14d: Scatchard’s Plot of m-Hydroxyphenylacetic acid and LDL-VLDL Scatchard's Plot (m-Hydroxyphenylacetic acid- 0.18 LDL/VLDL) 0.15 y = -73452x + 0.1726 {(F0-F)/F0}/ 0.12 R² = 0.8259 [Q] 0.09 (A.U. x μM-1) 0.06 0.03 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D14e: Benesi-Hildebrand Plot of m-Hydroxyphenylacetic acid and LDL-VLDL Benesi-Hildebrand Plot (m-Hydroxyphenylacetic acid- 25 LDL/VLDL) 20 y = 5E-06x + 5.6871 1/{(F0-F)/F0} 15 R² = 0.9614 (A.U.-1) 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

389 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts p-Hydroxyphenylacetic acid

Figure D15a: Fluorescence Quenching Spectrum of p-Hydroxyphenylacetic acid and LDL-VLDL

Figure D15b: Stern-Volmer Plot of p-Hydroxyphenylacetic acid and LDL-VLDL Stern-Volmer Plot (p-Hydroxyphenylacetic acid-

1.14 LDL/VLDL) 1.12 y = 74559x + 1.037 1.1 R² = 0.9843 F0/F 1.08 (A.U.) 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

390 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D15c: Double Logarithm Plot of p-Hydroxyphenylacetic acid and LDL-VLDL Double Logarithm Plot (p-Hydroxyphenylacetic acid-

LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2y = 0.5265x + 2.1925 -0.4 R² = 0.9907 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

Figure D15d: Scatchard’s Plot of p-Hydroxyphenylacetic acid and LDL-VLDL (Scatchard's Plot) (p-Hydroxyphenylacetic acid- 0.25 LDL/VLDL) 0.2 y = -138618x + 0.2257 0 0 {(F -F)/F }/ 0.15 R² = 0.9203 [Q] (A.U. x μM-1) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D15e: Benesi-Hildebrand Plot of p-Hydroxyphenylacetic acid and LDL-VLDL Benesi-Hildebrand Plot (p-Hydroxyphenylacetic acid- 20 LDL/VLDL) 15 y = 3E-06x + 8.4424 1/{(F0-F)/F0} 10 R² = 0.9963 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

391 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Homogentisic acid

Figure D16a: Fluorescence Quenching Spectrum of Homogentisic acid and LDL- VLDL

Figure D16b: Stern-Volmer Plot of Homogentisic acid and LDL-VLDL Stern-Volmer Plot (Homogentisic acid-LDL/VLDL) 1.25

1.2

1.15 F0/F y = 97794x + 1.0955 R² = 0.965 (A.U.) 1.1

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

392 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D16c: Double Logarithm Plot of Homogentisic acid and LDL-VLDL Double Logarithm Plot (Homogentisic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4y = 0.4512x + 1.9413 R² = 0.9964 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 log [Q] (M)

Figure D16d: Scatchard’s Plot of Homogentisic acid and LDL-VLDL Scatchard's Plot (Homogentisic acid-LDL/VLDL) 0.4

0.3 {(F0-F)/F0}/ y = -216897x + 0.3566 [Q] 0.2 R² = 0.8894 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D16e: Benesi-Hildebrand Plot of Homogentisic acid and LDL-VLDL Benesi-Hildebrand Plot (Homogentisic acid-LDL/VLDL) 14 12 y = 2E-06x + 5.3016 10 R² = 0.9771 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

393 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Ellagic acid

Figure D17a: Fluorescence Quenching Spectrum of Ellagic acid and LDL-VLDL

Figure D17b: Stern-Volmer Plot of Ellagic acid and LDL-VLDL Stern-Volmer Plot (Ellagic acid-LDL/VLDL) 1.35 1.3 1.25 y = 271287x + 1.0291 F0/F 1.2 R² = 0.9914 (A.U.) 1.15 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

394 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D17c: Double Logarithm Plot of Ellagic acid and LDL-VLDL Double Logarithm Plot (Ellagic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.786x + 4.1846 -0.4 R² = 0.9792 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D17d: Scatchard’s Plot of Ellagic acid and LDL-VLDL Scatchard's Plot

0.4 (Ellagic acid-LDL/VLDL)

0.3 {(F0-F)/F0}/ y = -160195x + 0.3843 [Q] 0.2 R² = 0.7996 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D17e: Benesi-Hildebrand Plot of Ellagic acid and LDL-VLDL Benesi-Hildebrand Plot (Ellagic acid-LDL/VLDL) 12 10 y = 2E-06x + 2.4982 8 R² = 0.971 1/{(F0-F)/F0} 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

395 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Eudesmic acid

Figure D18a: Fluorescence Quenching Spectrum of Eudesmic acid and LDL-VLDL

Figure D18b: Stern-Volmer Plot of Eudesmic acid and LDL-VLDL Stern-Volmer Plot (Eudesmic acid-LDL/VLDL) 1.3 1.25 1.2 y = 198824x + 1.0244 F0/F 1.15 R² = 0.999 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

396 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D18c: Double Logarithm Plot of Eudesmic acid and LDL-VLDL Double Logarithm Plot (Eudesmic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4y = 0.8419x + 4.4177 R² = 0.9875 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D18d: Scatchard’s Plot of Eudesmic acid and LDL-VLDL Scatchard's Plot

0.3 (Eudesmic acid-LDL/VLDL) 0.25 0.2 y = -146026x + 0.3009 {(F0-F)/F0}/ R² = 0.9633 [Q] 0.15 -1 (A.U. x μM ) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D18e: Benesi-Hildebrand Plot of Eudesmic acid and LDL-VLDL Benesi-Hildebrand Plot (Eudesmic acid-LDL/VLDL) 15

10 y = 3E-06x + 3.6866 1/{(F0-F)/F0} R² = 0.9999 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

397 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Syringic acid

Figure D19a: Fluorescence Quenching Spectrum of Syringic acid and LDL-VLDL

Figure D19b: Stern-Volmer Plot of Syringic acid and LDL-VLDL Stern-Volmer Plot (Syringic acid-LDL/VLDL) 1.16 1.14 1.12 1.1 y = 93971x + 1.0474 F0/F 1.08 R² = 0.9837 (A.U.) 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

398 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D19c: Double Logarithm Plot of Syringic acid and LDL-VLDL Double Logarithm Plot (Syringic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4y = 0.5425x + 2.4046 R² = 0.9988 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

Figure D19d: Scatchard’s Plot of Syringic acid and LDL-VLDL Scatchard's Plot

0.25 (Syringic acid-LDL/VLDL) 0.2 {(F0-F)/F0}/ 0.15 y = -145103x + 0.2648 [Q] R² = 0.9355 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D19e: Benesi-Hildebrand Plot of Syringic acid and LDL-VLDL Benesi-Hildebrand Plot (Syringic acid-LDL/VLDL) 20

15 y = 3E-06x + 5.4934 1/{(F0-F)/F0} R² = 0.9977 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

399 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Gallic acid

Figure D20a: Fluorescence Quenching Spectrum of Gallic acid and LDL-VLDL

Figure D20b: Stern-Volmer Plot of Gallic acid and LDL-VLDL Stern-Volmer Plot (Gallic acid-LDL/VLDL) 1.25

1.2

1.15 F0/F y = 176654x + 1.0094 R² = 0.9989 (A.U.) 1.1

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

400 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D20c: Double Logarithm Plot of Gallic acid and LDL-VLDL Double Logarithm Plot (Gallic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y-0.4 = 0.8837x + 4.5662 R² = 0.9968 log {(F0-F)/F} -0.6 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

Figure D20d: Scatchard’s Plot of Gallic acid and LDL-VLDL Scatchard's Plot

0.25 (Gallic acid-LDL/VLDL) 0.2 {(F0-F)/F0}/ 0.15 y = -59882x + 0.2145 [Q] R² = 0.8633 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D20e: Benesi-Hildebrand Plot of Gallic acid and LDL-VLDL Benesi-Hildebrand Plot (Gallic acid-LDL/VLDL) 20

15 y = 4E-06x + 2.3492 R² = 0.9951 1/{(F0-F)/F0} 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

401 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Protocatechuic acid

Figure D21a: Fluorescence Quenching Spectrum of Protocatechuic acid and LDL- VLDL

Figure D21b: Stern-Volmer Plot of Protocatechuic acid and LDL-VLDL Stern-Volmer Plot (Protocatechuic acid-LDL/VLDL) 1.25

1.2 y = 162390x + 1.0454 R² = 0.9887 F0/F 1.15 (A.U.) 1.1

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

402 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D21c: Double Logarithm Plot of Protocatechuic acid and LDL-VLDL Double Logarithm Plot (Protocatechuic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.6843x + 3.4239 -0.4 R² = 0.9986 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D21d: Scatchard’s Plot of Protocatechuic acid and LDL-VLDL Scatchard's Plot (Protocatechuic acid-LDL/VLDL) 0.4

0.3 {(F0-F)/F0}/ y = -148129x + 0.3167 [Q] 0.2 R² = 0.9544 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D21e: Benesi-Hildebrand Plot of Protocatechuic acid and LDL-VLDL Benesi-Hildebrand Plot (Protocatechuic acid-LDL/VLDL) 14 12 y = 3E-06x + 3.2994 10 R² = 0.9986 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

403 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts m-Hydroxybenzoic acid

Figure D22a: Fluorescence Quenching Spectrum of m-Hydroxybenzoic acid and LDL- VLDL

Figure D22b: Stern-Volmer Plot of m-Hydroxybenzoic acid and LDL-VLDL Stern-Volmer Plot (m-Hydroxybenzoic acid-LDL/VLDL) 1.25

1.2

1.15 y = 155147x + 1.0404 F0/F R² = 0.9973 (A.U.) 1.1

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

404 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D22c: Double Logarithm Plot of m-Hydroxybenzoic acid and LDL-VLDL Double Logarithm Plot (m-Hydroxybenzoic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.6849x + 3.3987 -0.4 R² = 0.9999 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D22d: Scatchard’s Plot of m-Hydroxybenzoic acid and LDL-VLDL Scatchard's Plot (m-Hydroxybenzoic acid-LDL/VLDL) 0.3 0.25 y = -137860x + 0.2975 0 0 0.2 {(F -F)/F }/ R² = 0.9323 [Q] 0.15 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D22e: Benesi-Hildebrand Plot of m-Hydroxybenzoic acid and LDL-VLDL Benesi-Hildebrand Plot (m-Hydroxybenzoic acid-LDL/VLDL) 15

y = 3E-06x + 3.5222 10 1/{(F0-F)/F0} R² = 0.9966 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

405 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts p-Hydroxybenzoic

Figure D23a: Fluorescence Quenching Spectrum of p-Hydroxybenzoic acid and LDL- VLDL

Figure D23b: Stern-Volmer Plot of p-Hydroxybenzoic acid and LDL-VLDL Stern-Volmer Plot (p-Hydroxybenzoic acid-LDL/VLDL) 1.2

1.15

F0/F y = 136397x + 1.0379 1.1 (A.U.) R² = 0.9955

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

406 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D23c: Double Logarithm Plot of p-Hydroxybenzoic acid and LDL-VLDL Double Logarithm Plot (p-Hydroxybenzoic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.6756x + 3.2933 -0.4R² = 0.9999 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D23d: Scatchard’s Plot of p-Hydroxybenzoic acid and LDL-VLDL Scatchard's Plot (p-Hydroxybenzoic acid-LDL/VLDL) 0.3 0.25 y = -125750x + 0.2708 {(F0-F)/F0}/ 0.2 R² = 0.9395 [Q] 0.15 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D23e: Benesi-Hildebrand Plot of p-Hydroxybenzoic acid and LDL-VLDL Benesi-Hildebrand Plot (p-Hydroxybenzoic acid-LDL/VLDL) 20

15 y = 3E-06x + 3.8603 1/{(F0-F)/F0} R² = 0.9976 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

407 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts p-Hydrosalicylic acid

Figure D24a: Fluorescence Quenching Spectrum of p-Hydrosalicylic acid and LDL- VLDL

Figure D24b: Stern-Volmer Plot of p-Hydrosalicylic acid and LDL-VLDL Stern-Volmer Plot (p-Hydrosalicylic acid-LDL-VLDL) 1.25

1.2

1.15 F0/F y = 132390x + 1.0512 (A.U.) 1.1 R² = 0.9913

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

408 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D24c: Double Logarithm Plot of p-Hydrosalicylic acid and LDL-VLDL Double Logarithm Plot (p-Hydrosalicylic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.5993x + 2.8578 -0.4 R² = 0.9976 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D24d: Scatchard’s Plot of p-Hydrosalicylic acid and LDL-VLDL Scatchard's Plot (p-Hydrosalicylic acid-LDL/VLDL) 0.3 0.25 {(F0-F)/F0}/ 0.2 y = -163283x + 0.3136 [Q] 0.15 R² = 0.9316 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D24e: Benesi-Hildebrand Plot of p-Hydroxybenzoic acid and LDL-VLDL Benesi-Hildebrand Plot (p-Hydrosalicylic acid-LDL/VLDL) 14 12 10 y = 2E-06x + 4.1752 R² = 0.9962 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

409 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Apocynin

Figure D25a: Fluorescence Quenching Spectrum of Apocynin and LDL-VLDL

Figure D25b: Stern-Volmer Plot of Apocynin and LDL-VLDL Stern-Volmer Plot (Apocynin-LDL/VLDL) 1.3 1.25 1.2 y = 193015x + 1.043 F0/F 1.15 R² = 0.9947 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

410 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D25c: Double Logarithm Plot of Apocynin and LDL-VLDL Double Logarithm Plot (Apocynin-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.732x + 3.765 -0.4R² = 0.9997 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D25d: Scatchard’s Plot of Apocynin and LDL-VLDL Scatchard's Plot (Apocynin-LDL/VLDL) 0.4

0.3 {(F0-F)/F0}/ y = -147592x + 0.3354 [Q] 0.2 R² = 0.9565 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D25e: Benesi-Hildebrand Plot of Apocynin and LDL-VLDL Benesi-Hildebrand Plot

14 (Apocynin-LDL/VLDL) 12 y = 3E-06x + 2.7808 10 R² = 0.9991 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

411 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Vanillic acid

Figure D26a: Fluorescence Quenching Spectrum of Vanillic acid and LDL-VLDL

Figure D26b: Stern-Volmer Plot of Vanillic acid and LDL-VLDL Stern-Volmer Plot (Vanillic acid-LDL/VLDL) 1.18 1.16 1.14 1.12 y = 91765x + 1.0626 0 F /F 1.1 R² = 0.9972 (A.U.) 1.08 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

412 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D26c: Double Logarithm Plot of Vanillic acid and LDL-VLDL Double Logarithm Plot (Vanillic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

y-0.4 = 0.4492x + 1.8793 R² = 0.996 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D26d: Scatchard’s Plot of Vanillic acid and LDL-VLDL Scatchard's Plot

0.4 (Vanillic acid-LDL/VLDL)

0.3 {(F0-F)/F0}/ y = -195154x + 0.3218 [Q] 0.2 R² = 0.8863 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D26e: Benesi-Hildebrand Plot of Vanillic acid and LDL-VLDL Benesi-Hildebrand Plot

14 (Vanillic acid-LDL/VLDL) 12 10 y = 2E-06x + 5.8451 R² = 0.9755 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

413 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Chlorogenic acid

Figure D27a: Fluorescence Quenching Spectrum of Chlorogenic acid and LDL-VLDL

Figure D27b: Stern-Volmer Plot of Chlorogenic acid and LDL-VLDL Stern-Volmer Plot (Chlorogenic acid-LDL/VLDL) 1.35 1.3 1.25 y = 271029x + 1.0207 0 1.2 F /F R² = 0.9993 (A.U.) 1.15 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

414 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D27c: Double Logarithm Plot of Chlorogenic acid and LDL-VLDL Double Logarithm Plot (Chlorogenic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4y = 0.8841x + 4.7691 R² = 1 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D27d: Scatchard’s Plot of Chlorogenic acid and LDL-VLDL Scatchard's Plot (Chlorogenic acid-LDL/VLDL) 0.4

0.3 y = -110169x + 0.3342 {(F0-F)/F0}/0.2 R² = 0.9754 [Q] (A.U. x μM-1)0.1 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D27e: Benesi-Hildebrand Plot of Chlorogenic acid and LDL-VLDL Benesi-Hildebrand Plot (Chlorogenic acid-LDL/VLDL) 14 12 y = 3E-06x + 1.6953 10 R² = 0.9998 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

415 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Ferulic acid

Figure D28a: Fluorescence Quenching Spectrum of Ferulic acid and LDL-VLDL

Figure D28b: Stern-Volmer Plot of Ferulic acid and LDL-VLDL Stern-Volmer Plot (Ferulic acid-LDL/VLDL) 1.3 1.25 1.2 F0/F y = 214706x + 1.0491 1.15 (A.U.) R² = 0.9891 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

416 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D28c: Double Logarithm Plot of Ferulic acid and LDL-VLDL Double Logarithm Plot (Ferulic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.7404x + 3.855 -0.4R² = 0.9864 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D28d: Scatchard’s Plot of Ferulic acid and LDL-VLDL Scatchard's Plot (Ferulic acid-LDL/VLDL) 0.4

0.3 {(F0-F)/F0}/ y = -176581x + 0.3852 [Q] 0.2 R² = 0.9884 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D28e: Benesi-Hildebrand Plot of Ferulic acid and LDL-VLDL Benesi-Hildebrand Plot (Ferulic acid-LDL/VLDL) 12 10 y = 2E-06x + 2.4192 8 R² = 0.9947 1/{(F0-F)/F0} 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

417 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Isoferulic acid

Figure D29a: Fluorescence Quenching Spectrum of Isoferulic acid and LDL-VLDL

Figure D29b: Stern-Volmer Plot of Isoferulic acid and LDL-VLDL Stern-Volmer Plot (Isoferulic acid-LDL/VLDL) 1.25

1.2

1.15 F0/F y = 165441x + 1.0115 (A.U.) 1.1 R² = 0.9768

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

418 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D29c: Double Logarithm Plot of Isoferulic acid and LDL-VLDL Double Logarithm Plot (Isoferulic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -0.2-5.8

-0.4y = 0.8213x + 4.1692 log {(F0-F)/F} -0.6 R² = 0.9909 (A.U.) -0.8 -1 -1.2 -1.4 log [Q] (M)

Figure D29d: Scatchard’s Plot of Isoferulic acid and LDL-VLDL Scatchard's Plot

0.25 (Isoferulic acid-LDL/VLDL) 0.2 {(F0-F)/F0}/ 0.15 y = -99066x + 0.2309 [Q] R² = 0.9207 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D29e: Benesi-Hildebrand Plot of Isoferulic acid and LDL-VLDL Benesi-Hildebrand Plot

20 (Isoferulic acid-LDL/VLDL)

15 y = 4E-06x + 4.0016 R² = 0.9947 1/{(F0-F)/F0} 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

419 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Isoferulic acid-3-o-glucuronide

Figure D30a: Fluorescence Quenching Spectrum of Isoferulic acid-3-o-glucuronide and LDL-VLDL

Figure D30b: Stern-Volmer Plot of Isoferulic acid-3-o-glucuronide and LDL-VLDL Stern-Volmer Plot (Isoferulic acid-3-o-glucuronide-

1.2 LDL/VLDL)

1.15 y = 152022x + 1.018 F0/F R² = 0.9996 1.1 (A.U.)

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

420 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D30c: Double Logarithm Plot of Isoferulic acid-3-o-glucuronide and LDL- VLDL Double Logarithm Plot (Isoferulic acid-3-o-glucuronide- LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 y = 0.8208x + 4.1533 -0.5R² = 0.9997 log {(F0-F)/F} (A.U.) -1

-1.5 log [Q] (M)

Figure D30d: Scatchard’s Plot of Isoferulic acid-3-o-glucuronide and LDL-VLDL Scatchard's Plot

(Isoferulic0.3 acid-3-o-glucuronide- LDL/VLDL) 0 0 0.2 {(F -F)/F }/ y = -73368x + 0.2167 [Q] R² = 0.9387 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D30e: Benesi-Hildebrand Plot of Isoferulic acid-3-o-glucuronide and LDL- VLDL Benesi-Hildebrand Plot (Isoferulic acid-3-o-glucuronide- 20 LDL/VLDL) 15 y = 4E-06x + 2.862 1/{(F0-F)/F0} R² = 0.998 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

421 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Dihydroferulic acid

Figure D31a: Fluorescence Quenching Spectrum of Dihydroferulic acid and LDL- VLDL

Figure D31b: Stern-Volmer Plot of Dihydroferulic acid and LDL-VLDL Stern-Volmer Plot (Dihydroferulic acid-LDL/VLDL) 1.2

1.15

F0/F y = 114449x + 1.0539 1.1 (A.U.) R² = 0.9691

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

422 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D31c: Double Logarithm Plot of Dihydroferulic acid and LDL-VLDL Double Logarithm Plot (Dihydroferulic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4y = 0.572x + 2.6598 log {(F0-F)/F} R² = 0.9889 -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D31d: Scatchard’s Plot of Dihydroferulic acid and LDL-VLDL Scatchard's Plot (Dihydroferulic acid-LDL/VLDL) 0.3 0.25 y = -161246x + 0.3014 0 0 0.2 {(F -F)/F }/ R² = 0.9588 [Q] 0.15 (A.U. x μM-1) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D31e: Benesi-Hildebrand Plot of Dihydroferulic acid and LDL-VLDL Benesi-Hildebrand Plot (Dihydroferulic acid-LDL/VLDL) 15

y = 3E-06x + 4.4761 10 R² = 0.9976 1/{(F0-F)/F0} (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

423 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Caffeic acid

Figure D32a: Fluorescence Quenching Spectrum of Caffeic acid and LDL-VLDL

Figure D32b: Stern-Volmer Plot of Caffeic acid and LDL-VLDL Stern-Volmer Plot (Caffeic acid-LDL/VLDL) 1.3 1.25 1.2 F0/F y = 206544x + 1.0582 1.15 (A.U.) R² = 0.9971 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

424 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D32c: Double Logarithm Plot of Caffeic acid and LDL-VLDL Double Logarithm Plot (Caffeic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.729x + 3.7786 -0.4 R² = 1 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D32d: Scatchard’s Plot of Caffeic acid and LDL-VLDL Scatchard's Plot

0.4 (Caffeic acid-LDL/VLDL)

0.3 {(F0-F)/F0}/ y = -202092x + 0.4052 [Q] 0.2 R² = 0.9197 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D32e: Benesi-Hildebrand Plot of Caffeic acid and LDL-VLDL Benesi-Hildebrand Plot (Caffeic acid-LDL/VLDL) 12 10 y = 2E-06x + 2.9965 8 R² = 0.9942 1/{(F0-F)/F0} 6 (A.U.-1) 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

425 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Caffeic acid-3-o-glucuronide

Figure D33a: Fluorescence Quenching Spectrum of Caffeic acid-3-o-glucuronide and LDL-VLDL

Figure D33b: Stern-Volmer Plot of Caffeic acid-3-o-glucuronide and LDL-VLDL Stern-Volmer Plot (Caffeic acid-3-o-glucuronide- 1.3 LDL/VLDL) 1.25 y = 175809x + 1.0697 1.2 R² = 0.956 F0/F 1.15 (A.U.) 1.1 1.05 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

426 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D33c: Double Logarithm Plot of Caffeic acid-3-o-glucuronide and LDL-VLDL Double Logarithm Plot (Caffeic acid-3-o-glucuronide- LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.6331x + 3.2349 -0.4 R² = 0.9837 log {(F0-F)/F} (A.U.) -0.6

-0.8

-1 log [Q] (M)

Figure D33d: Scatchard’s Plot of Caffeic acid-3-o-glucuronide and LDL-VLDL Scatchard's Plot (Caffeic acid-3-o-glucuronide- 0.4 LDL/VLDL) 0.3 {(F0-F)/F0}/ y = -205445x + 0.3989 [Q] 0.2 R² = 0.9782 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D33e: Benesi-Hildebrand Plot of Caffeic acid-3-o-glucuronide and LDL-VLDL Benesi-Hildebrand Plot (Caffeic acid-3-o-glucuronide- 15 LDL/VLDL) 10 y = 2E-06x + 3.0829 1/{(F0-F)/F0} R² = 0.9989 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

427 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Caffeic acid-4-o-glucuronide

Figure D34a: Fluorescence Quenching Spectrum of Caffeic acid-4-o-glucuronide and LDL-VLDL

Figure D34b: Stern-Volmer Plot of Caffeic acid-4-o-glucuronide and LDL-VLDL Stern-Volmer Plot (Caffeic acid-4-o-glucuronide- 1.25 LDL/VLDL) 1.2 y = 144853x + 1.0529 1.15 R² = 0.9836 F0/F (A.U.) 1.1

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

428 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D34c: Double Logarithm Plot of Caffeic acid-4-o-glucuronide and LDL-VLDL Double Logarithm Plot (Caffeic acid-4-o-glucuronide- LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

y-0.4 = 0.6283x + 3.067 R² = 0.9966 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D34d: Scatchard’s Plot of Caffeic acid-4-o-glucuronide and LDL-VLDL Scatchard's Plot (Caffeic acid-4-o-glucuronide- 0.4 LDL/VLDL) 0.3 {(F0-F)/F0}/ y = -164272x + 0.3255 [Q] 0.2 R² = 0.9583 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D34e: Benesi-Hildebrand Plot of Caffeic acid-4-o-glucuronide and LDL-VLDL Benesi-Hildebrand Plot (Caffeic acid-4-o-glucuronide- 15 LDL/VLDL) y = 2E-06x + 3.6947 10 R² = 0.9996 1/{(F0-F)/F0} (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

429 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Dihydrocaffeic acid

Figure D35a: Fluorescence Quenching Spectrum of Dihydrocaffeic acid and LDL- VLDL

Figure D35b: Stern-Volmer Plot of Dihydrocaffeic acid and LDL-VLDL Stern-Volmer Plot (Dihydrocaffeic acid-LDL/VLDL) 1.25

1.2

1.15 F0/F y = 143787x + 1.0483 R² = 0.9933 (A.U.) 1.1

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

430 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D35c: Double Logarithm Plot of Dihydrocaffeic acid and LDL-VLDL Double Logarithm Plot (Dihydrocaffeic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.6339x + 3.0857 -0.4 R² = 0.9999 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D35d: Scatchard’s Plot of Dihydrocaffeic acid and LDL-VLDL Scatchard's Plot (Dihydrocaffeic acid-LDL/VLDL) 0.3 0.25 y = -156408x + 0.3132 0 0 0.2 {(F -F)/F }/ R² = 0.9351 [Q] 0.15 -1 (A.U. x μM ) 0.1 0.05 0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D35e: Benesi-Hildebrand Plot of Dihydrocaffeic acid and LDL-VLDL Benesi-Hildebrand Plot

14 (Dihydrocaffeic acid-LDL/VLDL) 12 y = 2E-06x + 3.8449 10 R² = 0.9969 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

431 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Dihydrocaffeic acid-3-o-sulfate

Figure D36a: Fluorescence Quenching Spectrum of Dihydrocaffeic acid-3-o-sulfate and LDL-VLDL

Figure D36b: Stern-Volmer Plot of Dihydrocaffeic acid-3-o-sulfate and LDL-VLDL Stern-Volmer Plot (Dihydrocaffeic acid-3-o-sulfate- 1.2 LDL/VLDL)

1.15 y = 115625x + 1.0399 R² = 0.9976 F0/F 1.1 (A.U.)

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

432 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D36c: Double Logarithm Plot of Dihydrocaffeic acid-3-o-sulfate and LDL- VLDL Double Logarithm Plot (Dihydrocaffeic acid-3-o-sulfate- 0 -6.6 -6.4LDL/VLDL)-6.2 -6 -5.8 y = 0.6179x + 2.8958 -0.5 R² = 0.9992 log {(F0-F)/F} (A.U.) -1

-1.5 log [Q] (M)

Figure D36d: Scatchard’s Plot of Dihydrocaffeic acid-3-o-sulfate and LDL-VLDL Scatchard's Plot (Dihydrocaffeic acid-3-o-sulfate- 0.3 LDL/VLDL) y = -130923x + 0.2613 {(F0-F)/F0}/ 0.2 R² = 0.9114 [Q] (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure XD36e: Benesi-Hildebrand Plot of Dihydrocaffeic acid-3-o-sulfate and LDL- VLDL Benesi-Hildebrand Plot

(Dihydrocaffeic20 acid-3-o-sulfate- LDL/VLDL) 15 y = 3E-06x + 4.7247 1/{(F0-F)/F0} R² = 0.9917 10 (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

433 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Dihydrocaffeic acid-3-o-glucuronide

Figure D37a: Fluorescence Quenching Spectrum of Dihydrocaffeic acid-3-o- glucuronide and LDL-VLDL

Figure D37b: Stern-Volmer Plot of Dihydrocaffeic acid-3-o-glucuronide and LDL- VLDL Stern-Volmer Plot (Dihydrocaffeic acid-3-o-glucuronide- 1.2 LDL/VLDL) 1.15 y = 85919x + 1.0549 F0/F 1.1 R² = 0.9872 (A.U.)

1.05

1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

434 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D37c: Double Logarithm Plot of Dihydrocaffeic acid-3-o-glucuronide and LDL-VLDL Double Logarithm Plot (Dihydrocaffeic acid-3-o-glucuronide- LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 -0.4 y = 0.4679x + 1.9757 log {(F0-F)/F} -0.6 R² = 0.9577 (A.U.) -0.8 -1 -1.2 log [Q] (M)

Figure D37d: Scatchard’s Plot of Dihydrocaffeic acid-3-o-glucuronide and LDL-VLDL Scatchard's Plot (Dihydrocaffeic acid-3-o-glucuronide- 0.3 LDL/VLDL) y = -178643x + 0.302 0 0 0.2 {(F -F)/F }/ R² = 0.9739 [Q] (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D37e: Benesi-Hildebrand Plot of Dihydrocaffeic acid-3-o-glucuronide and LDL-VLDL Benesi-Hildebrand Plot (Dihydrocaffeic acid-3-o-glucuronide- 15 LDL/VLDL) y = 2E-06x + 5.5537 10 R² = 0.9919 1/{(F0-F)/F0} (A.U.-1) 5

0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

435 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Sinapic acid

Figure D38a: Fluorescence Quenching Spectrum of Sinapic acid and LDL-VLDL

Figure D38b: Stern-Volmer Plot of Sinapic acid and LDL-VLDL Stern-Volmer Plot (Sinapic acid-LDL/VLDL) 1.18 1.16 1.14 1.12 F0/F 1.1 y = 130515x + 1.0185 (A.U.) 1.08 R² = 0.9666 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

436 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D38c: Double Logarithm Plot of Sinapic acid and LDL-VLDL Double Logarithm Plot (Sinapic acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -0.2-5.8 -0.4y = 0.8794x + 4.4589 -0.6 R² = 0.9757 log {(F0-F)/F} -0.8 (A.U.) -1 -1.2 -1.4 -1.6 log [Q] (M)

Figure D38d: Scatchard’s Plot of Sinapic acid and LDL-VLDL Scatchard's Plot (Sinapic acid-LDL/VLDL) 0.2

0.15 {(F0-F)/F0}/ [Q] 0.1 y = -57430x + 0.1864 (A.U. x μM-1) R² = 0.9648 0.05

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D38e: Benesi-Hildebrand Plot of Sinapic acid and LDL-VLDL Benesi-Hildebrand Plot (Sinapic acid-LDL/VLDL) 25

20 y = 5E-06x + 2.3305 R² = 0.9965 1/{(F0-F)/F0} 15 -1 (A.U. ) 10 5 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

437 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts o-Coumaric acid

Figure D39a: Fluorescence Quenching Spectrum of o-Coumaric acid and LDL-VLDL

Figure D39b: Stern-Volmer Plot of o-Coumaric acid and LDL-VLDL Stern-Volmer Plot (o-Coumaric acid-LDL/VLDL) 1.18 1.16 1.14 1.12 y = 104890x + 1.0384 0 F /F 1.1 R² = 0.9944 (A.U.) 1.08 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

438 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D39c: Double Logarithm Plot of o-Coumaric acid and LDL-VLDL Double Logarithm Plot (o-Coumaric acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2

-0.4y = 0.6985x + 3.4519 R² = 0.9998 log {(F0-F)/F} -0.6 (A.U.) -0.8

-1

-1.2 log [Q] (M)

Figure D39d: Scatchard’s Plot of o-Coumaric acid and LDL-VLDL Scatchard's Plot (o-Coumaric acid-LDL/VLDL) 0.4

0.3 {(F0-F)/F0}/ y = -167739x + 0.315 [Q] 0.2 R² = 0.8694 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D39e: Benesi-Hildebrand Plot of o-Coumaric acid and LDL-VLDL Benesi-Hildebrand Plot (o-Coumaric acid-LDL/VLDL) 14 12 10 y = 2E-06x + 4.5416 R² = 0.9723 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

439 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts p-Coumaric acid

Figure D40a: Fluorescence Quenching Spectrum of p-Coumaric acid and LDL-VLDL

Figure D40b: Stern-Volmer Plot of p-Coumaric acid and LDL-VLDL Stern-Volmer Plot (p-Coumaric acid-LDL/VLDL) 1.18 1.16 1.14 1.12 F0/F 1.1 y = 89338x + 1.0705 (A.U.) 1.08 R² = 0.9979 1.06 1.04 1.02 1 0.00E+00 2.00E-07 4.00E-07 6.00E-07 8.00E-07 1.00E-06 1.20E-06 [Q] (M)

440 Appendix D: Ka Plots of LDL-VLDL, Fluorescence Spectra, and λmax Shifts

Figure D40c: Double Logarithm Plot of p-Coumaric acid and LDL-VLDL Double Logarithm Plot (p-Coumaric acid-LDL/VLDL) 0 -6.6 -6.4 -6.2 -6 -5.8 -0.2 y = 0.4964x + 2.3997 -0.4 R² = 0.9981 log {(F0-F)/F} (A.U.) -0.6

-0.8

-1 log [Q] (M)

Figure D40d: Scatchard’s Plot of p-Coumaric acid and LDL-VLDL Scatchard's Plot (p-Coumaric acid-LDL/VLDL) 0.4

0.3 {(F0-F)/F0}/ y = -175011x + 0.3498 [Q] 0.2 R² = 0.9286 (A.U. x μM-1) 0.1

0 0.00E+00 4.00E-07 8.00E-07 1.20E-06 [Q] (M)

Figure D40e: Benesi-Hildebrand Plot of p-Coumaric acid and LDL-VLDL Benesi-Hildebrand Plot (p-Coumaric acid-LDL/VLDL) 14 12 10 y = 2E-06x + 3.4647 R² = 0.9957 1/{(F0-F)/F0} 8 (A.U.-1) 6 4 2 0 0.00E+00 1.00E+06 2.00E+06 3.00E+06 4.00E+06 1/[Q] (M-1)

441