Hill's Coefficients, Cooperativity, Positive And
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Nucleosome-Mediated Cooperativity Between Transcription Factors
Nucleosome-mediated cooperativity between transcription factors Leonid A. Mirny1 Harvard–MIT Division of Health Sciences and Technology, and Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139 Edited* by José N. Onuchic, University of California San Diego, La Jolla, CA, and approved October 12, 2010 (received for review December 3, 2009) Cooperative binding of transcription factors (TFs) to promoters and A B other regulatory regions is essential for precise gene expression. The classical model of cooperativity requires direct interactions between TFs, thus constraining the arrangement of TF sites in reg- ulatory regions. Recent genomic and functional studies, however, demonstrate a great deal of flexibility in such arrangements with variable distances, numbers of sites, and identities of TF sites lo- cated in cis-regulatory regions. Such flexibility is inconsistent with L C N O D T R cooperativity by direct interactions between TFs. Here, we demon- P 0 0 0 0 P O O strate that strong cooperativity among noninteracting TFs can be K K 2 2 NN O O T R achieved by their competition with nucleosomes. We find that the P 1 1 P 1 1 K O O mechanism of nucleosome-mediated cooperativity is analogous to c = O 10 1..10 3 2 2 K cooperativity in another multimolecular complex: hemoglobin. This N N2 O2 T R [P] P 2 2 = 15 P surprising analogy provides deep insights, with parallels between O2 O2 KO … … the heterotropic regulation of hemoglobin (e.g., the Bohr effect) [N ] L = 0 100 1000 N O and the roles of nucleosome-positioning sequences and chromatin [O0] n n T4 R4 modifications in gene expression. -
Pi-Pi Stacking Mediated Cooperative Mechanism for Human Cytochrome P450 3A4
Molecules 2015, 20, 7558-7573; doi:10.3390/molecules20057558 OPEN ACCESS molecules ISSN 1420-3049 www.mdpi.com/journal/molecules Article Pi-pi Stacking Mediated Cooperative Mechanism for Human Cytochrome P450 3A4 Botao Fa 1, Shan Cong 2 and Jingfang Wang 1,* 1 Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China; E-Mail: [email protected] 2 Department of Bioinformatics and Biostatistics, College of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +86-21-3420-7344 (ext. 123); Fax: +86-21-3420-4348. Academic Editor: Antonio Frontera Received: 13 January 2015 / Accepted: 19 March 2015 / Published: 24 April 2015 Abstract: Human Cytochrome P450 3A4 (CYP3A4) is an important member of the cytochrome P450 superfamily with responsibility for metabolizing ~50% of clinical drugs. Experimental evidence showed that CYP3A4 can adopt multiple substrates in its active site to form a cooperative binding model, accelerating substrate metabolism efficiency. In the current study, we constructed both normal and cooperative binding models of human CYP3A4 with antifungal drug ketoconazoles (KLN). Molecular dynamics simulation and free energy calculation were then carried out to study the cooperative binding mechanism. Our simulation showed that the second KLN in the cooperative binding model had a positive impact on the first one binding in the active site by two significant pi-pi stacking interactions. The first one was formed by Phe215, functioning to position the first KLN in a favorable orientation in the active site for further metabolism reactions. -
Allosteric Effects and Cooperative Binding
Biochemistry I, Fall Term Lecture 13 Sept 28, 2005 Lecture 13: Allosteric Effects and Cooperative Binding Assigned reading in Campbell: Chapter 4.7, 7.2 Key Terms: • Homotropic Allosteric effects • Heterotropic Allosteric effects • T and R states of cooperative systems • Role of proximal His residue in cooperativity of O2 binding by Hb • Regulation of O2 binding to Hb by bis-phosphoglycerate (BPG) Oxygen Binding to Myoglobin and Hemolobin: Myoglobin binds one O2: Hemoglobin binds four O2: Allosteric Effects and Cooperativity: Allosteric effects occur when the binding properties of a macromolecule change as a consequence of a second ligand binding to the macromolecule and altering its affinity towards the first, or primary, ligand. There need not be a direct connection between the two ligands (i.e. they may bind to opposite sides of the protein, or even to different subunits) • If the two ligands are the same (e.g. oxygen) then this is called a homo-tropic allosteric effect. • If the two ligands are different (e.g. oxygen and BPG), then this is called a hetero-tropic allosteric effect. In the case of macromolecules that have multiple ligand binding sites (e.g. Hb), allosteric effects can generate cooperative behavior. Allosteric effects are important in the regulation of enzymatic reactions. Both allosteric activators (which enhance activity) and allosteric inhibitors (which reduce activity) are utilized to control enzyme reactions. Allosteric effects require the presence of two forms of the macromolecule. One form, usually called the T or tense state, binds the primary ligand (e.g. oxygen) with low affinity. The other form, usually called the R or relaxed state, binds ligand with high affinity. -
Statistical Mechanics of Allosteric Enzymes
Statistical Mechanics of Allosteric Enzymes Tal Einav,† Linas Mazutis,‡ and Rob Phillips∗,¶ Department of Physics, California Institute of Technology, Pasadena, California 91125, United States, Institute of Biotechnology, Vilnius University, Vilnius, Lithuania, and Department of Applied Physics and Division of Biology, California Institute of Technology, Pasadena, California 91125, United States E-mail: [email protected] Abstract The concept of allostery in which macromolecules switch between two different conforma- tions is a central theme in biological processes ranging from gene regulation to cell signaling to enzymology. Allosteric enzymes pervade metabolic processes, yet a simple and unified treatment of the effects of allostery in enzymes has been lacking. In this work, we take the first step towards this goal by modeling allosteric enzymes and their interaction with two key molecular players - allosteric regulators and competitive inhibitors. We then apply this model to characterize existing data on enzyme activity, comment on how enzyme parameters (such as substrate binding affinity) can be experimentally tuned, and make novel predictions on how to control phenomena such as substrate inhibition. arXiv:1701.03988v1 [q-bio.SC] 15 Jan 2017 ∗To whom correspondence should be addressed †Department of Physics, California Institute of Technology, Pasadena, California 91125, United States ‡Institute of Biotechnology, Vilnius University, Vilnius, Lithuania ¶Department of Applied Physics and Division of Biology, California Institute -
Mathematical Toolkit for Quantitative Analysis of Cooperative Binding of Two Or More Ligands to a Substrate Jacob Peacock and James B
Mathematical toolkit for quantitative analysis of cooperative binding of two or more ligands to a substrate Jacob Peacock and James B. Jaynes Dept. of Biochemistry and Molecular Biology, Thomas Jefferson University, Philadelphia PA 19107 United States of America [email protected] Abstract We derive mathematical expressions for quantitative analysis of cooperative binding covering the following cases: 1) a single ligand binds to either two non-equivalent sites, or an arbitrary number of equivalent sites, on a substrate (Fig. 1), and 2) two different ligands bind distinct sites on a substrate (Figs. 2, 3). We show how to analyze "competition experiments" using non-linear regression, where a ligand binds to a single site on a labeled substrate in the presence of increasing amounts of identical but unlabeled competitor substrate, to simultaneously determine the Kd and active ligand concentration (Fig. 4A). We compare the performance of this competition method with the commonly used saturation binding method (Fig. 4B). We also provide methods to analyze such experiments that include a second competitor substrate with non-specific binding sites. We show how to build on results from single-ligand competition experiments to fully characterize cooperative binding in systems with two distinct ligands and binding sites (Fig. 4C and Section 5). We generalize the methodology to more than two cooperating ligands, such as an array of DNA binding proteins (Fig. 6). See Peacock and Jaynes [1] for discussion of the various ways these tools can be used, and results using them. • Visualize characteristics and limitations of Hill plots applied to more realistic binding models than those described by the Hill equation, which implies multiple simultaneous ligand binding. -
Lec-08-Handout
NPTEL VIDEO COURSE – PROTEOMICS PROF. SANJEEVA SRIVASTAVA HANDOUT LECTURE-08 ENZYME: BASIC CONCEPTS, CATALYTIC AND REGULATORY STRATEGIES Slide 1 Today, we will talk about enzyme: basic concepts, catalytic and regulatory strategies. Slide 2 Lecture outline: • Basic concepts of enzyme including enzyme kinetics, energetics and enzyme inhibition. • Different type of catalytic strategies and regulatory strategies. Slide 3 So as you all know, enzymes play very important role in biochemistry All enzymes are proteins therefore it will essential to study about enzymes while studying basic concepts of amino acids and proteins. Although it may not be directly linked to the proteomics but understanding of enzyme and proteins is very fundamental for the advanced understanding of concepts related to proteomics. Slide 4 So what are enzymes? • Enzymes are molecular catalysts. • Almost all enzymes are proteins and as we have discussed in the previous lecture there are twenty amino acids that make up the basic building blocks of all proteins. • Enzymes can accelerate a given reaction up to million folds. Let’s take an example of carbonic anhydrase which catalyzes hydration of carbon di oxide. Now this enzyme can catalyze 106 molecules per second. • Enzymes are highly specific and catalyze single or closely related reaction. DEPARTMENT OF BIOSCIENCES & BIOENGINEERING INDIAN INSTITUTE OF TECHNOLOGY (IIT) BOMBAY, MUMBAI, INDIA Page 1 NPTEL VIDEO COURSE – PROTEOMICS PROF. SANJEEVA SRIVASTAVA Slide 5 In terms of enzyme specificity, let me give you few examples- • Trypsin- it is highly specific, it cleaves peptide on carboxyl side of Lys/Arg. • Another enzyme thrombin, which participates in blood clotting, it is even more specific that trypsin. -
Structure and Evolution of Protein Allosteric Sites
Structure and evolution of protein allosteric sites by Alejandro Panjkovich Thesis submitted to Universitat Aut`onoma de Barcelona in partial fulfillment of the requirements for the degree of Doctor of Philosophy Director - Prof. Xavier Daura Tesi Doctoral UAB/ANY 2013 Ph.D. Program - Protein Structure and Function Institut de Biotecnologia i Biomedicina caminante, no hay camino, se hace camino al andar Antonio Machado,1912 Acknowledgements First of all I would like to thank my supervisor and mentor Prof. Xavier Daura for his consistent support and trust in my work throughout these years. Xavi, I deeply appreciate the freedom you gave me to develop this project while you were still carefully aware of the small details. Working under your supervision has been a rich and fulfilling experience. Of course, thanks go as well to current and past members of our institute, especially Rita Rocha, Pau Marc Mu˜noz,Oscar Conchillo, Dr. Mart´ınIndarte, Dr. Mario Ferrer, Prof. Isidre Gibert, Dr. Roman Affentranger and Dr. Juan Cedano for their technical and sometimes philo- sophical assistance. Help from the administrative staff was also significant, I would like to thank in particular Eva, Alicia and Miguel who where always ready to help me in sorting out unexpected bureaucratic affairs. I would also like to thank Dr. Mallur Srivatasan Madhusudhan and his group (especially Kuan Pern Tan, Dr. Minh Nguyen and Binh Nguyen), and also Dr. Gloria Fuentes, Cassio Fernandes, Youssef Zaki, Thijs Kooi, Rama Iyer, Christine Low and many others at the Bioinformatics Institute BII - A∗STAR in Singapore for the many interesting discussions and support during my stage over there. -
Metabolism of Glycogen Glycogenesis
LEC: 10Biochemistry Dr. Anwar J Almzaiel Metabolism of glycogen Glycogen is the major storage form of carbohydrate in animal and corresponds to starch in plant. It occurs mainly in liver (up to 6%) and muscle(up to 1%). However, because of great mass, muscle represents some 3-4 times as much as glycogen store as liver. It is branched polymer of α- glucose. The function of muscle glycogen is to act as a readily available source of hexose units for glycolysis within the muscle itself. Liver glycogen is largely concerned with storage and export of hexose units for maintenance of the blood glucose, particularly between meals. After (12-18 hours) of fasting, the liver becomes almost totally depleted of glycogen, whereas muscle glycogen is only depleted significantly after prolonged various exercise. Why the cell can store glycogen but not glucose? Because when glucose increased, osmatic pressure in the cell increase, causing water movement toward the cell and leading to burst so when glucose accumulates in the cell, it will convert to glycogen which consists of branched series of glucose. Glycogenesis The process of glycogenesis start when glucose-6-phosphat is changed to glucose-1-phosphate by mutase mutas glucose-6-phosphatglucosee 1-phosphate The reaction is reversible and depends on concentration of substrate (glucose- 6-phosphat), if there is a large amount or quantities of glucose-6-phosphat will lead to formation of glucose 1-phosphate and the opposite is right. No loss in the energy in this reaction As glucose 1-phosphate formed, it will react with high energy compound UTP (uradin triphosphate), which react with glucose to give UDP glucose (uradin diphosphate glucose) and pyrophosphate released glucose 1-phosphate is high energetic compound and called (active glucose molecule), this reaction is carried by (UDP glucose pyrophosphorylase) 1 LEC: 10Biochemistry Dr. -
Thermodynamic Versus Kinetic Discrimination of Cooperativity of Enzymatic Ligand Binding
Open Access Austin Biochemistry Special Article - Enzyme Kinetics Thermodynamic versus Kinetic Discrimination of Cooperativity of Enzymatic Ligand Binding Das B1, Banerjee K2 and Gangopadhyay G1* 1Department of Chemical Physics, SN Bose National Abstract Centre for Basic Sciences, India In this work, we have introduced thermodynamic measure to characterize the 2Department of Chemistry, A.J.C. Bose College, India nature of cooperativity in terms of the variation of standard free energy change *Corresponding author: Gangopadhyay G, SN Bose with the fraction of ligand-bound sub-units of a protein in equilibrium, treating National Centre for Basic Sciences, Block-JD, Sector-III, the protein-ligand attachment as a stochastic process. The fraction of ligand- Salt Lake, Kolkata-700106, India bound sub-units of cooperative ligand-binding processes are calculated by the formulation of stochastic master equation for both the KNF and MWC Allosteric Received: December 26, 2018; Accepted: May 23, cooperative model. The proposed criteria of this cooperative measurement is 2019; Published: May 30, 2019 valid for all ligand concentrations unlike the traditional kinetic measurement of Hill coefficient at half-saturation point. A Kullback-Leibler distance is also introduced which indicates how much average standard free energy is involved if a non-cooperative system changes to a cooperative one, giving a quantitative synergistic measure of cooperativity as a function of ligand concentration which utilizes the full distribution function beyond the mean and variance. For the validation of our theory to provide a systematic approach to cooperativity, we have considered the experimental result of the cooperative binding of aspartate to the dimeric receptor of Salmonella typhimurium. -
Allosteric Enzymes: Properties and Mechanism | Microbiology
Allosteric Enzymes: Properties and Mechanism | Microbiology In this article we will discuss about the properties and mechanisms of action of allosteric enzymes. Properties of Allosteric Enzymes: Allosteric or Regulatory enzymes have multiple subunits (Quaternary Structure) and multiple active sites. Allosteric enzymes have active and inactive shapes differing in 3D structure. Allosteric enzymes often have multiple inhibitor or activator binding sites involved in switching between active and inactive shapes. Allosteric enzymes have characteristic “S”-shaped curve for reaction rate vs. substrate concentration. Why? Because the substrate binding is “Cooperative.” And the binding of first substrate at first active site stimulates active shapes, and promotes binding of second substrate. A modulator is a me-tabolite, when bound to the allosteric site of an enzyme, alters its kinetic characteristics. The modulators for allosteric enzyme may be ei-ther stimulatory or inhibitory. A stimulator is often the sub-strate itself. The regulatory enzymes for which substrate and modulator are identical are called homo-tropic. When the modulator has a structure different then the substrate, the enzyme is called heterotropic. Some enzymes have more then one modulators. The allosteric enzymes also have one or more regulatory or aliosteric sites for binding the modulator. Enzymes with several modulators generally have different specific binding sites for each (Fig. 12.15). The sigmoid curve is given by homo-tropic enzymes in which the substrate also serve as a positive (stimulator) modu-lator (12.16). Curve for the non-regulatory enzymes is hy-perbolic, as also predicted by the Michaelis-Menten equa-tion, whereas allosteric en-zymes do not show Michaelis- Menten relationship because their kinetic behaviour is greatly altered by variation in the concentration of modula-tors. -
Structural Basis for Regiospecific Midazolam Oxidation by Human Cytochrome P450 3A4
Structural basis for regiospecific midazolam oxidation by human cytochrome P450 3A4 Irina F. Sevrioukovaa,1 and Thomas L. Poulosa,b,c aDepartment of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697-3900; bDepartment of Chemistry, University of California, Irvine, CA 92697-3900; and cDepartment of Pharmaceutical Sciences, University of California, Irvine, CA 92697-3900 Edited by Michael A. Marletta, University of California, Berkeley, CA, and approved November 30, 2016 (received for review September 28, 2016) Human cytochrome P450 3A4 (CYP3A4) is a major hepatic and Here we describe the cocrystal structure of CYP3A4 with the intestinal enzyme that oxidizes more than 60% of administered drug midazolam (MDZ) bound in a productive mode. MDZ therapeutics. Knowledge of how CYP3A4 adjusts and reshapes the (Fig. 1) is the benzodiazepine most frequently used for pro- active site to regioselectively oxidize chemically diverse com- cedural sedation (9) and is a marker substrate for the CYP3A pounds is critical for better understanding structure–function rela- family of enzymes that includes CYP3A4 (10). MDZ is hydrox- tions in this important enzyme, improving the outcomes for drug ylated by CYP3A4 predominantly at the C1 position, whereas metabolism predictions, and developing pharmaceuticals that the 4-OH product accumulates at high substrate concentrations have a decreased ability to undergo metabolism and cause detri- (up to 50% of total product) and inhibits the 1-OH metabolic mental drug–drug interactions. However, there is very limited pathway (11–14). The reaction rate and product distribution structural information on CYP3A4–substrate interactions available strongly depend on the assay conditions and can be modulated by to date. -
Binding Modes and Metabolism of Caffeine
This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited. Article Cite This: Chem. Res. Toxicol. 2019, 32, 1374−1383 pubs.acs.org/crt Binding Modes and Metabolism of Caffeine Zuzana Jandova,† Samuel C. Gill,‡ Nathan M. Lim,§ David L. Mobley,‡ and Chris Oostenbrink*,† † Institute of Molecular Modeling and Simulation, University of Natural Resources and Life Sciences, Vienna, 1180 Vienna, Austria ‡ § Department of Chemistry and Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, California 92697, United States *S Supporting Information ABSTRACT: A correct estimate of ligand binding modes and a ratio of their occupancies is crucial for calculations of binding free energies. The newly developed method BLUES combines molecular dynamics with nonequilibrium candidate Monte Carlo. Nonequilibrium candidate Monte Carlo generates a plethora of possible binding modes and molecular dynamics enables the system to relax. We used BLUES to investigate binding modes of caffeine in the active site of its metabolizing enzyme Cytochrome P450 1A2 with the aim of elucidating metabolite-formation profiles at different concentrations. Because the activation energies of all sites of metabolism do not show a clear preference for one metabolite over the others, the orientations in the active site must play a key role. In simulations with caffeine located in a spacious pocket above the I-helix, it points N3 and N1 to the heme iron, whereas in simulations where caffeine is in close proximity to the heme N7 and C8 are preferably oriented toward the heme iron.