applied sciences

Article Peak Fitting Applied to Fourier Transform and Raman Spectroscopic Analysis of

Azin Sadat and Iris J. Joye * Department of Food Science, University of Guelph, Guelph, ON N1G 2W1, Canada; [email protected] * Correspondence: [email protected]; Tel.: +1-(519)-824-4120 (ext. 52470)

 Received: 7 August 2020; Accepted: 19 August 2020; Published: 26 August 2020 

Abstract: FTIR and Raman spectroscopy are often used to investigate the secondary structure of proteins. Focus is then often laid on the different features that can be distinguished in the Amide 1 1 I band (1600–1700 cm− ) and, to a lesser extent, the Amide II band (1510–1580 cm− ), signature regions for C=O stretching/N-H bending, and N-H bending/C-N stretching vibrations, respectively. Proper investigation of all hidden and overlapping features/peaks is a necessary step to achieve reliable analysis of FTIR and FT-Raman spectra of proteins. This paper discusses a method to identify, separate, and quantify the hidden peaks in the amide I band region of infrared and Raman spectra of four globular proteins in aqueous solution as well as hydrated zein and gluten proteins. The globular proteins studied, which differ widely in terms of their secondary structures, include immunoglobulin G, concanavalin A, lysozyme, and trypsin. Peak finding was done by analysis of the second derivative of the original spectra. Peak separation and quantification was achieved by curve fitting using the Voigt function. Structural data derived from the FT-Raman and FTIR analyses were compared to literature reports on structure. This manuscript proposes an accurate method to analyze protein secondary structure based on the amide I band in vibrational spectra.

Keywords: infrared (IR) spectroscopy; Raman spectroscopy; peak fitting; gluten; zein

1. Introduction Infrared spectroscopy is one of the oldest techniques to study the secondary structure of macropeptides and proteins [1–5]. Alternative techniques such as (CD) and X-ray crystallography have also been utilized to gain information about protein structure; X-ray crystallography relies on the protein’s ability to crystallize [6]. CD spectroscopy is a technique based on the absorption of light and measures the difference in absorbance of left and right circularly polarised light [7–9]. CD will require protein extraction prior to analysis and will, hence, not allow the in situ study of proteins (i.e., gluten) in a range of complex food systems, such as dough and baked products. However, FTIR and FT-Raman techniques have the ability to study the proteins in the complex food matrix without the need for extensive sample preparation or extraction [10]. Nuclear magnetic resonance spectroscopy can also be used to study protein structure in solution but the processing of data obtained for large proteins is a very complicated process [6]. Infrared and Raman spectroscopy, on the other hand, are non-invasive vibrational spectroscopy techniques and can be used to study the protein structure in the native state and in a wide range of different environments [6]. For instance, FTIR has been used to study the changes in gluten secondary structure during dough mixing [11–14], enzymatic modification [15], hydration [16,17], and upon bran addition to a viscoelastic gluten dough [18]. Protein-containing samples display nine characteristic vibrational absorption bands in an IR 1 spectrum (~200–3300 cm− ) which arise from different vibrational modes of the amide groups of proteins (found in the peptide bonds), namely amide A, B, and I-VII [19]. Among these, the amide

Appl. Sci. 2020, 10, 5918; doi:10.3390/app10175918 www.mdpi.com/journal/applsci Appl. Sci. 2020, 10, 5918 2 of 16

I band which mainly probes stretching vibrations of the C=O bonds in the peptide backbone has been proven to be the most sensitive and popular band to study protein secondary structure [5,19]. Each type of secondary structure correlates to a slightly different C=O stretching in the amide I band region of the spectrum due to its unique molecular geometry and pattern [6,19]. Amide II also provides information on the vibrational bands of the protein backbone. However, it derives mostly from in-plane N-H bending (40–60% of the potential energy), and C-N stretching (18–40%), resulting in less sensitivity and specificity for protein conformational changes compared to the amide I band [19]. When studying aqueous solutions of proteins, strong interference of intense infrared absorption of water often distorts the IR spectra, complicating the practical use of FTIR in high moisture systems [10]. The H-O-H scissoring/bending vibration shows a strong absorbance in the amide I band region, which makes the analysis of this band difficult. A common approach is subtracting the reference spectrum of the pure solvent, i.e., water. There has been a number of studies for proteins solubilized in H2O in which a reference H2O spectrum was subtracted from the sample spectrum [5,20–22]. Other strategies have also been explored and utilized thus far to solve this issue, such as using D2O as a solvent instead of H2O[1,2,23,24]. However, the use of D2O results in very different solvent properties relative to H2O and it is known to affect hydrogen bond dynamics [6,25,26]. The different solvent properties of D2O compared with H2O can alter the structure of proteins by changing the balance between intra- and intermolecular hydrogen bonds and hydration interactions [26]. Overall, an ideal subtraction needs the complete overlay of both the reference water spectrum and the sample water spectrum [27]. As the interaction of molecules (i.e., proteins) with water can cause small shifts in the H2O bending signal, there is a risk of creating subtraction artefacts. Unfortunately, there is no good strategy developed thus far to deal with this issue for FTIR analysis of protein secondary structure [27]. In Raman spectroscopy, interference with a strong H2O signal is less of an issue as the intensity of the scattering depends on changes in polarizability of a molecule [10]. Raman is inherently more sensitive towards non-polar groups like C=C, C-C, and S-S [28]. Water as a strongly polar molecule with weak polarizability only gives very weak Raman signals [29]. As such, Raman is considered to be a more suitable technique to study the protein structure in complex high moisture matrices and aqueous solutions [10]. Raman, however, suffers from other limitations such as low signal to noise ratios and fluorescence interference. Fluorescence interference is especially worrisome for proteins as the aromatic amino acids (i.e., tryptophan, tyrosine, and phenylalanine) display strong fluorescent properties [10,28]. The fluorescence issue can be overcome by using more -shifted laser light for the Raman analysis as these typically do not contain enough energy to cause excitation of the intrinsic fluorophores in proteins and, hence, reduce fluorescence emission [28]. The amide I band in FTIR and FT-Raman spectra of protein samples is literally composed as a superimposition of C=O stretching signals of the different secondary structures in a protein. This results in a complex signal that is challenging to study [30]. Overlapping of peaks will be caused by two factors: (i) the finite instrumental resolution and (ii) the intrinsic physical nature of the sample (i.e., solid or liquid) [31]. Increasing the instrument’s resolution can partly solve the first factor and give better-resolved peaks. However, this leads to a lower signal to noise ratio 1 and typically noisier scans [27]. In addition, choosing resolutions higher than 4 cm− for solid and liquid samples does not necessarily add more information and generally only results in noisier spectra [27]. The decreased spectral resolution due to the intrinsic physical nature of the sample can be partially overcome by mathematical band narrowing/resolution enhancement methods [30]. Fourier self-deconvolution, second derivative analysis, and band curve-fitting are three mathematical resolution enhancement methods that enable studying individual secondary structures within the highly complex amide I band [2,5,24]. These techniques allow the quantitative estimation of protein secondary structures [2,24,32]. Fourier self-deconvolution is a mathematical resolution enhancement method by which the spectrum is divided by the instrumental function to reverse signal distortion in the Fourier domain [4,31,33]. Appl. Sci. 2020, 10, 5918 3 of 16

Hence, it pulls apart and sharpens the overlapping hidden peaks. However, deconvolution can only be applied if the peaks are broader than the instrumental resolution [27]. In general, the deconvolution is an unstable numerical process that can produce hundreds or thousands of new peaks that are not real, a phenomenon known as overdeconvolution [27,31]. Therefore, precautions need to be taken while doing deconvolution as it might distort and destroy the original spectral data. Second derivative analysis can be used as a guide in the deconvolution process to distinguish the real peaks. Derivative spectroscopy involves the generation of the nth derivative of the original spectrum. While the first order derivative visualizes the rate of intensity change with respect to the wavenumber of an FTIR spectrum, the second derivative contains information on the change of this rate (slope) of the spectrum [6]. The presence of overlapping peaks and shoulders affects the change in the slope of the spectrum; which explains why studying the second derivative is a perfect tool to unveil overlapping features [27]. A minimum in the second derivative of a spectrum corresponds to a local maximum in the original spectrum [27]. Furthermore, the area under the second derivative peaks is proportional to the area of the corresponding peak in the original spectrum [27]. Thus, derivative spectroscopy can theoretically also be used for quantitative analysis. However, one has to keep in mind that the derivatives are especially sensitive to noise in the original spectrum. It is, hence, of utmost importance to have a good signal-to-noise ratio in the original spectra [27]. Alternatively, one can use smoothing techniques to reduce the noise level. One of such smoothing techniques is the Savitsky–Golay algorithm [27,31]. Several papers have used the second derivative analysis to estimate the contribution of each secondary structure in protein solutions [2,5,23]. However, the accurate measurements of the contribution of each secondary structure to the amide I band using this method have been elusive. Band curve-fitting was used in this paper to calculate quantitatively the area of each secondary structure [2,5,20–22], which is basically a three step process: (i) having a good initial idea about the physical state (i.e., hydration level) of your system to identify potential hidden overlapping peaks, (ii) using derivative spectroscopy in order to locate the overlapping hidden peaks [31,34], and finally (iii) curve fitting of the experimental spectrum by a function which is the sum of the individual peaks [31]. The goal of this paper is to describe a solid method for measuring and analyzing the spectral data to study protein secondary structures in high moisture matrices using vibrational spectroscopy techniques. For this purpose, a range of standard proteins with well-known secondary structures were analyzed in order to develop and test the method. Hydrated zein and gluten samples were then measured with the described method of data analysis. FT-Raman is used as a complementary technique to FTIR to study the protein secondary structures. The interference of water with the amide I band signal of proteins is minimized in FT-Raman analysis and, in contrast to what is done on FTIR data, no water subtraction is needed prior to peak fitting of the resulting Raman spectra.

2. Materials and Methods

2.1. Materials Immunoglobulin G (bovine, I-5506), concanavalin A (jack bean, C-2010), lysozyme (chicken egg white, L-6876), and trypsin (bovine pancreas, T-8253) were purchased from Sigma Aldrich (St. Louis, MO, USA). Zein from maize was obtained from Flo Chemical Corp (Ashburnham, MA, USA), while the commercial gluten flour was purchased from a local market (Bulk Barn, Guelph, ON, Canada).

2.2. Sample Preparation All reference protein samples were measured as 5.0% (w/v) aqueous solutions at pH 6.5 for FTIR analysis and 20% (w/v) for FT-Raman analysis. The hydrated zein and gluten samples were prepared by mixing each protein (20 g) with 75 g water for 5 min using a 100 g pin mixer. The hydrated zein was mixed at 40 ◦C in order to reach its glass transition temperature (Tg). Appl. Sci. 2020, 10, 5918 4 of 16

2.3. Attenuated Total Reflectance (ATR) FTIR Spectroscopy A Vertex 70 series spectrophotometer (Bruker Optics, Billerica, MA, USA) was used to study secondary structure of the proteins. This spectrometer was equipped with a Bio-ATR Cell II measurement accessory (to study reference protein solutions) and a horizontal multi-reflectance ZnSe crystal accessory (to study hydrated zein and gluten). The instrument housed a deuterated triglycine sulfate (DTgS) detector and a KBr beam splitter. The spectra of proteins were collected in 1 1 the 800–3000 cm− region at room temperature using 4 cm− resolution. An aperture diameter of 8 and 6 mm, and number of scans of 128 and 32 were used for reference proteins, and hydrated zein and gluten, respectively. A common problem associated with the accurate measurement of protein infrared spectra is the occurrence of liquid water and water vapor bands in the amide I region due to the presence of water vapor in the radiation path [5]. In order to minimize the presence of water vapor in the system, the internal humidity of the instrument was brought to zero by replacing the desiccants the night before measurement and purging the system with N2 gas during the measurement. The humidity in the instrument was zero during the measurements. The FTIR spectra of the protein solutions and hydrated proteins (sample measurement) and continuous phase (reference measurement) were collected at least in triplicate. All the measured spectra were subjected to a two-step normalization process, vector and offset. The vector normalization is used to correct for the differences in the depth of penetration and calculates the average of the y-value of the spectrum, which then is subtracted from the spectrum. The spectrum is then divided by the square root of the sum of the squares of all y-values. As a result, the spectra are scaled such, that the sum squared deviation over the indicated equals one [35]. The offset normalization is performed to correct for the baseline and it shifts the spectrum intensities in such way that the minimum absorbance will equal 0. All the original FTIR spectra shown in the paper are background corrected and normalized. The average of normalized reference spectra (Milli-Q water) was then subtracted from each normalized sample measurement. OPUS software (Bruker Optics, Billerica, MA, USA) was used for spectra acquisition, normalization, and subtraction of the reference spectrum [5]. The data are reported as mean values and standard deviations.

2.4. FT-Raman Measurement The FT-Raman spectra of proteins were recorded using a Bruker FRA 106/s module (Bruker, Billerica, MA, USA) on a Bruker IFS66vs FT-Raman spectrometer (Billerica, MA, USA) with excitation at 1 1064 nm and 2 cm− resolution in 180◦ backscattering geometry. A total of 4000 scans for zein and gluten 1 and 1000 scans for reference proteins were recorded between 1800 and 1100 cm− using a laser power of 525 mW. Hydrated zein and gluten samples were packed in a standard 2 mm cavity cell. The reference proteins solutions were measured in quartz cuvettes (10 mm path length). The baseline correction was conducted with a 5 point Savitsky–Golay function. All the measurements were conducted in duplicate. The data are reported as mean values and standard deviations.

2.5. Peak Fitting The spectra were analyzed using OriginPro 2019 (OriginLab Corporation, Northampton, MA, USA). Peak analyzer (using the Levenberg-Marquardt algorithm) was used to perform non-linear fitting of the peaks in the spectral data. Baseline corrections were performed using a second derivative (zeroes) method for finding anchor points and detecting the baseline. Hidden peaks were also detected using a second derivative method followed by smoothing with the 7–9 point Savitsky–Golay function with polynomial order of 2. The peak fitting was then performed using the Voigt function which is the convolution of a Gaussian function and a Lorentzian function [36] (Equation (1)); where y0 = offset, xc = center, A = area, Appl. Sci. 2020, 10, 5918 5 of 16

WG = Gaussian full width at half maxima (FWHM), WL = Lorentzian FWHM, t = wavenumber, n = number of peaks.

n Z 2 X 2ln2 W ∞ e t y = y + A L − dt (1) 0 3/2 2  2  2 π W √ WL √ x xc 1 G ln2 W + 4ln2 W− −∞ G G The baseline, peak center, peak width parameters were fixed and released during fitting to help with initializing the parameters. The iteration procedure was stopped when the best fit was achieved (reduced chi-square < 1 10 6). The residual data plots have been obtained for all the curve fittings × − and are shown in supplementary data files. All the secondary structural content was estimated by dividing the areas under the bands assigned to specific secondary structures by the total secondary structure area under the amide I band and reported as a percentage.

3. Results

3.1. Secondary Structure Estimation for Standard Proteins The infrared spectra of four native proteins (concanavalin A, immunoglobulin G, lysozyme, and trypsin) were investigated. Samples were allowed to stir for an hour at room temperature before recording the spectra in order to dissolve and hydrate completely. The FTIR spectrum of pure water was subtracted from the spectra of the protein solutions. Figure1a shows the FTIR spectrum of the standard protein solutions. All proteins show a similar peak 1 around 1636 cm− , which does not seem to give specific information about their secondary structure. However, after subtracting the reference water spectrum from the protein spectra (Figure1b), a more distinct spectrum with individual peaks appeared for each protein.

Figure 1. FTIR spectra of the standard proteins in aqueous solution (5.0% w/v); (a) original spectra (replicates), (b) water-subtracted spectra (replicates).

The individual underlying secondary structure components cannot be readily observed in the amide I band (Figure1). This is because the width of the di fferent component bands is larger than the separation between the individual component bands peaks [37]. Thus, the second derivative of the spectrum was used as narrowing/peak sharpening method to identify hidden peaks. By performing peak fitting on water-subtracted spectra according to the analysis described in the Materials and Methods section, the overlapping hidden peaks were identified and reconstructed. The overall curve fitted and the second derivative of the concanavalin A spectrum are shown in Figure2. The spectrum exhibits several discrete peaks in the amide I region. The minimum of the peaks in the second derivative spectrum corresponds to the maximum of the hidden absorbance peaks on the water-subtracted spectrum. The curve fitted and second derivative spectra of the other standard proteins are included in the Figures S1-1–S1-16). The curve fitted plots of three replications of each standard protein illustrated the high reproducibility between the replicates (Figures S1-1–S1-16). Appl. Sci. 2020, 10, 5918 6 of 16

Figure 2. Infrared spectrum in the amide I region of the aqueous solution of concanavalin A. The upper and lower figures represent the curve fitted, and the second derivative spectrum, respectively.

The characteristic mean absorption bands of the secondary structures in proteins are indicated in Table1. The secondary structures were estimated from (the sum of) the relative area of the peaks centered at these absorption [5,6].

Table 1. Secondary structure assignments of amide I band components in proteins a.

1 Amide I Position (cm− ) Assignment 1610–1627 Intermolecular β-sheet 1628–1642 β-sheet FTIR 1643–1650 Random coil 1650–1659 α-helix and Gln sidechain 1660–1699 β-turn 1620–1648 β-sheet 1649–1660 α-helix 1660–1665 Random coil Raman 1665–1680 β-sheet 1658–1680 β-turn 1680–1699 β-turn a Data adapted from refs [5,38,39].

The relative amount of each secondary structure of the proteins (Table2) is calculated from the area under the (hidden) peaks in the original spectra assigned to specific secondary structures. 1 The component centered between 1650–1659 cm− has been assigned to the α-helix secondary structure. 1 Bands in the region of 1610–1642 cm− are usually assigned to β-sheet structure [5,19]. The random coil 1 conformation shows IR bands around 1643 and 1649 cm− [19]. Upon peak fitting, four hidden bands 1 between 1610–1640 cm− appeared in the infrared spectrum of concanavalin A and immunoglobulin A which were all assigned to β-sheet secondary structures [5]. The water-subtracted spectra of concanavalin A and immunoglobulin G (Figure1b) exhibited a very strong amide I band maxima near 1 1636 cm− reflecting their high β-sheet content confirmed by X-ray studies [40,41]. The peak at about 1 1636 cm− was the major hidden band observed in immunoglobulin G and concanavalin A spectra, corresponding to 54% and 29% of the total amide I band area, respectively. Trypsin also showed a 1 dominant band at 1636 cm− comprising 70% of the total β-sheet content of the secondary structure. It also had 29 2% β-turn structure based on the bands in 1660–1699 cm 1 region. The water-subtracted ± − Appl. Sci. 2020Appl.,Appl.Appl.10, 5918Sci. Sci.Sci. 2020 20202020, ,,10 1010, ,,x xx FOR FORFOR PEER PEERPEER REVIEW REVIEWREVIEW 7 of 16 777 of ofof 17 1717 Appl. Sci. 2020, 10, x FOR PEER REVIEW 7 of 17 subtractedsubtractedsubtracted infrared infraredinfrared spectra spectraspectra of ofof lysozyme lysozymelysozyme showed showedshowed a aa re rerelativelylativelylatively narrow narrownarrow amide amideamide I I I band bandband with withwith 1 a aa maximum maximummaximum infrared spectra of lysozyme showed a relatively narrow amide I band with a maximum near 1654 cm− , subtracted infrared spectra of lysozyme showed a relatively narrow amide I band with a maximumnearnearnear 1654 16541654 cm cmcm−−1−1,1, , which whichwhich is isis the thethe characteristic characteristiccharacteristic of ofof proteins proteinsproteins with withwith a aa large largelarge content contentcontent of ofof α αα-helical-helical-helical secondary secondarysecondary which is the characteristic of proteins with a large content of α-helical secondary structure [19,23] −1 near 1654 cm , which is the characteristic of proteins with a large content of α-helical secondarystructurestructurestructure [19,23] [19,23][19,23] (Figure (Figure(Figure 3). 3).3). After AfterAfter curve curvecurve fitting, fitting,fitting, lysozyme lysozymelysozyme had hadhad a aa distinct distinctdistinct α αα-helical-helical-helical component componentcomponent1 of ofof 46% 46%46% (Figure3). After curve fitting, lysozyme had a distinct α-helical component of 46% at the 1654 cm− structure [19,23] (Figure 3). After curve fitting, lysozyme had a distinct α-helical componentatat atof the thethe 46% 1654 16541654 cm cmcm−−1−1 1 band bandband position. position.position. band position. at the 1654 cm−1 band position. TableTableTable 2. 2.2. Relative RelativeRelative amount amountamount of ofof protein proteinprotein secondary secondarysecondary structur structurstructureseses determined determineddetermined by byby FTIR FTIRFTIR and andand FT-Raman FT-RamanFT-Raman peak peakpeak Table 2. Relative amount of protein secondary structures determined by FTIR and FT-Raman peak Table 2. Relative amount of protein secondary structures determined by FTIR and FT-Raman peak fittingfittingfitting and andand comparison comparisoncomparison with withwith X-ray X-rayX-ray an ananddd circular circularcircular dichroism dichroismdichroism (CD) (CD)(CD) studies. studies.studies. fitting and comparison with X-ray and circular dichroism (CD) studies. fitting and comparison with X-ray and circular dichroism (CD) studies. SecondarySecondarySecondary Structure StructureStructure (%) (%)(%) ProteinProteinProtein Secondary Structure (%) MethodMethodMethod Secondary Structure (%) Protein ααα-Helix-Helix-Helix βββ-Sheet-Sheet-Sheet βββ-Turn-Turn-Turn RandomRandomRandom Coil CoilCoilMethod Protein Method α-Helix β-Sheet β-Turn Random Coil α-Helix β-Sheet β-Turn Random Coil 777 ± ±± 1 11 67 67 67 ± ±± 2 22 19 19 19 ± ±± 3 33 7 7 7 ± ±± 1 11 FTIR FTIR FTIR 7 1 67 2 19 3 7 1 FTIR 7 ± 1 67 ± 2 19 ± 3 7 ± 1 FTIR ImmunoglobulinImmunoglobulinImmunoglobulin± G GG ± 999 ±646464 212121 ± 6 6 6 FT-RamanFT-RamanFT-Raman Immunoglobulin G 9 64 21 6 FT-Raman Immunoglobulin G 9 64 21 6 FT-Raman 333 676767 181818 12 12 12 X-rayX-rayX-ray [42] [42][42] 3 67 18 12 X-ray [42] 3 67 18 12 X-ray [42] 999 ± ±± 1 11 57 57 57 ± ±± 1 11 22 22 22 ± ±± 1 11 12 12 12 ± ±± 0 00 FTIR FTIR FTIR 9 1 57 1 22 1 12 0 FTIR 9 ± 1 57 ± 1 22 ± 1 12 ± 0 FTIR ± ± 888 ±595959 232323 ± 10 10 10 FT-RamanFT-RamanFT-Raman ConcanavalinConcanavalinConcanavalin8 A AA 59 23 10 FT-Raman 8 59 23 10 FT-RamanConcanavalin A 333 606060 222222 15 15 15 X-rayX-rayX-ray [42] [42][42] Concanavalin A 3 60 22 15 X-ray [42] 3 60 22 15 X-ray [42] 8–20 41–678–208–208–20 8–1541–6741–6741–67 8–158–158–15 6–36 6–36 6–36 6–36 CD [7,8 CD] CD CD [7,8] [7,8][7,8] 8–20 41–67 8–15 6–36 CD [7,8] 16 2 46 1631616 ± ±± 2 22 29 46 46 46 ± ±2± 3 33 29 29 29 ± ±± 29 22 3 9 9 9 ± ±± 3 33 FTIR FTIR FTIR FTIR ± ± ± ± 16 ± 2 46 ± 3 29 ± 2 9 ± 3 FTIR Trypsin TrypsinTrypsinTrypsin14 44141414 29444444 292929 12 12 12 12 FT-RamanFT-RamanFT-RamanFT-Raman Trypsin 14 44 29 12 FT-Raman 9 56999 24565656 242424 11 11 11 11 X-ray [42X-rayX-rayX-ray] [42] [42][42] 46 3 21 1 26 1 8 0 FTIR 9 56 24 11 X-ray [42] ± ±464646 ± ±± 3 33 21 21 21± ± ±± 1 11 26 26 26 ± ±± 1 11 ± 8 8 8 ± ±± 0 00 FTIR FTIR FTIR 42 27 27 4 FT-Raman 46 ± 3 21 ± 1 26 ± 1 8 ± 0 FTIR Lysozyme 424242 272727 272727 4 4 4 FT-Raman FT-Raman FT-Raman LysozymeLysozymeLysozyme45 19 23 13 X-ray [42] 42 27 27 4 FT-Raman 454545 191919 232323 13 13 13 X-ray X-ray X-ray [42] [42][42] Lysozyme 45 21 26 8 CD [8] 45 19 23 13 X-ray [42] 454545 212121 262626 8 8 8 CD CD CD [8] [8][8] 45 21 26 8 CD [8]

1 −−1−11 Figure 3. FigureCurveFigureFigure 3. 3. fitted3. Curve CurveCurve amide fitted fittedfitted Iamide amideamide regions I I I regions regionsregions (1600–1700 (1600–1700 (1600–1700(1600–1700 cm− cm) cmcm in)) ) FTIR in inin FTIR FTIRFTIR spectra spectra spectraspectra of of ofof the the thethe referencereference referencereference proteins proteinsproteins ( (a(aa)) ) Figure 3. Curve fitted amide I regions (1600–1700 cm−1) in FTIR spectra of the reference proteinsproteins (a (a) ) immunoglobulinimmunoglobulinimmunoglobulinimmunoglobulin G, G,G, ( (b(bb)) ) concanavalinconcanavalin concanavalinconcanavalin A, A,A, ( (c(c)c) ) trypsin,trypsin, trypsin,trypsin, andand andand (( (d(dd))) ) lysozyme;lysozyme; lysozyme;lysozyme; α αα-helix,-helix,-helix,-helix, β ββ-sheet,-sheet,-sheet, β ββ-turn,-turn,-turn, and andand immunoglobulin G, (b) concanavalin A, (c) trypsin, and (d) lysozyme; α-helix, β-sheet, ββ-turn,-turn, and and random randomrandom coil coil coil areas areas areas are are are distinguished distinguisheddistinguished with withwith the the thethe following following followingfollowing patterns patterns patterns ( ( ( ),), ), ( ((), ), ), (((), ), ), ), and andand ( (( ), ), ), random coil areas are distinguished with the following patterns ( ), ( ), ( ), andand ( ), ), respectively.respectively.respectively.respectively. respectively. Appl. Sci. 2020, 10, 5918 8 of 16

FT-Raman spectra of the same reference proteins were collected to complement the FTIR data. For this purpose, the 20% w/v protein aqueous solutions were prepared and were allowed to stir for an hour at room temperature before measurement. The protein solutions were prepared at higher concentration for FT-Raman since FT-Raman spectra are characterized by a lower signal to noise ratio compared with FTIR. The FT-Raman spectra of standard proteins were then subjected to 15-point Savitsky–Golay smoothing to increase the signal to noise ratio. The original FT-Raman spectra of standard proteins in aqueous solutions show that water does not heavily distort the Raman spectra (Figure4). Water only shows a very weak Raman signal in the amide I region, making subtraction of the water spectrum redundant. Thus, the FT-Raman spectra of the proteins were not subjected to water subtraction.

Figure 4. FT-Raman spectra of standard proteins in aqueous solution (20% w/v).

The curve fitted plots from the FT-Raman profiles show the presence of different components in 1 1 the amide I region (Figure5). The regions between 1649 and 1660 cm − , and 1660 and 1665 cm− are 1 attributed to α-helix and random coil structures, respectively. The region between 1620 and 1647 cm− , 1 and 1665 and 1680 cm− are signature regions for β-sheet structures [43,44], while bands centered 1 between 1680 and 1699 cm− are assigned to β-turn structures. The quantitative analysis of the area under each FTIR band revealed very similar and consistent results to the quantitative analysis of the 1 FT-Raman bands (Table2). Lysozyme exhibited a dominant α-helical component around 1654 cm− (Figure5) corresponding to 42% of its total secondary structural content. Both concanavalin A and 1 immunoglobulin G showed a major band at about 1669 cm− (30% of the total amide I band), which was assigned to β-sheet secondary structures. Peak fitting of the amide I band of trypsin also produced distinct components at 12 wavenumber values (Figure5). β-sheet was the dominant secondary structure of trypsin as was also observed in its FTIR spectrum. Appl.Appl.Appl. Sci. Sci.Sci. 2020 20202020, ,,10 1010,, ,x xx FOR FORFOR PEER PEERPEER REVIEW REVIEWREVIEW 999 of ofof 17 1717 Appl. Sci. 2020, 10, x FOR PEER REVIEW Appl. Sci. 2020, 109, 5918of 17 9 of 16

1 −−1−11 Figure 5. CurveFigureFigureFigure fitted 5. 5.5. Curve CurveCurve amide fitted fittedfitted I region amide amideamide I (1600–1700I I region regionregion (1600–1700 (1600–1700(1600–1700 cm− ) in cm cmcm FT-Raman)) ) in inin FT-Raman FT-RamanFT-Raman spectra spectra spectraspectra of the of ofof the reference thethe reference referencereference proteins proteinsproteins Figure 5. Curve fitted amide I region (1600–1700 cm−1) in FT-Raman spectra of the referenceproteins proteins (a ) immunoglobulin((a(aa)) )immunoglobulin immunoglobulinimmunoglobulin G, G, ( G,bG,) ( (b concanavalin(bb)) )concanavalin concanavalinconcanavalin A, A, A, (A,c )( (c( trypsin,cc)) )trypsin, trypsin,trypsin, and and andand (d ( ( )d(dd lysozyme;)) )lysozyme; lysozyme; lysozyme;α α α -helix,α-helix,-helix,-helix,β β β-sheet,β-sheet,-sheet,-sheet, β β β-turn,-turn,-turn, and andand (a) immunoglobulin G, (b) concanavalin A, (c) trypsin, and (d) lysozyme; α-helix, β-sheet, ββ-turn,-turn, and and random randomrandom coil coil coil areas areas areas are are are distinguished distinguished distinguished with with withwith the the thethe following following followingfollowing patterns patterns patterns ( ( ( ),), ), ( ((), ), ), (((), ), ), ), and andand ( (( ), ), ), random coil areas are distinguished with the following patterns ( ), ( ), ( ), andand ( ), ), respectively.respectively.respectively.respectively. respectively. Goodness-of-fitGoodness-of-fitGoodness-of-fitGoodness-of-fit tests were usedtests teststests were towerewere assess used usedused all to toto peak assess assessassess fittings. all allall peak peakpeak By fittings. fittings. performingfittings. By ByBy performing performingperforming the nonlinear the thethe curve nonlinear nonlinearnonlinear curve curvecurve Goodness-of-fit tests were used to assess all peak fittings. By performing thefitting, nonlinear the reducedfitting,fitting,fitting, curve the the the chi-square reduced reducedreduced ischi-square chi-squarechi-square minimized is isis minimized inminimizedminimized the iteration in inin the thethe process iteration iterationiteration to obtain process processprocess the to toto optimal obtain obtainobtain the thethe parameter optimal optimaloptimal parameter parameterparameter fitting, the reduced chi-square is minimized in the iteration process to obtain thevalues. optimal Theparametervalues.values.values. reduced The TheThe chi-square reducedreducedreduced chi-squarechi-square ischi-square obtained isisis by obtainedobtainedobtained dividing bybyby the dividingdividingdividing residual thethethe sum residuresiduresidu of squarealalal sumsumsum (RSS) ofofof squaresquaresquare by the (RSS)(RSS)(RSS) bybyby thethethe values. 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(also R RR22 2 value valueknownvalue (also (also(also as coe known knownknownfficient as asas ofcoefficient coefficientcoefficient determination) of ofof determination) determination)determination) is another is isis another anotheranother 2 not be justified for the given dataset. R2 value (also known as coefficient of determination)measure ofis measure theanothermeasuremeasure goodness-of-fit. of ofof the thethe goodness-of-fit. goodness-of-fit.goodness-of-fit. The closer the The TheThe fitted closer closercloser value the thethe fitted fittedisfitted to the value valuevalue actual is isis to toto data the thethe actualpoint, actualactual thedata datadata closer point, point,point, R the thethewill closer closercloser R RR22 2 will willwill measure of the goodness-of-fit. The closer the fitted value is to the actual data point,be the to the closer valuebebebe R to2 to to ofwill the thethe 1. Thisvalue valuevalue will of ofof 1. 1. be1. 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The adjusted R2 can be a better measure of goodness-of fit as itnumber also penalizes of modelthethethe number number numberfor parameters. of ofof model modelmodel The parameters. parameters.parameters. reduced chi-square, The TheThe reduced reducedreduced R , and chi-square, chi-square,chi-square, adjusted R RR 22,2, , and andareand reportedadjusted adjustedadjusted for R RR22 2 are eachareare reported reportedreported peak for forfor each eacheach the number of model parameters. The reduced chi-square, R2, and adjusted R2 arefitting reported in the peakforpeakpeak Tables each fitting fittingfitting S1-1–S1-16) in inin the thethe Tables TablesTables and Tables S1-1–S1-16) S1-1–S1-16)S1-1–S1-16) S2-1–S2-10. and andand Tables TablesTables S2-1–S2-10. S2-1–S2-10.S2-1–S2-10. peak fitting in the Tables S1-1–S1-16) and Tables S2-1–S2-10. 3.2. Secondary3.2.3.2.3.2. Structure Secondary SecondarySecondary Estimation Structure StructureStructure for Estimation EstimationEstimation Gluten and for forfor ZeinGluten GlutenGluten and andand Zein ZeinZein 3.2. Secondary Structure Estimation for Gluten and Zein In the presentInInIn the study, thethe present presentpresent the secondary study, study,study, the thethe structure secondary secondarysecondary of gluten structure structurestructure was of of studiedof gluten glutengluten after was waswas hydration studied studiedstudied after afterafter and hydration hydration mixinghydration for and andand mixing mixingmixing In the present study, the secondary structure of gluten was studied after hydration5 min. The andfor measurementfor formixing 5 55 min. min.min. The TheThe and measurement measurementmeasurement data analysis and andand were data datadata conducted analysis analysisanalysis we basedwewererere conducted conductedconducted on the method based basedbased described on onon the thethe method methodmethod and tested described describeddescribed and andand 1 for 5 min. The measurement and data analysis were conducted based on the methodon the described referencetestedtestedtested and proteins. on onon the thethe reference referencereference For FTIR proteins. proteins.proteins. spectra For ofForFor gluten FTIR FTIRFTIR spectr spectr andspectr zein,aaa of ofof gluten aglutengluten wider and andand range zein, zein,zein, (1500–1700 a aa wider widerwider range rangerange cm− (1500–1700 (1500–1700)(1500–1700 has cm cmcm−−1−1)1) ) tested on the reference proteins. For FTIR spectra of gluten and zein, a wider rangebeen (1500–1700 selectedhashashas tocm been beenbeen perform−1) selected selectedselected peak to toto fitting perform performperform in order peak peakpeak to fitting fittingfitting do a proper in inin order orderorder baseline to toto do dodo a a correction.a proper properproper baseline baselinebaseline However, correction. correction.correction. the amide However, However,However, the thethe has been selected to perform peak fitting in order to do a proper baseline correction.II band However, hasamideamide notamide beenthe IIII II subjectedbandbandband hashashas to notnotnot the beenbeen quantitativebeen subjectedsubjectedsubjected analysis tototo thethethe because quanquanquantitativetitativetitative of its less analysisanalysisanalysis protein becausebecausebecause conformational ofofof itsitsits lesslessless proteinproteinprotein 1 amide II band has not been subjected to the quantitative analysis because sensitivityof its less conformational comparedconformationalproteinconformational with sensitivity sensitivity amidesensitivity I [6 compared compared].compared Nevertheless, with withwith amide amideamide the peaks I I I [6]. [6].[6]. Nevertheless, Nevertheless,Nevertheless, at 1540, 1545, the thethe and peaks peakspeaks 1551 at atat cm 1540, 1540,1540,− 1545,are 1545,1545, and andand 1551 15511551 α 1 β conformational sensitivity compared with amide I [6]. Nevertheless, the peaks at 1540,usually 1545, assigned andcmcmcm− −15511−1 1 are areare to usually usuallyusually-helical assigned assignedassigned structure, to toto whileα αα-helical-helical-helical the structure, peaksstructure,structure, at 1520 while whilewhile to the the 1525the peaks peakspeaks cm− at atatare 1520 15201520 assigned to toto 1525 15251525 to cm cmcm-sheet−−1−1 1 are areare assigned assignedassigned to toto cm−1 are usually assigned to α-helical structure, while the peaks at 1520 to 1525 cmsecondary−1 are assigned structuresβββ-sheet-sheet-sheet to secondary secondarysecondary [45]. structures structuresstructures [45]. [45].[45]. β-sheet secondary structures [45]. The curve fittedTheTheThe curve curvecurve spectra fitted fittedfitted obtained spectra spectraspectra from obtained obtainedobtained three from replicatesfromfrom three threethree of rep reprep hydratedlicateslicateslicates of ofof gluten hydrated hydratedhydrated samples gluten glutengluten show samples samplessamples good show showshow good goodgood The curve fitted spectra obtained from three replicates of hydrated gluten samplesreproducibility showreproducibilityreproducibilityreproducibility good (Figures S2-1–S2-10). (Figures (Figures(Figures S2-1–S2-10). TheS2-1–S2-10).S2-1–S2-10). relative secondary The TheThe relative relativerelative structure secondary secondarysecondary contents structure structurestructure of hydrated contents contentscontents gluten of ofof hydrated hydrated werehydrated gluten glutengluten α β reproducibility (Figures S2-1–S2-10). The relative secondary structure contents estimatedof hydrated fromwerewerewere gluten peak estimated estimatedestimated fitting from fromfrom of both peak peakpeak FTIR fitting fittingfitting and of ofof FT-Raman both bothboth FTIR FTIRFTIR results. and andand FT-Raman FT-RamanFT-Raman The percentage results. results.results. of The TheThe-helix, percentage percentagepercentage-sheet, of ofof α αα-helix,-helix,-helix, β ββ--- were estimated from peak fitting of both FTIR and FT-Raman results. The percentage of α-helix, β- Appl.Appl.Appl. Sci. Sci. Sci.2020 2020 2020, 10, 10, x10, FORx, xFOR FOR PEER PEER PEER REVIEW REVIEW REVIEW 1010 of10 of 17 of 17 17 Appl. Sci. 2020, 10, 5918 10 of 16 Appl.Appl.Appl. Sci. Sci. Sci.2020 2020 2020, 10, 10, x10, xFOR, FORx FOR PEER PEER PEER REVIEW REVIEW REVIEW 1010 of10 of 17 of 17 17 sheet,sheet,sheet, β -turn,β β-turn,-turn, and and and random random random coil coil coil structures structures structures are are are 36 36 36± ±1, ±1, 42 1, 42 ±42 ±1, ±1, 22 1, 22 ±22 ±0, ±0, and 0, and and 0 0± 0±0%, ±0%, 0%, respectively, respectively, respectively, as as obtainedas obtained obtained sheet,sheet,sheet, β β-turn, -turn,β-turn, and and and random random random coil coil coil structures structures structures are are are 36 36 ±36 ±1, ±1, 42 1, 42 ±42 ±1, ±1, 22 1, 22 ±22 ±0, ±0, and 0, and and 0 0± 0±0%, ±0%, 0%, respectively, respectively, respectively, as as obtainedas obtained obtained fromfromfrom FTIR FTIR FTIR βanalysis. -turn,analysis. analysis. and This This This random data data data was was coil was consistent structuresconsistent consistent with with are with the 36 the the FT-Raman FT-Raman1, FT-Raman 42 1, results 22 results results0, thatand that that indicate 0indicate indicate0%, the respectively, the the presence presence presence ofas of of obtained fromfromfrom FTIR FTIR FTIR analysis. analysis. analysis. This This This data data data was was was consistent consistent consistent with with with the the the ±FT-Raman FT-Raman FT-Raman± results results results± that that that indicate indicate ±indicate the the the presence presence presence of of of 3636 36± ±5, ±5, 485, 48 48±from ±6, ±6, 226, 22 FTIR22± ±7, ±7, and7, analysis.and and 0 0± 0±0% ±0% 0% Thisα -helix,α α-helix,-helix, data β -sheet, wasβ β-sheet,-sheet, consistent β -turn,β β-turn,-turn, and withand and random random the random FT-Raman coil coil coil structure, structure, structure, results respectively. thatrespectively. respectively. indicate The The the The presence 3636 36± ±5, ±5, 485, 48 48± ±6, ±6, 226, 22 22± ±7, ±7, and7, and and 0 0± 0 ±0% ±0% 0% α α-helix, -helix,α-helix, β β-sheet, -sheet,β-sheet, β β-turn, -turn,β-turn, and and and random random random coil coil coil structure, structure, structure, respectively. respectively. respectively. The The The FT-RamanFT-RamanFT-Raman ofspectra spectra36 spectra5 ,of 48of ofgluten gluten gluten6, 22 (Figure (Figure (Figure7, and 6) 06) shows6) shows 0%showsα 10-helix, 10 10major major majorβ-sheet, bands bands bands βrelated -turn,related related andto to tosecondary randomsecondary secondary coil structure. structure. structure,structure. The The respectively.The FT-RamanFT-RamanFT-Raman spectra spectra spectra± of of ofgluten ±gluten gluten (Figure ±(Figure (Figure 6) 6) −shows6)1 ± shows−1 − shows1 10 10 10major major major bands bands bands related related related to to tosecondary secondary secondary structure. structure. structure. The The The bandsbandsbands at at 1632,at The1632, 1632, FT-Raman1641, 1641, 1641, 1673, 1673, 1673, spectraand and and 1680 1680 1680 of cm gluten cm cmareareare (Figure assigned assigned assigned6) showsto to toβ -sheetβ β-sheet 10-sheet major secondary secondary secondary bands structures, structures, related structures, to while secondarywhile while those those those structure. −1− 1 −1 centeredbandsbandscenteredcenteredbands at at at1632,at 1632,at 1664,at1632, 1664, 1664, 1641, 1641, 1686,1641, 1686, 1686, 1673, 1673, and1673, and and and 1693and 1693and 1693 1680 1680cm 1680cm cm− 1cm −arecm1− are1cm are originatingare areoriginating originatingare assigned assigned assigned 1from fromto fromto βto β-sheet -turn-sheetβ β-turn-sheet-turn secondarysecondary secondarysecondary secondarysecondary structures,structures. structures,structures. structures,structures. whileThe whileThe whileThe α -helixαthose α-helixthose -helixthose The bands at 1632, 1641, 1673, and 1680 cm− are assigned to β-sheet secondary structures, while those −1− 1 −1 bandscenteredcenteredbandsbandscentered were were atwere at 1664,atcentered 1664, centered 1664,centered 1686, 1686, 1686, at at and 1649 atand 1649 and1649 1693 and1693 and1693 and cm1655 cm1655 cm1655are cmare cm are cm−originating1 .originating− 1 The−.originating1 The. The1 three three three from lowfrom lowfrom low frequencyβ frequencyβ-turn frequency-turnβ-turn secondary secondary secondarybands bands bands near structures.near structures.near structures. 1604 1604 1604 and and Theand The 1609The 1609 α1609 α-helix -helixcmα -helixcm cm−1 −1 − 1 centered at 1664, 1686, and 1693 cm− are originating from β-turn secondary structures. The α-helix −1−1 −1 −1−1 −1 dobandsbandsdo dobandsnot not not were contributewere contribute werecontribute centered centered centered to to thetoat atthe the1649at secondary1649 secondary1649 secondary and and and 1655 1655 structure1655 structure cmstructure cm cm. The. The.and Theand andthree threeare threeare 1are relatedlow lowrelated relatedlow frequency frequency frequencyto to aromaticto aromatic aromatic bands bands bands side sidenear sidenear nearchain chain 1604 chain1604 1604 of andof andaminoof andamino 1609amino 1609 1609 acids cm acids cmacids cm 1 bands were centered at 1649 and 1655 cm− . The three bands near 1604 and 1609 cm− dodo donot not not contribute contribute contribute to to theto the the secondary secondary secondary structure structure structure and and and are are are related related related to to aromaticto aromatic aromatic side side side chain chain chain of of aminoof amino amino acids acids acids [46].[46].[46]. do not contribute to the secondary structure and are related to aromatic side chain of amino acids [46]. [46].[46].[46].

FigureFigureFigure 6. 6.Curve 6. Curve Curve fitted fitted fitted amide amide amide I andI andI and II IIregions II regions regions in in ( ina ()a (FTIR)a FTIR) FTIR and and and (b ()b (FT-Ramanb) FT-Raman) FT-Raman spectra spectra spectra of of hydrated of hydrated hydrated gluten; gluten; gluten; αFigureFigure-helix,ααFigure-helix,-helix, 6. 6.β Curve -sheet, 6.βCurve Figure-sheet,β Curve-sheet, fitted fittedand 6.fittedand andCurve amideβ amide-turnβ amide-turnβ-turn fittedI andIareas andIareas andareas amideII II regionsare IIregionsare regionsare Ifilled andfilled filledin in II( withina ( regions)awith (FTIR)witha FTIR) theFTIR the andthe inandfollowing and(following a(followingb )(b) FTIR (FT-Raman)b FT-Raman) FT-Raman andpatterns patterns patterns (b )spectra FT-Ramanspectra spectra( ( ( of of ), hydrated of ),hydrated( spectra ), hydrated( ( ), ), ( ofgluten; ), gluten;( hydrated (gluten; ), ), ), gluten; respectively.αα-helix,respectively.-helix,respectively.α-helix, β -sheet,β -sheet,αβ -helix,-sheet, and and βand-sheet, β -turnβ -turnβ-turn and areas areas βareas-turn are are areasare filled filled filled are with filledwith with the withthe the following following the following following patterns patterns patterns patterns ( ( ( ( ), ),),( ),( ( ( ),), ),( ( ),( (), ), respectively. ), ), respectively.respectively.respectively. TheTheThe secondary secondary secondaryThe secondarystructure structure structure of structureof zeinof zein zein was was was ofalso also zeinalso investigated investigated investigated was also investigatedafter after after hydration hydration hydration after and and hydrationand mixing mixing mixing with andwith with water mixing water water for for withfor water TheTheThe secondary secondaryfor secondary 5 min structure atstructure structure 40 ◦C (Figureof of zeinof zein zein 7was ).was was The also also also amount investigated investigated investigated of α-helix, after after after hydration βhydration -sheet,hydrationβ and -turn,and and mixing mixing mixing and randomwith with with water water water coil for for were for 34 2, 5 5min 5min min at at 40at 40 40°C °C °C(Figure (Figure (Figure 7). 7). 7).The The The amount amount amount of of αof -helix,α α-helix,-helix, β -sheet,β β-sheet,-sheet, β -turn,β β-turn,-turn, and and and random random random coil coil coil were were were 34 34 34± ±2, ±2, 422, 42 42± ±4, ±4, 4, ± 5 5min 5min min at at 40at 4042 40°C °C °C(Figure 4(Figure, (Figure 24 7).4, 7). and7).The The The 0amount amount amount0%, respectively, of of αof α-helix, -helix,α-helix, β basedβ-sheet, -sheet,β-sheet, on β β-turn, FTIR-turn,β-turn, and measurements. and and random random random coil coil coil These were were were data34 34 34± ±2,matched ±2, 422, 42 42± ±4, ±4, 4, well with 2424 24± ±4, ±4, and4, and and 0 ±0± 0 ±0%, ±0%, 0%, respectively,± respectively, respectively,± based based based on on onFTIR FTIR FTIR measurements. measurements. measurements. These These These data data data matched matched matched well well well with with with FT- FT- FT- α β β Raman2424Raman Raman24± ±4, ±4, andresults4, and results andresultsFT-Raman 0 0± 0showing ±0%, showing±0%, showing 0%, respectively, respectively, results respectively, 36 36 36± ± showing2, ±2, 452, 45 based45± based ± 2, based ±2, 36182, 18 on 18±on ±4, 2,on FTIR± 4, FTIRand 454, FTIRand and measurements.0 2, measurements.0± 0measurements. 18±0% ±0% 0% of4, of αof and -helix,α α-helix,-helix, 0 These These β 0%These -sheet,β β-sheet, -sheet,ofdata data data -helix,β -turn,matchedβ matchedβ-turn, -turn,matched and-sheet, and andwell randomwell randomwell random with -turn,with with coil,FT- coil,FT- andcoil, FT- random ± ± 2± ± 2 respectively.RamanRamanrespectively.respectively.Raman results results resultscoil, The showingThe respectively. showingThe showingreduced reduced reduced 36 36 36±chi-square, ± The2,chi-square, ±2,chi-square, 452, 45 reduced 45± ±2, ±2, 182, 18R 18±2R chi-square,,±R 4,2 ,and±4,2 , and 4, and andadjusted 0adjusted 0adjusted± 0 ±0% R±0% 0% ,of andofR αof2R α-helix,R2of adjusted-helix,α2of -helix,ofgluten gluten glutenβ β-sheet, -sheet,β R-sheet,and and ofand β zeingluten β-turn,zein -turn,βzein-turn, peak peak and and peakand and fittingsrandom zein fittingsrandom fittingsrandom peak were coil, were coil,werefittings coil, were 2 2 2 2 calculatedrespectively.respectively.calculatedcalculatedrespectively. calculatedto to assesstoThe assessThe assessThe reduced reducedthe toreducedthe the goodness assess goodness goodness chi-square, chi-square, thechi-square, of goodness of fit.of fit. fit.TheR TheR2 ,The R, and ofR2and, 2 R fit.andR2 and2adjusted andadjusted The adjusted-adjusted adjusted- adjusted-R andR R2 R Rof adjusted-2R2 ofvaluesR 2 ofgluten2values glutenvalues gluten wereR wereand wereand valuesand > zein >0.99 zein > 0.99zein 0.99 were forpeak peakfor forpeak all> all fittings all0.99peakfittings peak fittingspeak for fittings fittingswere allfittingswere were peak fittings indicatingcalculatedcalculatedindicatingindicatingcalculated indicatingthatto tothat assessthatto assess the assess the the fitted thefitted the thatfitted the goodness valuesgoodness thevaluesgoodness values fitted ar arofe arof valueseclose fit. ofe closefit. close fit.The Theto The areto thetoR theR2 closetheand 2Ractual and 2actual and actual adjusted- toadjusted- adjusted-data the data data actual points pointsR pointsR2 2valuesR values data2 (Tablesvalues (Tables (Tablespoints were were wereS2-1–S2-10). S2-1–S2-10). >S2-1–S2-10). (Tables >0.99 >0.99 0.99 for for S2-1–S2-10). for all Theall The all peakThe peak chi-square peak chi-square chi-square fittings fittings fittings The chi-square valueindicatingindicatingvaluevalueindicating was was was valuereducedthat thatreduced reducedthat the the was the fitted to fitted to reduced fittedlessto less valuesless valuesthan valuesthan than to 1E-6arless 1E-6ar e 1E-6ar eclose andeclose than andclose and theto 1E-6tothe theto fitthe fitthe andactualwasfit actualwas actualwas thecompletely completelydata completely fitdata data was points points points completely converged converged(Tables converged(Tables (Tables S2-1–S2-10). converged S2-1–S2-10).in S2-1–S2-10).in allin all allcurve-fittings. curve-fittings. curve-fittings. in The The all The chi-square curve-fittings. chi-square chi-square valuevaluevalue was was was reduced reduced reduced to to lessto less less than than than 1E-6 1E-6 1E-6 and and and the the the fit fit wasfit was was completely completely completely converged converged converged in in allin all allcurve-fittings. curve-fittings. curve-fittings.

FigureFigureFigure 7. 7.Curve 7. CurveFigure Curve fitted fitted 7.fittedCurve amide amide amide fitted I andI Iand andamide II IIregions II regions regions I and in IIin (ina regions() a (FTIR)a )FTIR FTIR and in and (anda ()b ( FTIR) b (FT-Ramanb) )FT-Raman FT-Raman and (b) spectra FT-Raman spectra spectra of of hydratedof spectrahydrated hydrated ofzein; zein; hydrated zein; zein; αFigureFigure-helix,ααFigure-helix,-helix, 7. 7.β Curve -sheet, 7.β Curveα-sheet,β Curve-sheet,-helix, fitted andfitted andfitted βand-sheet, amideβ amide-turnβ amide-turnβ-turn and I areasIand areasand βI areasand-turn II IIare regions IIare regions areasare regionsfilled filled filled arein inwith ( filledin awith ()awith ()FTIR a FTIRthe) withFTIRthe the andfollowing and thefollowing andfollowing ( b following(b) ()FT-Ramanb FT-Raman) FT-Ramanpatterns patterns patterns patterns spectra spectra( spectra( ( ( ),of ),of(), ), hydratedof( (hydrated( hydrated ),), ),( ( ),( zein;( zein; ),zein; ), respectively. ), ), respectively.αα-helix,respectively.-helix,respectively.α-helix, β -sheet,β -sheet,β -sheet, and and and β -turnβ -turnβ-turn areas areas areas are are are filled filled filled with with with the the the following following following patterns patterns patterns ( ( ( ), ),( ),( ( ), ),( ),( ( ), ), ), respectively.respectively.respectively. Appl. Sci. 2020, 10, 5918 11 of 16

4. Discussion As mentioned earlier, the amide I band in FTIR spectra is mainly composed of C=O stretching (around 80%) [37] and, to a lesser extent, NH bending vibrations. The exact location of these vibrations depends on the hydrogen bonds these C=O form with proximate NH groups [19]. The secondary structure of a protein determines with which NH group hydrogen bonds will be formed, turning the vibrational spectra into fingerprints of the secondary structure [6]. The secondary structure of a protein backbone is considered as the linear sum of some fundamental secondary structural elements (α-helix, β-sheet, β-turn, and random coil) [6]. The percentage of each secondary structure is only related to their spectral intensity since the molar absorptivity of C=O stretching vibration for all secondary structural elements is essentially the same [6]. As stated above, the secondary structure of four standard proteins was investigated by both FTIR and FT-Raman. These proteins were chosen because of their known three-dimensional structures that have been extensively studied by circular dichroism [8,9], FTIR [5], Raman spectroscopy [47], and X-ray crystallography [42,48]. Inspection of the FTIR spectra showed that while the amide I band shows the same peak position in original spectra, the band shapes were quite different after water subtraction (Figure1). This shows the necessity of the water subtraction for FTIR spectra since the broad and intense peak of water overlapping with the amide I region makes the protein fingerprint peaks difficult to distinguish [27]. Conversely, FT-Raman spectra were not subjected to water subtraction due to the weak signal of OH stretching vibration (of water) in the Raman amide I region [29]. Curve fitting was done (Figure3) to analyse the FTIR spectra in a quantitative way. The relative amounts of each secondary structure of the four proteins calculated as outlined above were consistent with the relative amounts reported in previous FTIR [5], circular dichroism [9], and X-ray crystallography [42] studies. Concanavalin A is often used as a reference protein for FTIR analysis since it is known for its high content of β-sheet structure. The curve-fitted spectrum of concanavalin 1 A showed a peak maximum around 1636 cm− corresponding to the antiparallel intramolecular β-sheet conformation which is the main secondary structural component in concanavalin A [37,49]. 1 An intense band was also observed at 1626 cm− , which is associated to the intermolecular β-sheets with stronger hydrogen bonds. It has been proposed that this band comes from the so-called “distorted β-type structures” that are formed by peptide residues located at the end of the main strands of the 1 β-sheets [37]. The band around 1618 cm− is also attributed to intermolecular β-sheets with strong H-bonds [49]. It is worthy to note in this context that a stronger hydrogen bond will lead to a lower C=O stretching frequency [50]. The band assignment of protein secondary structures is further complicated by absorption of side chains in the protein structures [38]. This absorption is superimposed on the amide I and II bands absorption (Table3) and contributes 10 to 20% of the overall absorption of globular proteins in the amide I and II regions [6,20,21]. Aromatic side chains of amino acids also contribute to the FT-Raman amide I and II regions. In particular, tyrosine, phenylalanine, and tryptophan show 1 1 overlapping peaks at about 1618, 1585, and 1609 cm− , respectively [49,50]. The 1615–1618 cm− peaks observed in FTIR spectra of the proteins, which are assigned to intermolecular β-sheet, is due to the 1 tyrosine aromatic side chains in the FT-Raman spectra. The bands at about 1605 and 1616 cm− were present in all reference protein FT-Raman spectra (Figure5) and correspond to the ring vibrations from aromatic residues. These bands were not included in the quantitative analysis of the FT-Raman 1 results; only the area under the peaks present between 1620 and 1699 cm− region were studied for the FT-Raman analysis of the protein secondary structure. In addition to the structural analysis of the reference proteins, the secondary structure of gluten and zein proteins was also investigated by both FTIR and FT-Raman spectroscopy using the same analysis method optimized for the reference proteins. Similar to the procedure for reference proteins, the pure liquid water spectrum was subtracted from the FTIR spectra of zein and gluten. Other approaches to correct for water for the hydrated states of gluten proteins have already been explored such as using spectra of H2O-D2O mixtures as the correcting spectra [18]. However, the bending frequency of HDO Appl. Sci. 2020, 10, 5918 12 of 16

(Deuterium hydrogen oxide) coincides with the amide II band, which makes its analysis virtually impossible [1]. In addition, the change in the shape of the amide II band as a result of HDO signal can affect the peak fitting of the amide I since it can change the baseline of the spectrum. Therefore, the pure water spectrum was subtracted from the zein and gluten FTIR spectra in this study.

1 a Table 3. Absorbance bands of amino acid side chains in the 1600–1700 cm− .

1 Amino acid Absorbance Band Assignment IR Frequency Position (cm− ) C=O (stretching) 1678 3 Asparagine ± NH bending 1622 2 ± C=O stretching 1670 4 Glutamine ± N-H bending 1610 4 ± C=N asymmetric 1673 3 Arginine ± C=N symmetric stretching 1633 3 ± Lysine NH+ asymmetric bending 1629 1 ± Tyrosine Ring vibration 1602 2 ± a Data adopted from refs [6,51].

Gluten proteins are typically classified into two major sub-groups: glutenins and gliadins [52]. The ‘monomeric’ gliadins, which are imparting viscosity in a viscoelastic gluten network, are often described to be built as a three domain structure: a short N-terminal domain, a repetitive central domain rich in glutamine and , and a non-repetitive C-terminal domain rich in sulfur containing amino acids. According to previous reports, the N-and C-terminal domains are rich in α-helix structures, while the central domain mainly adopts β-turn secondary structures in hydrated gluten [52,53]. The glutenin macropolymers have a similar three domain structure. In hydrated gluten, the glutenin central domain comprises mainly β-turn secondary structures forming β-spiral super secondary structures [53]. The β-spirals are assumed to contribute to the intrinsic elasticity of a viscoelastic gluten network [54]. Based on the loop and train model proposed by Belton [55], β-turn structures are present in the loop regions (water-protein interactions) while the intermolecular β-sheets are dominating the train regions (protein-protein interactions). It seems that the interchain β-sheet structures are formed at the expense of β-turns [18]. The intermolecular β-sheet structure showed two signature peaks at 1616 1 and 1623 cm− [49], corresponding to 36% of the total amide I band. As mentioned earlier, this strong 1 short wavenumber peak (1616 cm− ) is specifically due to the β-sheets with stronger hydrogen bonds [37,49], and its presence shows the formation of high amount of intermolecular β-sheets upon hydration and mixing of gluten. The formation of intermolecular β-sheets has been also attributed to the association of high molecular weight (HMW) glutenin subunits [56]. Zein proteins lack the HMW 1 glutenin subunit-type structures [57] which can explain the absence of 1616 cm− hidden band in the zein FTIR spectra (Figure7a) compared with gluten FTIR spectra (Figure6a). Similarly, the band at 1 1620 cm− in FT-Raman spectra is also assigned to intermolecular hydrogen-bonded β-sheets [58] which is more pronounced in hydrated gluten FT-Raman spectra (Figure6b) compared with what is 1 observed for hydrated zein (Figure7b). In addition, the absorption band at 1636 cm − is characteristic of amide groups involved in the extended β-sheets in the gluten network [59]. The appearance of this band has been attributed to kneading and stretching processes [59]. The gluten in its unhydrated state (9% moisture content) has been reported to contain 39% β-sheet, 30% random coil, 17% α-helix, and 14% β-turn structure [18]. Therefore, β-sheet and random coil are the main secondary structural elements of gluten at low moisture contents. Upon hydration (up to 50% w/w), Bock and Damodaran [18] reported an increase in β-turn (from 14 to 65%) at the expense of decrease in β-sheet and random coil structure. They suggested that the β-turn is the preferred secondary structure of gluten in its hydrated state. These results are not in line with our results as β-sheets are found to be the dominating secondary structures in the here studied hydrated gluten samples. However, the systems studied by Bock and Damodaran [18] were completely different compared with the here studied gluten-only samples. The buildup of this high β-sheet content in the Appl. Sci. 2020, 10, 5918 13 of 16 hydrated gluten is a result of mechanical input energy during the mixing process [11], which also 1 possibly resulted in the formation of intermolecular β-sheets observed at 1616 and 1623 cm− (Figure6). Zein proteins are highly hydrophobic. Commercial zein is protein-body-free and mainly contains α-zein [60]. Four domains can be distinguished in the α-zein structure: an N-terminal signal sequence, an N-terminal β-turn domain, a domain consisting of nine repeating sequences (flanked by glutamine residues), and a C-terminal domain [61]. The latest model to describe α-zein structure has been proposed by Momany et al. [62]. The proposed complete structure is built of nine α-helix structures, present in a central domain, in addition to an N-terminal segment. According to Shewry and Tatham [63], the secondary structure of α-zein dissolved in aqueous ethanol includes 40–60% α-helix conformations and a small amount of β-sheet structures. When the protein’s temperature is raised above its glass transition temperature (Tg > 35 ◦C), a reversible change from an α-helix-dominated conformation to more β-sheet structures has been observed imparting viscoelastic properties to zein [57]. α-helix and β-sheet are generally considered “ordered” secondary structures, while β-turn and random coil are considered “unordered” protein secondary structures [64]. The transition from the glassy state to the rubbery state (upon reaching Tg) is accompanied by an increase in ordered protein structures [64]. This can explain the fact that β-sheet and α-helix structures are the dominant structures in the here studied hydrated zein samples mixed at above 40 ◦C. On the other hand, the unordered β-turn and random coil secondary structures are often linked to protein surface hydrophobicity as these structures facilitate the exposure of hydrophobic residues [65]. It has been suggested that the random coil structure formation is promoted by weakening of hydrogen bonds. Conversely, development of α-helix structures is promoted by protein hydration and the subsequent hydrogen bond formation [64,65]. This might explain the undetectable low levels of random coil structures in the hydrated zein sample. Chen et al. [65] reported a decrease in the percentage of random coil structures to zero by dissolving zein in both ethanol and isopropanol. The estimation of the contribution of the amino acid side chain groups to the IR absorption spectra, especially when the content of these residues is high, helps a more refined estimation of secondary structure content [6]. The amino acids side chains, which absorb in the amide I region are those of asparagine, glutamine, arginine, lysine, and tyrosine (Table3). These amino acids account for about 16, 147, 13, 8, and 12 residues/mole of gluten [51] and 10, 41, 2, 0, and 8 residues/mole of α-zein [52], respectively. Previously, researchers [18,21], estimated that these residues contribute about 10 to 20% of the total absorption intensity of the amide I band. Due to the unusually high content of glutamine residues in both zein and gluten, the contribution of glutamine to the amide I band absorption would likely be at the higher end of this estimated range. The presence of several heterogeneous polypeptides in both gluten and zein, however, makes the estimation of side chain contribution to the amide I signal near impossible.

5. Conclusions Decomposing the amide I band into its separate components is key to a successful FTIR analysis of the protein secondary structure. This has been achieved by different mathematical methods developed during the recent years. In this study, a data analysis technique to explore protein secondary structure through infrared and Raman spectroscopy has been optimized. Both FT-Raman and FTIR data revealed well-defined spectral features with similar secondary structural estimation for the proteins studied. The relative amounts of different secondary structures were determined from band curve fitting and agreement was found between the results derived from FTIR and FT-Raman spectroscopy and literature reports. The present results show the strength of FTIR and FT-Raman as non-invasive techniques to study the conformation of the proteins and provide support for using the amide I infrared and Raman spectra to study protein secondary structures in complex systems. The data obtained by these non-invasive techniques will in the near future provide new insights into the structure of various proteins in complex food systems. Appl. Sci. 2020, 10, 5918 14 of 16

Supplementary Materials: The following are available online at http://www.mdpi.com/2076-3417/10/17/5918/s1, Figures S1-1–S1-16 Curve fitted, second derivative, residual plot, and peak analysis result of FTIR and FT-Raman spectra of all replicate measurements of standard proteins; Tables S1-1–S1-16 Statistical analysis of curve fitting performed on FTIR and FT-Raman spectra of all replicate measurements of standard proteins; Figures S2-1–S2-10 Curve fitted, second derivative, residual plot, and peak analysis result of FTIR and FT-Raman spectra of all replicate measurements of gluten and zein proteins; Tables S2-1–S2-10 Statistical analysis of curve fitting performed on FTIR and FT-Raman spectra of all replicate measurements of gluten and zein proteins. Author Contributions: Conceptualization, A.S. and I.J.J.; methodology, A.S. and I.J.J.; formal analysis, A.S.; investigation, A.S.; resources, I.J.J.; data curation, A.S. and I.J.J.; writing—original draft preparation, A.S.; writing—review and editing, I.J.J.; visualization, A.S.; supervision, I.J.J.; project administration, I.J.J.; funding acquisition, I.J.J. All authors have read and agreed to the published version of the manuscript. Funding: Azin Sadat wishes to acknowledge the Ontario Trillium Scholarship for funding her project. This research was funded by the NSERC Discovery Grant program (Canada, RGPIN-2017-05213). Acknowledgments: The authors would like to thank Leonid Brown for providing the FT-Raman facility and technical assistance in the FT-Raman measurements and Paul Rowntree for providing technical and scientific assistance in the FTIR measurement and data analyzation. Conflicts of Interest: The authors declare no conflict of interest.

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