Sequential Proton Loss Electron Transfer in Deactivation of Iron(IV

Article pubs.acs.org/JAFC

Sequential Proton Loss Electron Transfer in Deactivation of Iron(IV) Binding Protein by Tyrosine Based Food Components Ning Tang and Leif H. Skibsted* Department of Food Science, University of Copenhagen, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark S Supporting Information *

ABSTRACT: The iron(IV) binding protein ferrylmyoglobin, MbFe(IV)O, was found to be reduced by tyrosine based food components in aqueous solution through a sequential proton loss electron transfer reaction mechanism without binding to the protein as confirmed by isothermal titration calorimetry. Dopamine and epinephrine are the most efficient food components reducing ferrylmyoglobin to oxymyoglobin, MbFe(II)O2, and metmyoglobin, MbFe(III), as revealed by multivariate curve resolution alternating least-squares with second order rate constants of 33.6 ± 2.3 L/mol/s (ΔH⧧ of 19 ± 5 kJ/mol, ΔS⧧ of −136 ± 18 J/mol K) and 228.9 ± 13.3 L/mol/s (ΔH⧧ of 110 ± 7 kJ/mol, ΔS⧧ of 131 ± 25 J/mol K), respectively, at pH 7.4 and 25 °C. The other tyrosine based food components were found to reduce ferrylmyoglobin to metmyoglobin with similar reduction rates at pH 7.4 and 25 °C. These reduction reactions were enhanced by protonation of ferrylmyoglobin and facilitated proton transfer at acidic conditions. Enthalpy−entropy compensation effects were observed for the activation parameters (ΔH⧧ and ΔS⧧), indicating the common reaction mechanism. Moreover, principal component analysis combined with heat map were performed to understand the relationship between density functional theory calculated molecular descriptors and kinetic data, which was further modeled by partial least squares for quantitative structure−activity relationship analysis. In addition, a three tyrosine residue containing protein, lysozyme, was also found to be able to reduce ferrylmyoglobin with a second order rate constant of 66 ± 28 L/mol/s as determined by a competitive kinetic method. KEYWORDS: tyrosine, ferrylmyoglobin, sequential proton loss electron transfer, density functional theory, quantitative structure−activity relationship

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INTRODUCTION The hypervalent pigment ferrylmyoglobin MbFe(IV)O and its protein radical form, perferrylmyoglobin •MbFe(IV)O, formed during digestion of meat by reaction of metmyoglobin, MbFe(III), with hydrogen peroxide are powerful prooxidants in meat and meat products.1−3 They are known to oxidize a number of compounds present in living cells causing cellular damage and to initiate lipid and protein oxidation during meat processing and storage.4,5 Besides being radical initiators, the hypervalent pigments are also involved in the formation of the reactive oxygen species (ROS) in the human gut.6 Moreover, hypervalent forms of myoglobin are regarded as one of the main causes of colon cancer due to the high intake of red meat.7,8 Ferrylmyoglobin and perferrylmyoglobin can be deactivated by amino acids, peptides, and proteins or antioxidants such as carotenoids, ascorbate, flavonoids, and plant polyphenols.6,9−11 In this way, the oxidative damage caused by reactive oxygen species (ROS) is prevented through reduction of the high oxidation states of heme iron. Therefore, researchers have focused on a better understanding of how formation of hypervalent iron can be counteracted by combining the intake of red meat with foods rich in natural antioxidants.12 L-Tyrosine is an essential amino acid and important in structural protein synthesis and neurotransmitter production. Dietary sources of tyrosine are dairy products, meat, eggs, fish, and oats. With a phenol group, tyrosine is expected to be an antioxidant,13,14 and it has been found to be one of the main contributors to the antioxidant activity of egg yolk.15 In © XXXX American Chemical Society

addition, tyrosine has been found to have modulating effects in animal or human trials during conditions of oxidative stress.16 Previous studies have shown that tyrosine, as one of the main phenolic compounds present in the human body, was highly active in mediating heme protein redox reactions.17−19 Although studies have focused on the reduction of ferrylmyoglobin by different kinds of antioxidants, the mechanism of reduction of myoglobin ferryl species by tyrosine is not known in any detail. With the nutritional and physiological significance of tyrosine, it seems important to investigate the effects of this amino acid based food component on myoglobin induced oxidative reactions. Accordingly, thermodynamics and kinetics of the reactions between tyrosine based food components and ferrylmyoglobin have been investigated. Quantum mechanical calculations (DFT) were also performed to investigate the reaction mechanism. Moreover, chemometric methods were applied to analyze the obtained data in order to support structure−activity relationship. The results of these investigations should provide a better understanding of the role of tyrosine in the mechanism of physiology and pathology related to heme proteins. Received: Revised: Accepted: Published: A

May 24, 2017 July 3, 2017 July 6, 2017 July 6, 2017 DOI: 10.1021/acs.jafc.7b02420 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

Article

Journal of Agricultural and Food Chemistry

Figure 1. Structures of investigated tyrosine based food components and the pathway for phenolamine production from tyrosine. AADC: Aromatic L-amino acid decarboxylase. DBH: Dopamine beta-monooxygenase. PNMT: Phenylethanolamine N-methyltransferase. CYP2D6: Cytochrome P450 2D6.

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MATERIALS AND METHODS

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RESULTS AND DISCUSSION

based food components were monitored using stopped flow spectroscopy and UV/vis spectroscopy by recording spectra from 450 to 700 nm in aqueous solution at pH 4.0, 7.4, and 11.0 at 25 °C. As shown in Figures 2, S1, and S2, according to the recorded spectra changes, the investigated tyrosine based food components all reduced ferrylmyoglobin with different reaction rates. As ferrylmyoglobin is not stable in acidic conditions, a pH jump technique was used for the reduction experiments at pH 4.0, and the obtained spectral shape exhibited strong changes, especially the final spectra (Figure S1). As can be seen from Figure S2, the initial spectral shape also changed at pH 11.0 with a more sharp and defined peak at 550 nm. Since there was no buffer effect, this change was attributed to the presence of the hydroxo form of metmyoglobin with a pKa value of 8.75.24 Evolving factor analysis (EFA) of recorded spectral data matrices was performed to determine the number of chemical species involved in the ferrylmyoglobin reduction reactions, identifying the reaction intermediates and products. Calculated EFA results are shown in Figures 3, S3, and S5 with the considered threshold of noise. Figure 3 shows the EFA results of ferrylmyoglobin reduction experiments at pH 7.4. In the forward analysis (emerge), for dopamine and epinephrine, two factors were identified to explain the spectral data at the

Chemicals. Tyr-Gly and Tyr-Tyr of analytical grade were obtained from Bachem (Bubendorf, Switzerland). All other chemicals with different purities were purchased from Sigma-Aldrich (Steinheim, Germany). Water was purified by Milli-Q system (Millipore Corp., Bedford, MA, USA). (Details are provided in the Supporting Information.) Methods. Reaction products were identified by multivariate curve resolution alternating least-squares (MCR-ALS). The overall reaction kinetics was analyzed by hard modeling. Binding effect was determined by isothermal titration calorimetry according to the previously described method.20 The reaction mechanism was investigated by quantum mechanical calculations (density functional theory) using the Gaussian 09 package program.21,22 Multivariate data analysis (principal component analysis, heat map, and partial least squares regression) was applied to study the quantitative structure−activity relationship (QSAR). Rate constants of reduction of ferrylmyoglobin by lysozyme were determined using competitive kinetics.23 (Details are provided in the Supporting Information.)

Multivariate Curve Resolution Alternating LeastSquares Analysis. With tyrosine based food components (Figure 1) added in excess to ensure the pseudo first order condition, the reactions between ferrylmyoglobin and tyrosine B

DOI: 10.1021/acs.jafc.7b02420 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Figure 2. Absorption spectral changes of ferrylmyoglobin reacted with (A) 0.002 mol/L tyrosine, (B) 0.01 mol/L tyramine, (C) 0.01 mol/L octopamine, (D) 0.01 mol/L synephrine, (E) 0.01 mol/L dopamine, (F) 0.0005 mol/L epinephrine, (G) 0.01 mol/L Gly-Tyr, (H) 0.01 mol/L TyrGly, and (I) 0.01 mol/L Tyr-Tyr in aqueous solution at pH 7.4 and 25 °C. The arrows indicate the increasing or decreasing absorption during the reaction. Inset figures: the absorbance changes of ferrylmyoglobin reacted with tyrosine based food components at 580 nm with different total reaction time (according to the reaction rate). The red line is the nonlinear regression fitting for the calculation of the first order rate constant.

beginning, and the third factor corresponding to the emergence of a new chemical species became significant at the 80th spectrum (12 s) for dopamine and the 60th spectrum (27 s) for epinephrine (Figures 3E and 3F). As the number of significant factors obtained from the EFA results is equal to the number of chemical species that contribute to the reaction analyzed,25 three chemical species were relevant for the reduction of ferrylmyoglobin by dopamine and epinephrine. In addition, the presence of two chemical species at the beginning indicated two forms of ferrylmyoglobin: ferrylmyoglobin and reduced ferrylmyoglobin (metmyoglobin) formed from autoreduction. The emergence of the third chemical species corresponded to the product formed by the reaction with dopamine or epinephrine. For other tyrosine based food components, the EFA results are shown in Figure 3, panels A−D and G−I. It can be seen that only two chemical species were relevant for the reduction reaction in all cases. Furthermore, similar information was obtained from the backward analysis (disappear), and only one factor was observed to be relevant at the end of the reaction in all cases, indicating that the initial chemical species (ferrylmyoglobin) was not present at the end of the reaction. For the reactions at pH 4.0, as can be seen from Figure S3, different tyrosine based food components showed quite different EFA results regardless of the number of phenolic

hydroxyl groups. There were two chemical species relevant for the reduction of ferrylmyoglobin by tyrosine, tyramine, octopamine, and epinephrine (Figure S3, panels A−C and F), while three chemical species were relevant for the reaction with synephrine, dopamine, Gly-Tyr, Tyr-Gly, and Tyr-Tyr (Figure S3, panels D, E, and G−I). Figure S5 shows the reduction reactions at pH 11.0; three chemical species were found to be relevant for the reactions for all the investigated tyrosine based food components. In addition, in accordance with the backward analysis of reactions at pH 7.4, the initial chemical species (ferrylmyoglobin) was also found not to be present at the end of the reaction at pH 4.0 and 11.0 (Figures S3 and S5). The obtained EFA profiles as the initial estimation with soft modeling constraints, such as non-negativity for concentration and spectral profiles and closure for concentration profiles, were used to perform the MCR-ALS. The concentration and spectral profiles recovered from MCR-ALS are shown in Figures 4, S4, and S6. Figure 4 illustrates the profiles obtained from the reactions at pH 7.4, and the model evaluation parameters are shown in Table 1. As can be seen from Table 1, the models obtained from MCR-ALS at pH 7.4 explained more than 99.9% (99.9986 ± 0.001%) variance with the fitting error less than 0.48% (0.3 ± 0.1%) for all studied tyrosine based food components, which suggested a very good agreement between C


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Figure 3. Evolving factor analysis (EFA) of the reaction between ferrylmyoglobin and (A) 0.002 mol/L tyrosine, (B) 0.01 mol/L tyramine, (C) 0.01 mol/L octopamine, (D) 0.01 mol/L synephrine, (E) 0.01 mol/L dopamine, (F) 0.0005 mol/L epinephrine, (G) 0.01 mol/L Gly-Tyr, (H) 0.01 mol/ L Tyr-Gly, and (I) 0.01 mol/L Tyr-Tyr in aqueous solution at pH 7.4 and 25 °C. The black and red lines correspond to the forward and backward directions, respectively. The blue line represents the considered threshold of noise.

the original spectral data and the obtained concentration and spectral profiles. According to the EFA results showed in Figure 3, for dopamine and epinephrine, three chemical species were identified in the reaction mixture, and these chemical species can be assigned as follows based on the obtained spectral profiles (Figure 4J,L). The black lines represent ferrylmyoglobin and are characterized by two maximum absorption peaks at 550 and 580 nm, which was identical to the pure spectrum of ferrylmyoglobin under the same conditions.26,27 The red lines correspond to metmyoglobin with the characteristic peaks at 510 and 635 nm,28 which was also confirmed by comparing with the pure spectrum. The slow reduction of metmyoglobin by excess dopamine and epinephrine led to the formation of oxymyoglobin as indicated by the final spectra (blue lines) with the characteristic peaks at 540 and 580 nm as shown in Figure 4J,L.29 With the assumption of the presence of ferrylmyoglobin, metmyoglobin, and oxymyoglobin, their MCR-ALS recovered concentration profiles are shown in Figure 4I,K. As can be seen from the results, the concentration of ferrylmyoglobin decreased to zero during 15 s for dopamine and 35 s for epinephrine in agreement with the EFA results that initial chemical species was not present at the end of the reaction. With decreasing ferrylmyoglobin concentration, the increasing concentration of metmyoglobin was observed and became steady after some time. The oxymyoglobin was formed in low

concentration and steadily increased throughout the reaction. In addition, the formed oxymyoglobin concentration depended on the concentration of added dopamine or epinephrine and reaction rates. According to the above obtained information, the following reaction pathway is proposed: MbFe(IV )O + R−OH → MbFe(III) + R = O

k1 (1)

MbFe(IV )O → MbFe(III)

kautoreduction

MbFe(III) + R−OH + O2 → MbFe(II)O2 + RO

(2)

k2 (3)

MbFe(II)O2 → MbFe(III) + O2•−

k3

(4)

As the presence of oxygen in aqueous solution, reaction 4 illustrates the spontaneous oxidation of oxymyoglobin to metmyoglobin with superoxide anion radical formation. For other tyrosine based food components, as shown in Figure 4, panels B, D, F, H, N, P, and R, the EFA identified two chemical species that can be assigned as ferrylmyoglobin and metmyoglobin suggested by the characteristic peaks at 550 and 580 nm and at 510 and 635 nm,26−28 respectively, indicating that only reactions 1 and 2 occurred during the ferrylmyoglobin reduction. Their MCR-ALS recovered concentration profiles are shown in Figure 4, panels A, C, E, G, M, O, D


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Figure 4. Concentration profiles (A, C, E, G, I, K, M, O, Q) and spectral profiles (B, D, F, H, J, L, N, P, R) obtained from multivariate curve resolution alternating least-squares (MCR-ALS). Panels A and B, C and D, E and F, G and H, M and N, O and P, and Q and R correspond to the concentration and spectral profiles of the reaction between ferrylmyoglobin and tyrosine, tyramine, octopamine, synephrine, Gly-Tyr, Tyr-Gly, and Tyr-Tyr in aqueous solution at pH 7.4 and 25 °C, respectively. The black and red lines represent ferrylmyoglobin and metmyoglobin, respectively. Panels I and J correspond to the concentration and spectral profiles of the reaction between ferrylmyoglobin and dopamine, and panels K and L to those between ferrylmyoglobin and epinephrine, in aqueous solution at pH 7.4 and 25 °C, respectively. The black, red, and blue lines represent ferrylmyoglobin, metmyoglobin, and oxymyoglobin, respectively.

compounds are related to human metabolism and play an important role in stimulating lipolysis, oxidation of fat through increased thermogenesis, and regulating the nervous system.32,33 In the present study, these biogenic amines together with tyrosine based dipeptides shown in Figure 1 were found to be efficient reductants for reducing ferrylmyoglobin especially at low pH forming different reaction products through different reaction pathways according to the above MCR-ALS results. Based on the proposed reaction pathway (Figure 5), the kinetics can be described by different kinetic equations according to the involved chemical species (Supporting Information). However, from a practical point of view, it is important not only to detect the reaction pathway and individual rate constants but also to know the overall reducing ability toward ferrylmyoglobin reduction. Therefore, hard modeling approach was used to get this information as the observed kinetics of the reduction of ferrylmyoglobin can be characterized by pseudo first order reactions for all experimental conditions. The first order rate constants were calculated by fitting the kinetic model (eq 5, Supporting Information), initiating the algorithm with random parameter values, as shown in the inset figures in Figures 2, S1, and S2. Then the observed rate constants as a function of increasing

and Q; the same pattern was observed in all cases. With decreasing ferrylmyoglobin concentration, the concentration of metmyoglobin was increasing and then became steady indicating the end of the reaction. In accordance with the EFA results, MCR-ALS recovered concentration and spectral profiles for the reactions at pH 4.0 and 11.0 exhibited quite different patterns due to the pH change leading to the reactivity change of ferrylmyoglobin and tyrosine based food components. For reactions at pH 4.0, the relevant chemical species can be identified as ferrylmyoglobin (black lines), protonated form of metmyoglobin (red lines), and protonated form of oxymyoglobin (blue lines) (Figure S4), while the involved species at pH 11.0 were identified as ferrylmyoglobin, hydroxo form of metmyoglobin (blue lines), and oxymyoglobin (red lines) (Figure S6). (Analysis details are provided in the Supporting Information.) Kinetics and Mechanisms. Tyramine, octopamine, synephrine, dopamine, and epinephrine are biogenic amines that exist in a wide range of food products containing proteins or free amino acids such as meat products, dairy products, and fruits.30,31 They are decarboxylation products derived from the amino acid L-tyrosine through different metabolism pathways, as shown in Figure 1. Many studies showed that these E


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Table 1. Total Reaction Time of the Reduction of Ferrylmyoglobin by Tyrosine Based Food Components in Aqueous Solution at pH 4.0, 7.4, and 11.0 at 25 °C, Lack of Fit (LOF) Values and Explained Variance (R2) of the Models Obtained by Multivariate Curve Resolution Alternating Least Squares, and Rate Constants of Different Reaction Pathway Shown in Figure 5 as Calculated by Multivariate Curve Resolution Alternating Least Squares reaction time (s)

LOF (PCA)

R2

LOF

k1 (1/s)

k2 (1/s)

k3 (1/s)

pH 4.0 tyrosine tyramine octopamine synephrine dopamine epinephrine Gly-Tyr Tyr-Gly Tyr-Tyr

45 45 45 45 10 30 45 15 45

0.33 0.28 0.36 0.14 0.31 0.39 0.28 0.12 0.16

0.38 0.38 0.42 0.16 0.35 0.42 0.32 0.17 0.20

tyrosine tyramine octopamine synephrine dopamine epinephrine Gly-Tyr Tyr-Gly Tyr-Tyr

1584 120 120 120 15 45 120 120 120

0.29 0.22 0.30 0.18 0.12 0.35 0.32 0.24 0.17

0.48 0.26 0.33 0.21 0.19 0.37 0.37 0.27 0.22


12000 7200 7200 10200 40200 72000 9000 7200 6900

0.26 0.17 0.18 0.27 0.49 0.38 0.68 0.23 0.34

0.41 0.35 0.37 0.43 0.59 0.50 0.77 0.37 0.45

99.9986 99.9985 99.9982 99.9998 99.9987 99.9982 99.9990 99.9997 99.9996

0.12 0.21 0.16 0.17 1.70 0.18 0.30 0.72 0.28

99.9977 99.9993 99.9989 99.9995 99.9960 99.9986 99.9987 99.9992 99.9995

0.0087 0.0391 0.0394 0.0374 0.3250 0.1375 0.0386 0.0369 0.0514

99.9983 99.9988 99.9986 99.9981 99.9965 99.9975 99.9941 99.9986 99.9980

0.0021519 0.0037175 0.0003630 0.0004756 0.0007448 0.0000600 0.0007274 0.0009346 0.0009830

0.03 0.48

0.03 0.14

0.08 0.07 0.02

0.28 0.35 0.11

0.0241 0.0039

0.00132 0.01340

0.0003478 0.0004574 0.0032084 0.0002121 0.0000895 0.0000296 0.0027605 0.0035589 0.0030030

0.000001153 0.000000039 0.000017231 0.000000867 0.000000073 0.000000033 0.000025167 0.000075941 0.000262310

pH 7.4

pH 11.0

Figure 5. Proposed reaction pathways for the reduction of ferrylmyoglobin by investigated tyrosine based food components in aqueous solution at 25 °C.

concentration of tyrosine based food components follow the equation below:

kobs = kautoreduction + k1[R−OH] F

(5)


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Figure 6. (A) Representative figure for obtained first order rate constant in 1/s as a function of concentrations of investigated tyrosine based food components. The red lines are the linear regressions for the calculation of second order rate constant in L/mol/s. (B) Representative Eyring plot for the reduction of ferrylmyoglobin by tyrosine based food components in aqueous solution at pH 7.4. The red lines represent the linear regression for the calculation of enthalpy of activation (ΔH⧧) and entropy of activation (ΔS⧧). (C) Enthalpy−entropy compensation plot (ΔH⧧ versus ΔS⧧) for the reduction of ferrylmyoglobin by investigated food components at different pH 4.0, 7.4, and 11.0. The lines are the linear regressions for the calculations of isokinetic temperatures.

Table 2. Second Order Rate Constants for the Reduction of Ferrylmyoglobin by Tyrosine Based Food Components in Aqueous Solution at pH 4.0, 7.4, and 11.0 at 25 °C rate constant (L/mol/s) pH 4.0 tyrosine tyramine octopamine synephrine dopamine epinephrine Gly-Tyr Tyr-Gly Tyr-Tyr

11.4 13.8 8.1 4.7 133.7 146.6 24.3 47.6 12.6

± ± ± ± ± ± ± ± ±

0.6 0.6 0.3 0.6 0.4 24.8 0.4 6.6 0.2

fractionsa

pH 7.4

pH 11.0

± ± ± ± ± ± ± ± ±

0.08 ± 0.00004 0.03 ± 0.00005 0.01 ± 0.004 0.02 ± 0.002 0.2 ± 0.06 0.02 ± 0.001 0.05 ± 0.01 0.07 ± 0.01 0.09 ± 0.01

4.2 1.9 2.9 2.6 33.6 228.9 1.8 2.0 2.0

0.3 0.2 0.1 0.1 2.3 13.3 0.2 0.1 0.03

702 (kf2) 553 (kf2) 8.1 (kf2) 4.7 (kf2) 133.7 (kf4) 146.6 (kf4) −121 (kf1) −195 (kf1) −44 (kf1)

4.5 (kf3) 13.8 (kf3) 391162 (kf5) 228902 (kf5) −7449 (kf1+f6+f7) 2890 (kf1+f2+f3+f6+f8) 24.3 (kf2+f3) 47.6 (kf2+f3) 12.6 (kf2+f3)

0.08 (kf1+f4+f5) −2150 (kf1+f4) −195 (kf1+f3+f4) −115 (kf1+f3+f4) 750 (kf2+f3+f5) −136470 (kf5+f7+f9) 3.9 (kf4+f5+f6) 6.3 (kf4+f5+f6) 1.5 (kf4+f5+f6+f7+f8+f9+f10)

a

Sum of the fractions of the rate constants contributing to the overall rate constants. Fractions in parentheses correspond to the structures with charges shown in Figure S8.

where kautoreduction is the rate constant for the natural decay of ferrylmyoglobin. k1 is the second order rate constant for the reduction of ferrylmyoglobin by tyrosine based food components. At constant pH and temperature, the observed rate constants were found to depend linearly on the concentration of tyrosine based food components, as can be

seen from Figure 6A. The obtained second order rate constants for reducing ferrylmyoglobin by tyrosine based food components are shown in Table 2. At physiological pH 7.4, dopamine and epinephrine were found to be the most efficient biogenic amines, with second order rate constants of 33.6 ± 2.3 L/mol/s and 228.9 ± 13.3 L/mol/s, respectively. Among three G


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Table 3. Activation Parameters for the Reduction of Ferrylmyoglobin by Tyrosine Based Food Components in Aqueous Solution at pH 4.0, 7.4, and 11.0 pH 4.0 ΔH⧧ (kJ/mol) tyrosine tyramine octopamine synephrine dopamine epinephrine Gly-Tyr Tyr-Gly Tyr-Tyr

107 76 63 52 60 84 49 44 69

± ± ± ± ± ± ± ± ±

15 5 18 37 10 3 1 3 9

pH 7.4 ΔS⧧ (J/mol K) 134 33 −17 −56 −4 78 −55 −62 6

± ± ± ± ± ± ± ± ±

48 17 60 121 34 10 5 9 30

ΔH⧧ (kJ/mol) 110 65 73 58 19 110 92 121 59

± ± ± ± ± ± ± ± ±

8 12 15 9 5 7 10 26 0.1

pH 11.0 ΔS⧧ (J/mol K) 128 −17 9 −20 −136 131 70 169 −35

± ± ± ± ± ± ± ± ±

26 40 51 31 18 25 32 87 0.4

ΔH⧧ (kJ/mol) 124 219 176 33 88 113 19 79 135

± ± ± ± ± ± ± ± ±

15 12 11 12 7 5 14 12 42

ΔS⧧ (J/mol K) 148 460 307 −167 39 102 −206 −2 187

± ± ± ± ± ± ± ± ±

51 39 35 40 23 18 47 39 140

myoglobin, were identified for the reactions at pH 7.4 (Figure 4L). Besides the equilibrium of ferrylmyoglobin, the tyrosine based food components also presented in different forms in aqueous solution according to the pKa values and solution pH. Based on the calculated molar fraction distribution diagrams (Figure S7) and structures with charge distribution (Figure S8), protonated forms (amino group) were predominant at pH 4.0 and 7.4 and deprotonated forms were predominant at pH 11.0. In addition, based on the distribution of different forms of tyrosine based food components at different pH, the overall reduction rate constant can be calculated using the following equation:

dipeptides, they exhibited similar reducing ability toward ferrylmyoglobin reduction with the average second order rate constant of 1.9 ± 0.1 L/mol/s (Table 2). For Tyr-Tyr containing two phenolic hydroxyl groups, the reduction of ferrylmyoglobin by Tyr-Tyr was faster than that by Gly-Tyr and Tyr-Gly (containing one phenolic hydroxyl group) at the same concentration. In addition, the obtained kobs values were very close to the values obtained from MCR-ALS, as can be seen from Table 1, providing further information about the validity of MCR-ALS established models. As shown in Table 2, for reactions involving only one phenolic hydroxyl group, tyrosine exhibited the highest reducing ability with a second order rate constant of 4.2 ± 0.3 L/mol/s. Moreover, quite different values of first order and second order rate constants were obtained, suggesting that the redox properties of phenolic hydroxyl group were affected by the changes of the −R group. In addition, as shown in Figure 2, the integrity of the isosbestic points indicated the minimal structure changes of myoglobin during the reduction by tyrosine based food components. In accordance with the MCR-ALS results, the reactions at pH 4.0 were much faster, as can be seen from the second order rate constants (Table 2). Tyr-Gly exhibited the highest increase toward the reducing ability with the ratio of 23.8 between the second rate constant at pH 4.0 and 7.4, followed by Gly-Tyr (13.5) and tyramine (7.3). However, the reactions at pH 11.0 were very slow, which may be due to the deprotonation of the hydroxyl group (Table 2). Previous studies showed that protonation of ferrylmyoglobin with the pKa value of 4.9 at low pH would cause the changes on the reactivity of ferrylmyoglobin.6,34 Therefore, the reduction of ferrylmyoglobin by tyrosine based food components at pH 4.0 corresponded to at least two parallel reactions: the reduction of ferrylmyoglobin and protonated ferrylmyoglobin. At pH 4.0, the faster reaction involving protonated ferrylmyoglobin was dominant, leading to the increase in the overall reduction rate constant. This pH effect was also observed for other reductants rather than specific acid catalysis as observed for the auto reduction of ferrylmyoglobin and auto oxidation of oxymyoglobin.24,26 The reactivity of the hydroxo form of ferrylmyoglobin was not well-known, but the observed slower reaction was in agreement with previous studies. Notably, in contrast to other tyrosine based food components, the expected increase for the rate constant was not observed for epinephrine at pH 4.0. This surprising result may relate to different reaction pathways as observed from MCR-ALS results. Unlike dopamine, only the protonated form of metmyoglobin was identified as reaction products at pH 4.0 (Figure S4L). However, two reaction products, metmyoglobin and oxy-

k1 = f (H3A)kH3A + f (H 2A−)kH2A − + f (HA2 −)kHA 2 − + f (A3 −)kA 3 −

(6)

The obtained rate constants based on eq 6 are shown in Table 2. As can be seen from the table, some negative values were obtained, indicating that the acid base equilibrium caused species changes were not the only reason leading to the rate constant changes at different pH. This result was in agreement with previous discussion that the reactivity changes of ferrylmyoglobin also contributed to overall reduction rate constant changes at different pH. The temperature dependence of the second order rate constant for the reduction of ferrylmyoglobin by tyrosine based food components was investigated at three different temperatures of 25 °C, 30 °C, and 35 °C at pH 4.0, 7.4, and 11.0. The reactions can be characterized by Arrhenius theory and then converted to enthalpy of activation (ΔH⧧) and entropy of activation (ΔS⧧) using the transition state theory based on the following equation: ⎛k⎞ ⎛ K ⎞ ΔS‡ ΔH ‡ ln⎜ ⎟ = − + ln⎜ B ⎟ + ⎝ h ⎠ ⎝T ⎠ RT R

(7)

where k is the second order rate constant, KB is the Boltzmann constant, and h is Planck’s constant. According to eq 7, enthalpy of activation (ΔH⧧) and entropy of activation (ΔS⧧)

( Tk )

were then obtained from the linear relationship between ln

and 1 as shown in Figure 6B. The obtained activation T parameters are shown in Table 3. As can be seen, the relatively high values of enthalpy of activation (ΔH⧧) combined with positive values of entropy of activation (ΔS⧧) for the reduction of ferrylmyoglobin indicated the outer sphere electron transfer mechanism for all tyrosine based food components at pH 7.4 except for dopamine.6 Previous studies also showed that some phenolic compounds exhibited the same electron transfer H


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Table 4. Calculated Dissociation Constants of Phenol Groups (pKa), Calculated Partition Coefficient (log P) and Distribution Coefficient (log D), Dipole Moments (μ), Bond Dissociation Enthalpy (BDE), Ionization Potential (IP), Proton Dissociation Enthalpy (PDE) from Radical Cations, Proton Affinity (PA) and Electron Transfer Enthalpy (ETE) from Anions of Phenol Groups Calculated by DFT/B3LYP/6-31G(d,p), Frontier Orbitals (EHOMO and ELUMO), and HOMO−LUMO Energy Gap (ΔE) of Dominant Fractions of Tyrosine Based Food Component in Aqueous Solution at pH 4.0 and 7.4a


μ (Debye)

BDEb (kJ/mol)

IP (kJ/mol)

PDEb (kJ/mol)

PAb (kJ/mol)

ETEb (kJ/mol)

EHOMO (eV)

ELUMO (eV)

ΔE (eV)

−1.47 −1.21 −1.53 −1.39 −1.44

12.86 13.83 14.59 12.63 15.36

430 484 496 495 454

−5.93

−0.26

5.67

−0.21 −0.21 1.73

−2.62, −2.61 −2.64, −2.63 −0.68, −0.69

24.20 25.72 25.30

268 293 303 304 273 292 287 268 255 295 252 283

5.84 5.83 5.90 5.87 5.67

13.76

262 247 241 240 255 215 217 259 265 246 272 254

−0.11 −0.41 −0.46 −0.47 −0.28

−2.95, −1.63

100 55 48 49 73 53 51 74 211 79 126 139

−5.95 −6.24 −6.36 −6.34 −5.95

0.33

331 340 345 345 329 308 305 328 322 342 326 339

−5.60 −5.83 −5.78

−0.09 −0.51 −0.31

5.51 5.32 5.47

pKab

log P

log Dc

9.79 10.41 9.64 9.76 12.93 10.01 12.65 9.69 9.52 9.52 9.81 9.22

0.87 1.13 0.21 0.62 0.85

−1.47, −1.99, −2.91, −2.67, −2.27,

452 309 461 399

a

pKa, log P, and log D were calculated using Marvin Calculator Plugins. Marvin 5.4.1, 2010, ChemAxon (http://www.chemaxon.com). bFor dopamine and epinephrine, the first and second numbers correspond to the calculated values for p-OH and m-OH, respectively. For Tyr-Tyr, the first and second numbers correspond to the calculated values for OH group in N-terminal and C-terminal, respectively. cThe first and second numbers represent the calculated values at pH 4 and 7.4, respectively.

mechanism with the reaction being enthalpy controlled (Table S1).9,34,35 In contrast to these reductants, the reduction by some inorganic compounds like nitrite, iodide, and thiocyanate exhibited relatively low ΔH⧧ and negative ΔS⧧ and indicated the inner sphere electron transfer mechanism, which was also observed for dopamine.36,37 In addition, as can be seen from Table 3, higher values of enthalpy of activation were obtained with increasing pH in agreement with the observed slower reactions. Based on the obtained activation parameters (Table 3) for tyrosine based food components, the enthalpy of activation ΔH⧧ for the reduction of ferrylmyoglobin was found very linearly depended on the entropy of activation ΔS⧧ as shown in Figure 6C. This enthalpy−entropy compensation effect can be characterized using the following equation: ΔH ‡ = α + β ΔS‡

through direct electron transfer from the reductants to iron(IV) center. Quantum Mechanical Calculations. Based on previous studies about the proton or electron transfer reaction mechanism of polyphenols, three reaction mechanisms may be relevant for the reduction of ferrylmyoglobin by tyrosine based food components as shown in Figure S11.38,39 Hydrogen atom transfer (HAT), in which the proton and electron are transferred in one kinetic step, can be described using the equation below: ArOH + Fe(IV )O → ArO• + Fe(III )−OH

(9)

Single electron transfer was followed by proton transfer (SETPT), which is a two-step reaction mechanism initiated by electron transfer (eq 10) and then followed by a proton release from the cation radical (eq 11). Notably, the proton transfer is fast.

(8)

where α is an energy related quantity, and β is defined as the isokinetic temperature. Based on the plot of Figure 6C, the isokinetic temperature for the reduction of ferrylmyoglobin by tyrosine based food components was 330.3 K at pH 7.4. In addition, a linear relationship between ΔH⧧ and ΔS⧧ was also observed for all the reductants listed in Tables 3 and S1 for which the activation parameters were known at physiological pH (Figure S9). Obviously, the excellent linear correlation between ΔH⧧ and ΔS⧧ suggesting a compensation effect indicated a common reaction mechanism for the electron transfer to the iron(IV) center. Moreover, previous studies have suggested that some small molecules like chlorogenate and ascorbate would lead to complex formation prior to the electron transfer.36,37 Therefore, isothermal titration calorimetry experiments were performed by titrating tyrosine based food components into metmyoglobin solution to investigate this binding effect. As shown in Figure S10, the obtained heat was close to the heat generated by titrating tyrosine based food components to Tris-HCl buffer solution indicating that there was no binding reaction between tyrosine based food components and metmyoglobin. The reduction reaction was

ArOH + Fe(IV )O → ArOH•+ + Fe(III )−O

(10)

ArOH•+ + Fe(III )−O → ArO• + Fe(III )−OH

(11)

Sequential proton loss electron transfer (SPLET) is the reverse mechanism with respect to SET-PT initiated by the proton loss (eq 12). The anion formed from proton loss undergoes the electron transfer (eq 13). ArOH → ArO− + H+

(12)

ArO− + Fe(IV )O → ArO• + Fe(III )−O

(13)

H+ + Fe(III )−O → Fe(III )−OH

(14)

Based on the above equations, the same thermodynamic balance will be obtained (ΔGHAT = ΔGSET‑PT = ΔGSPLET) as the reactants and products are the same for these three reaction mechanisms. The rate-limiting step, however, is different, leading to the competition between these three mechanisms governed by the kinetics and critical step of each mechanism. According to these reaction mechanisms, DFT/B3LYP/631G(d,p) calculations were performed to obtain the related I


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difference indicates how easily the transition from ground state to excited state may occur.39 According to the results shown in Table 4, the highest HOMO energy (−5.93 eV) was found for epinephrine and followed by dopamine (−5.95 eV) among the investigated tyrosine based biogenic amines. When combined with the dipeptides, there are some discrepancies with respect to the experimental kinetic data as Gly-Tyr exhibited the lowest HOMO energy. However, the lowest HOMO−LUMO gap (ΔE = −5.32 eV) of Tyr-Gly may partially explained the highest reaction rate constant (47.6 ± 6.6 L/mol/s) at pH 4.0 among the dipeptides. In addition, the electronic density distribution of HOMO and LUMO orbitals provides information about the regions with highest tendency to donate or accept electrons. It can be observed from Figure 7 that in

numerical descriptors for the predominant species at pH 4.0, 7.4, and 11.0 based on calculated distribution diagrams shown in Figure S7. According to eqs 9−14, the thermodynamic quantities of the three reaction mechanisms were calculated for the dominant species at pH 4.0 and 7.4 (Figures S7 and S8), and the obtained values are shown in Table 4. In addition, some other molecular descriptors such as pKa, log P, and dipole moment (μ), were also calculated and are listed in Table 4. Notably, the calculated bond dissociation enthalpy (BDE) of tyrosine was 331 kJ/mol, which is in good agreement with the experimental value of 356 kJ/mol as investigated by the electron paramagnetic resonance (EPR) technique. In addition, HAT, SET-PT, and SPLET reaction mechanisms are mainly governed by BDE, ionization potential (IP), and proton affinity (PA) descriptors, respectively. Therefore, the thermodynamically preferred reaction mechanism can be determined by comparing these descriptors. According to Table 4, PA values were found to be significantly lower than the corresponding BDE and IP values, indicating that the SPLET reaction mechanism was the thermodynamically preferred reaction mechanism for reduction of ferrylmyoglobin by tyrosine based food components in aqueous solution. This result is in agreement with the previous report showing that the SPLET reaction mechanism was thermodynamically favored for quenching radicals by phenols in aqueous solution.40,41 In addition, the calculated PA values have a good correlation with the obtained kinetic data, which also demonstrated that dopamine and epinephrine were the most efficient reductants among the investigated tyrosine based food components. However, the lowest PA value (215 kJ/mol) was found for the meta OH group in dopamine, while the para OH group corresponded to the lowest PA value (217 kJ/mol) in epinephrine. Notably, the obtained electron transfer enthalpy (ETE) values are all higher than PA values but still comparable with BDE values, suggesting that HAT and SPLET were competitive reaction mechanisms for reduction of ferrylmyoglobin in aqueous solution. For the SET-PT reaction mechanism, the first step (IP), as shown in Table 4, is highly endothermic, whereas the second step (PDE) is less energetically demanding and the high IP values clearly indicated that the SET-PT reaction mechanism was not thermodynamically preferred for reduction of ferrylmyoglobin in aqueous solution. Similar results were also obtained for radical quenching reactions by other phenolic compounds.40,42 In addition, the ETE values are lower than IP values in all cases as expected, indicating that the electron transfer from anions was more exergonic than from un-ionized forms. Therefore, the reduction reaction should be interpreted as the SPLET reaction mechanism when the proton dissociation is a thermodynamically eligible process. In addition, the calculated thermodynamic quantities exhibited good correlation with the experimental kinetic data, confirming that the proposed reaction mechanism as some thermodynamically unfavorable reactions can require very small activation energies and the endothermic process with the reaction enthalpy less than 45 kJ/mol should be considered.43 Frontier orbitals are another important molecular descriptor providing important information about the electron transfer ability of molecules. Higher HOMO energy of molecules indicated stronger electron donating ability, while lower LUMO energy suggested stronger electron accepting ability.44 The HOMO−LUMO energy gap is often used as an indicator of the kinetic stability and chemical reactivity of the molecules. This

Figure 7. HOMO LUMO orbitals of the dominant fractions of tyrosine based food components correspond to the reduction of ferrylmyoglobin in aqueous solution at pH 4.0 and 7.4.

general the HOMO orbitals were delocalized on the whole molecules while LUMO orbitals were mainly delocalized on the benzene rings for tyrosine based biogenic amines. Big differences were observed for dipeptides: for Tyr-Tyr, the HOMO orbital was delocalized on the C terminal benzene ring while the LUMO orbital was delocalized on the N terminal benzene ring. For Tyr-Gly, the HOMO orbital was only delocalized on the glycine residue instead of the tyrosine residue. In addition, according to the HOMO energies, the J


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Figure 8. Principal component analysis scores and loadings plots for the reduction of ferrylmyoglobin by investigated food components in aqueous solution at pH 4.0, 7.4, and 11.0. A and D: PC1 versus PC2. B and E: PC1 versus PC3. C and F: PC2 versus PC3. For score plots (A, B, and C), the black, red, and blue colors represent the reactions at pH 4.0, 7.4, and 11.0, respectively. For loading plots (D, E, and F), the black, red, green, blue, cyan, magenta, yellow, dark yellow, navy, purple, wine, olive, dark cyan, royal, and orange colors represent pKa, log P, log D, μ, BDE values, IP values, PDE values, PA values, ETE values, HOMO energy, LUMO energy, HOMO−LUMO energy gap, second order rate constants, enthalpy of activation, and entropy of activation, respectively.

order of the electron donating ability of investigated tyrosine based food components is in agreement with their IP values except Tyr-Gly. The calculated IP value represents the electron transfer ability of from the HOMO orbitals of the molecules. In the case of Tyr-Gly, the HOMO orbital was delocalized on the glycine residue, indicating that the electron transfer from TyrGly during the ferrylmyoglobin reduction was from glycine residue instead of tyrosine residue. This difference provides further information to explain the much faster reaction of the reduction of ferrylmyoglobin by Tyr-Gly at pH 4.0. Although the deprotonated forms (−NH2 and −OH) of tyrosine based food components were dominant species in aqueous solution at pH 11.0 as pH > pKa (Figures S7 and S8), similar results were obtained for the HOMO LUMO orbitals. (Analysis details are shown in the Supporting Information.) Principal Component Analysis. Principal component analysis (PCA) was performed to understand the relationships between the DFT calculated molecular descriptors and kinetic data. Figure 8 shows the scores and loadings plot with three principle components, for all samples, separated by pH. As can be seen from Figure 8, the first three PCs explained 77% of the total variance, with PC1 accounting for 45%, PC2 for 17%, and

PC3 for 15%. Moreover, the separation for samples was very obvious with the samples at pH 4.0 and 7.4 and samples at pH 11.0 separated by PC1, whereas the samples at pH 4.0 exhibited very good correlation with the samples at pH 7.4 as they corresponded to the same fractions (Figures S7 and S8). Regarding the loading plot (Figure 8D−F), PC1 was positively correlated with HOMO energy, LUMO energy, and PA values and negatively correlated with IP and ETE values, which was in line with the importance of the SPLET reaction mechanism analyzed before. Furthermore, PC2 was positively correlated with log D and negatively associated with dipole moments (μ), whereas PC3 was positively correlated with enthalpy of activation and entropy of activation. The two PC loading plot Figure 8 D shows the relationship between the obtained thermodynamic and kinetic parameters. The variations in PA values were more correlated to LUMO energy, and variations in second order rate constants were more aligned to that of HOMO−LUMO energy gap than PA values. In addition, BDE values were more correlated to ETE values, whereas BDE values were not found to correlate to PA values. The two PC score plot Figure 8 A separates the samples into different groups, enabling the interpretation of the results on the basis of K


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Figure 9. Heat map and dendrogram calculated from the obtained thermodynamic and kinetic data (Tables 3 and 4) for the reduction of ferrylmyoglobin by investigated food components in aqueous solution at pH 4.0, 7.4, and 11.0. The first number 1, 2, or 3 beside each sample represents reaction at pH 4.0, 7.4, or 11.0, respectively. For dopamine and epinephrine, the second number 1 or 2 represents the p-OH or m-OH, respectively. For Tyr-Tyr, the second number 1 or 2 represents the OH group in N terminal or C terminal, respectively.

all investigated parameters. As can be seen from Figure 8 A, the reduction of ferrylmyoglobin by dopamine and epinephrine at pH 11.0 was mostly characterized by PA values and LUMO energy. The reduction of ferrylmyoglobin by tyrosine based biogenic amines at pH 4 and 7.4 was characterized by second order rate constant. Moreover, the cluster on the negative side of PC2 including all the dipeptides was more characterized by dipole moment (μ), and high values of dipole moment (μ) were found for all dipeptides, indicating the high polarity (Tables 4 and S2). Furthermore, PCA was also performed separately for the reactions at each pH (Figure S13), and all obtained results illustrate the importance of the SPLET reaction mechanism for reduction of ferrylmyoglobin by studied tyrosine based food components. As shown above, the obtained PCA results provide important information for a more in depth approach to elucidate the effects of DFT calculated molecular descriptors on the kinetic data. For a more clear visualization of the reduction of ferrylmyoglobin by tyrosine based food components at different pH, a heat map with cluster analysis was generated with autoscaled data, and the results are shown in Figure 9. It is very obvious that the samples with high values of second order rate constant corresponded to the low PA values and low values of enthalpy

of activation. Three main clusters were obtained according to the unsupervised cluster analysis. Cluster 1 was composed of reduction of ferrylmyoglobin by epinephrine, dopamine, TyrTyr, tyramine, and octopamine at pH 11.0, which was characterized by high values of activation parameters. Cluster 2 included all the reduction reactions studied by tyrosine based food components at pH 4.0 and 7.4, which was expected as the same fraction was responsible for the reduction of ferrylmyoglobin. Cluster 3 was composed of the reactions with synephrine, tyrosine, Tyr-Gly, and Gly-Tyr, which were characterized by relatively low activation parameters. Reactions of ferrylmyoglobin reduction by tyrosine and Tyr-Gly at pH 11.0 were grouped in the same group, providing further information that the electron transfer from Tyr-Gly may be different from the other tyrosine based food components. Quantitative Structure−Activity Relationship Model. The partial least squares (PLS) regression analysis was performed to investigate the correlations between the second order rate constant (log k1) obtained at different pH as dependent variables and DFT calculated thermodynamic descriptors as independent variables. As SPLET reaction mechanism was identified as the main reaction mechanism, the BDE, IP, and PDE parameters were excluded during the L


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Figure 10. Partial least regression analysis for QSAR modeling. (A) The linear relationship between the predicted log k1 and observed log k1. The red line is the linear regression. (B) Permutation validation of the PLS model. (C) PLS regression coefficients of investigated parameters. The numbers 1, 2, 3, 4, 5, 6, 7, 8, and 9 represent pKa, log P, log D, μ, PA, ETE, EHOMO, ELUMO, and ΔE, respectively. (D) The variable importance for the projection (VIP) of the investigated parameters. The numbers 1, 2, 3, 4, 5, 6, 7, 8, and 9 represent pKa, log P, EHOMO, PA, ETE, ELUMO, μ, log D, and ΔE, respectively. (E) The score plot of the PLS model. The black, red, and blue colors represent the reaction at pH 4.0, 7.4, and 11.0, respectively. (F) The loadings plot of the PLS model. The black, red, green, blue, cyan, magenta, yellow, dark yellow, navy, and purple colors represent pKa, log P, log D, μ, PA, ETE, EHOMO, ELUMO, ΔE, and log k1, respectively.

as shown in Figure 10 B. According to the permutation rules, the newly obtained R2Y and Q2Y correspond to the real cumulative R2Y and Q2Y when correlation coefficient equals 1, whereas intercepts of R2Y and Q2Y are obtained when correlation coefficient equals 0, which are the parameters for measuring over fitting. As shown in Figure 10 B, the intercepts of R2Y and Q2Y were 0.058 and −0.254 respectively, which were much lower than the desirable limits (R2Y < 0.3 and Q2Y < 0.05),47 indicating that the established QSAR model was valid. Based on the obtained model, the coefficients of each investigated thermodynamic descriptors were calculated (Figure 10 C) and resulted in the following QSAR model:

PLS analysis for saving computational time in future studies. The PLS analysis gave the maximum correlation and QSAR model and the results are shown in Figure 10. With two PLS extracted principal components, the established QSAR model exhibited very good fitness between the observed and predicted log k1 as shown in Figure 10 A. The cumulative explained variance of log k1 was characterized by R2Y with the value of 0.71, and the RMSEE was 0.75. The robustness and internal predictability was characterized by Q2Y as calculated to be 0.58, which was higher than the generally defined value of 0.5 indicating the good performance of the QSAR model and good internal predictability.45 Moreover, the difference between the R2Y and Q2Y was lower than 0.3, suggesting no overfitting in the obtained model.46 The model was initially validated by cross validation during the PLS modeling, and the predictive power of the model was further validated by permutation test, where the Y data (log k1) was recorded randomly and permuted 100 times to generate the scrambled log k1 but with unperturbed X data for the new fitting and cross validation. After the permutation test, the newly obtained cumulative R2Y and cumulative Q2Y were plotted against the correlation coefficient

log k1 = 0.34 pK a − 0.42 log P + 0.30 log D + 0.36μ − 0.19 PA + 0.10 ETE − 0.17E HOMO − 0.18E LUMO + 0.12ΔE + 0.26 (R2 Y = 0.71, Q 2 Y = 0.58, RMSEE = 0.75)

(15)

During the PLS analysis, the variable importance for the projection (VIP) of thermodynamic descriptors was further M


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method succeeded in studying this reaction with the obtained second order rate constant of 66 ± 28 L/mol/s. Compared to cysteine containing proteins shown in Figure S15, the reaction was much slower. Previous study indicated that the reduction of ferrylmyoglobin by cysteine containing proteins was mainly through the thiol group in cysteine residues.23 Therefore, the obtained slower reaction rate was in accordance with the result that the reduction of ferrylmyoglobin by cysteine was faster than by tyrosine. In the gastrointestinal tract, the amino acid mixtures may be more relevant for reducing ferrylmyoglobin. Therefore, the combinations of tyrosine and cysteine were selected to reduce ferrylmyoglobin, and the results are shown in Figure S16. As indicated by first and second order rate constants, no synergistic and antagonistic effects were observed, suggesting that the electron transfers from the −OH group in tyrosine and the −SH group in cysteine to the iron(IV) center in ferrylmyoglobin were not affected by each other. However, a significant antagonism was observed for green tea polyphenol combinations containing epicatechin, indicating that the less efficient reductants may block the access for the efficient reductants.50

calculated to quantitatively summarize the importance of the variables for explaining the variations in second order rate constant (log k1). The VIP values were calculated by summing the squares of the PLS loading weights and weighted by the amount of sum of squares explained in each model component (Figure 10D). The average VIP value equals 1 as the sum of squares of all VIP values is equal to the number of terms in the model. An obtained VIP value higher than 1 indicates that the corresponding X variable is important, whereas a value lower than 0.5 indicates that the variable is not of importance. As indicated by Figure 10 D, the pKa was calculated to be the most important thermodynamic descriptor for governing the second order rate constant with a VIP value of 1.15, followed by log P (1.10) and EHOMO (1.07), while log D and ΔE were in the last two positions with smaller VIP value. In general, a higher value of pKa indicates a smaller extent of proton dissociation at a given pH. Therefore, the pKa values of the −OH group calculated in the present study are directly related to the first step of the SPLET reaction mechanism during the ferrylmyoglobin reduction. In addition, log P of tyrosine based food components was found to be of importance for reduction of ferrylmyoglobin by PLS analysis in agreement with a previous study which also showed the electron transfer ability of phenolic antioxidants related to their partition coefficients.48 Moreover, the scores of log k1 in first model dimension t [1] versus second t [2] and loading weights of thermodynamic descriptors in the first principal component w*c [1] versus second w*c [2] are plotted in Figure 10, panels E and F, respectively. As can be seen from the Figure 10F, it was clear that w*c [1] mainly focused on the reaction mechanism information about PA, ETE, HOMO energy, and LUMO energy, whereas the w*c [2] was related to log P and pKa. Moreover, PA, HOMO energy, and LUMO energy were indicated to be negatively correlated with log k1, but ETE had a positive correlation with log k1 along w*c [1]. These results were in agreement with the previous PCA results indicating the importance of the SPLET reaction mechanism for reduction of ferrylmyoglobin. As shown in Figure 10E, in accordance with the PCA results, a very good separation between the samples at pH 4.0 and 7.4 and the samples at pH 11.0 was observed. In addition, the excluded thermodynamic descriptors also exhibited effects on the obtained second order rate constants according to previous principal component analysis, therefore, PLS analysis was also performed using all the investigated parameters, and the results are shown in Figure S14. The performance of the obtained QSAR model was slightly declined, but the HOMO−LUMO energy gap and log D were still identified to be the least significant thermodynamic descriptors. Dipole moment (μ), however, was found to be the most important variable for the second order rate constant. This result suggested the importance of the dipole moment (μ) for HAT and SET-PT reaction mechanism. Protein−Protein Interaction. The three tyrosine residue containing protein, lysozyme, is widely used in the food industry as an antimicrobial agent. There is no free thiol group in lysozyme as the cysteine residues are all oxidized forming 4 disulfide bridges.49 As cystine (oxidized cysteine) does not possess the ability of reducing ferrylmyoglobin,27 the reduction of ferrylmyoglobin by lysozyme is more likely through the tyrosine residues (Tyr 20, Tyr 23, and Tyr 53). Therefore, lysozyme was selected to investigate the electron transfer from tyrosine residues in protein to ferrylmyoglobin. As shown in Figure S15, the previously established competitive kinetic

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jafc.7b02420. Materials and methods, results and discussion, and figures and tables (PDF)

■

AUTHOR INFORMATION

Corresponding Author

*Tel: 45-3533 3221. E-mail: [email protected]. ORCID

Leif H. Skibsted: 0000-0003-1734-5016 Funding

N.T. is grateful for the support from China Scholarship Council (CSC) (201406170034). Notes

The authors declare no competing financial interest.

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