Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 151 (2015) 111–123

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Conformational and vibrational analyses of meta-tyrosine: An experimental and theoretical study Guohua Yao a, Jingjing Zhang a, Qing Huang a,b,⇑ a Key Laboratory of Ion Beam Bioengineering, Institute of Technical Biology and Agriculture Engineering, Hefei Institutes of Physical Science, Chinese Academy of Sciences and Anhui Province, PR China b University of Science & Technology of China, Hefei, Anhui 230026, PR China

h i g h l i g h t s

g r a p h i c a l a b s t r a c t

 The structural and vibrational

properties of m-tyr were systematically investigated.  The Raman spectra of solvent and recrystallized m-tyr were recorded and analyzed.  SMD solvent model can reproduce the vibrational spectra of solid state amino acid.

a r t i c l e

i n f o

Article history: Received 18 November 2014 Received in revised form 18 June 2015 Accepted 22 June 2015 Available online 23 June 2015 Keywords: Meta-tyrosine Raman spectrum SMD solvent model Amino acid DFT-D3

a b s t r a c t M-tyrosine is one kind of positional isomer of tyrosine which is widely applied in agrichemical, medicinal chemistry, and food science. However, the structural and vibrational features of m-tyrosine have not been reported or systematically investigated. In this work, potential energy surface (PES) calculations were used for searching and determining the stable zwitterionic conformers of m-tyrosine, and the Raman spectra of m-tyrosine and deuterated m-tyrosine were measured and interpreted based on theoretical computation. For the spectral simulation, several DFT-based quantum chemistry (QC) methods were employed, and the M06-2X functional with SMD solvent model was found to be best in reproducing the Raman spectra and geometrical property. As such, this study has not only presented a detailed study of m-tyrosine’s vibrational property which is lack in the literature, but also may shed some light on the optimal choice of QC methods for calculation of conformations and vibrational properties of zwitterionic amino acids. Ó 2015 Elsevier B.V. All rights reserved.

1. Instruction Tyrosine belongs to one class of a-amino acids containing aromatic ring in its side chain. In addition to the common para-tyrosine (p-tyrosine, p-tyr or 4-hydroxyphenylalanine), there are two additional regioisomers, namely, meta-tyrosine ⇑ Corresponding author at: P.O. Box 1138, Shushanhu Road 350, Hefei 230031, PR China. E-mail address: [email protected] (Q. Huang). http://dx.doi.org/10.1016/j.saa.2015.06.073 1386-1425/Ó 2015 Elsevier B.V. All rights reserved.

(m-tyrosine, m-tyr or 3-hydroxyphenylalanine) and ortho-tyrosine (o-tyrosine, o-tyr or 2-hydroxyphenylalanine). The m-tyr and o-tyr isomers are non-proteinogenic amino acids and rarely found in nature. However, they are available synthetically and can also arise through non-enzymatic free-radical hydroxylation of phenylalanine under conditions of oxidative stress like hydroxyl radicals or peroxynitrite [1–4]. Beside, tyrosine positional isomers can be generated from radiation induced chemical reactions of free phenylalanine as well as phenylalanine containing proteins, and so they can be used as markers in irradiated foods

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for dose estimation. For example, the method of o-tyrosine detection by high-performance liquid chromatography (HPLC) or chromatography has been used for monitoring irradiated protein-rich foods [5,6]. Also, the accumulation of m-tyrosine in mammalian tissues has been used as an indicator for determining the oxidative stress and aging process [7]. M-tyrosine, which can be extracted from the roots of fescue grasses, acts as a potent allelopathic, a root growth inhibitor [8– 11]; but the mechanism of m-tyrosine’s herbicidal activity is still elusive [10]. Several bacteria use m-tyrosine as a precursor for the synthesis of antibiotics such as mureidomycins, pacidamycins, and napsamycins [12]. In fact, m-tyrosine has been applied in medicinal chemistry and in the study of metabolic pathways in the central nervous system [12]. M-tyrosine and analogs thereof have found applications in the treatment of Parkinson’s disease [13], Alzheimer’s disease, arthritis, as agents for pancreatic disorders [14]. M-tyrosine and o-tyrosine have antitumor effects, potentially driving tumor cells into a state of dormancy and inhibiting humor growth [15,16]. On the other hand, there are many studies on the synthesis of the m-tyrosine and their analogs [14,17,18]. Because research on molecular structural and spectral properties can lead to deeper insights and wider applications, there have been a lot of spectral and theoretical studies devoted to the investigation of structural and vibrational properties of p-tyrosine. For example, people have employed neutron diffraction technique to determinate the crystal and molecular structure of p-tyrosine in zwitterionic form [19], Raman spectroscopy and density functional theory (DFT) calculation to study the vibrational property of p-tyr in hydrated media [20,21], ab initio methods to study the neutral form conformers in gas phase [22], polarized Raman scattering to scrutinize the crystal and molecular structures [23], quantum chemistry (QC) computation to investigate the molecular structures of p-tyrosine dimers, anions, cations and zwitterions [24], and Raman and far-infrared (IR) spectroscopy tools to reveal the zwitterionic structures and vibration properties [25]. However, to the best of our knowledge, the experimental and theoretical study of Raman and IR spectra of o-tyr and m-tyr has never been reported. In view of the importance of m-tyr, the present study intended to fill the gap and provide a detailed experimental and theoretical study of m-tyrosine. Our results revealed that the M06-2X method with SMD solvent model can excellently simulate the Raman spectra and geometry. 2. Experimental details 2.1. Materials and instruments Analytical grade p-tyrosine (p-tyr), m-tyrosine (m-tyr) were purchased from Sigma–Aldrich Co, Ltd. Potassium bromide (KBr) in spectral purity and D2O (99.9%) were purchased from Sinopharm Chemical Reagent Co., Ltd. Distilled water was used in the experiments. All the Raman spectra with resolution ca. 3 cm 1 were taken in the 200–3500 cm 1 range using HORIBA JOBIN YVON XploRA Raman spectrometer excited with a 532 nm laser. The laser power was set at ca. 1.2 mW, and the acquisition time was 30 s. All the IR spectra were recorded in the 400–4000 cm 1 range using a FTIR spectrometer (BRUKER ALPHA-T) at room temperature, with 128 scans for each spectrum and spectral resolution ca. 2 cm 1. 2.2. Sample preparation and spectral measurements M-tyrosine or p-tyrosine was dissolved in distilled water at concentration of 1 mM, and then recrystallized on a quartz substrate for Raman spectral recording. The Raman spectra of

p-tyrosine were also measured so as to help assignment of the bands of m-tyrosine and to assess the theoretical methods utilized in the calculations. Partially deuterated m-tyrosine, in which the hydrogens in the NH+3 group and the OH group are substituted by deuterium, was prepared by dissolving m-tyrosine in D2O. The isotope Raman spectra were recorded from the recrystallization of deuterated m-tyrosine on a quartz substrate at room temperature under dry environment. In addition, Raman spectra of dissolved m-tyrosine and recrystallized m-tyrosine at acidic and alkaline conditions were measured. M-tyrosine solutions at 0.5 M with pH = 1 or pH = 13 were prepared and their Raman spectra were recorded. These Raman spectra represent the vibrational information of m-tyrosine at acidic and alkaline solvent conditions. The m-tyrosine solutions at acidic and alkaline solvent conditions were recrystallized on the quartz substrates, and the respective Raman spectra of m-tyrosine-Cl and Na-m-tyrosine crystal were recorded. For the FTIR measurements, the m-tyrosine or p-tyrosine powders were mixed with KBr and then pressed into pallets, respectively. The FTIR spectra of the pallet samples were recorded in the range of 800–4000 cm 1.

3. Computational details The initial configurations were obtained by full optimization at B3LYP/6-31G(d) level of theory, followed by the vibrational frequency calculations. The calculations using B3LYP/6-31G(d) can provide a relatively quick screening of the configurations. However, B3LYP often gives rise to inaccurate hydrogen bond energies of biologically relevant molecules, while the small 6-31G(d) basis set does not provide sufficient precision [26,27]. Therefore, higher precision level approaches should be attempted for more accurate simulation. To search for a better method and check the validity of our approach, both p-tyrosine and m-tyrosine were simulated referring to the mostly used or highly evaluated theoretical methods and the reported data of p-tyrosine found in the literature [28,29]. These methods include three kinds of GGA (generalized gradient approximation [30]) functionals, e.g., BLYP (pure functionals), B3LYP (three-parameter hybrid functionals), M06-2X (hybrid meta functionals with the kinetic energy density gradient) [31,32], and their DFT-D3 correction versions denoted as B3LYP-D3, BLYP-D3, M06-2X-D3 [33]. Since in many molecular crystals, the intra- and inter-molecular dispersion effects are large, Grimme’s group recommended the routine application of their new standard atom pair-wise dispersion correction (DFT-D3) for molecular crystals [34]. B3LYP-D3 and BLYP-D3 used in this work have included the BJ-damping corrections (the damping function proposed by Becke and Johnson, which determines the short-range behavior of the dispersion correction and is needed to avoid near-singularities for small inter-nuclear distance and double-counting effects of electron correlation at intermediate distances.) [29], while M06-class functionals do not need additional damping function [31]. The basis sets are 6-311++G(d,p), which were found suitable for amino acids [21,25,26]. In the present work, we studied the zwitterionic forms of m-tyrosine because the zwitterion constitutes the most important form for most amino acids as they maintain the structures and functions of peptides and proteins. The solvent effects are considered to be crucial in stabilizing the zwitterionic structures of amino acids. In the previous work, the solvent effects were taken into account by using IEF-PCM (integral-equation-formalism polarizable continuum model, abbreviated as PCM) model [24,25,35]. Here both PCM model and an new implicit solvent models SMD

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[36] under default setting in Gaussian 09 package were employed for the calculations of both the energy and vibrational properties. In the previous work [21,23,25,37], possible conformers of p-tyrosine have been studied with the Raman and IR experiments combined with quantum chemical calculations. The calculated conformers which agree with the experimental spectra are the same as the crystal structure in Ref. [19]. Both the COO and NH+3 are on the gauche position, as shown in Fig. 1. From the X-ray diffractions in Ref. [38], m-tyrosine is constructed with an anti-position for the COO and a gauche position for the NH+3. In the present work, different QC methods (M06-2X, BLYP, B3LYP with or without D3 correction) with two solvent models (PCM and SMD) were used to simulate the geometries and spectra of p-tyrosine and m-tyrosine at crystal structure and compare the calculation results with the experimental results. The Raman and IR spectra calculated from this preferred theoretical method were used to assign the vibrational modes of m-tyrosine and p-tyrosine. All the calculations were performed under Gaussian 09 program D.01 version [39]. Vibrational frequency assignments were made based on the results of the Gaussview program 5.0.8 version [40] and the potential energy distribution (PED) matrix as expressed in terms of a combination of local symmetry and internal coordinates. 4. Results and discussion 4.1. Structural properties 4.1.1. Conformation definitions The schematic diagram of the zwitterionic conformers of m-tyrosine with labeling of the atoms are shown in Fig. 1. As the Cb–C1 and Ca–Cb bonds of m-tyrosine are rotatable, a series of conformers with different torsion angles may exist. The energy scanning of the potential energy surface (PES) was carried out as the first step in searching the stable conformers. The energy landscapes of m-tyrosine shows the variation of the electronic energy as a function of s1 (Ca–Cb–C1–C2) and s2 (Cc–Ca–Cb–C1) torsion angles, as shown in Fig. 2A. E(s1, s2) values were calculated by a single-point approach through successive steps of 15° on each torsion angle. As shown in Fig. 2A, there are 6 valleys in the PES which are colored in blue. In the actual conformer searching, a series of initial structures at different torsion angles were constructed, and then were optimized without restriction of torsion angles. Only six stable conformers of m-tyrosine were obtained which are denoted as A1, A2, B1, B2, C1, C2 as shown in Fig. 2B. These six stable conformers are exactly corresponding to the six deepest valleys of the PES in Fig. 2A. Among the six conformers, the A1 conformer corresponds to the reported crystal structure [38], as will be discussed in detail in Sections 4.1.3 and 4.1.4.

Fig. 1. Schematic diagrams for the structures of m-tyrosine and p-tyrosine with labeling of atoms.

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From the Newman projections it is clear to identify these six conformers: (1) Both A1 and A2 have the COO- group at the anti-position and NH+3 at the gauche position with respect to the side chain; A1 and A2 have the nearly opposite dihedral angel s1 (Ca–Cb–C1–C2); (2) Both B1 and B2 have the gauche position for the COO and the NH+3 groups; B1 and B2 have nearly the opposite s1. (3) Both C1 and C2 have the gauche position for the COO and the anti-position for the NH+3; C1 and C2 have nearly the opposite s1. It should be noted that the conformers by the flip of phenolic OH group related to s3(N1–Ca–Cc–O1) are also stable. They are denoted as A1r and A2r , B1r and B2r , C1r and C2r (as shown in Fig. S1), where the lowercase letter ‘r’ means the reverse of phenolic OH group. They differ from that of conformers A1, A2, B1, B2, C1 and C2 by a flip of the hydroxyl group on the phenol ring, respectively. Therefore, there are totally 12 stable zwitterionic conformers for m-tyrosine. Here we only present the calculations for A1, A2, B1, B2, C1 and C2 conformers, since their vibrational properties are very similar to their counterparts (A1r, A2r, B1r, B2r, C1r and C2r conformers). The energy and vibrational properties of these counterparts are given in Supporting information (Figs. S1 and S5). 4.1.2. Structures of m-tyrosine and p-tyrosine from different theoretical approaches The optimized structures of different tyrosine types by different approaches were compared with the crystal structures. The geometrical parameters of m-tyrosine were determined by X-ray diffractions, and some important bond lengths were corrected in Ref. [38]. These bond lengths are compared with the calculation results in Table S1 (in the Supplementary materials) and their RMSDs (root mean squared deviation) of calculated bond lengths with respect to experimental values are shown in Fig. 3A. Table S2 in the Supplementary materials shows the comparison of the calculated geometrical parameters for p-tyrosine by different DFT methods with its reported crystal structure [19], and their RMSDs are shown in Fig. 3B. The key points from the tables and figures are summarized as follows. Firstly, it shows that on the whole SMD gives out better structure results for different kinds of methods with or without D3 corrections. For m-tyrosine, the SMD model can achieve more accurate geometrical parameters than the PCM model, about 20.97% better averaged for six methods. For p-tyrosine, the results using the SMD model are 7.20% better in average. Secondly, the contributions of D3 correction in different methods are different. For m-tyrosine, D3 corrections achieve 7.20% better results in average, with 0.00% for M06-2X, 10.71% for BLYP, and 10.95% for B3LYP. For p-tyrosine, it shows that D3 corrections also get a bit better result about 1.48% in average for three methods under the SMD or PCM model, i.e., 0.00% for M06-2X, 3.13% for BLYP and 1.30% for B3LYP, respectively. For B3LYP and BLYP, D3 corrections are recommended in the amino acids calculation, while D3 correction seems not necessary for the M06-2X method. The M06-2X method with SMD model gets the best geometric result, since RMSDs are only 0.00571 Å and 0.0120 Å for m-tyrosine and p-tyrosine, respectively. To get a better understanding for the improvement caused by SMD model, it requires the discussion of the choice of solvent models in more detail. Firstly, in the calculation, the quantum mechanical continuum implicit solvent models should be adopted because the zwitterionic form of amino acids cannot be obtained by structural optimization in the gas phase since one proton in the NH+3 group will move to the COO group to form the neutral species. The solvent models, based on the quantum mechanical charge density of a solute molecule interacting with a continuum medium, provide a suitable way to stabilize zwitterionic structures of amino acids. The solvent models are in fact composed of a solute put into

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Fig. 2. (A) 3D and 2D representations of potential energy surface (PES) of m-tyrosine calculated at M06-2X/6-311++G(d,p) level of theory. PES shows the variation of electronic energy of m-tyrosine as a function of conformational angles s1 and s2 (Fig. 1). (B) These six deepest valleys of PES in blue color correspond to six stable conformers. Accordingly, the Newman projections (left) and corresponding optimized structures (right) for six conformers of m-tyrosine are shown. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

a void cavity within a continuous dielectric medium mimicking the solvent [41], therefore, they have been extended to treat complex phases such as ionic solutions, heterogeneous systems, liquid–gas and liquid–liquid interfaces, crystals, etc. [41]. In our case, the water solvent models involve the electrostatic and nonelectrostatic contributions, polarization effects, and the factors including the hydrogen bonding, stacking effect, van der Waals interaction, dispersion, etc. Secondly, it is noticed that the SMD model can yield better results than the PCM model as it results in higher accuracy for solvation free energies. The SMD model is a new universal continuum solvation model that employs a dielectric medium with surface tension at the solute–solvent boundary [36]. This model separates the observable solvation free energy into two main components. The first component is the bulk electrostatic contribution arising from a self-consistent reaction field treatment that involves the solution of the nonhomogeneous Poisson equation (NPE) for electrostatics in terms of the IEF-PCM. The second component is called the cavity–dispersion–solvent-structure term (CDS) and is the

contribution arising from short-range interactions between the solute and solvent molecules in the first solvation shell. The SMD model employs a single set of parameters optimized over six electronic structure methods, while the model parameters are intrinsic Coulomb radii for the bulk electrostatic calculation and atomic surface tension coefficients for the CDS contribution. The SMD model includes consistently optimized parameters for the first solvation shell. The SMD model differs from conventional IEF-PCM model mainly in two aspects. Firstly, the SMD model can employ either the single set of parameters optimized for the IEF-PCM algorithm, or the parameters obtained by other algorithms (e.g., COSMON, CPCM) for solving the NPE in which the solute is represented by its electron density in real space. Secondly, the SMD model has the better treatment of the CDS-type contributions, by extending the strategy in the SM8 parametrization; this strategy has led to more accurate models than those for which the electrostatic and nonelectrostatic terms are determined separately. From the calculation of solvation free energies, the SMD model performs much better than the PCM model in QC packages, such as, Gaussian03,

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Fig. 3. RMSD of calculated bond lengths with respect to experimental values of (A) m-tyrosine and (B) p-tyrosine using different methods and solvent models.

GAMESS and NWChem [36]. Thus, the accurate energy calculations with the SMD model lead to the exact optimized structure of m-tyrosine at the crystal medium condition. In order to get an in-depth understanding of the D3 correction in different methods, here we give some explanation regarding the Kohn–Sham density functional theory (DFT) and Grimme’s dispersion correction. In general, DFT is an ideal solution to balance the hardware resource and the accuracy of computational chemistry. However, the proposed exchange–correlation functionals suffer from severe problems, for instance, the self-interactionerror (SIE, also called delocalization-error in many-electron systems) and the lack of long-range correlation effects, e.g. London-dispersion. Since most density functionals are inaccurate for dispersion-dominated weak interactions, one way to improve the performance of DFT is to augment the DFT energy by a special dispersion term. The method of dispersion correction reported by Grimme et al. is an add-on to standard Kohn–Sham density functional theory (namely DFT-D), whose atom-pairwise specific dispersion coefficients and cutoff radii are both computed from first principles, refined with higher accuracy, broader range of applicability, and less empiricism. D3 correction refers to the third version of Grimme’s dispersion correction yielding results with enhanced accuracy [33]. Grimme et al. studied various density functions (DFs) carried out on the new GMTKN30 database for general main group thermodynamics, kinetics and non-covalent interactions, and they found that DFT methods with D3 correction perform better for a wide range of intramolecular and thermochemical problems [28]. They also tested the finite damping as introduced by Becke and Johnson (BJ-damping), and concluded that BJ-damping leads to a little better results for non-bonded distance and more clear effects of intramolecular dispersion, and DFT-D3(BJ) seems to be a theoretically satisfying revision of DFT-D3 [29]. Dispersion interactions exist between every atom and molecule, and amino acids always contain weak interactions like intramolecular and intermolecular H-bonds, which more or less need dispersion corrections. Therefore, DFT-D3 method performs better for the structure calculation. But the M06-2X functional is based on a different approach to correct the dispersion effect, namely, a hybrid meta exchange–correlation functional that has been optimized to give good performance for a broad range of properties including non-covalent interactions [31,32]. Thus, dispersion corrections are favorable in structural calculation, and BLYP-D3, B3LYP-D3 with BJ-damping can result in more improvements than M06-2X-D3.

On the whole, dispersion correction is necessarily considered, specifically for the conversional GGA (BLYP, B3LYP). But M06-2X deals with dispersion effects itself, so the results of M06-2X and M06-2X-D3 is almost the same. For the structural calculation, M06-2X is still better than BLYP-D3 and B3LYP-D3, because M06-2X-D3 is an excellent hybrid meta-GGA utilizing the kinetic energy density gradient, which doubles the amount of non-local exchange and the correlation functional with the opposite-spin and parallel-spin correlation treated differently. Therefore, the energies and structures of different conformers applied and discussed in the following are based on the results from M06-2X without D3 correction. This is actually our recommended theoretical method for the amino acid structure calculations. 4.1.3. Comparison of the zero-point corrected energies of different mtyrosine conformers The structures, energies (with zero-point corrections) and vibrational spectra of six conformers were calculated using 12 theoretical methods, respectively. The B1 conformer has the lowest energies, thus the energies of other conformers are compared with B1 conformer. The zero-point corrected energies of all conformers relative to B1 are shown in Table 1. The descending order of energies of different conformers using the SMD model is generally consistent to that using the PCM model when calculated at the same theoretical method. The descending orders of energies resulted from M06-2X, M06-2X-D3, BLYP-D3 and B3LYP-D3 are the same, which is B series (B1, B2) < A series (A1, A2) < C series (C1, C2). For BLYP and B3LYP, however, the calculated energy order is roughly A series < B series < C series. Comparison between the experimental and calculated structure parameters (Fig. 3) reveals that the methods with D3 correction can produce better optimized structure. Therefore, the energies from D3 corrected methods are more credible. Fig. 4 shows the averaged relative energy (DE in kJ/mol) of various conformers of m-tyrosine with D3 correction. From Fig. 4, it can be seen that B1 conformer has the lowest energy among the six conformers, lower than A1, A2, B2, C1 and C2 by 2.94, 1.16, 1.36, 5.88 and 6.49 kJ/mol, respectively. The energies of A1r, A2r, B1r, B2r, C1r and C2r are at the same level as A1, A2, B1, B2, C1 and C2, respectively (as shown in Fig. S1). The crystal m-tyrosine is in the A1 conformer instead of the B1 conformer [38]. This is because in the solid crystal state, not only the single molecular energy is important in stabilizing a specific conformer, but also the crystal packing forces resulting from intermolecular

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Table 1 The relative zero-point corrected energy (DE in kJ/mol) of various conformers of m-tyrosine with respect to B1 at different theoretical methods and solvent models. Method Model

M06–2X SMD

M06–2X PCM

M06–2X-D3 SMD

M06–2X-D3 PCM

A1 A2 B1 B2 C1 C2

3.45 2.15 0.00 1.51 5.65 6.95

4.89 3.74 0.00 2.06 13.49 13.58

3.67 2.32 0.00 1.53 6.56 7.11

5.05 3.94 0.00 2.14 13.66 13.73

BLYP SMD 4.24 3.96 0.00 0.32 1.26 1.55

Blyp PCM 2.01 2.19 0.00 1.14 6.90 2.01

BLYP-D3 SMD 2.34 0.47 0.00 0.76 5.11 5.59

BLYP-D3 PCM 3.08 3.35 0.00 1.95 12.77 3.08

B3LYP SMD

B3LYP PCM

3.31 3.64 0.00 1.34 4.99 1.36

1.49 1.47 0.00 1.06 7.93 1.49

B3LYP-D3 SMD

B3LYP-D3 PCM

Mean

STDEV

2.31 0.65 0.00 1.65 6.19 6.29

3.03 3.24 0.00 1.56 13.09 13.07

2.94 1.16 0.00 1.36 5.88 6.49

0.72 1.32 0.00 0.41 0.63 0.69

obtained by X-ray crystallography. The geometries were optimized with M06-2X/6-311++G(d,p) using the SMD model to obtain the stable zwitterionic form. The RMSDs of bond lengths of different conformers are at the same level. Different conformers can be identified by the characteristic dihedral angles s1(C2–C1–Cb–Ca) and s2(C1–Cb–Ca–Cc). For example, A1 and A2, B1 and B2, C1 and C2 have the inverse s1 (C2–C1–Cb–Ca) angle, respectively. A1 conformer is mostly close to the experimental torsion angles, and its s1(C2–C1–Cb–Ca), s2(C1–Cb–Ca–Cc), and s4(N1–Ca–Cc–O1) are approximately 70°, 180°, 5°, respectively. A1 conformer has the same orientation for the OH group as the crystal structure in Ref. [38], and the OH group acts as hydrogen donors in inter-molecular hydrogen bonds. Other conformers may also exist in other conditions, such as in solution or even in gas phase. 4.2. Vibrational analyses

Fig. 4. The averaged relative energy (DE in kJ/mol) of m-tyrosine conformers based on different theoretical approaches with D3 correction.

interaction are also important. In other words, we cannot determine the solid state conformer just from the comparison of the single molecular energies of different conformers of amino acid. 4.1.4. Comparison of the structures of different m-tyrosine conformers In Table 2, the calculated geometric parameters of 6 conformers of m-tyrosine are compared with the experimental results

4.2.1. Calculated Raman spectra with different methods The Raman spectra of A1 conformer of m-tyrosine were simulated with theoretical methods. The results are compared with the experimental spectra in Fig. S3A. The Raman spectra of p-tyrosine (Fig. S3B) were also calculated using the crystal conformer [19]. The vibrational analysis was carried out within the harmonic oscillator approximation. The harmonic vibrational frequency scaling factors of M06–2X/6–311++G(d,p) and B3LYP/6–311++G(d,p) and BLYP/6–311++G(d,p) are 0.983 [42], 0.9688 [43] and 1.0001 [43], respectively. This means that the frequency scaling factors of BLYP can be ignored in the spectral simulation. Generally speaking, all of these selected methods can produce acceptable Raman spectra compared with the experiments. The

Table 2 Bond lengths (Å) and dihedral angles (°) of m-tyr conformers calculated under M06-2X/6-311++G(d,p) with SMD model.

Bond lengths (Å) C1–C6 C6–C5 C5–C4 C4–C3 C3–C2 C1–C2 C1–Cb Cb–Ca Ca–N Ca–Cc Cc–O1 Cc–O2 C5–Oa RSMD

Exp.a

A1

A2

B1

B2

C1

C2

1.389(0.002) 1.406(0.002) 1.388(0.002) 1.385(0.002) 1.388(0.002) 1.399(0.002) 1.515(0.002) 1.530(0.002) 1.498(0.002) 1.538(0.002) 1.257(0.002) 1.255(0.002) 1.363(0.002)

1.394 1.394 1.391 1.391 1.391 1.397 1.510 1.528 1.495 1.541 1.252 1.249 1.372 0.00571

1.397 1.390 1.395 1.388 1.395 1.394 1.509 1.530 1.494 1.539 1.251 1.250 1.371 0.00682

1.397 1.391 1.394 1.388 1.394 1.396 1.511 1.533 1.495 1.540 1.251 1.250 1.371 0.00649

1.396 1.393 1.392 1.390 1.392 1.397 1.510 1.534 1.495 1.540 1.252 1.250 1.371 0.00600

1.395 1.391 1.394 1.389 1.394 1.393 1.507 1.534 1.494 1.541 1.254 1.249 1.372 0.00697

1.394 1.392 1.392 1.390 1.392 1.396 1.508 1.534 1.494 1.542 1.254 1.249 1.372 0.00627

71.6(0.1) 171.6(0.1) 16.0(0.1)

72.8 177.4/182.6 5.2 13.884

106.8 178.6/181.4 6.4 103.322

97.4 60.9 7.8 135.164

85.0 60.9 9.1 161.890

105.2 59.5 31.5 68.128

77.8 60.1 33.5 108.086

Dihedral angles (°)

s1(C2–C1–Cb–Ca) s2(C1–Cb–Ca–Cc) s4(N–Ca–Cc–O1) RMSD a

Experimental Data from Ref. [38], the standard deviations in distances were 0.002 Å and in angles 0.1°.

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Fig. 5. Raman spectra of m-tyrosine: (A) deuterated Raman spectrum, (B) native Raman spectrum and (C) Raman spectrum calculated at M06-2X-D3/6-311++G(d,p) under SMD model.

spectra calculated with BLYP-D3 and B3LYP-D3 are nearly the same as those with BLYP and B3LYP, which is expectable since adding D3 correction has only a slight effect on structural parameters. But the spectra using different solvent models (SMD or PCM) show evident changes. On the whole, utilizing the SMD model and D3 correction improves the calculation results for m-tyrosine and p-tyrosine in terms of both molecular geometries and Raman spectra. The precisely calculated structure can therefore yield more accurate electronic density outside the molecule, which is also important for the electromagnetic properties, such as polarizability, electric dipole moment, of a molecule. Therefore, it is not surprising that using the SMD model and D3 correction can give rise to more precise band positions and band intensities for simulated Raman spectra. By comparing the computed and the measured Raman spectra of p-tyrosine and m-tyrosine, we found out that M06-2X method

within the SMD solvent model can give rise to the best calculation results, especially in the intensities of Raman bands. Thus the calculated results through this approach are used for the following spectroscopic analyses. However, BLYP-D3 may also useful in simulating the vibrational spectra of unknown molecule, because they do not need to be scaled to fit the experimental data by a scaling factor of the force constant matrix, which means that they may still have the predictive potential in some aspects. Due to the different positions of the hydroxyl group connected to the side-chain aromatic ring, drastic differences appear in the IR and Raman spectra of m-tyrosine and p-tyrosine as shown in Fig. 7. With reference to the study of molecular vibrations of p-tyrosine reported previously [21,23,25,37], the calculation of m-tyrosine was carried out and compared in Table 3. Here, we mainly focus on the 1700–400 cm 1 region which gives the most useful information on the backbone and side-chain vibrational modes. Some

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important vibrational modes in the Raman spectrum are shown in Fig. S2. 4.2.2. Raman spectra of natural abundant and deuterated m-tyrosine From Fig. 5 and Table 3, it can be seen that most of the strongest Raman bands of m-tyrosine are from the skeletal modes of the aromatic ring. The bands at 1609, 1604 cm 1 are mainly associated with the in-phase vibrations of the stretching of opposite C@C bonds of the aromatic ring. The weak shoulder band at 1510 cm 1 is due to the half-ring stretch of the benzene group (in-phase stretching of adjacent C@C bonds). The strongest Raman band at 1002 cm 1 is due to the breathing vibration of the benzene ring. The 1293 cm 1 band is mainly the Cb–C1 stretching mode that weakly couples with the benzene breathing. The Raman band at 731 cm 1 is assigned to the in-plane deformation of the benzene ring (scissoring vibration of C2–C3–C4 angle), which is strongly coupled with the out-of-plane motion of the Cc atom on COO group. The Raman band at 552 cm 1 is assigned to the in-plane deformation (in-phase scissoring vibration of

C5–C6–C1 angle and C2–C3–C4 angle) coupled with the out-of-plane deformation of the aromatic ring. The Raman band at 612 cm 1 is assigned to the out-of-plane deformation of the aromatic ring coupled with the in-plane deformation (in-phase scissoring vibration of C2–C1–C6 angle and C3–C4–C5 angle). The 529 cm 1 band can be assigned to the in-plane deformation of the aromatic ring (in-phase scissoring vibration of C1–C2–C3 angle and C4–C5–C6 angle). The bands at 1464, 1168, 1079, 455 cm 1 are mainly associated with the in-plane bending of C–H or C–OH on the aromatic ring. The bands from the out-of-plane deformation of the aromatic ring appear at low-wavenumber region, i.e., 709, 666, 612, 463 cm 1, with low intensities. Since the modes from the aromatic ring give rise to intense Raman bands, they can be used as vibrational markers in biological systems. Several bands due to the C–C stretching of the backbone are also rather strong. The band at 1359 cm 1 mainly results from bending and stretching of Ca–Cb coupled with bending of Ca–H/Cb–H. The band at 925 cm 1 is the stretching mode of Ca–Cc, and the band at 871 cm 1 is the symmetric stretching mode of Ca–Cc and Ca–N

Fig. 6. Raman spectra of m-tyrosine dissolved at (A) pH = 1 and (B) pH = 13 aqueous solutions, and solid m-tyrosine recrystallized from (C) pH = 1 and (D) pH = 13 solutions. The schematic diagrams of m-tyrosine in these situations are shown on the right of the spectra.

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119

Fig. 7. Raman and FTIR spectra of m-tyrosine and p-tyrosine.

bonds. The 1413 cm 1 band is assigned to the symmetric stretching mode of O@C@O group. The dissolution of m-tyrosine in D2O causes the hydrogens of the NH+3 group and the OH group to be substituted by deuterium. The Raman and IR spectra of deuterated m-tyrosine were measured and assigned based on calculation with the same method and basis sets. In the deuterated Raman spectra, the vibration modes of the aromatic ring and the COO group modes shift slightly to lower frequencies by no more than 6 cm 1. On the other hand, the bands from the ND+3 group and the OD group shift to lower frequencies considerably. The asymmetric bending mode of the NH+3 group shifts from 1518 cm 1 to 1063 cm 1 after deuteration, while the two weak bands at 1116 and 1068 cm 1 due to the rocking vibration of the NH+3 group move to 823 and 783 cm 1, respectively. The weak band from in-plane bending mode of the OH group moves from 1233 cm 1 to 954 cm 1. In the native IR spectrum (Table 3 and Fig. S4), these corresponding four bands resulting from the NH+3 group and the OH group locate at 1504, 1229, 1113, 1067 cm 1, respectively. In the deuterated IR spectrum (Fig. S4), these four bands cannot be found at the original positions,

showing that they either shift to far lower frequency region or encounter a dramatic decrease in intensity. 4.2.3. Raman spectra of m-tyrosine at acidic and alkaline conditions It is known that the acidity of environment can dramatically influence the proton-binding of amino acids. Similar to p-tyrosine [23], m-tyrosine in solution becomes NH2CH (CH2C6H4O )COO at pH = 13 and NH+3CH(CH2C6H4OH)COOH at pH = 1. The recrystallized m-tyrosine solid samples contain either Na+ (recrystallized from pH = 13 solution) or Cl (recrystallized from pH = 1 solution) as counter ions [19,44,45]. The schematic diagrams of these forms are shown in Fig. 6. Fig. 6 displays the Raman spectra of m-tyrosine in solutions as well as in crystals at different pH conditions. It can be seen that the band nearby 1000 cm 1 due to the breathing mode of the aromatic ring is always most intense and rarely affected by pH conditions or the phases of matter. It should be noted that the corresponding band is rather weak in p-tyrosine, thus this strong Raman band can be used as a mark band of m-tyrosine. The other bands associated with the vibrations of the aromatic ring are

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Table 3 Observed and calculated Raman and IR wavenumbers (cm isoelectric point.

1

) and potential energy distribution (PED in percentage) assignments for m-tyrosine and p-tyrosine recrystallized at

m-tyrosine

p-tyrosine

Assignments (PED %)

Cal.a

mOH (100) maNH3 (99) maNH3 (98) msNH3 (92) msCH (98) mCH (100) mCH (99) mCH (99) maCbH2 (77) mCaH (76) msCbH2 (99) mC2@C3 (25), mC5@C6 (26) mC1@C6 (28), mC3@C4 (17) maCO2 (62), daNH3 (16)

3781 3436 3417 3346 3157 3143 3125 3115 3085 3074 3010 1654 1640 1585 1574 1548 1517 1466 1456 1441 1411 1367 1347 1332 1317 1279 1252 1227 1184 1163 1150 1123 1093 1079 1068 1000 991

daNH3 (61) daNH3 (68) mC–C(ring) (31), bCH (30) bCH (58), mC–C(ring) (25) dsNH3 (88) scissCbH2 (82) msCO2 (53), mCa–Cc (12) bCaH (39), bCbH (15), mCa–Cb (11) bCaH (28), wagCbH2 (27) mC–C (ring) (27), wagCbH2 (19) bCH (73) mCb–C1 (18), breath-ring (15), mC–OH (11) wagCbH2 (42), bCaH (21) bOH (21), swCbH2 (11) bCH (42), bOH (37), mC–C (ring) (15) bCH (42), mC–OH (17), mCa–Cb (10) bCH (59) rockNH3 (31), mCa–Cb (20) bCH (26), mC–C (ring) (11) mCa–N (15), rockNH3 (12) rockNH3 (37), swCbH2 (21) breath-ring (75) cCH (83) mC–OH (12), def-ring (11), rockNH3 (10) maCc–Ca–Cb (24), rockNH3(19) mCa–Cc (19), rock CbH2 (18), rock NH3 (16) cCH (84) cCH (55) ms Cc–Ca–N (38), rock CbH2 (22), cCH (14) cCH (45), s-ring (15) cCO2 (21), cCH (21), scissCO2 (15) def-ring (40), cCO2 (16) s-ring (42), cCH (37) s-ring (22), scissCO2 (15) s-ring (46), def-ring (27) def-ring (42), s-ring (28) def-ring (72) scissCa–Cc–O (44) s-ring (51), bC–OH (20) bC–OH (45), s-ring (25) scissCb–Ca–N (45) cO–H (95) scissCc–Ca–N (26), sciss Ca–Cc–O (21) cCb (39) swNH3 (33), wag-ring (27) s-ring (59), cC–OH(19) scissCc–Ca–N (21) swNH3 (68) sciss Cb–Ca–Cc (49) wag-ring (57) swCO2 (43) rock-ring (69) sw-ring (70)

965 926 912 903 879 839 799 785 733 701 662 598 559 526 503 454 450 392 367 308 295 251 233 211 219 190 84 61 46 40

Ramanb

3083 m 3054 m 3044 m 3030 m 2977 s 2929 m 2860 w 1609 s 1604 sh

1518 m 1510 sh 1464 m 1444 m 1413 m 1359 s 1347 sh 1339 vw 1316 w 1293 vs 1270 s 1233 w 1168 m 1142 w

IRb

Assignments (PED %)

Cal.a

3512 w 3414 w 3277 m 3214 w

mOH (100) maNH3 (99) maNH3 (93) msNH3 (99) mCH (94) mCH (98) mCH (97) mCH (92) mCaH (99) maCbH2 (100) msCbH2 (99) mC2@C3 (40), mC5@C6 (31) mC3@C4 (34), mC1@C6 (32) maCO2 (68), daNH3 (13) daNH3 (70), maCO2 (10)

3785 3449 3427 3354 3156 3142 3130 3127 3109 3084 3030 1656 1637 1588 1569 1553 1520 1458 1454 1442 1428 1372 1339 1334 1314 1290 1241 1216 1199 1170 1159 1109 1105 1077 1025 1015 986

3029 w 2974 w 2928 w 2855 vw

1657 s 1578 s 1504 m

1459 s 1441 sh 1410 s 1356 s

1315 w 1288 w 1266 s 1229 w 1164 s 1135 m

1116 m 1079 s

1113 w 1078 w

1068 sh 1002 vs

1067 m 998 w

991 sh

987 m 935 s 923 sh

925 s 893 w 871 s 806 sh 797 sh 731 s 709 vw 666 vw 612 m 552 s 529 m 503 vw 463 vwsh 455 vwsh

318 w 250 sh 247 sh 254 w 164 sh 96 m 76 m 56 m

868 m 795 m 731 w 704 m 664 m 611 vw 547 m 528 sh 502 vw 461 w 453 w

daNH3 (90) bCH (50), mC–C (ring) (17) dsNH3 (70) bCH (29), mC–C (ring) (27) scissCbH2 (65) msCO2 (41), scissCbH2 (13), mCa–Cc (11) bCaH (55), wagCbH2 (12) wagCbH2 (24), bCaH (18), msCO2 (13) bCH (29), mC–C(ring) (28), bOH (23) bCH (36), bCbH (16), mC–C (ring) (10) bCaH (19), wagCbH2 (15), mCa–Cb (13) breath-ring (45), mC–OH (38) mCb–C1 (26), bCH (14), mC–C (ring) (11) swCbH2 (32) bOH (44), bCH (20) bCH (64) bCaH (22), rockNH3 (15) bCH (49) rockNH3 (20) mCa–N (29), rockNH3 (18) mC–C(ring) (75), bCH (12) cCH (89)

cCH (60) mCa–Cb (23), rockNH3 (20) msCb–Ca–N (35), rockCbH2 (26) cCH (16), breath-ring (11), s-ring (10) cCH (61) cCH (69) breath-ring (50), cCH (19) cCH (22), scissCb–Ca–Cc (21), cCO2 (17), sciss CO2 (17) s-ring (18), cCO2 (17) s-ring (45) def-ring (63) scissCc–Ca–N (35), rock NH3 (20), sciss CO2 (19) s-ring (30), def-ring (11) scissCa-Cc–O (29), s–ring (27) s-ring (36), scissCc–Ca–N (26) bC–OH (55), rock-ring (15) s-ring (47) s-ring (43) cO–H (52), cCb (24) cO–H (42), cCb (27) wag-ring (48) scissCc–Ca–N (74) rock-ring (36),

swNH3 (51), wag-ring (14) swNH3 (60) wag-ring (49)

swNH3 (38), sw-ring (34) swCO2 (58) sw-ring (77)

961 948 900 865 847 837 831 799 739 716 641 619 574 516 487 433 420 417 375 360 324 292

Ramanb

IRb

3225 vw 3076 sh 3062 vs 3039 s

3204 m 3078 vw

3012 2965 2930 1617 1596

3024 w 2962 w 2930 w

s vs vs vs sh

3041 w

1609 vs 1589 vs 1514 s 1453 m 1438 m 1421 sh 1367 m 1329 vs

1436 m 1417 m 1364 s 1330 vs

1302 vw 1283 sh 1270 s 1251 sh 1202 s 1181 s 1156 m 1098 w

1266 m 1245 s 1214 m 1176 w 1153 w 1099 w

1045 m

1043 w

985 m 847 m

986 w 898 w 841 m

832 vs 799 m 742 w 717 w 644 m

830 sh 799 m 741 m 714 w 650 m

530 w 492 w

575 m 530 m 493 w

433 s

434 w

382 w 338 w

170 153 91 74 58 40

Abbreviations: m, stretching; d, angle deformation; wag, wagging; sciss, scissoring; rock, rocking; b, in plane angle deformation; c, out of plane angle deformation; sw, twist of the whole group; a, antisymmetry; s, symmetry; ring, benzene ring; CH, C–H bond on the aromatic ring; breath, breathing; def-ring, in plane C–C–C angle deformation on the ring; s-ring, out of plane deformation of ring; s, strong; m, medium; w, weak; vw, very weak; sh, shoulder peak. a Simulated by M06-2X with SMD model, scaling factor is 0.983. b The experimental spectral data from this work.

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121

Fig. 8. Raman spectra of 6 conformers of m-tyrosine calculated by M06-2X/6-311++G(d,p) using SMD solvent model.

observed near 540, 730, 1080 cm 1 with considerable intensities. Most bands shift a little to lower-wavenumber region compared to the native condition, maybe due to two reasons: (1) the different form of m-tyrosine molecule; (2) the interaction of m-tyrosine molecule with the ions such as Na+, Cl , OH or H+. Therefore, more

accurate analyses of these Raman shifts and conformers of m-tyrosine in these conditions need quantum chemistry calculation with special carefulness. In aqueous solutions at pH = 1 and pH = 13, the bands associated with the OH/NH bending of benzene-OH, NH+3 or NH2 groups

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are either dramatically broadened or even undistinguishable, presumably due to the intermolecular hydrogen bonding between m-tyrosine and solvent molecules. In the pH = 1 solution Raman spectrum, the broad bands at 1300 to 1550 cm 1 are attributed to the deformation of the NH+3 and OH groups. In the pH = 13 solution Raman spectrum, these bands are much narrow, probably because of the weakened hydrogen bonding between the benzene-O- and NH2 groups with the solvent in the alkaline environment. Meanwhile, the bands at 925, 871, 1116 cm 1, which are partly connected with the rocking of NH+3, almost disappear in the solution Raman spectra. 4.2.4. Comparison of spectra of m-tyrosine and p-tyrosine Despite that the molecular structures of m-tyrosine and p-tyrosine differ only on the positions of the OH group, their vibrational features (especially the Raman spectra) are obviously different as shown in Fig. 7. For both m-tyrosine and p-tyrosine, the Raman bands associated with the aromatic ring vibration are among most intensive ones. However, the positions of these bands are different in the two isomers. The bands of m-tyrosine at 1617, 1293, 1079, 1002, 552 cm 1 shift to 1609, 1270, 1045, 832, 644 cm 1 in p-tyrosine, respectively. The relatively intensities of these bands are also quite different in m-tyrosine and p-tyrosine. The spectral differences in the strong benzene bands make Raman spectroscopy to be a useful tool in the identification of m-tyrosine and p-tyrosine isomers. On the other hand, m-tyrosine and p-tyrosine have the same amino acid backbone, thus it is not surprising that some bands from the backbone of m-tyrosine and p-tyrosine are at the similar positions in the Raman spectra. For instances, the scissoring vibration of CbH2 locates at 1444 cm 1 for m-tyrosine and at 1438 cm 1 for p-tyrosine; the symmetric stretching vibration of COO locates at 1413 cm 1 for m-tyrosine and at 1421 cm 1 for p-tyrosine; the angel deformation mode of CaH locates at 1359 cm 1 for m-tyrosine and at 1367 cm 1 for p-tyrosine. 4.2.5. Comparison of Raman spectra of m-tyrosine zwitterionic conformers The simulated Raman spectra of the 6 conformers of zwitterionic m-tyrosine are presented in Fig. 8, which were calculated by M06-2X/6-311++G(d,p) using the SMD solvent model. For all the 6 conformers, the Raman bands due to the aromatic ring modes are calculated at similar positions with comparable relative intensities. However, the spectra of different conformers do exhibit alteration for several medium or weak bands. According to our calculations, these bands can be assigned to the backbone vibrations of m-tyrosine. This suggests that the Raman spectra of the different conformers show some small changes mainly caused by the distortion of Cc–Ca–Cb–C1 dihedral angle, and the A, B and C series of conformers can be distinguished in terms of Cc–Ca–Cb–C1 dihedral angle. The Raman spectra of the two conformers in the same series (for instance, A1 and A2) only have slight difference. On the other hand, A1 and A2 show small differences for vibrational modes associating Ca and Cb atoms (925, 1270, 1359 cm 1 bands in experimental spectrum), reflecting that the orientation of the C6H5OH group has a weak effect on the backbone of m-tyrosine. 5. Conclusions In summary, this work has presented a detailed study of vibrational spectral property of m-tyrosine. The vibrational modes of zwitterionic m-tyrosine are assigned based on both experimental spectra and theoretical calculations. The Raman spectra of m-tyrosine in solution and recrystallized m-tyrosine at acidic and

alkaline conditions have been also recorded experimentally. M-tyrosine and p-tyrosine can be easily distinguished by the Raman bands associated with aromatic ring vibrations. For the theoretical computation, the PES calculation is useful for researching the stable conformers of m-tyrosine, from which the A1 conformer with the anti-position for the COO and the gauche position for the NH+3 can best fit to the experimental data for the zwitterionic form of m-tyrosine. To interpret the vibrational modes and frequencies precisely, SMD solvent model with the M06-2X method has been employed and it is found that the SMD model can significantly improve the accuracy for the geometry and spectra of p-tyrosine and m-tyrosine among all 6 kinds of DFT methods. In addition, D3 correction for conventional GGA methods (B3LYP, BLYP) is helpful for the description of crystalline amino acids. Both the M06-2X and B3LYP-D3 methods can reach excellent geometry structure of solid state tyrosine. The M06-2X method results in the Raman spectrum simulation with frequency scaling factor, whereas the BLYP-D3 method can reproduce decent spectrum without the necessity of frequency scaling factor. Based on the experimental measurement and theoretical calculation of the structures and Raman spectra, our approach can thus precisely predict the different conformers of m-tyrosine under different conditions. As such, this study has not only provided the vibrational assignments of m-tyrosine, but also demonstrated the deliberation of the optimal choice of quantum chemistry methods for simulating crystalline amino acids. Acknowledgements This work was partly supported by the National Basic Research Program of China (2013CB934304), the National Natural Science Foundation of China (11175204, 11475217), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA08040107), and the Anhui Provincial Natural Science Foundation (1508085QB44). The authors would like to thank Dr. Dong-ming Chen for his kind help with the QC computation achieved in this work. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.saa.2015.06.073. Reference [1] G.A. Molnar, Z. Wagner, L. Marko, T. Koszegi, M. Mohas, B. Kocsis, Z. Matus, L. Wagner, M. Tamasko, I. Mazak, B. Laczy, J. Nagy, I. Wittmann, Kidney Int. 68 (2005) 2281–2287. [2] G.A. Molnar, V. Nemes, Z. Biro, A. Ludany, Z. Wagner, I. Wittmann, Free Radical Res. 39 (2005) 1359–1366. [3] T.G. Huggins, M.C. Wellsknecht, N.A. Detorie, J.W. Baynes, S.R. Thorpe, J. Biol. Chem. 268 (1993) 12341–12347. [4] S.K. Chauhan, R. Kumar, S. Nadanasabapathy, A.S. Bawa, Compr. Rev. Food Sci. Food Saf. 8 (2009) 4–16. [5] S. Chen, L.H. Fan, J. Song, C.C. Liu, H. Zhang, Meat Sci. 93 (2013) 226–232. [6] S.M. Glidewell, N. Deighton, B.A. Goodman, J.R. Hillman, J. Sci. Food Agric. 61 (1993) 281–300. [7] C. Matayatsuk, A. Poljak, S. Bustamante, G.A. Smythe, R.W. Kalpravidh, P. Sirankapracha, S. Fucharoen, P. Wilairat, Redox Rep. 12 (2007) 219–228. [8] T.F. Huang, T. Tohge, A. Lytovchenko, A.R. Fernie, G. Jander, Plant J. 63 (2010) 823–835. [9] L. Klipcan, N. Moor, N. Kessler, M.G. Safro, Proc. Natl. Acad. Sci. U.S.A. 106 (2009) 11045–11048. [10] C. Bertin, L.A. Weston, T. Huang, G. Jander, T. Owens, J. Meinwald, F.C. Schroeder, Proc. Natl. Acad. Sci. U.S.A. 104 (2007) 16964–16969. [11] F. Khan, M. Kumari, S.S. Cameotra, PLoS ONE 8 (2013) e75928. [12] M. Winn, R.J.M. Goss, K. Kimura, T.D.H. Bugg, Nat. Prod. Rep. 27 (2010) 279– 304. [13] S. Ahmad, R.S. Phillips, C.H. Stammer, J. Med. Chem. 35 (1992) 1410–1417. [14] C.E. Humphrey, M. Furegati, K. Laumen, L. La Vecchia, T. Leutert, J. Constanze, D. Muller-Hartwieg, M. Vogtle, Org. Process Res. Dev. 11 (2007) 1069–1075.

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