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Active Site Engineering of #-Transaminase Guided by Docking Orientation Analysis and Virtual Activity Screening Sang-Woo Han, JUYEON KIM, Hyun-Soo Cho, and Jong-Shik Shin ACS Catal., Just Accepted Manuscript • Publication Date (Web): 17 Apr 2017 Downloaded from http://pubs.acs.org on April 17, 2017

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ACS Catalysis

Active Site Engineering of -Transaminase Guided by Docking Orientation Analysis and Virtual Activity Screening

Sang-Woo Han,† Juyeon Kim,‡ Hyun-Soo Cho,‡ and Jong-Shik Shin*,†

†

Department of Biotechnology, Yonsei University, Yonsei-Ro 50, Seodaemun-Gu, Seoul 03722,

South Korea ‡

Department of Systems Biology, Yonsei University, Yonsei-Ro 50, Seodaemun-Gu, Seoul

03722, South Korea * Corresponding author. E-mail: [email protected], Phone: (+82)-2-2123-5884, Fax: (+82)2-362-7265

KEYWORDS: chiral amine, asymmetric synthesis, transaminase, molecular modeling, protein engineering

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ABSTRACT Creation of enzyme variants displaying desirable catalytic performance usually necessitates tedious and time-consuming procedures for library generation and selection, which may be circumvented by a computational method based on a precise understanding on reaction mechanism in the context of active site environment. Despite the great potential of -transaminases (-TAs) for asymmetric synthesis of chiral amines from ketones, it remains elusive why -TAs exhibit marginal activities for most ketones in contrast to their high activities for -keto acids and aldehydes. To address the puzzling question, crystal structure determination and molecular modeling of -TAs were carried out to analyze docking orientations of the amino acceptors in the Michaelis complex. We found that ketones, unlike the reactive substrates, led to nonproductive binding complexes where the bound substrate was hardly accessible to a nucleophilic attack by the pyridoxamine cofactor to initiate reductive amination of the amino acceptor. This finding led us to perform in silico mutagenesis of the S-selective -TA from Ochrobactrum anthropi to ameliorate the unfavorable nucleophilic attack trajectory to structurally demanding ketones. The resulting variant, carrying L57A/W58A mutations, was predicted to allow an unprecedented re-face attack on butyrophenone, leading to 105-fold activity improvement with no loss in stereoselectivity. This study is expected to provide an efficient computational strategy for creation of high turnover TA variants tailored for a target ketone by affording in silico assessment of the effect of active site mutation on an enzyme activity.


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INTRODUCTION Research efforts to synthesize pharmaceutically valuable chiral amines using -transaminases (TAs) have been spurred by a unique capability of the enzyme to perform asymmetric transfer of an amino group to ketones from cheap amino donors, including isopropylamine and alanine.1-6 TAs display stringent stereoselectivity, good stability and no requirement for externally added cofactor, which renders the enzyme attractive for industrial process development.1,7 Thermodynamic limitation for the amination of ketones has been identified as a major obstacle for scalable process development and the last decade has witnessed technical advances for overcoming the unfavorable reaction equilibrium by enzymatic or physicochemical removal of a coproduct. 16

Beside the thermodynamic aspect, a fundamental obstacle to the -TA-catalyzed amination of

ketones is a frustratingly poor kinetic performance of the enzyme for ketones compared with those for reactive amino acceptors such as -keto acids and aldehydes.8-11 For example, the apparent specificity constant (i.e. kcat/KM) of an S-selective -TA from Ochrobactrum anthropi (OATA) for acetophenone was measured to be only 4  10-4 % relative to that for pyruvate, i.e. a metabolically native substrate.9 The huge gap between the industrial and biological needs for -TAs poses a crucial challenge for implementing scalable processes and should be compensated by increasing enzyme loading to achieve reasonable reaction rates for amination of ketones. This imposes a cost burden on a manufacturing setting and consequently leads one to hesitate to consider the biocatalytic approach instead of a chemocatalytic one such as asymmetric hydrogenation of imines.12 To overcome this limitation, creation of -TA variants displaying a high turnover rate for asymmetric amination of ketones was studied by several protein engineering strategies mainly relying on identification of key active site residues by molecular modeling and then iterative


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rounds of mutant library generation and selection.4,13-15 Considering that the library screening is costly and time-consuming, it is highly desirable to fashion a computational method enabling in silico strategy for rational design.16,17 Recent study demonstrated that extensive protein engineering of fold class I transaminase led to up to a 8,900-fold activity increase for bulky arylalkylamines.17 To this end, one should have a comprehensive understanding of a molecular basis underlying what determines the enzyme activity for a given substrate and a resulting computational method permitting prediction of whether a specific mutation is beneficial for a desirable activity improvement. However, it often remains difficult to elucidate what roles are played by individual active site residues to facilitate a rate-determining step in a concerted manner, especially when the reaction mechanism involves multiple reaction steps as illustrated by pyridoxal 5-phosphate (PLP)-dependent enzymes such as transaminases (TAs).18 -TAs belong to subgroup II of a TA family18-22 which shuttles between two enzyme forms responsible for initiating each half reaction (Scheme 1).23,24 The two half reactions for the whole catalytic cycle, i.e. oxidative deamination of an amino donor and reductive amination of an amino acceptor, run the exactly same pathway in opposite directions and involve a series of reaction intermediates, including carbinolamine, ketimine, quinonoid and external aldimine.23,24 It is generally accepted that abstraction of a C proton from an external aldimine is at least partially rate-determining for the deamination pathway whereas a rate-determining step for the amination pathway remains elusive.25-28 Owing to the complexity of the reaction mechanism and the limited information on the rate-determining step, in silico evaluation of an activity change induced by a specific mutation of-TA has not yet been available. In this study, we aimed at developing such a computational method affording in silico mutant selection and thereby mechanism-based engineering of-TA toward a target ketone. To this end,


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we performed docking orientation analysis of various substrates to explore whether an enzyme activity for a given substrate could be assessed by molecular modeling in terms of geometric requirements with respect to catalytically important active site residues upon substrate binding. We demonstrated that the mechanistic insights gained by the docking analysis could be successfully exploited to create a -TA variant displaying a high turnover performance for structurally demanding ketones.

EXPERIMENTAL SECTION Chemicals. L-alanine (L-1a) and glyoxylate (15b) were purchased from Acros Organics Co. (Geel, Belgium). Butyrophenone (5b) was purchased from Alfa Aesar (Ward Hill, MA, USA). Dimethyl sulfoxide (DMSO) and benzylamine (2a) were purchased from Duksan Pure Chemicals Co. (Ansan, South Korea). Pyruvate (1b) was obtained from Kanto Chemical Co. (Tokyo, Japan). All other chemicals were purchased from Sigma Aldrich Co. (St. Louis, MO, USA).

Site-directed Mutagenesis of -TA OATAL57A/W58A was created using a QuikChange Lightning site-directed mutagenesis kit (Agilent Technologies Co.) according to an instruction manual. Forward (5'-CGAAGCGATGTCAGGA GCGGCGAGTGTTGGCGTG-3') and reverse (5'-CACGCCAACACTCGCCGCTCCTGACATC GCTTCG-3') mutagenesis primers were designed using a primer design program (http://www. genomics.agilent.com). The template used for the mutagenesis PCR was pET28-OATAW58A that was previously constructed.29 Intended mutagenesis was confirmed by DNA sequencing. OATAM54A/W58A and OATAW58A/M419A were constructed using the same procedures. Forward and


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reverse mutagenesis primers for OATAM54A/W58A were 5'-GCGCTATATCGAAGCGGCGTCA GGACTGGCGAGTG-3' and 5'-CACTCGCCAGTCCTGACGCCGCTTCGATATAGCGC-3', respectively. Forward and reverse mutagenesis primers for OATAW58A/M419A were 5'GGCGTCATTTCCCGCGCAGCGGGCGATACGC-3' and 5'-GCGTATCGCCCGCTGCGCGG GAAATGACGCC-3', respectively. The -TA from Chromobacterium violaceum (CVTA) was cloned by directional cloning. The CVTA gene was amplified by colony PCR of C. violaceum KCTC 2897 using forward and reverse primers of 5'-GATATACATATGCAGAAGCAACGTACGACCAGCC-3' and 5'-GTGGTGCTC GAGAGCCAGCCCGCGCGCCTTCA-3', respectively. The PCR product was digested by NdeI/XhoI and then ligated with a linearized pET26b plasmid. Cloning was confirmed by DNA sequencing.

Preparation of Purified -TA Overexpression of the His6-tagged -TAs was carried out as described elsewhere with minor modifications.30 Escherichia coli BL21(DE3) cells transformed with the pET28a(+) expression vectors harboring the -TA gene were cultivated in LB medium (typically 1 L) containing 50 g/mL kanamycin at 37 °C. Overexpression of -TAs were induced by adding IPTG (final concentration = 0.1 mM) into the culture broth when OD600 reached to 0.4 and then cells were cultivated for 10 h. The culture broth was centrifuged (10,000 × g, 10 min, 4 °C) and the resulting cell pellet was resuspended in 15 mL resuspension buffer (50 mM Tris-HCl, pH 7, 50 mM NaCl, 1 mM EDTA, 1 mM -mercaptoethanol, 0.1 mM PMSF, 0.02 % sodium azide and 0.5 mM PLP).


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The cells were disrupted by a sonicator and then centrifuged (13,000 × g, 60 min, 4 °C) to remove cell debris. Protein purification was carried out on ÄKTAprime plus (GE Healthcare). The cell-free extract was loaded on a HisTrap HP column (GE Healthcare) and the His6-tagged -TA was eluted by an elution buffer (20 mM sodium phosphate, 0.5 M sodium chloride, 0.5 mM PLP, pH 7.4) with a linear gradient of imidazole (0.02 - 0.5 M). Imidazole was removed by a HiTrap desalting column (GE Healthcare) using an elution buffer (50 mM sodium phosphate, 0.15 M sodium chloride and 0.2 mM PLP, pH 7). When necessary, the enzyme solution was concentrated using an ultrafiltration kit (Ultracel-30) purchased from Millipore Co. Protein concentration was determined by measuring UV absorbance at 280 nm (UV-1650PC, Shimadzu Co.). Molar extinction coefficients of the homodimeric -TAs were obtained by protein extinction coefficient calculator (http://www.biomol.net/en/tools/proteinextinction.htm) and were used for concentration determination (78,076 M-1 cm-1 for the wild-type OATA; 67,076 M-1 cm-1 for OATAW58A, OATAL57A/W58A, OATAM54A/W58A and OATAW58A/M419A). Molar extinction coefficients for PDTA and CVTA were 122,576 and 160,616 M-1 cm-1, respectively.

Measurement of Enzyme Activity for Donor/acceptor Substrate pairs All enzyme assays were carried out at 37 °C and pH 7 (50 mM Tris buffer). Standard substrate conditions for activity assay were 10 mM (S)--methylbenzylamine ((S)-3a) and 10 mM 1b. Typical reaction volume was 50 L and the enzyme reaction was stopped after 10 min by adding 300 µL acetonitrile. Acetophenone (3b) produced was analyzed by HPLC. Enzyme activities of OATA for 1a-3a were measured at 10 mM amino donor and 10 mM 15b in 50 mM Tris buffer (pH 7) at 37 oC. Glycine, benzaldehyde (2b) and 3b were analyzed by HPLC


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to measure the amino donor reactivities of 1a, 2a and 3a, respectively. Activities of OATA for 1b3b were measured at 20 mM rac-1-methyl-3-phenylpropylamine and 10 mM amino acceptor in 50 mM Tris buffer (pH 7) at 37 oC. Benzylacetone (8b) produced was analyzed by HPLC.

Amino Acceptor Specificities of -TAs Amino acceptor reactivity was examined by comparing initial rates measured three times at 10 mM amino acceptor, 10 mM (S)-3a and 15 % (v/v) DMSO in 50 mM Tris buffer (pH 7) at 37 oC, unless otherwise specified. Nineteen amino acceptors were tested and the specific initial rates were normalized by that for 1b. Owing to a wide range of enzyme activities for diverse amino acceptors, varying enzyme concentrations and reaction times were used for precise measurements of initial rates (i.e. conversion < 4 %). The initial rate measurements were performed with reaction samples taken during the time span showing linear increases in the product concentration with respect to time, ensuring that the reaction sample did not reach reaction equilibrium. Ketone product was analyzed by HPLC.

Crystal Structure Determination Purified OATA and OATAW58L were preincubated with 5 mM of L-1a or (S)-3a, respectively, for 2 hours at 4 °C. Crystals of -TAs were obtained at 17 °C from a sitting drop containing 10 mg/ml protein, 25 mM HEPES (pH 7.5), 150 mM NaCl and 0.1 mM PLP by a vapor diffusion technique where a reservoir solution contained 25 % (w/v) PEG3350 and 0.1 M Tris buffer (pH 8.0). Crystals appeared within 7 days under the incubation conditions. Crystals were transferred into the reservoir solution supplemented with 15 % ethylene glycol for cryoprotection and then flash-frozen in liquid nitrogen.


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Diffraction data were collected using the Pohang Synchrotron beamline 5C and 7A (Pohang, South Korea). The diffraction data were indexed, integrated and scaled in space group P2 12121 with a MOSFILM program.31 The structures of OATA and OATAW58L were solved by molecular replacement using MOLREP32 in the CCP4 suite.33 The -TA structure from Chromobacterium violaceum (PDB ID: 4BA5)34 was used as a search model. The resulting structure was refined by REFMAC35 and PHENIX,36 and then manually adjusted by Coot,37 leading to the final Rwork/Rfree of 13.51/17.43 % and 14.33/17.86 % for OATA and OATAW58L, respectively. The final X-ray structures of OATA and OATAW58L were deposited in PDB as entry ID 5GHF and 5GHG, respectively.

Molecular Modeling Molecular modeling was performed with the Discovery Studio package (version 3.5.0, Accelrys). Crystal structures of the S-selective -TAs from O. anthropi (PDB ID : 5GHF and 5GHG for OATA and OATAW58L, respectively), Paracoccus denitrificans (PDB ID : 4GRX),38 C. violaceum (PDB ID : 4A6T)39 and Vibrio fluvialis (PDB ID : 4E3Q)13 were used for the molecular simulations. 5GHF, 5GHG and 4E3Q are E-PMP forms whereas 4GRX and 4A6T are E-PLP forms. All the TAs assume a homodimeric structure where both active-site arginines form inward conformations (i.e., pointing away from the solvent side), except for 4GRX where one subunit harbors an outward-pointing active-site arginine. Docking simulations of aldehydes and ketones required active site structures, harboring an outward-pointing arginine, which were constructed by structural replacement of the original inward-pointing arginine with the outward conformation of 4GRX after superimposing the target -TA structure on 4GRX. The structural substitution was done by parallel transport of coordinates


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of the arginine, so C of the replaced arginine coincided with that of the target -TA. No steric clash of the replaced arginine was observed against the active site residues. Similarly, structural replacement of the internal aldimine by the active site lysine and PMP of 4E3Q, with C  of the replaced lysine coincided on the target -TA, led to construction of E-PMP structures of 4GRX and 4A6T. Steric clash around the replaced lysine and PMP was not observed and the hydrogen bond network between PMP and the phosphate binding cup was found to be well conserved. Structural models of OATA mutants (i.e. OATAW58A, OATAM54A/W58A, OATAL57A/W58A and OATAW58A/M419A) were prepared by substitution of the mutation sites (i.e. M54, L57, W58 and M419) with alanine using the OATAW58L crystal structure as a template. Docking simulations were carried out with the Discovery Studio package using the CDOCKER module under a default setting (2,000 steps at 700 K for a heating step; 5,000 steps at 300 K for a cooling step; 8 Å grid extension) within the active site defined by the Binding-Site module. When necessary, the active site was expanded by the Binding-Site module for docking of bulky substrates to avoid spatial restriction. The active site harboring an inward-pointing arginine was used for docking simulation of -keto acids. Aldehydes and ketones were docked on the active site harboring an outward-pointing arginine. Among 100 binding poses generated by the docking simulations, we chose the most stable pose as a Michaelis complex after filtering improper poses leading to an (R)-amine product considering stringent S-stereoselectivity of -TAs used for the docking simulation. In the case of -keto acids, we discarded docking poses where the carbonyl oxygen points toward Y20 and thereby hydrogen bond with active site lysine is geometrically forbidden.

Kinetic Analysis


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To obtain kinetic parameters for 2b, a pseudo-one-substrate kinetic model was used under the fixed concentration of the cosubstrate as described before.40 Initial rate data were fitted to a Michaelis-Menten equation, and the KM and kcat values were calculated from the slope and yintercept of the double-reciprocal plot. The kinetic parameters were determined from three independent initial rate measurements performed with the same batch of purified enzyme over 1 70 mM 2b using 100 mM (S)-3a as a cosubstrate. The initial rate was measured by HPLC analysis of produced 3b.

Measurements of Activity Improvements for Ketones Activity improvements of OATA by W58A or L57A/W58A mutations were based on initial rate measurements which were carried out three times under the reaction conditions of 10 mM ketone (3b-5b), 500 mM L-1a and 15 % DMSO in 50 mM Tris buffer (pH 7) at 37 oC. Owing to much lower activity of the wild-type OATA than those of OATAW58A and OATAL57A/W58A, varying enzyme concentrations (i.e. 2 - 200 M) and reaction times (i.e. 10 min - 18 h) were used to ensure generation of amine products whose concentrations are high enough for reliable HPLC analysis. Reaction progresses for all the initial rate measurements showed fairly good time-dependent linear increases in the concentrations of the amine products. Aliquots of the reaction mixture (typically 100 L) were taken at predetermined reaction time and mixed with 37.5 L 16 % perchloric acid to stop the enzyme reaction. Amine produced was analyzed by chiral HPLC.

HPLC Analysis All the HPLC analyses were performed on a Waters HPLC system. Analysis of 2b and 3b were performed using a Sunfire C18 column (Waters Co.) with isocratic elution of 40 % methanol/60 %


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water/0.1 % trifluoroacetic acid at 1 mL/min by UV detection at 254 nm. 8b was analyzed using the Sunfire C18 column with isocratic elution of 60 % methanol/40 % water/0.1 % trifluoroacetic acid at 1mL/min by UV detection at 220 nm. Quantitative chiral analyses of 3a, -ethylbenzylamine and -propylbenzylamine were carried out using a Crownpak CR(-) column (Daicel Co., Japan) with isocratic elution of water (pH adjusted to 2.0 by perchloric acid) at 0.6 mL/min. UV detection was done at 200 nm. For quantitative analysis of glycine, derivatization with 1-fluoro-2,4-dinitrophenyl-5-L-alanine amide (Marfey’s reagent) was employed.41,42 In a typical derivatization procedure, 10 L of Marfey’s reagent stock (14 mM dissolved in acetonitrile), 18 L of sodium bicarbonate solution (1 M) and 50 L of DMSO were added to 22 L reaction samples (the molar ratio of Marfey’s reagent to amine or amino acid was > 1.4). The reaction mixture was thoroughly mixed and incubated at 40 °C for 8 hours. The derivatization reaction was quenched by adding 20 L of 1 N HCl solution into the mixture. The resulting mixtures (20 L) were analyzed on a Waters HPLC system using the Sunfire C18 column with isocratic elution of 40 % methanol/60 % water/0.1 % trifluoroacetic acid at 1mL/min by UV detection at 340 nm.

RESULTS AND DISCUSSION Good Donor-Acceptor Pair Relationship The TA reactions consist of multiple reaction steps that occur in a reversible manner (Scheme 1). The reversibility of the whole catalytic cycle renders amination products of reactive amino acceptors competent as an amino donor and vice versa. For example, -ketoglutarate is a universal amino acceptor for most TAs such as aspartate transaminase (AspTA) and aromatic amino acid


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transaminase (AroTA), and thereby its amination product (i.e. glutamate) serves as a good amino donor.43,44 Likewise, -TAs follow the “good donor-acceptor pair relationship” (GDAPR).8 For example, L-alanine (L-1a) and benzylamine (2a) are reactive amino donors for an S-selective TA from O. anthropi (OATA) and consequently their deamination products (i.e. pyruvate (1b) and benzaldehyde (2b), respectively) display high amino acceptor reactivities (Figure 1). However, an intriguing aspect of the -TA reactions is that GDAPR is not applicable to amine-ketone substrate pairs. For example, OATA shows only 0.08 % activity for acetophenone (3b) relative to that for (S)--methylbenzylamine ((S)-3a) which is a typical amine substrate for S-selective -TAs. Besides the (S)-3a/3b pair, OATA shows marginal activities for most ketones although the resulting amines are as reactive as L-1a.9,45 Comparison of -TA Activities for -Keto Acids, Aldehydes and Ketones Based on the initial rate measurements, the enzyme activity of OATA for 3b corresponded to 0.04 and 0.03 % activities relative to 1b and 2b, respectively (Figure 1). The low activity of OATA for ketone, compared with -keto acid and aldehyde, was also observed with sixteen additional amino acceptors, i.e. eleven ketones (4b-14b), one -keto acid (15b) and four aldehydes (16b-19b) (Table 1). OATA showed less than 1 % activity, relative to 1b, for all the ketones whereas the additional -keto acid and aldehydes (15b-19b) turned out good amino acceptors whose relative reactivities ranged from 17 to 63 %. The biased substrate specificity for amino acceptors, depending on the type of functional group, was also found with other S-selective -TAs from Paracoccus denitrificans (PDTA)46 and Chromobacterium violaceum (CVTA)10 (Table 1). Both enzymes showed high activities for -keto acids and aldehydes, ranging from 12 to 64 % activity relative to 1b. Similarly to OATA, PDTA showed low activities for all the ketones tested (3b-


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14b), i.e. less than 2 % relative to 1b. Likewise, CVTA showed such low activities for the ketones (≤ 2 % relative to 1b) except benzylacetone (8b). Taken together, the three -TAs display biased amino acceptor specificity, i.e. unfavorably for ketones, which is seemingly related to the chemical type of substrate.

X-ray Structure Determination and Docking Simulations The striking discrepancy of the (S)-3a/3b pair from GDAPR, as shown in Figure 1, seems puzzling, considering the reversible nature of the -TA reactions. The drastic activity loss for 3b, despite the high activity for (S)-3a, does not occur at a binding step because KM values of OATA for (S)3a and 3b are not very different (i.e. 150 and 110 mM, respectively).9 This led us to presume that changes in the activation energy barrier for specific catalytic steps, induced by the structural difference of 3b relative to 1b and 2b, might disfavor the amination pathway selectively over the deamination pathway. Because the substituents flanking the carbonyl group of the amino acceptors remain the same throughout the catalytic pathway, we posited that the disparity in changes in the reaction energetics would commence from the first catalytic step, i.e. the nucleophilic attack on the bound substrate by the amino group of PMP as designated by a curved arrow in Scheme 1. To explore this possibility, we decided to construct structural models of Michaelis complexes and compare how differently the bound substrates are vulnerable to the nucleophilic attack. To this end, we set out to determine an X-ray structure of the PMP form of OATA. Crystal growth was carried out under the presence of L-1a to completely convert a bound cofactor to a PMP form. Indeed, the X-ray structure determined at 1.8 Å resolution, deposited in the PDB as entry 5GHF, represented the desired E-PMP structure (see Table S1 for structure refinement


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statistics). The overall structure of OATA shows a typical fold Type I of PLP enzymes where each monomer of the homodimeric structure is divided into two domains (Figure S1).21,22,47 Docking simulation of 1b into the PMP form of OATA showed that spatial orientation of 1b in the active site is coordinated by multiple hydrogen bonds (H-bonds) of the carbonyl oxygen (O) and the carboxyl group with W58 and R417 in a large (L) pocket which is exposed to a solvent side (Figure 2A). As a result, the methyl substituent of 1b is placed in a small (S) pocket capable of accepting up to an ethyl group.1,8,22 In contrast, lack of the carboxyl group in 2b and 3b leads to the H-bond formation only between O and a nearby residue (Figure 2B and 2C). Note that R417 play a crucial role in the dual substrate recognition and moves away from the L pocket to provide a hydrophobic environment for the phenyl group of 2b and 3b,48 as observed with AspTA and AroTA.49 It is known that conversion of carbinolamine to E-PMP in the deamination pathway is mediated by the active site lysine (K287) acting as a catalytic base for the hydroxyl proton.24 This suggests that the nucleophilic attack on the carbonyl carbon (C) of the bound substrate in the amination pathway is facilitated by a H-bond between O and K287, as shown in Scheme 1, owing to an increased electrophilicity of the carbonyl group. Hence, we posited that productive binding should fulfil proximity conditions for both O-NK287 and C-NPMP, designated by black and red lines, respectively, in Figure 2. Docking simulation of 1b showed that both interatomic distances were close to 4 Å. Even better proximity was found with 2b because of the aldehydic hydrogen much smaller than the methyl substituent of 1b and the resulting reduction of the steric constraint in the S pocket, allowing H-bond formation between O and K287. In contrast, 3b shows the interatomic distances longer than those observed with 1b despite the same substituent placed in the S pocket, seemingly because of the bulky phenyl substituent in the L pocket. More strikingly, the


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nucleophilic attack on 3b is shown to be sterically hindered by the methyl substituent (∠C-CNPMP = 118o) in contrast to the attack on 1b (i.e. the triatomic angle = 90o). Based on the accessibility of the carbonyl group to the nucleophilic attack, the docking models are consistent with kcat for 3b (9.7  10-3 s-1)9 much lower than kcat values for 1b and 2b (2.69 and 1.7 s-1,50 respectively).

Development of Docking Orientation Analysis Considering the docking results of 1b-3b, the marginal activity for 3b seems to be relevant to inability of the enzyme to initiate the catalytic cycle due to an unfavorable nucleophilic approach to the bound substrate. To examine whether this finding is generalizable, we carried out additional docking simulations with eleven ketones (4b-14b) and five reactive amino acceptors (i.e. glyoxylate (15b) and four aldehydes (16b-19b)) listed in Table 1. For elaborate analysis of the angular orientation of the bound substrate, we defined two characteristic angles for the nucleophilic approach, i.e. the Bürgi–Dunitz angle (BD) for O-C-NPMP and the dihedral angle (DH) between the plane harboring O, C and NPMP and the plane harboring O, C and C (Figure 3).51-53 The ideal BD and DH for the nucleophilic attack on the carbonyl bond are known to be 105o and 90o, respectively.51 Measurements of angular orientations as well as proximity conditions of nineteen amino acceptors are listed in Table S2. A positive correlation was observed between C-NPMP and O-NK287 (r2 = 0.96), leading us to choose C-NPMP as a descriptor for the proximity conditions (Figure S2). The optimal C-NPMP found in the transition state for the nucleophilic attack is known to be 2.5 Å.54 The plot of DH vs BD showed that BD values for seven reactive substrates (75o  13o) are similar to those for twelve ketones (80o  14o), indicating that BD is not


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a crucial factor for determining amino acceptor reactivity (Figure S3). Notably, segregation of the two substrate groups occurred on the DH vs BD plot across DH = 25o. Therefore, DH was chosen as a descriptor for the angular orientations. The proximity descriptor was plotted against the angle descriptor, revealing that the amino acceptors are found in two regions among four divided by the dotted lines that intersect at DH = 25o and C-NPMP = 4 Å (Figure 4). The reactive substrates are exclusively found in region HR where unhindered and proximal nucleophilic attack is allowed. Note that the optimal substrate orientation for the nucleophilic attack (i.e. DH = 90o and C-NPMP = 2.5 Å) is located in region HR. In contrast, ketones lie only in region LR where the nucleophilic attack is disfavored (i.e. hindered and distal attack). It is notable that docking orientations of reactive -keto acids, i.e. 1b and 15b, are far away from the optimal one designated by the star. A possible explanation is that a conformational change in the active site may be induced by substrate binding and guide the keto acids to adopt spatial orientations closer to the optimal one.55 This process, even if it occurs, seems to fail in such an induced fit for ketones that initially adopt a nonproductive docking pose located in region LR. To examine whether poor substrates other than ketones were also found in region LR, docking simulations were carried out with four nonreactive-keto acids carrying a side chain bulkier than an ethyl group. Consistent with ketones, all the -keto acids were found in region LR (Figure S4).

Verification of the Docking Orientation Analysis To verify the separate clustering of amino acceptors on the C-NPMP vs DH plot depending on reactivity, we also performed docking simulations of the nineteen substrates with three additional S-selective -TAs, i.e. PDTA, CVTA and the -TA from Vibrio fluvialis (VFTA) (see Table S3


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for docking data).13,38,39 Similarly to OATA, the three -TAs rendered docking orientations of the good and poor substrates present in region HR and LR, respectively (Figure 5). The only exception was observed with CVTA for 8b. Despite the considerable reactivity (i.e. 12 % relative to 1b), 8b was found in region LR. It is plausible that the decent reactivity would be related to an electronic configuration of the carbonyl group with respect to the aromatic system which is different from other arylalkyl ketones (i.e. 3b-7b) where the carbonyl group is conjugated to a neighboring aromatic system. High reactivity of 8b over other arylalkyl ketones was also observed with OATA and PDTA although the reactivity is much lower than that of 1b (Table 1). The intersection point between the two regions are (60o, 4 Å), (40o, 4 Å) and (37o, 4 Å) for PDTA, VFTA and CVTA, respectively. Taken together with OATA, C-NPMP less than 4 Å seems to be a prerequisite for a reactive amino acceptor irrespective of -TAs although the threshold DH is dependent on the enzyme. The docking analyses with four -TAs suggest that activity improvements for ketones may be achieved by active site engineering that permits shift in the docking orientation from region LR to HR. To test this idea, we carried out docking simulations with the OATAW58L variant created in the previous study where the W58L single mutation was demonstrated to induce dramatic increases in the reaction rates for ketones (i.e. 80 to 490-fold activity improvements for the ketones used in Figures 4 and 5).9 X-ray structure determination of the E-PMP form of OATAW58L was carried out as done with the wild-type enzyme (see Table S1 for structure refinement statistics). OATAW58L, deposited in the PDB as entry 5GHG, showed nearly identical structure to the wild-type enzyme (i.e. RMSD of backbone atoms = 0.23 Å) except K287, M419 and PMP (Figure S5). Docking analysis performed with the PMP structure of OATAW58L (see Table S4 for docking data) revealed that all the ketones, except propiophenone (4b) and butyrophenone (5b), moved to region HR


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(Figure 6). Compared with 1b, relative activities of OATAW58L for the ketones found in region HR (3b and 6b-14b) were higher than 1 % (i.e. 1.4 to 11.3 % as listed in Table S4). In contrast, despite the activity improvements by the W58L mutation, OATAW58L showed still marginal activities for the two ketones which remained in region LR, i.e. 0.07 and 0.002 % relative to 1b for 4b and 5b, respectively, due to steric interference in the S pocket. Note that 4b and 5b carry an ethyl and a npropyl group, respectively, instead of the methyl group of 3b.

Computational Active Site Engineering To explore whether the C-NPMP vs DH analysis can be exploited as a guide for active site engineering toward a target ketone, we set out in silico mutagenesis of OATA to create a mutant customized for 5b. Docking simulations of 5b in OATA and OATAW58L indicated that improvement in the docking orientation, as shown in Figure 7, resulted from creation of room by the W58L mutation which allowed 5b to enter a little deeper into the active site (Figure S6). However, the n-propyl substituent of 5b, compared with the methyl substituent of 3b, is too bulky to enter the S pocket and consequently prevents the phenyl group of 5b from being accommodated in the L pocket (Figure S6). Starting with OATAW58L, the first in silico mutagenesis we did was 58A mutation to create more room in the L pocket. Indeed, docking simulation predicted that the phenyl substituent of 5b approached the L pocket (Figure S7) and as a result 5b became closer to region HR (Figure 7). Intriguingly, OATAW58A rendered 5b present in a new region where no docking pose had been found before. More notably, the nucleophilic attack by the amino group of PMP of OATA W58A was predicted to occur on a re-face of 5b (Figure S7) instead of the conventional si-face attack shown in Figure 2.


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To direct 5b closer to region HR by providing more room in the L pocket, we decided to introduce an additional alanine mutation near 58A. To this end, we chose M54, L57 and M419 (Figure S5). Docking simulation of 5b in the resulting double mutants showed a similar degree of improvement in C-NPMP (Figure 7). However, 57A/58A mutant was chosen as a final candidate because 54A/58A and 58A/419A mutants led to unfavorable DH below 25o. The 57A/58A mutation was predicted to lead to the re-face attack on 5b (Figure 8) as observed with OATAW58A, whereas the other two double mutants did not change the nucleophilic attack trajectory (Figure S8). To verify the in silico engineering guided by the docking orientation analysis, activities of OATAW58A and OATAL57A/W58A for 3b-5b were measured (Table 2). Indeed, progressive activity improvements by additional mutations were observed with 4b and 5b. In contrast, 50 % loss in the activity for 3b was observed as 57A mutation was added to OATAW58A, indicative of fidelity of our engineering strategy directed toward a target ketone. As a result, OATAL57A/W58A showed 2,500- and 130,000-fold activity increases for 4b and 5b, respectively, compared with the wildtype enzyme. The activity of OATAL57A/W58A for 5b corresponds to 3.3 % activity of the wild-type enzyme for 1b. For practical applications of engineered enzymes, it is important that the enzyme variant, displaying desirable catalytic properties, retains intrinsic stability of the parental enzyme or gains enhanced stability. We monitored the enzyme stability for 6 days, showing that OATAL57A/W58A displayed even higher stability than its parental enzyme did (Figure S9). After 6 day-incubation at 37 oC, residual activities of OATA and OATAL57A/W58A were 81  11 and 98  1 %, respectively. Encouraged by the high stability of OATAL57A/W58A, we carried out small-scale asymmetric amination of 5b (5 mM in 1 mL reaction volume) using isopropylamine as an amino donor under


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reduced pressure for equilibrium shift by acetone removal (Figure 9). Reaction yield reached 28 % at 4.5 h and then leveled off because of undesirable evaporation of the ketone substrate. Residual 5b in the reaction mixture was only 0.6 mM at 4.5 h, indicating that 60 % ketone was already evaporated. The evaporation problem could be overcome in a preparative-scale reaction system that harbors a condenser to retrieve the volatile ketone substrate as demonstrated by Savile et al.4 Enantiopurity of the produced (S)--propylbenzylamine was over 99 % ee. In contrast to the engineered variant, its parental enzyme led to negligible generation of the amine product. After 9 h-reaction, OATAL57A/W58A and OATA produced 1.43 and less than 0.0001 mM amine product, respectively. We ruled out two mutant candidates in the course of improving attack trajectory as shown in Figure 7. We prepared the two dropout mutants and measured their activities for 5b. OATAM54A/W58A and OATAW58A/M419A showed specific initial rates of 0.54 ( 0.10) 10-3 and 1.30 ( 0.12) 10-3 M/min/M enzyme, respectively. These activities were much lower than those of OATAL57A/W58A, corroborating practical utility of the docking orientation analysis to guide creation of a better mutant. It is notable that the docking simulation results predict that the nucleophilic attack trajectory of OATAL57A/W58A depends on substrates, i.e. si-face on 3b vs re-face on 4b and 5b (Figure 8). This is seemingly because productive binding of the structurally demanding ketones without steric clash in the S pocket necessitates change in the attack trajectory when introducing alanine mutations to residues 57 and 58 in the L pocket. Irrespective of the attack trajectory, OATAL57A/W58A retained stringent S-stereoselectivity because no trace amount of (R)-amine was detected during amination of 3b-5b. Note that both si- and re-face attacks shown in Figure 8 lead to the same (S)-amine product because chirality of the resulting amine is determined during


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protonation of the achiral quinonoid intermediate as shown in Scheme 1. These results demonstrate that our in silico engineering strategy, guided by the docking analysis and the computational assessment of mutational effects, may be exploited to create a desirable -TA variant for a target ketone without time-consuming mutant construction and activity screening.

CONCLUSION We elucidated the molecular basis of the puzzling substrate bias of -TAs for amino acceptors using docking orientation analysis. Our finding of the separate clustering of high-reactivity and low-reactivity substrate groups on the C-NPMP vs DH plot was exploited to devise virtual activity screening for efficient active site redesign directed for a target ketone. To the best of our knowledge, this is the first example of revealing a predictive link between the -TA activity and the nucleophilic attack trajectory analysis and applying the findings to computational active site engineering of -TA. We expect that more extensive in silico mutagenesis scored by the virtual activity assessment using the C-NPMP vs DH plot analysis leads to even better activity for 5b by permitting shift of the docking pose to region HR.

ASSOCIATED CONTENT Supporting Information: The Supporting Information is available free of charge on the ACS Publications website. Data collection and structure refinement statistics for crystal structure determinations; docking parameters of amino acceptors; crystal structure of OATA, Plots of proximity and angle parameters; docking analysis of nonreactive -keto acids; comparison of


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active site structures of OATA and OATAW58L; and docking structures of 5b with OATAW58L, OATAW58A, OATAM54A/W58A and OATAW58A/M419A; stability of OATAL57A/W58A.

AUTHOR INFORMATION Corresponding Author: * E-mail for J.-S.S.: [email protected] Notes: The authors declare no competing financial interest.

ACKNOWLEDGMENT This work was funded by the National Research Foundation of Korea under the Basic Science Research Program (2016R1A2B4008470). H.-S.C. acknowledges the NRF grant funded by the Korea government (NRF-2014M3C1A3051476).

ABBREVIATIONS CVTA, -TA from Chromobacterium violaceum; GDAPR, good donor-acceptor pair relationship; OATA, -TA from Ochrobactrum anthropi; PDTA, -TA from Paracoccus denitrificans; PLP, pyridoxal 5-phosphate; PMP, pyridoxamine 5-phosphate; TA, transaminase; VFTA, -TA from Vibrio fluvialis; -TA, -transaminase.


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(19) Mehta, P. K.; Hale, T. I.; Christen, P. Eur. J. Biochem. 1993, 214, 549-561. (20) Eliot, A. C.; Kirsch, J. F. Annu. Rev. Biochem. 2004, 73, 383-415. (21) Schiroli, D.; Peracchi, A. Biochim. Biophys. Acta 2015, 1854, 1200-1211. (22) Steffen-Munsberg, F.; Vickers, C.; Kohls, H.; Land, H.; Mallin, H.; Nobili, A.; Skalden, L.; van den Bergh, T.; Joosten, H. J.; Berglund, P.; Hohne, M.; Bornscheuer, U. T. Biotechnol. Adv. 2015, 33, 566-604. (23) Hirotsu, K.; Goto, M.; Okamoto, A.; Miyahara, I. Chem. Rec. 2005, 5, 160-172. (24) Toney, M. D. Arch. Biochem. Biophys. 2014, 544, 119-127. (25) Feng, L.; Geck, M. K.; Eliot, A. C.; Kirsch, J. F. Biochemistry 2000, 39, 15242-15249. (26) Kuramitsu, S.; Hiromi, K.; Hayashi, H.; Morino, Y.; Kagamiyama, H. Biochemistry 1990, 29, 5469-5476. (27) Goldberg, J. M.; Kirsch, J. F. Biochemistry 1996, 35, 5280-5291. (28) Cassimjee, K. E.; Manta, B.; Himo, F. Org. Biomol. Chem. 2015, 13, 8453-8464. (29) Park, E. S.; Kim, M.; Shin, J. S. Appl. Microbiol. Biotechnol. 2012, 93, 2425-2435. (30) Park, E. S.; Shin, J. S. Adv. Synth. Catal. 2014, 356, 3505-3509. (31) Battye, T. G.; Kontogiannis, L.; Johnson, O.; Powell, H. R.; Leslie, A. G. Acta Crystallogr. D Biol. Crystallogr. 2011, 67, 271-281. (32) Vagin, A.; Teplyakov, A. Acta Crystallogr. D Biol. Crystallogr. 2010, 66, 22-25. (33) Winn, M. D.; Ballard, C. C.; Cowtan, K. D.; Dodson, E. J.; Emsley, P.; Evans, P. R.; Keegan, R. M.; Krissinel, E. B.; Leslie, A. G.; McCoy, A.; McNicholas, S. J.; Murshudov, G. N.; Pannu, N. S.; Potterton, E. A.; Powell, H. R.; Read, R. J.; Vagin, A.; Wilson, K. S. Acta Crystallogr. D Biol. Crystallogr. 2011, 67, 235-242. (34) Sayer, C.; Isupov, M. N.; Westlake, A.; Littlechild, J. A. Acta Crystallogr. D Biol. Crystallogr. 2013, 69, 564-576. (35) Vagin, A. A.; Steiner, R. A.; Lebedev, A. A.; Potterton, L.; McNicholas, S.; Long, F.; Murshudov, G. N. Acta Crystallogr. D Biol. Crystallogr. 2004, 60, 2184-2195. (36) Adams, P. D.; Afonine, P. V.; Bunkoczi, G.; Chen, V. B.; Davis, I. W.; Echols, N.; Headd, J. J.; Hung, L. W.; Kapral, G. J.; Grosse-Kunstleve, R. W.; McCoy, A. J.; Moriarty, N. W.; Oeffner, R.; Read, R. J.; Richardson, D. C.; Richardson, J. S.; Terwilliger, T. C.; Zwart, P. H. Acta Crystallogr. D Biol. Crystallogr. 2010, 66, 213-221. (37) Emsley, P.; Cowtan, K. Acta Crystallogr. D Biol. Crystallogr. 2004, 60, 2126-2132. (38) Rausch, C.; Lerchner, A.; Schiefner, A.; Skerra, A. Proteins 2013, 81, 774-787.


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(39) Humble, M. S.; Cassimjee, K. E.; Hakansson, M.; Kimbung, Y. R.; Walse, B.; Abedi, V.; Federsel, H. J.; Berglund, P.; Logan, D. T. FEBS J. 2012, 279, 779-792. (40) Park, E. S.; Shin, J. S. Appl. Environ. Microbiol. 2013, 79, 4141-4144. (41) B'Hymer, C.; Montes-Bayon, M.; Caruso, J. A. J. Sep. Sci. 2003, 26, 7-19. (42) hushan, R.; Brückner, H. Amino Acids 2004, 27, 231-247. (43) Yano, T.; Kagamiyama, H. Proc. Natl. Acad. Sci. U.S.A. 2001, 98, 903-907. (44) Hayashi, H.; Inoue, K.; Nagata, T.; Kuramitsu, S.; Kagamiyama, H. Biochemistry 1993, 32, 12229-12239. (45) Malik, M. S.; Park, E. S.; Shin, J. S. Green Chem. 2012, 14, 2137-2140. (46) Park, E.; Kim, M.; Shin, J. S. Adv. Synth. Catal. 2010, 352, 3391-3398. (47) Jansonius, J. N. Curr. Opin. Struct. Biol. 1998, 8, 759-769. (48) Steffen-Munsberg, F.; Vickers, C.; Thontowi, A.; Schätzle, S.; Meinhardt, T.; Svedendahl Humble, M.; Land, H.; Berglund, P.; Bornscheuer, U. T.; Höhne, M. ChemCatChem 2013, 5, 154-157. (49) Malashkevich, V. N.; Onuffer, J. J.; Kirsch, J. F.; Jansonius, J. N. Nature Struct. Biol. 1995, 2, 548-553. (50) The kcat of OATA for 2b was measured in this study. (51) Radisky, E. S.; Koshland, D. E., Jr. Proc. Natl. Acad. Sci. U.S.A. 2002, 99, 10316-10321. (52) Radisky, E. S.; Lee, J. M.; Lu, C. J.; Koshland, D. E., Jr. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 6835-6840. (53) Sonnet, P. E.; Mascavage, L. M.; Dalton, D. R. Bioorg. Med. Chem. Lett. 2008, 18, 744-748. (54) Oliveira, E. F.; Cerqueira, N. M.; Fernandes, P. A.; Ramos, M. J. J. Am. Chem. Soc. 2011, 133, 15496-15505. (55) Islam, M. M.; Goto, M.; Miyahara, I.; Ikushiro, H.; Hirotsu, K.; Hayashi, H. Biochemistry 2005, 44, 8218-8229.


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Scheme 1. The -TA reaction pathway for reductive amination of acetophenone. Upon binding to the active site of the pyridoxamine 5-phosphate (PMP) form of the enzyme (E-PMP), the ketone substrate undergoes a nucleophilic attack by an amino group of PMP. The resulting carbinolamine is converted to a ketimine which is processed to an external aldimine via a quinonoid intermediate. Transaldimination by an active site lysine leads to formation of an amine product and the PLP form of the enzyme (E-PLP) which is capable of a reverse reaction (i.e. oxidative deamination of an amino donor).


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Table 1. Substrate specificity of -TAs for amino acceptors. Relative activity (%)a

Amino acceptor O

R1

R2

OA TAb

PDTA

CVTA

1b

-COOH

-CH3

100  2

100  6

100  19

2b

-C6H5

-H

130  3

84  11

41  1

3b

-C6H5

-CH3

0.04  0.005

2.0  0.1c

0.9  0.1c

4b

-C6H5

-CH2CH3

0.0004  0.0002

0.2  0.01

n.d. d

5b

-C6H5

-(CH2)2CH3

n.d. d

0.14  0.02

n.d. d

6b

-C6H5-p-CH3

-CH3

0.02  0.001

0.2  0.05

2.0  0.1

7b

-C6H5-p-OCH3

-CH3

0.012  0.001

0.2  0.01

1.7  0.2

8b

-(CH2)2C6H5

-CH3

0.22  0.002

1.1  0.07

12  1

9b

-CH2CH3

-CH3

0.03  0.002

0.11  0.01

0.9  0.04

10b

-(CH2)3CH3

-CH3

0.06  0.002

0.14  0.02

0.3  0.01

11b

-(CH2)5CH3

-CH3

0.08  0.004

0.13  0.01

0.8  0.1

12b

-CH(CH3)2

-CH3

0.07  0.002

0.13  0.02

1.4  0.01

13b

-CH2CH(CH3)2 -CH3

0.008  0.004

0.12  0.02

0.3  0.01

14b

-(CH2)2CH3

-CH3

0.03  0.002

0.13  0.01

0.3  0.02

15b

-COOH

-H

17  1

12  1

38  6

16b

-CH2CH3

-H

63  1

20  1

64  4

17b

-(CH2)2CH3

-H

45  1

42  4

42  7

18b

-(CH2)3CH3

-H

39  4

45  3

41  3

19b

-(CH2)4CH3

-H

41  3

39  3

36  4

R1

a

R2

Relative activity represents specific initial rates normalized by those for 1b. Reaction conditions:

10 mM amino acceptor, 10 mM (S)-3a and 15 % DMSO in 50 mM Tris buffer (pH 7) at 37 oC. Specific initial rates of OATA and PDTA for 1b were 0.023 ± 0.002 and 0.21 ± 0.01 mM/min/M


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ACS Catalysis

enzyme, respectively. Specific initial rate of CVTA for 1b was measured in the absence of DMSO and was 0.22 ± 0.04 mM/min/M enzyme. b

Specific initial rates for 2b and 3b were measured at the reaction conditions described in Figure

1 and were normalized by that for 1b measured at the same reaction conditions. Relative activities for 4b-14b were adapted from Han et al.9 c

Reaction conditions to measure specific initial rate for 3b were 10 mM 3b, 20 mM rac-1-methyl-

3-phenylpropylamine and 15 % DMSO in 50 mM Tris buffer (pH 7). The specific initial rate were normalized by those for 1b measured at the same reaction conditions. d

n.d.: not detectable.


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Page 30 of 42

Table 2. Activity improvements of OATAW58A and OATAL57A/W58A for 3b-5b. Specific reaction rate (10-3 M/min/M enzyme)a

ketone

a

OATA

OATAW58A

OATAL57A/W58A

3b

52  4

20000  1100

9800  400

4b

0.84  0.08

450  50

2100  200

5b

0.033  0.003

14  1

4300  300

Reaction conditions: 10 mM ketone, 500 mM L-1a and 15 % DMSO in 50 mM Tris buffer

(pH 7) at 37 oC.


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ACS Catalysis

Figure legends. Fig.1

Comparison of -TA activities for representative substrates. (A) Three typical substrate pairs. (B) Enzyme activities of OATA. Reaction conditions: 10 mM both amino donor and acceptor. Glyoxylate and 1-methyl-3-phenylpropylamine were used as a cosubstrate to measure amino donor and acceptor reactivity, respectively. The vertical bar for 3b is not visible in the figure due to the too low reactivity. Specific initial rate represents initial reaction rate normalized by enzyme concentration.

Fig. 2

Docking models of OATA using 1b (A), 2b (B) and 3b (C) as ligands. The bound substrates are shown in a ball-and-stick representation. The red and brown circles show the L and S pocket, respectively. The green dotted lines represent H-bonds. The distances for C-NPMP and O-NK287 are designated by the red and black lines, respectively. The blue line designates ∠C-C-NPMP. PMP is represented by thick sticks. The active site is visualized by a Connolly surface.

Fig. 3

Graphical representation of DH and BD.

Fig. 4

Docking analysis of nineteen amino acceptors with OATA. The star symbol represents the optimal docking orientation. HR and LR stand for high reactivity and low reactivity, respectively.

Fig. 5

Docking analysis of nineteen amino acceptors with (A) PDTA, (B) VFTA and (C) CVTA. Arrow shown in Figure 5C represents 8b.

Fig. 6

Docking analysis of nineteen amino acceptors with OATAW58L.

Fig. 7

In silico engineering of OATA for activity improvement toward 5b.

Fig. 8

Docking of 3b-5b in OATAL57A/W58A. Yellow, green and blue sticks represent 3b, 4b and 5b, respectively. Mutation sites are shown as a CPK model.


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ACS Catalysis 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Fig. 9

Page 32 of 42

Small-scale asymmetric synthesis of (S)--propylbenzylamine using OATAL57A/W58A. Reaction conditions: 5 mM 5b and 100 mM isopropylamine, 15 % (v/v) DMSO, 0.1 mM PLP, 15 mg/mL -TA in 50 mM Tris (pH 7) at 460 Torr and 37 oC.


32

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ACS Catalysis

Fig. 1


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ACS Catalysis 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 34 of 42

Fig. 2


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ACS Catalysis

Fig. 3


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ACS Catalysis 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 36 of 42

Fig. 4


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ACS Catalysis

Fig. 5


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ACS Catalysis 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 38 of 42

Fig. 6


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ACS Catalysis

Fig. 7


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ACS Catalysis 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Fig. 8


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ACS Catalysis

Fig. 9


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TOC graphic


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