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Gerrit J Poelarends - One of the best experts on this subject based on the ideXlab platform.
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biocatalytic asymmetric michael additions of nitromethane to α β unsaturated aldehydes via Enzyme bound iminium ion intermediates
ACS Catalysis, 2019Co-Authors: Chao Guo, Thangavelu Saravanan, Mohammad Saifuddin, Masih Sharifi, Gerrit J PoelarendsAbstract:The Enzyme 4-oxalocrotonate tautomerase (4-OT) exploits an N-terminal proline as main catalytic residue to facilitate several promiscuous C-C bond-forming reactions via Enzyme-bound enamine intermediates. Here we show that the active site of this Enzyme can give rise to further synthetically useful catalytic Promiscuity. Specifically, the F50A mutant of 4-OT was found to efficiently promote asymmetric Michael additions of nitromethane to various α,β-unsaturated aldehydes to give γ-nitroaldehydes, important precursors to biologically active γ-aminobutyric acids. High conversions, high enantiocontrol, and good isolated product yields were achieved. The reactions likely proceed via iminium ion intermediates formed between the catalytic Pro-1 residue and the α,β-unsaturated aldehydes. In addition, a cascade of three 4-OT(F50A)-catalyzed reactions followed by an enzymatic oxidation step enables assembly of γ-nitrocarboxylic acids from three simple building blocks in one pot. Our results bridge organo- and biocatalysis, and they emphasize the potential of Enzyme Promiscuity for the preparation of important chiral synthons.
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Biocatalytic Asymmetric Michael Additions of Nitromethane to α,β-Unsaturated Aldehydes via Enzyme-bound Iminium Ion Intermediates
2019Co-Authors: Chao Guo, Thangavelu Saravanan, Mohammad Saifuddin, Masih Sharifi, Gerrit J PoelarendsAbstract:The Enzyme 4-oxalocrotonate tautomerase (4-OT) exploits an N-terminal proline as main catalytic residue to facilitate several promiscuous C–C bond-forming reactions via Enzyme-bound enamine intermediates. Here we show that the active site of this Enzyme can give rise to further synthetically useful catalytic Promiscuity. Specifically, the F50A mutant of 4-OT was found to efficiently promote asymmetric Michael additions of nitromethane to various α,β-unsaturated aldehydes to give γ-nitroaldehydes, important precursors to biologically active γ-aminobutyric acids. High conversions, high enantiocontrol, and good isolated product yields were achieved. The reactions likely proceed via iminium ion intermediates formed between the catalytic Pro-1 residue and the α,β-unsaturated aldehydes. In addition, a cascade of three 4-OT(F50A)-catalyzed reactions followed by an enzymatic oxidation step enables assembly of γ-nitrocarboxylic acids from three simple building blocks in one pot. Our results bridge organo- and biocatalysis, and they emphasize the potential of Enzyme Promiscuity for the preparation of important chiral synthons
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recent developments in Enzyme Promiscuity for carbon carbon bond forming reactions
Current Opinion in Chemical Biology, 2015Co-Authors: Yufeng Miao, Edzard M. Geertsema, Mehran Rahimi, Gerrit J PoelarendsAbstract:Numerous Enzymes have been found to catalyze additional and completely different types of reactions relative to the natural activity they evolved for. This phenomenon, called catalytic Promiscuity, has proven to be a fruitful guide for the development of novel biocatalysts for organic synthesis purposes. As such, Enzymes have been identified with promiscuous catalytic activity for, one or more, eminent types of carbon-carbon bond-forming reactions like aldol couplings, Michael(-type) additions, Mannich reactions, Henry reactions, and Knoevenagel condensations. This review focuses on Enzymes that promiscuously catalyze these reaction types and exhibit high enantioselectivities (in case chiral products are obtained).
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Recent Advances in the Study of Enzyme Promiscuity in the Tautomerase Superfamily
Chembiochem : a European journal of chemical biology, 2013Co-Authors: Bert-jan Baas, Ellen Zandvoort, Edzard M. Geertsema, Gerrit J PoelarendsAbstract:Catalytic Promiscuity and evolution: Many Enzymes exhibit catalytic Promiscuity--the ability to catalyze reactions other than their biologically relevant one. These reactions can serve as starting points for both natural and laboratory evolution of new enzymatic functions. Recent advances in the study of Enzyme Promiscuity in the tautomerase superfamily are discussed.
V Popov - One of the best experts on this subject based on the ideXlab platform.
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diaminopelargonic acid transaminase from psychrobacter cryohalolentis is active towards s 1 phenylethylamine aldehydes and alpha diketones
Applied Microbiology and Biotechnology, 2018Co-Authors: Ekaterina Yu Bezsudnova, T N Stekhanova, A V Popinako, T V Rakitina, Alena Yu Nikolaeva, Konstantin M Boyko, V PopovAbstract:Substrate and reaction Promiscuity is a remarkable property of some Enzymes and facilitates the adaptation to new metabolic demands in the evolutionary process. Substrate Promiscuity is also a basis for protein engineering for biocatalysis. However, molecular principles of Enzyme Promiscuity are not well understood. Even for the widely studied PLP-dependent transaminases of class III, the reliable prediction of the biocatalytically important amine transaminase activity is still difficult if the desired activity is unrelated to the natural activity. Here, we show that 7,8-diaminopelargonic acid transaminase (synthase), previously considered to be highly specific, is able to convert (S)-(-)-1-phenylethylamine and a number of aldehydes and diketones. We were able to characterize the (S)-amine transaminase activity of 7,8-diaminopelargonic acid transaminase from Psychrobacter cryohalolentis (Pcryo361) and analyzed the three-dimensional structure of the Enzyme. New substrate specificity for α-diketones was observed, though only a weak activity towards pyruvate was found. We examined the organization of the active site and binding modes of S-adenosyl-L-methionine and (S)-(-)-1-phenylethylamine using X-ray analysis and molecular docking. We suggest that the Pcryo361 affinity towards (S)-(-)-1-phenylethylamine arises from the recognition of the hydrophobic parts of the specific substrates, S-adenosyl-L-methionine and 7-keto-8-aminopelargonic acid, and from the flexibility of the active site. Our results support the observation that the conversion of amines is a promiscuous activity of many transaminases of class III and is independent from their natural function. The analysis of amine transaminase activity from among various transaminases will help to make the sequence-function prediction for biocatalysis more reliable.
Dan S. Tawfik - One of the best experts on this subject based on the ideXlab platform.
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Enzyme Promiscuity and evolution in light of cellular metabolism.
The FEBS journal, 2020Co-Authors: Dan S. TawfikAbstract:This Special Issue is composed of 10 reviews that delve into the intricacies behind Enzyme Promiscuity and evolution, an area that is of increasing interest in the biological research community. In particular, the reviews in this Special Issue explore Enzyme Promiscuity and evolution in the context of cellular metabolism, as discussed in this introductory Editorial. It is our hope that you enjoy these fascinating and informative reviews and we wish to thank the authors for their compelling contributions to The FEBS Journal. doi: 10.1111/febs.12650.
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Catalytic versatility and backups in Enzyme active sites: the case of serum paraoxonase 1.
Journal of molecular biology, 2012Co-Authors: Moshe Ben-david, Mikael Elias, Jean-jacques Filippi, Elisabet Duñach, Israel Silman, Joel L Sussman, Dan S. TawfikAbstract:The origins of Enzyme specificity are well established. However, the molecular details underlying the ability of a single active site to promiscuously bind different substrates and catalyze different reactions remain largely unknown. To better understand the molecular basis of Enzyme Promiscuity, we studied the mammalian serum paraoxonase 1 (PON1) whose native substrates are lipophilic lactones. We describe the crystal structures of PON1 at a catalytically relevant pH and of its complex with a lactone analogue. The various PON1 structures and the analysis of active-site mutants guided the generation of docking models of the various substrates and their reaction intermediates. The models suggest that Promiscuity is driven by coincidental overlaps between the reactive intermediate for the native lactonase reaction and the ground and/or intermediate states of the promiscuous reactions. This overlap is also enabled by different active-site conformations: the lactonase activity utilizes one active-site conformation whereas the promiscuous phosphotriesterase activity utilizes another. The hydrolysis of phosphotriesters, and of the aromatic lactone dihydrocoumarin, is also driven by an alternative catalytic mode that uses only a subset of the active-site residues utilized for lactone hydrolysis. Indeed, PON1's active site shows a remarkable level of networking and versatility whereby multiple residues share the same task and individual active-site residues perform multiple tasks (e.g., binding the catalytic calcium and activating the hydrolytic water). Overall, the coexistence of multiple conformations and alternative catalytic modes within the same active site underlines PON1's Promiscuity and evolutionary potential.
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Enzyme Promiscuity a mechanistic and evolutionary perspective
Annual Review of Biochemistry, 2010Co-Authors: Olga Khersonsky, Dan S. TawfikAbstract:Many, if not most, Enzymes can promiscuously catalyze reactions, or act on substrates, other than those for which they evolved. Here, we discuss the structural, mechanistic, and evolutionary implications of this manifestation of infidelity of molecular recognition. We define Promiscuity and related phenomena and also address their generality and physiological implications. We discuss the mechanistic enzymology of Promiscuity—how Enzymes, which generally exert exquisite specificity, catalyze other, and sometimes barely related, reactions. Finally, we address the hypothesis that promiscuous enzymatic activities serve as evolutionary starting points and highlight the unique evolutionary features of promiscuous Enzyme functions.
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8 03 Enzyme Promiscuity evolutionary and mechanistic aspects
Reference Module in Chemistry Molecular Sciences and Chemical Engineering#R##N#Comprehensive Natural Products II#R##N#Chemistry and Biology, 2010Co-Authors: Olga Khersonsky, Dan S. TawfikAbstract:This chapter describes Enzyme Promiscuity. We define Promiscuity and related phenomena, and address its generality, degree, and magnitude. We discuss in detail the mechanistic aspects of Promiscuity – how Enzymes, that generally exert exquisite specificity, may catalyze other, and sometimes barely related, reactions. Finally, we address the evolutionary aspects, namely, how and by what mechanisms promiscuous enzymatic activities could serve as evolutionary starting points.
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Enzyme Promiscuity: evolutionary and mechanistic aspects.
Current opinion in chemical biology, 2006Co-Authors: Olga Khersonsky, Cintia Roodveldt, Dan S. TawfikAbstract:The past few years have seen significant advances in research related to the 'latent skills' of Enzymes - namely, their capacity to promiscuously catalyze reactions other than the ones they evolved for. These advances regard (i) the mechanism of catalytic Promiscuity - how Enzymes, that generally exert exquisite specificity, promiscuously catalyze other, and sometimes barely related, reactions; (ii) the evolvability of promiscuous functions - namely, how latent activities evolve further, and in particular, how promiscuous activities can firstly evolve without severely compromising the original activity. These findings have interesting implications on our understanding of how new Enzymes evolve. They support the key role of catalytic Promiscuity in the natural history of Enzymes, and suggest that today's Enzymes diverged from ancestral proteins catalyzing a whole range of activities at low levels, to create families and superfamilies of potent and highly specialized Enzymes.
Soha Hassoun - One of the best experts on this subject based on the ideXlab platform.
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analysis of metabolic network disruption in engineered microbial hosts due to Enzyme Promiscuity
Metabolic Engineering Communications, 2021Co-Authors: Vladimir Porokhin, Sara A Amin, Trevor B Nicks, Venkatesh Endalur Gopinarayanan, Nikhil U Nair, Soha HassounAbstract:Increasing understanding of metabolic and regulatory networks underlying microbial physiology has enabled creation of progressively more complex synthetic biological systems for biochemical, biomedical, agricultural, and environmental applications. However, despite best efforts, confounding phenotypes still emerge from unforeseen interplay between biological parts, and the design of robust and modular biological systems remains elusive. Such interactions are difficult to predict when designing synthetic systems and may manifest during experimental testing as inefficiencies that need to be overcome. Transforming organisms such as Escherichia coli into microbial factories is achieved via several engineering strategies, used individually or in combination, with the goal of maximizing the production of chosen target compounds. One technique relies on suppressing or overexpressing selected genes; another involves introducing heterologous Enzymes into a microbial host. These modifications steer mass flux towards the set of desired metabolites but may create unexpected interactions. In this work, we develop a computational method, termed Metabolic Disruption Workflow (MDFlow), for discovering interactions and network disruptions arising from Enzyme Promiscuity - the ability of Enzymes to act on a wide range of molecules that are structurally similar to their native substrates. We apply MDFlow to two experimentally verified cases where strains with essential genes knocked out are rescued by interactions resulting from overexpression of one or more other genes. We demonstrate how Enzyme Promiscuity may aid cells in adapting to disruptions of essential metabolic functions. We then apply MDFlow to predict and evaluate a number of putative promiscuous reactions that can interfere with two heterologous pathways designed for 3-hydroxypropionic acid (3-HP) production. Using MDFlow, we can identify putative Enzyme Promiscuity and the subsequent formation of unintended and undesirable byproducts that are not only disruptive to the host metabolism but also to the intended end-objective of high biosynthetic productivity and yield. As we demonstrate, MDFlow provides an innovative workflow to systematically identify incompatibilities between the native metabolism of the host and its engineered modifications due to Enzyme Promiscuity.
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Enzyme Promiscuity prediction using hierarchy informed multi label classification
Bioinformatics, 2021Co-Authors: Gian Marco Visani, Michael C Hughes, Soha HassounAbstract:MOTIVATION As experimental efforts are costly and time consuming, computational characterization of Enzyme capabilities is an attractive alternative. We present and evaluate several machine-learning models to predict which of 983 distinct Enzymes, as defined via the Enzyme Commission (EC) numbers, are likely to interact with a given query molecule. Our data consists of Enzyme-substrate interactions from the BRENDA database. Some interactions are attributed to natural selection and involve the Enzyme's natural substrates. The majority of the interactions however involve non-natural substrates, thus reflecting promiscuous enzymatic activities. RESULTS We frame this "Enzyme Promiscuity prediction" problem as a multi-label classification task. We maximally utilize inhibitor and unlabelled data to train prediction models that can take advantage of known hierarchical relationships between Enzyme classes. We report that a hierarchical multi-label neural network, EPP-HMCNF, is the best model for solving this problem, outperforming k-nearest neighbours similarity-based and other machine learning models. We show that inhibitor information during training consistently improves predictive power, particularly for EPP-HMCNF. We also show that all Promiscuity prediction models perform worse under a realistic data split when compared to a random data split, and when evaluating performance on non-natural substrates compared to natural substrates. AVAILABILITY AND IMPLEMENTATION We provide Python code for EPP-HMCNF and other models in a repository termed EPP (Enzyme Promiscuity Prediction) at https://github.com/hassounlab/EPP. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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analysis of metabolic network disruption in engineered microbial hosts due to Enzyme Promiscuity
bioRxiv, 2020Co-Authors: Vladimir Porokhin, Sara A Amin, Trevor B Nicks, Venkatesh Endalur Gopinarayanan, Nikhil U Nair, Soha HassounAbstract:Abstract Background Increasing understanding of metabolic and regulatory networks underlying microbial physiology has enabled creation of progressively more complex synthetic biological systems for biochemical, biomedical, agricultural, and environmental applications. However, despite best efforts, confounding phenotypes still emerge from unforeseen interplay between biological parts, and the design of robust and modular biological systems remains elusive. Such interactions are difficult to predict when designing synthetic systems and may manifest during experimental testing as inefficiencies that need to be overcome. Despite advances in tools and methodologies for strain engineering, there remains a lack of tools that can systematically identify incompatibilities between the native metabolism of the host and its engineered modifications. Results Transforming organisms such as Escherichia coli into microbial factories is achieved via a number of engineering strategies, used individually or in combination, with the goal of maximizing the production of chosen target compounds. One technique relies on suppressing or overexpressing selected genes; another involves on introducing heterologous Enzymes into a microbial host. These modifications steer mass flux towards the set of desired metabolites but may create unexpected interactions. In this work, we develop a computational method, termed Metabolic Disruption Workflow (MDFlow), for discovering interactions and network disruption arising from Enzyme Promiscuity – the ability of Enzymes to act on a wide range of molecules that are structurally similar to their native substrates. We apply MDFlow to two experimentally verified cases where strains with essential genes knocked out are rescued by interactions resulting from overexpression of one or more other genes. We then apply MDFlow to predict and evaluate a number of putative promiscuous reactions that can interfere with two heterologous pathways designed for 3-hydroxypropic acid (3-HP) production. Conclusions Using MDFlow, we can identify putative Enzyme Promiscuity and the subsequent formation of unintended and undesirable byproducts that are not only disruptive to the host metabolism but also to the intended end-objective of high biosynthetic productivity and yield. In addition, we show how Enzyme Promiscuity can potentially be responsible for the adaptability of cells to the disruption of essential pathways in terms of biomass growth.
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Enzyme Promiscuity prediction using hierarchy informed multi label classification
arXiv: Cell Behavior, 2020Co-Authors: Gian Marco Visani, Michael C Hughes, Soha HassounAbstract:As experimental efforts are costly and time consuming, computational characterization of Enzyme capabilities is an attractive alternative. We present and evaluate several machine-learning models to predict which of 983 distinct Enzymes, as defined via the Enzyme Commission, EC, numbers, are likely to interact with a given query molecule. Our data consists of Enzyme-substrate interactions from the BRENDA database. Some interactions are attributed to natural selection and involve the Enzyme's natural substrates. The majority of the interactions however involve non-natural substrates, thus reflecting promiscuous enzymatic activities. We frame this Enzyme Promiscuity prediction problem as a multi-label classification task. We maximally utilize inhibitor and unlabelled data to train prediction models that can take advantage of known hierarchical relationships between Enzyme classes. We report that a hierarchical multi-label neural network, EPP-HMCNF, is the best model for solving this problem, outperforming k-nearest neighbors similarity-based and other machine learning models. We show that inhibitor information during training consistently improves predictive power, particularly for EPP-HMCNF. We also show that all Promiscuity prediction models perform worse under a realistic data split when compared to a random data split, and when evaluating performance on non-natural substrates compared to natural substrates. We provide Python code for EPP-HMCNF and other models in a repository termed EPP (Enzyme Promiscuity Prediction) at this https URL.
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hierarchical classification of Enzyme Promiscuity using positive unlabeled and hard negative examples
arXiv: Cell Behavior, 2020Co-Authors: Gian Marco Visani, Michael C Hughes, Soha HassounAbstract:Despite significant progress in sequencing technology, there are many cellular enzymatic activities that remain unknown. We develop a new method, referred to as SUNDRY (Similarity-weighting for UNlabeled Data in a Residual HierarchY), for training Enzyme-specific predictors that take as input a query substrate molecule and return whether the Enzyme would act on that substrate or not. When addressing this Enzyme Promiscuity prediction problem, a major challenge is the lack of abundant labeled data, especially the shortage of labeled data for negative cases (Enzyme-substrate pairs where the Enzyme does not act to transform the substrate to a product molecule). To overcome this issue, our proposed method can learn to classify a target Enzyme by sharing information from related Enzymes via known tree hierarchies. Our method can also incorporate three types of data: those molecules known to be catalyzed by an Enzyme (positive cases), those with unknown relationships (unlabeled cases), and molecules labeled as inhibitors for the Enzyme. We refer to inhibitors as hard negative cases because they may be difficult to classify well: they bind to the Enzyme, like positive cases, but are not transformed by the Enzyme. Our method uses confidence scores derived from structural similarity to treat unlabeled examples as weighted negatives. We compare our proposed hierarchy-aware predictor against a baseline that cannot share information across related Enzymes. Using data from the BRENDA database, we show that each of our contributions (hierarchical sharing, per-example confidence weighting of unlabeled data based on molecular similarity, and including inhibitors as hard-negative examples) contributes towards a better characterization of Enzyme Promiscuity.
Alena Yu Nikolaeva - One of the best experts on this subject based on the ideXlab platform.
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Diaminopelargonic acid transaminase from Psychrobacter cryohalolentis is active towards (S)-(-)-1-phenylethylamine, aldehydes and α-diketones
Applied Microbiology and Biotechnology, 2018Co-Authors: Ekaterina Yu Bezsudnova, T N Stekhanova, A V Popinako, T V Rakitina, Alena Yu Nikolaeva, Konstantin M Boyko, Vladimir O. PopovAbstract:Substrate and reaction Promiscuity is a remarkable property of some Enzymes and facilitates the adaptation to new metabolic demands in the evolutionary process. Substrate Promiscuity is also a basis for protein engineering for biocatalysis. However, molecular principles of Enzyme Promiscuity are not well understood. Even for the widely studied PLP-dependent transaminases of class III, the reliable prediction of the biocatalytically important amine transaminase activity is still difficult if the desired activity is unrelated to the natural activity. Here, we show that 7,8-diaminopelargonic acid transaminase (synthase), previously considered to be highly specific, is able to convert ( S )-(-)-1-phenylethylamine and a number of aldehydes and diketones. We were able to characterize the ( S )-amine transaminase activity of 7,8-diaminopelargonic acid transaminase from Psychrobacter cryohalolentis ( Pcryo361 ) and analyzed the three-dimensional structure of the Enzyme. New substrate specificity for α-diketones was observed, though only a weak activity towards pyruvate was found. We examined the organization of the active site and binding modes of S-adenosyl-L-methionine and ( S )-(-)-1-phenylethylamine using X-ray analysis and molecular docking. We suggest that the Pcryo361 affinity towards ( S )-(-)-1-phenylethylamine arises from the recognition of the hydrophobic parts of the specific substrates, S-adenosyl-L-methionine and 7-keto-8-aminopelargonic acid, and from the flexibility of the active site. Our results support the observation that the conversion of amines is a promiscuous activity of many transaminases of class III and is independent from their natural function. The analysis of amine transaminase activity from among various transaminases will help to make the sequence-function prediction for biocatalysis more reliable.
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diaminopelargonic acid transaminase from psychrobacter cryohalolentis is active towards s 1 phenylethylamine aldehydes and alpha diketones
Applied Microbiology and Biotechnology, 2018Co-Authors: Ekaterina Yu Bezsudnova, T N Stekhanova, A V Popinako, T V Rakitina, Alena Yu Nikolaeva, Konstantin M Boyko, V PopovAbstract:Substrate and reaction Promiscuity is a remarkable property of some Enzymes and facilitates the adaptation to new metabolic demands in the evolutionary process. Substrate Promiscuity is also a basis for protein engineering for biocatalysis. However, molecular principles of Enzyme Promiscuity are not well understood. Even for the widely studied PLP-dependent transaminases of class III, the reliable prediction of the biocatalytically important amine transaminase activity is still difficult if the desired activity is unrelated to the natural activity. Here, we show that 7,8-diaminopelargonic acid transaminase (synthase), previously considered to be highly specific, is able to convert (S)-(-)-1-phenylethylamine and a number of aldehydes and diketones. We were able to characterize the (S)-amine transaminase activity of 7,8-diaminopelargonic acid transaminase from Psychrobacter cryohalolentis (Pcryo361) and analyzed the three-dimensional structure of the Enzyme. New substrate specificity for α-diketones was observed, though only a weak activity towards pyruvate was found. We examined the organization of the active site and binding modes of S-adenosyl-L-methionine and (S)-(-)-1-phenylethylamine using X-ray analysis and molecular docking. We suggest that the Pcryo361 affinity towards (S)-(-)-1-phenylethylamine arises from the recognition of the hydrophobic parts of the specific substrates, S-adenosyl-L-methionine and 7-keto-8-aminopelargonic acid, and from the flexibility of the active site. Our results support the observation that the conversion of amines is a promiscuous activity of many transaminases of class III and is independent from their natural function. The analysis of amine transaminase activity from among various transaminases will help to make the sequence-function prediction for biocatalysis more reliable.