Publication | Closed Access
Active Site Engineering of ω-Transaminase Guided by Docking Orientation Analysis and Virtual Activity Screening
63
Citations
38
References
2017
Year
Bioorganic ChemistryEngineeringMolecular BiologyPeptide ScienceChemical BiologyEnzymatic ModificationBiosynthesisActive Site MutationActive Site EngineeringActive Site EnvironmentStructure-function Enzyme KineticsComputational BiochemistryEnzyme VariantsVirtual Activity ScreeningBiochemistryBiocatalysisOrientation AnalysisMolecular ModelingBiomolecular EngineeringNatural SciencesEnzyme CatalysisEnzyme SpecificityProtein EngineeringMolecular Docking
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 of the reaction mechanism in the context of active site environment. Despite the great potential of ω-transaminases (ω-TAs) for asymmetric synthesis of chiral amines from ketones, it remains elusive why ω-TAs exhibit marginal activities for most ketones in contrast to their high activities for α-keto acids and aldehydes. To address this puzzling question, crystal structure determination and molecular modeling of ω-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 ω-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 ω-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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