title: Enantioselective enzymes by computational design and in silico screening.
abstract: Computational enzyme design holds great promise for providing new biocatalysts for synthetic chemistry. A strategy to design small mutant libraries of complementary enantioselective epoxide hydrolase variants for the production of highly enantioenriched (S,S)-diols and (R,R)-diols is developed. Key features of this strategy (CASCO, catalytic selectivity by computational design) are the design of mutations that favor binding of the substrate in a predefined orientation, the introduction of steric hindrance to prevent unwanted substrate binding modes, and ranking of designs by high-throughput molecular dynamics simulations. Using this strategy we obtained highly stereoselective mutants of limonene epoxide hydrolase after experimental screening of only 37 variants. The results indicate that computational methods can replace a substantial amount of laboratory work when developing enantioselective enzymes.
authors: Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 4, 9747 AG Groningen (The Netherlands).
authors: Hein J
authors: HJ
authors: Wijma
authors: Robert J
authors: RJ
authors: Floor
authors: Sinisa
authors: S
authors: Bjelic
authors: Siewert J
authors: SJ
authors: Marrink
authors: David
authors: D
authors: Baker
authors: Dick B
authors: DB
authors: Janssen
mesh_terms: D001665:Binding Sites; D055162:Biocatalysis; D020134:Catalytic Domain; D004851:Epoxide Hydrolases / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D056004:Molecular Dynamics Simulation; D009154:Mutation; D013237:Stereoisomerism; D013379:Substrate Specificity
chemical_list: D004851:Epoxide Hydrolases
keywords: biocatalysis; computational design; epoxide hydrolase; screening; stereoselectivity