Modeling Enzymatic Enantioselectivity using Quantum Chemical Methodology

Abstract

The computational study of enantioselective reactions is a challenging task that requires high accuracy, as very small energy differences have to be reproduced. Quantum chemical methods, most commonly density functional theory, are today an important tool in this pursuit. This Perspective describes recent efforts in modeling asymmetric reactions in enzymes by means of the quantum chemical cluster approach. The methodology is described briefly and a number of illustrative case studies performed recently at our laboratory are presented. The reviewed enzymes are limonene epoxide hydrolase, soluble epoxide hydrolase, arylmalonate decarboxylase, phenolic acid decarboxylase, benzoylformate decarboxylase, secondary alcohol dehydrogenase, acyl transferase, and norcoclaurine synthase. The challenges encountered in each example are discussed, and the modeling lessons learned are highlighted.