A Highly Stereoselective and Efficient Biocatalytic Synthesis of Chiral Syn-Aryl β-Hydroxy α-Amino Esters

Abstract

Chiral aryl β-hydroxy α-amino acids and their derivatives are essential pharmaceutical intermediates, widely used as chiral building blocks in drug synthesis. Nevertheless, the task of creating effective, extremely selective, and ecofriendly catalytic techniques for their production continues to be a major obstacle. Herein, loop engineering, combinatorial active-site saturation test/iterative saturation mutation (CAST/ISM), and the FuncLib strategies were applied to a carbonyl reductase (EaSDR6) from Exiguobacterium algae for the asymmetric biosynthesis of chiral syn-aryl β-hydroxy α-amino esters via dynamic reductive kinetic resolution (DYRKR) of aryl-α-amino β-keto esters with high yield and selectivity. Mutant M6 (A138 V/A190M/S193A/Y201W/N204A/V205E) exhibited a 909-fold improvement in catalytic efficiency (k_cat/K_m) and a significant increase in diastereoselectivity (from 59 to >99% d.e.) toward substrate 1a. It achieved 99% conversion within 8 h at a substrate concentration of 300 g L^–1 (highest substrate loading reported), enabling gram-scale biosynthesis of the florfenicol precursor (2S,3R)-2a. Additionally, the VAF (A90 V/S193A/Y201F) mutant demonstrated high stereoselectivity (>94% e.e., 94–99% d.e.), desired conversions (>63%), and isolated yields (40–88%) for synthesizing diverse (2S,3R)-aryl β-hydroxy α-amino esters. Molecular dynamics simulations and quantum mechanical calculations unveiled that mutations induced a higher ratio of closed conformational states of the substrate-binding loop that shrinks cavity A, facilitating accommodation of the acetamide group of substrate 1a in this region and enhancing substrate binding and controlling diastereoselectivity (especially A190 M and S193A). This work highlights the potential of engineered carbonyl reductase in highly stereoselective and efficiently synthesizing chiral syn-aryl β-hydroxy α-amino esters and establishes a solid foundation for future large-scale industrial applications.