Precision Engineering of Imine Reductases: From Structural Insights to Data-Driven Design

Abstract

Imine reductases (IREDs) have emerged as powerful biocatalysts for the enantioselective synthesis of chiral amines via reductive amination, filling a critical gap in accessing optically pure amines essential to pharmaceutical and fine chemical synthesis. However, native IREDs face limitations, including narrow substrate scope, insufficient stability, and strict nicotinamide adenine dinucleotide phosphate (reduced form) (NADPH) dependency. Protein engineering has repositioned IREDs as programmable biocatalysts capable of overcoming these barriers. This review consolidates recent advances into an integrated framework linking structural insights to predictive engineering strategies: (1) structural “hardware”—understanding the multiscale IRED architecture governing substrate recognition and stereoselectivity; (2) structure-driven engineering—translating these structural insights into rational, semi-rational, and cofactor engineering to enhance activity and expand substrate compatibility; and (3) computational “software”—leveraging mechanism-based modeling and machine learning to guide variant prediction and accelerate enzyme discovery. This framework aims to enable precision engineering of IREDs for challenging synthetic transformations.