Enhancing the Substrate Specificity of Nitrilase toward Aliphatic Nitriles Based on Substrate Channel Design

Abstract

Nitrilase has attracted widespread attention due to its efficiency, specificity, and ecofriendliness in the hydrolysis reactions of nitrile compounds. These enzymes can catalyze various substrates, including aliphatic nitriles and aromatic nitriles. However, high substrate specificity is key to efficient catalysis and high-purity product synthesis. This study aims to enhance the preference of nitrilase for aliphatic nitriles through substrate channel engineering to expand its industrial applications. We developed a semirational design workflow that integrates extensive search and deep optimization strategies, relying on computational tools such as substrate channel modeling and molecular docking to systematically identify and optimize key amino acid residues related to substrate binding. Taking 3-chloropropionitrile as an example, the specific activity of the optimal mutant G191A/L194W increased from 2.47 to 58.35 U·mg^–1, with the substrate conversion rate approaching 100%, while the catalytic activity toward aromatic nitriles significantly decreased. Molecular dynamics simulations revealed the correlation between substrate specificity and channel morphology regulated by W194 and promoted the formation of a specificity-enhanced mutant network. This study provides a structural and mechanistic basis for substrate channel design and enzyme function modification and validates its potential for industrial applications.