Accelerating D-Lactonohydrolase Activity: A Smart In Silico Design Strategy

This work presents an innovative computational approach for efficiently enhancing the activity of D-lactonohydrolase, a key enzyme in biocatalysis. This approach, termed 'Integrative In Silico Design,' combines computational modeling with experimental validation to accelerate enzyme optimization. The strategy leverages advanced computational techniques, including molecular dynamics simulations and machine learning, to identify key residues and mutations that contribute to enhanced enzyme activity. These predictions are then experimentally validated using directed evolution techniques. This iterative process effectively pinpoints mutations that significantly improve D-lactonohydrolase activity, leading to a substantial increase in enzyme efficiency. By integrating computational design and experimental validation, this study demonstrates a powerful approach for accelerating enzyme development and advancing sustainable biomanufacturing.