Unlocking D-lactonohydrolase Potential: A Smart In Silico Strategy for Enhanced Activity

This research introduces a novel computational strategy for efficiently boosting the activity of D-lactonohydrolase enzymes. Our 'smart in silico' approach combines computational design with directed evolution techniques, offering a rapid and effective method for optimizing enzyme performance. By leveraging the power of computational modeling, we have identified key residues responsible for substrate binding and catalysis. This knowledge has been used to guide directed evolution experiments, leading to the generation of highly active D-lactonohydrolase variants. Our findings demonstrate the potential of this synergistic computational strategy to significantly enhance enzyme activity, paving the way for the development of more efficient and sustainable biocatalysts.