Development of Evolutionally Algorithm-Based Protein Redesign Method

Abstract Enzymes have the potential to become next-generation biocatalysts for synthesizing fine chemicals, but tailoring highly functional enzymes depending on the applications remains a challenging task. In this study, we developed a novel enzyme redesign tool called GAOptimizer to overcome this hurdle. GAOptimizer generates artificial enzymes by accumulating positively-affected mutations through a genetic algorithm, using a template structure as the starting point for the evolution; mutations are selected from phylogenetically conserved residues in homologs of the template. Both stability and non-stability based scores can be used as fitness functions to determine whether mutations may have positive effects. The successful design of three distinct enzymes using GAOptimizer suggests that the tool can generate highly functional enzymes with enhanced properties, such as thermostability, solubility, and activity, by modifying fitness functions. GAOptimizer is freely available at the following URL: https://github.com/shognakano/GAOptimizer.