Development of evolutionary algorithm-based protein redesign method
Hiroki Ozawa, Ibuki Unno, Ryohei Sekine, Taichi Chisuga, Sohei Ito, Shogo Nakano
Abstract
Several enzymes are already used on the industrial scale because of the development of various enzyme engineering approaches. In this study, we developed a protein redesign tool, GAOptimizer, to tackle the challenge. GAOptimizer is a genetic algorithm-based tool for optimizing mutation combinations to engineer diverse enzymes. The tool requires two input parameters influencing the mutation selection: fitness functions and sequence libraries. Both stability-based and non-stability-based scores can serve as fitness functions, and these scores are used to determine if the selected mutations are favorable in the design process. Sequence libraries are crucial in defining the sequence space for selecting mutation candidates. We use GAOptimizer on three distinct native enzymes to validate its utility for screening applicable enzymes. Functional analyses of the designed enzymes show that GAOptimizer can produce enzymes exhibiting superior properties to their native enzymes with a high success rate.