Going Beyond the Local Catalytic Activity Space of Chitinase Using a Simulation-Based Iterative Saturation Mutagenesis Strategy

Many advances in modifying enzyme properties have been made based on the computation of stable transition states and experimental directed evolution. However, there are still great challenges related to difficult transition state (TS) calculations and the large number of evolutionary experiments needed for verification. The transition state analogue (TSA) has chemical similarity with the TS structure and can be used as a proxy for the unknown TS. Here, we proposed a computation-driven strategy to optimize structures of enzymes via simulation-based iterative saturation mutagenesis (ISM), aiming to stabilize the spatial effects of the TS with a TSA as a placeholder. This approach was applied to redesign structures of chitinase in order to increase its catalytic activity. After three rounds of simulation-based ISM, the catalytic activity of the triple mutant P55T/S216M/R301T was 29.3-fold higher than that of the wild type. The enrichment ratio of variants with increased activity reached 83% in the library selected for experimental verification. In this study, the strategy of optimizing enzymatic activity by computational ISM based on TSA has been streamlined, which facilitates the process of ISM and can be used to extend the bounds of the local optimal solution space.