Conclusion
In this study, we designed a computational strategy with double-screening step for the first time, with the attempt to develop enzymes with increased catalysis activity and thermostability. The fungal α-L-rhamnosidase was used to validate the strategy. First, through molecular docking and sequence alignment, seven mutant candidates, i.e., D525N, S356Y, D525G, S356I, A355N, S303V and V302N were predicted with improved catalysis efficiency. Furthermore, three of the seven mutant candidates were predicted with better thermostability by mutation energy (stable) analysis. By enzyme expression and characterization analysis, the mutant D525N among the three candidates was confirmed with improved catalysis efficiency and thermostability. Moreover, microstructure analysis in MD simulations revealed the mutation D525N was located within the range of 5 Å of the catalytic domain, improving RMSD, electrostatic, Van der Waal interaction and polar salvation values, and forming water bridge between the substrate and the enzyme. These results not only provide an effective strategy for developing excellent enzymes for industrial applications, not only add the theoretical basis for enzyme engineering.