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.