QM/MM free energy Simulations of an efficient Gluten Hydrolase (Kuma030) Implicate for a Reactant-State Based Protein-Design Strategy for General Acid/Base Catalysis

It is a grand attraction for contemporary biochemists to computationally design enzymes for novel chemical transformation or improved catalytic efficiency. Rosetta by Baker et al . is no doubt the leading software in the protein design society. Generally, optimization of the transition state (TS) is part of the Rosetta’s protocol to enhance the catalytic efficiency of target enzymes, since TS stabilization is the determining factor for catalytic efficiency based on the TS theory (TST). However, it is confusing that optimization of the reactant state (RS) also results in significant improvement of catalytic efficiency in some cases, such as design of gluten hydrolase (Kuma030). Therefore, it is interesting to uncover underlying reason why a better binding in the RS leading to an increased k cat . In this study, the combined quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) and free energy (PMF) simulations, p K a calculation, and the statistical analysis such as the ANOVA test were carried out to shed light on the interesting but elusive question. By integration of our computational results and general acid/base theory, we answered the question why optimization of RS stabilization leads to a better TS stabilization in the general acid/base catalysis. In addition, a new and simplified protein-design strategy is proposed for the general acid/base catalysis. The idea, that application of traditional well-defined enzyme mechanism to protein design strategy, would be a great help for methodology development of protein design.