(12b) Computational Exploration of Peptide Hydrolysis By Serine Protease: Combined Reaction Path and Process Variable Analysis

With a promise of being more efficient and environment friendly, the industrial application of enzymes has become one of the rapidly growing sectors. However, studies on the modification of enzymes and their respective catalytic processes for the non-biomedical field is comparatively small with respect to biomedical applications, such as drug development. An approach of significant importance to contribute to these studies on catalytic activity and to reduce chemical footprint from experimental setups is the molecular modeling of enzyme function. There have been a variety of atomistic modeling tools that have shown promise for the study of enzymatic catalysis, including quantum mechanical (QM) cluster, hybrid quantum mechanical(self-consistent field)/molecular mechanics (QM(SCF)/MM), and hybrid QM(EVB)/MM methodologies. The empirical valence bond (EVB) method is a hybrid QM/MM method that describes reactions by mixing diabatic states that correspond to classical valence bond structures, which represent the reactant, intermediate (or intermediates), and product states¹. Here we will focus upon the QM(EVB)/MM methodology, where key force field parameters are estimated from QM cluster (DFT) calculations.

Our results will focus upon the computational study of serine protease activity. In this study, the Gibbs free energy of activation (Δg^‡_cat), rate coefficient (k), and the Gibbs free energy of reaction (ΔG_rxn) were calculated using QM(EVB)/MM and free-energy perturbation (FEP)/umbrella sampling methods. These key thermochemical and kinetic parameters were utilized for detailed reaction path analysis on peptide bond cleavage with more than hundred numbers of samplings; Gibbs free energy surfaces of reaction were developed for reaction in water and in the native enzyme, also in noncatalyzed condition. Furthermore, influence of key environmental variables affecting catalysis such as temperature and pH were also analyzed, which can present paramount importance in process optimization for commercialized enzymes or for the scale-up of promising enzyme candidates. Moreover, key amino acid residues in the native enzyme active site were mutated to determine overall effects on catalytic activity. These learnings will be discussed in the context of enzyme design.

1. Adamczyk, A. J.; Warshel, A., Converting structural information into an allosteric-energy-based picture for elongation factor Tu activation by the ribosome. Proc. Natl. Acad. Sci. U. S. A. 2011, 108 (24), 9827-9832.