Computational enzymology is an active research subject because it elucidates functions and mechanisms of<br/>enzyme-catalyzed reactions occurring in living organisms at the atomic level. Enzyme modeling is a challenge because of the large size of most enzymes and approximations are made via QM-cluster models or QM/MM models. Our research group has been developing a Python-based framework for automating QM-cluster modeling called the Residue Interaction Network ResidUe Selector (RINRUS). In this study, we have explored systematic differences between RINRUS constructed QM-cluster models derived from an enzyme X-ray crystal structure and RINRUS constructed models from molecular dynamics (MD) simulation. We made a detour from conventional protein network analysis to partition the Residue Interaction Network nodes in terms of the main chain (MC) or side chain (SC) functional groups instead of defining a node as the complete<br/>amino acid residue. Symmetry-adapted perturbation theory (SAPT) and functional-group SAPT (F-SAPT) were employed to explore the interaction energies of residue fragments with an enzyme-substrate. The magnitude of change in total contacts for a given residue does not correspond to the magnitude of change in interaction energy, which agrees with previous work done in our group. The number of total residue-seed contacts in the X-ray crystal structure is usually larger than the number of contacts for MD-relaxed structures. Finally, the F-SAPT computations show that substrate interactions with polar uncharged residues are dominated by dispersion.

Evaluation of the active-site substrate interplay between X-ray crystal structure and molecular dynamics: A case study of chorismate mutase

Fall 2022 abstracts, posters, and presentations will launch in mid-September.

ACS Fall 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.