Enzyme simulations are notoriously challenging as their large size prevents modeling the whole enzyme with highly accurate but computationally expensive quantum mechanical (QM) methods. Currently, only the chemically important “active site” residues/substrates/cofactors are modeled with QM-methods. However, determining which biological sub-units necessarily should be included in the QM-model remains ambiguous, and current practices for model construction typically suffer from human bias and unclear methodology. My lab has been developing software called <i>RINRUS</i> (Residue Interaction Network ResidUe Selector) designed to use protein topology to construct residue interaction networks for the prediction of appropriate QM-only models of enzyme active sites. As the RINRUS workflow becomes more sophisticated and flexible, I hope to address reproducibility and throughput / data velocity issues that arise in atomic-level enzyme modeling. First, molecular dynamics (MD) simulations are sampled and refined with QM-cluster models to study the enzyme mechanism of chorismate mutase. The evolution and visualization of Residue Interaction Networks through the course of an MD simulation will also be discussed. In tandem with RINRUS development, we have applied computational enzymology to study fascinating proposed mechanisms of snake venom metalloproteinases, catechol-O-methyltransferase, and cytochrome P450 proteins involved in lignin valorization.

Residue interaction networks and the cheminformatics of atomic-level enzyme models

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.