(634f) Transition Path Methods for Understanding Catalysis By Proteins

Enzymes are capable of catalyzing reactions with barriers so high that their uncatalyzed versions are exceedingly slow. These proteins can provide an appropriate local environment to facilitate a chemical transformation on a biologically relevant scale, at ambient temperatures and pressures, for substrates that would otherwise be unreactive. Orotidine 5’-monophosphate decarboxylase (OMPDC) enhances the rate of decarboxylation of orotidylic acid by a factor of 10¹⁷ compared to its solution reaction, making it one of the greatest enzymatic rate enhancements known. Even more impressively, OMPDC achieves this catalytic enhancement without the assistance of co-factors; the origin of its proficiency arises solely from substrate interactions with solvent and enzyme amino-acid residues. Many prior studies are compatible with several mechanistic hypotheses. The objective of this project is to identify what strategies OMPDC employs to decarboxylate its substrate with such a substantial rate acceleration, and to develop a predictive model of chemical features that cause reactivity. Our approach uses a combination of multi-scale molecular mechanical and quantum mechanical (QM/MM) techniques, coupled with Monte-Carlo methods to create transition-path ensembles of reactive and non-reactive dynamic trajectories. We use these ensembles to generate structural features that are analyzed by machine learning methods in order to identify the atomistic-level causes of reactivity, and to provide a template for proposed mutations.