Life is sustained by the actions of various biomolecules along key metabolic and cellular pathways in our cells. The conformers and interactions of these biomolecules can be challenging to study, due to their transient natures and rapidly changing dynamics within the complex cell environments. This leads to the phenomenon of biomolecular "hidden states" – states not revealed by traditional experiments and in silico methods. Interactions between the biomolecules and their crowded cell environments further often influences the rapid changes these "hidden states" undergo. These "hidden states" include those of mis-folded proteins, ensembles of enzyme conformers as well as their small-molecule ligands, and multi-enzyme complexes.

Our research program centers on applying computational chemistry methods to build and simulate atomistic models of human cell environments. Using our "cells-on-computers", we aim to address the current challenges in characterizing biomolecular "hidden states" that arise from limitations of spatial-temporal resolutions of traditional experiments and in silico methods.

Characterizing biophysical properties, especially at the atomic level, of these rapidly evolving biomolecular states can lead to health advances. Our program’s long-term focus is to develop streamlined platforms for both investigating structural mechanisms of cell-specific human diseases and screening drugs in a rapid and cost-effective manner.

Current focuses of ongoing projects in our group include protein aggregation, mechanisms of red blood cell diseases, and metabolic pathways in cancer cells. We are constructing platforms to simulate structural mechanisms of cell-specific diseases, including disorders of red blood cells, such as sickle-cell anemia and thalassemia. We are also deconstructing how glycolytic enzymes communicate in cancer cells by forming islands of transient multi-enzyme complexes known as metabolons.