School of Physics, Quantum Matter Seminar| Dr. Mahmoud Moradi | University of Arkansas

With recent advances in various biophysical techniques, structural biology is at a tipping point. However, there seems to be an effective uncertainty relation between the spatial and temporal resolution of these techniques; the spatially high-resolution techniques such as x-ray crystallography are lacking a temporal resolution and the temporally high-resolution techniques such as single-molecule FRET spectroscopy are associated with very low spatial resolutions. Currently, a detailed picture of protein dynamics at the atomic level with a high spatiotemporal resolution can be produced only using all-atom molecular dynamics (MD) simulations. Unfortunately, many biomolecular processes such as large-scale protein conformational changes are associated with timescales inaccessible to brute-force MD. Although various enhanced sampling techniques have been developed over the past few decades to address this “timescale gap”, the application of these methods to biologically relevant systems remains challenging. We have developed a novel framework for improving enhanced sampling techniques for the computational study of conformational transitions of proteins. This methodology provides a robust framework for the study of functionally important conformational changes of proteins at the molecular level. The developed algorithms have been particularly used to study several classes of proteins including but not limited to membrane insertases, chloroplast signal recognition particles, fibroblast growth factor proteins, mechanosensitive channels, influenza hemagglutinin, and coronavirus spike proteins.