Physics-based characterization of functionally relevant protein conformational dynamics

NIH RePORTER · NIH · R35 · $364,879 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY With recent advances in structural biology and supercomputing technology, all-atom molecular dynamics (MD) simulation technique has gained momentum as a prominent tool for the study of protein structural dynamics. Brute-force MD, however, is not capable of adequately sampling most functionally relevant biomolecular processes such as large-scale protein conformational changes. Various approaches have been developed over the last three decades to address the “timescale gap” that hinders the use of MD in real- world applications. Free energy calculation methods, enhanced sampling techniques, and path-finding algorithms are examples of umbrella terms that describe many of these methods. This project specifically aims at employing, tailoring, and fine-tuning state-of-the-art enhanced sampling and path-finding algorithms to address important biological and biomedical questions. The overall aim of this project is to develop and employ robust and practical sampling and analysis protocols to study functionally relevant conformational changes of various proteins from fibroblast growth factor to coronavirus spike protein. Our proposed methodological framework specifically takes advantage of (1) robust theoretical formalisms rooted in nonequilibrium statistical mechanics and differential geometry; (2) system-specific enhanced sampling protocols that are tunable for the specific problem at hand; and (3) and integrative and synergistic approach to experimental (specifically smFRET) and computational (specifically MD) techniques. Some of the systems proposed to be studied here include proton-coupled oligopeptide transporters, influenza hemagglutinin, ATP-binding transporters, coronavirus spike proteins, mechanosensitive channel of large conductance, membrane insertase YidC, serotonin transporter, and fibroblast growth factor (FGF) protein. The common theme in all of these projects is the large-scale conformational changes involved in the function of these proteins. The successful use of the methodology proposed in this project will allow the characterization of these conformational changes at the molecular level and pave the groundwork for the routine application of state-of-the-art enhanced sampling techniques in the study of real world biological problems.

Key facts

NIH application ID
10700963
Project number
5R35GM147423-02
Recipient
UNIVERSITY OF ARKANSAS AT FAYETTEVILLE
Principal Investigator
Mahmoud Moradi
Activity code
R35
Funding institute
NIH
Fiscal year
2023
Award amount
$364,879
Award type
5
Project period
2022-09-15 → 2027-08-31