New Tools and Their Applications for Understanding Functional Protein Dynamics by NMR and Computation

About This Grant

The research conducted in this project will produce new and broadly applicable experimental methods, protocols, and analysis software for the more accurate and realistic characterization of proteins at the atomic level in their native environment for the fundamental understanding of their function in terms structure, dynamics, and interactions with binding partners. The tools developed through this project will make nuclear magnetic resonance (NMR) more widely accessible to both experts and non-experts through standardized workflows and free, easy-to-use software for automation, enhanced by AI/ML, for optimal reproducibility and quantitation. The project provides interdisciplinary training and research opportunities for STEM undergraduate students, graduate students, and postdoctoral fellows at Ohio State. The new NSF-funded National Gateway Ultrahigh Field NMR Center will help introduce a broader public to the discoveries and benefits of basic and applied molecular and materials research to society, including high school students to perform and analyze NMR experiments of common molecular compounds. The realistic representation of protein structure and dynamics at atomic detail is essential for understanding protein function. Protein dynamics can occur on a wide range of timescales covering pico- to milliseconds and beyond. Nanoparticle-assisted nuclear spin relaxation (NASR) provides unique opportunities to observe nano- to microsecond events at atomic resolution under near-physiological conditions that are hard to detect by other experimental methods. New types of NASR experiments utilizing different types of spin relaxation mechanisms will be developed and applied to protein systems to gain insights into their structural dynamics in relationship to their function. This includes backbone and side-chain dynamics studies of immunity protein and small GTPases with their interaction partners. The new data will also be used as benchmarks for extended molecular dynamics (MD) computer simulations assisted by AlphaFold for the generation of physically realistic conformational ensembles for the better understanding of the driving forces underlying protein-protein and protein-ligand interactions and allosteric signaling. Enhanced machine-learning based NMR spectral tools will be developed and incorporated into the new open source COLMARvista software for the autonomous processing and quantitative analysis of biomolecular NMR spectra. This includes multidimensional NMR experiments for the rapid and routine measurements of structural and dynamics protein parameters. These tools will help elucidate the intricate relationship between structural dynamics and function of proteins and their interaction partners. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.