Accurately predicting how fluctuating protein environments recognize molecular ligands have been a long-pursued challenge in computational chemistry and biophysics. The objective of this project is to develop and employ practical all-atom molecular dynamics simulation methods to study how protein environment changes govern protein-ligand recognition. This project is particularly encouraged by our novel sampling method developments, represented by the orthogonal space sampling scheme, which can uniquely enable synchronous acceleration of the motion of a focused (chemical) change and its coupled environmental responses, for instance conformational transitions and wetting/dewetting processes. This study includes three specific goals: (1) to understand how protein environment changes couple with protein-ligand binding and to realize accurate ranking of ligand relative binding affinities; (2) to enable simultaneous prediction of protein-ligand absolute binding affinities and binding complex structures; and (3) to elucidate how fluctuating enzymes recognize tight transition state analogue binders versus their natural substrates.

Public Health Relevance

Leap-frog efficiency improvements for free energy perturbation calculations will be realized to enable quantitative understanding of how protein environment changes govern protein-ligand recognition. These methods will be utilized to elucidate essential protein-ligand interactions. In addition to specific biophysical understanding, a powerful toolkit for quantitative protein-ligand binding predictions will be produced to be feasibly and widely employed in biochemical studies and drug discovery processes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM111886-05
Application #
9554996
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Lyster, Peter
Project Start
2014-09-01
Project End
2019-08-31
Budget Start
2018-09-01
Budget End
2019-08-31
Support Year
5
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Florida State University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
790877419
City
Tallahassee
State
FL
Country
United States
Zip Code
32306
Li, Xubin; Lv, Chao; Corbett, Karen M et al. (2016) Free energy landscape of a minimalist salt bridge model. Protein Sci 25:270-6
Wu, D; Fajer, M I; Cao, L et al. (2016) Generalized Ensemble Sampling of Enzyme Reaction Free Energy Pathways. Methods Enzymol 577:57-74
Lu, Chao; Li, Xubin; Wu, Dongsheng et al. (2016) Predictive Sampling of Rare Conformational Events in Aqueous Solution: Designing a Generalized Orthogonal Space Tempering Method. J Chem Theory Comput 12:41-52
Lv, Chao; Aitchison, Erick W; Wu, Dongsheng et al. (2016) Comparative exploration of hydrogen sulfide and water transmembrane free energy surfaces via orthogonal space tempering free energy sampling. J Comput Chem 37:567-74
Fajer, Piotr; Fajer, Mikolai; Zawrotny, Michael et al. (2015) Full Atom Simulations of Spin Label Conformations. Methods Enzymol 563:623-42
Hou, Ya-Ming; Gamper, Howard; Yang, Wei (2015) Post-transcriptional modifications to tRNA--a response to the genetic code degeneracy. RNA 21:642-4