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.

National Institute of Health (NIH)
Research Project (R01)
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Macromolecular Structure and Function D Study Section (MSFD)
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Preusch, Peter
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Florida State University
Schools of Arts and Sciences
United States
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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
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
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
Hou, Ya-Ming; Gamper, Howard; Yang, Wei (2015) Post-transcriptional modifications to tRNA--a response to the genetic code degeneracy. RNA 21:642-4
Fajer, Piotr; Fajer, Mikolai; Zawrotny, Michael et al. (2015) Full Atom Simulations of Spin Label Conformations. Methods Enzymol 563:623-42