The goal of the proposed research is to develop techniques for the accurate simulation and interpretation of NMR relaxation data for atomic- level motions in proteins. Characterizing the atomic-level dynamics of proteins is critical to understanding many processes in molecular biology, including ligand binding, protein recognition, and protein folding, and thus has wide medicinal applicability, particularly to drug design. NMR is the most broadly useful experimental method for characterizing atomic- level motions, but the experimental data require interpretation, which molecularly dynamics simulation can provide. The proposed research focuses on the side-chain dynamics of staphylococcal nuclease, a small protein for which NMR side-chain relaxation data are available. Previous simulations have focused primarily on the backbone dynamics of proteins because more NMR data are available for these motions, and the time scale of the motions monitored (N-H and Calpha-H bond vectors) is shorted. The proposed research will proceed by (1) establishing the level of agreement possible between stimulation and NMR relaxation data when the most realistic solvation methods are used, based on simulations of crystalline peptides and of solvated staphylococcal nuclease, (2) characterizing the effect of more approximate solvation models of side-chain motional parameters, as such methods can enable otherwise unfeasible calculations, (3) refining methods for identifying the important degrees of freedom for side-chain flexibility and quantitatively relating the degree of mobility to NMR order parameters, and (4) developing methods for relating conformational entropies to order parameters for side-chain motions.
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