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- W4240151357 abstract "<div>Molecular simulations are a valuable tool for studying biomolecular motions and thermodynamics. However, such motions can be slow compared to simulation timescales, yet critical. Specifically, adequate sampling of sidechain motions in protein binding pockets proves crucial for obtaining accurate estimates of ligand binding free energies from molecular simulations. The timescale of sidechain rotamer flips can range from a few ps to several hundred ns or longer, particularly in crowded environments like the interior of proteins. Here, we apply a mixed non-equilibrium candidate Monte Carlo (NCMC)/molecular dynamics (MD) method to enhance sampling of sidechain rotamers. The NCMC portion of our method applies a switching protocol wherein the steric and electrostatic interactions between target sidechain atoms and the surrounding environment are cycled off and then back on during the course of a move proposal. Between NCMC move proposals, simulation of the system continues via traditional molecular dynamics. Here, we first validate this approach on a simple, solvated valine-alanine dipeptide system and then apply it to a well-studied model ligand binding site in T4 lysozyme L99A. We compute the rate of rotamer transitions for a valine sidechain using our approach and compare it to that of traditional molecular dynamics simulations. Here, we show that our NCMC/MD method substantially enhances sidechain sampling, especially in systems where the torsional barrier to rotation is high (>10 kcal/mol). These barriers can be intrinsic torsional barriers or steric barriers imposed by the environment.</div><div>Overall, this may provide a promising strategy to selectively improve sidechain sampling in molecular simulations.</div>" @default.
- W4240151357 created "2022-05-12" @default.
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- W4240151357 date "2019-01-21" @default.
- W4240151357 modified "2023-09-30" @default.
- W4240151357 title "Enhancing Sidechain Rotamer Sampling Using Non-Equilibrium Candidate Monte Carlo" @default.
- W4240151357 doi "https://doi.org/10.26434/chemrxiv.7184876.v2" @default.
- W4240151357 hasPublicationYear "2019" @default.
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