Self-guided (SG) molecular simulation methods, namely self-guided molecular dynamics (SGMD) and self-guided Langevin dynamics (SGLD), enhance conformational search by promoting low-frequency motion. A simple local time averaging scheme is used to extract low-frequency properties with little overhead in computing costs. For molecular processes to form ordered structures like ligand binding and protein folding, it is believed that concerted motions play crucial roles. To enhance the concerted motion in molecular systems, we propose a spatial averaging scheme to extract the concerted motion of a local region. Applying guiding forces based on spatial averaging, self-guided molecular simulations can enhance concerted motion and reach ordered structures more efficiently. Through simulations of amyloid fibril peptides, we demonstrated that the spatial averaging in self-guided Langevin dynamics results in accelerated β-sheet formation.
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Laboratory of Computational Biology, National Heart, Lung and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, MD 20892, USA.
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