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Accelerate Sampling in Atomistic Energy Landscapes Using Topology-Based Coarse-Grained Models

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Department of Biochemistry and Molecular Biophysics, Kansas State University, Manhattan, Kansas 66506, United States
*Phone: (785) 532-2518. Fax: (785) 532-7278. E-mail: [email protected]
Cite this: J. Chem. Theory Comput. 2014, 10, 3, 918–923
Publication Date (Web):January 29, 2014
https://doi.org/10.1021/ct500031v
Copyright © 2014 American Chemical Society

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    Abstract

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    We describe a multiscale enhanced sampling (MSES) method where efficient topology-based coarse-grained models are coupled with all-atom ones to enhance the sampling of atomistic protein energy landscape. The bias from the coupling is removed by Hamiltonian replica exchange, thus allowing one to benefit simultaneously from faster transitions of coarse-grained modeling and accuracy of atomistic force fields. The method is demonstrated by calculating the conformational equilibria of several small but nontrivial β-hairpins with varied stabilities.

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    Three figures and a table showing coevolution of CG and atomistic models, conformational coverage, and folding kinetics and efficiency of CG and atomistic models in MSES. This material is available free of charge via the Internet at http://pubs.acs.org.

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