2020
DOI: 10.1021/acs.jctc.0c00429
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Coupling Coarse-Grained to Fine-Grained Models via Hamiltonian Replica Exchange

Abstract: The energy landscape of biomolecular systems contains many local minima that are separated by high energy barriers. Sampling this landscape in molecular dynamics simulations is a challenging task and often requires the use of enhanced sampling techniques. Here, we increase the sampling efficiency by coupling the fine-grained (FG) GROMOS force field to the coarse-grained (CG) Martini force field via the Hamiltonian replica exchange method (HREM). We tested the efficiency of this procedure using a lutein/octane … Show more

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Cited by 10 publications
(9 citation statements)
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“…The exchange is accepted based on the probability expressed by Equation ( 15 ): with where is the potential energy function (including the restraining potential) corresponding to the trajectory, and denotes the variables of the respective conformation of this trajectory at the attempted exchange point. A variant of HREMD was developed recently [ 215 ] for mixed-resolution MD simulations with the MARTINI [ 66 ] and GROMOS [ 216 ] force fields.…”
Section: Theory and Methodologymentioning
confidence: 99%
“…The exchange is accepted based on the probability expressed by Equation ( 15 ): with where is the potential energy function (including the restraining potential) corresponding to the trajectory, and denotes the variables of the respective conformation of this trajectory at the attempted exchange point. A variant of HREMD was developed recently [ 215 ] for mixed-resolution MD simulations with the MARTINI [ 66 ] and GROMOS [ 216 ] force fields.…”
Section: Theory and Methodologymentioning
confidence: 99%
“…It was highly effective in simulate reversible transitions of small β-hairpins and helical IDPs [34,124,125] and proved instrumental in further refinement of a GBMV2 implicit solvent protein force field for both ordered and disordered peptides [126]. Very recently, MSES was also observed to be effective in sampling the cis-trans transitions of lutein by coupling the atomistic model with the Martini CG model [127]. Nonetheless, the application of MSES to larger and more complex proteins has proven more challenging than originally expected, apparently due to the difficulty in effective coupling of CG and atomistic conformational fluctuations of a larger protein.…”
Section: Collective Variables-free Sampling Methods and Optimizationmentioning
confidence: 99%
“…The system is partitioned into two subsystems, that is, AA and CG. The crux of the method is that each subsystem interacts with itself at its corresponding level of description and that the interaction between the subsystems is at the CG level using the VS multiscale approach. It was previously shown that the VS multiscale method can properly reproduce the potentials of mean force (PMFs) between pairs of apolar amino acid side-chain analogs, yet failed to reproduce correct PMFs for the polar and charged AA solutes in the CG solvent . Therefore, to avoid polar resolution interfaces, we propose a dual resolution membrane structure with the AA–CG interface at the interleaflet region, constituting an apolar environment, illustrated in Figure .…”
Section: Methodsmentioning
confidence: 99%