ArticleJournal of computational chemistry2021
Accelerating atomistic simulations of proteins using multiscale enhanced sampling with independent tempering.
Article in Journal of computational chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Challenges of conventional iterative all-atom and coarse-grained multiscale molecular dynamics.Scientific reports · 2026Article
- Simulation of the trimeric globular head of C1q reveals temperature-sensitive network: implications for inflammation.Journal of molecular modeling · 2025Article
- Advanced Sampling Methods for Multiscale Simulation of Disordered Proteins and Dynamic Interactions.Biomolecules · 2021Review
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3 authors.
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Abstract
Efficient sampling of the conformational space is essential for quantitative simulations of proteins. The multiscale enhanced sampling (MSES) method accelerates atomistic sampling by coupling it to a coarse-grained (CG) simulation. Bias from coupling to the CG model is removed using Hamiltonian replica exchange, such that one could benefit simultaneously from the high accuracy of atomistic models and fast dynamics of CG ones. Here, we extend MSES to allow independent control of the effective temperatures of atomistic and CG simulations, by directly scaling the atomistic and CG Hamiltonians. The new algorithm, named MSES with independent tempering (MSES-IT), supports more sophisticated Hamiltonian and temperature replica exchange protocols to further improve the sampling efficiency. Using a small but nontrivial β-hairpin, we show that setting the effective temperature of CG model in all conditions to its melting temperature maximizes structural transition rates at the CG level and promotes more efficient replica exchange and diffusion in the condition space. As the result, MSES-IT drive faster reversible transitions at the atomic level and leads to significant improvement in generating converged conformational ensembles compared to the original MSES scheme.
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