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Constraint methods that accelerate free-energy simulations of biomolecules.

ABSTRACT: Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions.

SUBMITTER: Perez A

PROVIDER: S-EPMC4684272 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Constraint methods that accelerate free-energy simulations of biomolecules.

Perez Alberto A MacCallum Justin L JL Coutsias Evangelos A EA Dill Ken A KA

The Journal of chemical physics 20151201 24

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential f ...[more]

PMID: 26723628

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