6533b81ffe1ef96bd1277b38
RESEARCH PRODUCT
Non-equilibrium Markov state modeling of periodically driven biomolecules
Fabian KnochThomas Specksubject
Computer scienceFOS: Physical sciencesGeneral Physics and AstronomyMarkov processMolecular Dynamics Simulation010402 general chemistry01 natural sciencesMolecular dynamicssymbols.namesake0103 physical sciencesPhysics - Biological PhysicsStatistical physicsPhysical and Theoretical ChemistryCondensed Matter - Statistical Mechanicschemistry.chemical_classificationQuantitative Biology::BiomoleculesStatistical Mechanics (cond-mat.stat-mech)010304 chemical physicsMarkov chainBiomoleculeMolecular biophysicsDetailed balanceDipeptidesComputational Physics (physics.comp-ph)Markov Chains0104 chemical sciencesModels ChemicalchemistryBiological Physics (physics.bio-ph)Benchmark (computing)symbolsState (computer science)Physics - Computational Physicsdescription
Molecular dynamics simulations allow to study the structure and dynamics of single biomolecules in microscopic detail. However, many processes occur on time scales beyond the reach of fully atomistic simulations and require coarse-grained multiscale models. While systematic approaches to construct such models have become available, these typically rely on microscopic dynamics that obey detailed balance. In vivo, however, biomolecules are constantly driven away from equilibrium in order to perform specific functions and thus break detailed balance. Here we introduce a method to construct Markov state models for systems that are driven through periodically changing one (or several) external parameter. We illustrate the method for alanine dipeptide, a widely used benchmark molecule for computational methods, exposed to a time-dependent electric field.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-19 | The Journal of Chemical Physics |