Communication: Consistent interpretation of molecular simulation kinetics using Markov state models biased with external information.
@article{Rudzinski2016CommunicationCI, title={Communication: Consistent interpretation of molecular simulation kinetics using Markov state models biased with external information.}, author={Joseph F. Rudzinski and Kurt Kremer and T. Bereau}, journal={The Journal of chemical physics}, year={2016}, volume={144 5}, pages={ 051102 } }
Molecular simulations can provide microscopic insight into the physical and chemical driving forces of complex molecular processes. Despite continued advancement of simulation methodology, model errors may lead to inconsistencies between simulated and reference (e.g., from experiments or higher-level simulations) observables. To bound the microscopic information generated by computer simulations within reference measurements, we propose a method that reweights the microscopic transitions of the…
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References
SHOWING 1-10 OF 104 REFERENCES
Markov models of molecular kinetics: generation and validation.
- PhysicsThe Journal of chemical physics
- 2011
An upper bound for the approximation error made by modeling molecular dynamics with a Markov chain is described and it is shown that this error can be made arbitrarily small with surprisingly little effort.
Markov state models of biomolecular conformational dynamics.
- Biology, ChemistryCurrent opinion in structural biology
- 2014
Probability distributions of molecular observables computed from Markov models.
- PhysicsThe Journal of chemical physics
- 2008
A rigorous statistical method is proposed to approximate the complete statistical distribution of any observable of an MD simulation provided that one can identify conformational substates such that the transition process between them may be modeled with a memoryless jump process.
Hierarchical analysis of conformational dynamics in biomolecules: transition networks of metastable states.
- PhysicsThe Journal of chemical physics
- 2007
Cl clustering based on kinetics is examined, merging configurational microstates together so as to identify long-lived, i.e., dynamically metastable, states, and an approach is proposed to generate a hierarchical model of networks, each having a different number of metastable states.
Dynamic neutron scattering from conformational dynamics. II. Application using molecular dynamics simulation and Markov modeling.
- PhysicsThe Journal of chemical physics
- 2013
The procedure means that it is now practicable to interpret quasielastic scattering spectra in terms of well-defined intramolecular transitions with minimal a priori assumptions as to the nature of the dynamics taking place.
Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review
- PhysicsFront. Bioeng. Biotechnol.
- 2015
This work reviews a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study and shows the advantages presented and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.
Markov state model reveals folding and functional dynamics in ultra-long MD trajectories.
- PhysicsJournal of the American Chemical Society
- 2011
The MSM approach finds new statistically significant folding pathways, in which either beta-hairpin of the WW domain can form first, and predicts how WW domains may function through a conformational selection mechanism.
Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics.
- ChemistryThe Journal of chemical physics
- 2007
Given molecular dynamics trajectories initiated from a well-defined starting distribution, the algorithm discovers long lived, kinetically metastable states through successive iterations of partitioning and aggregating conformation space into kinetically related regions.
Gaussian Markov transition models of molecular kinetics.
- Computer ScienceThe Journal of chemical physics
- 2015
This work proposes a new class of kinetic models called Markov transition models (MTMs) that approximate the transition density of the MD propagator by a mixture of probability densities where a Gaussian mixture model is used to approximate the symmetrized transition density.