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Markov state models (MSMs) have been successful in computing metastable states, slow relaxation timescales and associated structural changes, and stationary or kinetic experimental observables of complex molecules from large amounts of…

Chemical Physics · Physics 2015-06-17 Frank Noe , Hao Wu , Jan-Hendrik Prinz , Nuria Plattner

Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to…

Biological Physics · Physics 2015-06-18 Matthew R. Perkett , Michael F. Hagan

Molecular dynamics (MD) simulations can model the interactions between macromolecules with high spatiotemporal resolution but at a high computational cost. By combining high-throughput MD with Markov state models (MSMs), it is now possible…

Chemical Physics · Physics 2018-06-13 Manuel Dibak , Mauricio J. del Razo , David De Sancho , Christof Schütte , Frank Noé

In the last decade, advances in molecular dynamics (MD) and Markov State Model (MSM) methodologies have made possible accurate and efficient estimation of kinetic rates and reactive pathways for complex biomolecular dynamics occurring on…

Biomolecules · Quantitative Biology 2020-01-29 Hongbin Wan , Vincent A. Voelz

Computational modeling of assembly is challenging for many systems because their timescales vastly exceed those accessible to simulations. This article describes the MultiMSM, which is a general framework that uses Markov state models…

Soft Condensed Matter · Physics 2024-05-07 Anthony Trubiano , Michael F. Hagan

Molecular Dynamics (MD) is a powerful computational microscope for probing protein functions. However, the need for fine-grained integration and the long timescales of biomolecular events make MD computationally expensive. To address this,…

Machine Learning · Computer Science 2026-03-30 Kacper Kapuśniak , Cristian Gabellini , Michael Bronstein , Prudencio Tossou , Francesco Di Giovanni

Markov state models (MSMs) are widely employed to analyze the kinetics of complex systems. But despite their effectiveness in many applications, MSMs are prone to systematic or statistical errors, often exacerbated by suboptimal…

Data Analysis, Statistics and Probability · Physics 2025-08-12 Yehor Tuchkov , Luke Evans , Sonya M. Hanson , Erik H. Thiede

Non-equilibrium Markov State Modeling (MSM) has recently been proposed [Phys. Rev. E 94, 053001 (2016)] as a possible route to construct a physical theory of sliding friction from a long steady state atomistic simulation: the approach…

Statistical Mechanics · Physics 2017-10-17 M. Teruzzi , F. Pellegrini , A. Laio , E. Tosatti

Markov state models (MSMs) have become a popular approach for investigating the conformational dynamics of proteins and other biomolecules. MSMs are typically built from numerous molecular dynamics simulations by dividing the sampled…

Biomolecules · Quantitative Biology 2015-06-12 Yuan Yao , Raymond Z. Cui , Gregory R. Bowman , Daniel Silva , Jian Sun , Xuhui Huang

Markov State Models (MSM) are widely used to elucidate dynamic properties of molecular systems from unbiased Molecular Dynamics (MD). However, the implementation of reweighting schemes for MSMs to analyze biased simulations, for example…

Chemical Physics · Physics 2020-11-26 Stefanie Kieninger , Luca Donati , Bettina G. Keller

When clustering molecular dynamics (MD) trajectories into a few metastable conformational states, the Markov state models (MSMs) assumption of timescale separation between fast intrastate fluctuations and rarely occurring interstate…

Soft Condensed Matter · Physics 2025-01-17 Sofia Sartore , Franziska Teichmann , Gerhard Stock

Gene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have…

Molecular Networks · Quantitative Biology 2016-10-19 Brian K. Chu , Margaret J. Tse , Royce R. Sato , Elizabeth L. Read

Many state of the art methods for the thermodynamic and kinetic characterization of large and complex biomolecular systems by simulation rely on ensemble approaches, where data from large numbers of relatively short trajectories are…

Data Analysis, Statistics and Probability · Physics 2017-04-05 Feliks Nüske , Hao Wu , Jan-Hendrik Prinz , Christoph Wehmeyer , Cecilia Clementi , Frank Noé

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…

Chemical Physics · Physics 2016-02-12 Joseph F. Rudzinski , Kurt Kremer , Tristan Bereau

Markov state models (MSMs) are a widely used method for approximating the eigenspectrum of the molecular dynamics propagator, yielding insight into the long-timescale statistical kinetics and slow dynamical modes of biomolecular systems.…

Biomolecules · Quantitative Biology 2015-03-30 Robert T. McGibbon , Vijay S. Pande

Amorphous materials exhibit structural heterogeneities that relax only on long timescales. Using machine learning techniques, we construct a Markov state model (MSM) for model glass formers that coarse-grains the dynamics into a…

Soft Condensed Matter · Physics 2022-08-31 Siavash Soltani , Chad W. Sinclair , Joerg Rottler

Adopting a $300 \, \mu$s-long molecular dynamics (MD) trajectory of the reversible folding of villin headpiece (HP35) published by D. E. Shaw Research, we recently constructed a Markov state model (MSM) of the folding process based on…

Biological Physics · Physics 2025-10-09 Daniel Nagel , Sofia Sartore , Gerhard Stock

A novel approach to simulate simple protein-ligand systems at large time- and length-scales is to couple Markov state models (MSMs) of molecular kinetics with particle-based reaction-diffusion (RD) simulations, MSM/RD. Currently, MSM/RD…

Chemical Physics · Physics 2021-12-10 Mauricio J. del Razo , Manuel Dibak , Christof Schütte , Frank Noé

Spatial multiscale methods have established themselves as useful tools for extending the length scales accessible by conventional statics (i.e., zero temperature molecular dynamics). Recently, extensions of these methods, such as the…

Numerical Analysis · Mathematics 2014-09-23 Andrew Binder , Mitchell Luskin , Danny Perez , Arthur F. Voter

Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is…

Chemical Physics · Physics 2015-06-22 Christian R. Schwantes , Robert T. McGibbon , Vijay S. Pande
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