Literature DB >> 26588955

EMMA: A Software Package for Markov Model Building and Analysis.

Martin Senne1, Benjamin Trendelkamp-Schroer1, Antonia S J S Mey1, Christof Schütte1, Frank Noé1.   

Abstract

The study of folding and conformational changes of macromolecules by molecular dynamics simulations often requires the generation of large amounts of simulation data that are difficult to analyze. Markov (state) models (MSMs) address this challenge by providing a systematic way to decompose the state space of the molecular system into substates and to estimate a transition matrix containing the transition probabilities between these substates. This transition matrix can be analyzed to reveal the metastable, i.e., long-living, states of the system, its slowest relaxation time scales, and transition pathways and rates, e.g., from unfolded to folded, or from dissociated to bound states. Markov models can also be used to calculate spectroscopic data and thus serve as a way to reconcile experimental and simulation data. To reduce the technical burden of constructing, validating, and analyzing such MSMs, we provide the software framework EMMA that is freely available at https://simtk.org/home/emma .

Year:  2012        PMID: 26588955     DOI: 10.1021/ct300274u

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  43 in total

1.  MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories.

Authors:  Robert T McGibbon; Kyle A Beauchamp; Matthew P Harrigan; Christoph Klein; Jason M Swails; Carlos X Hernández; Christian R Schwantes; Lee-Ping Wang; Thomas J Lane; Vijay S Pande
Journal:  Biophys J       Date:  2015-10-20       Impact factor: 4.033

2.  Milestoning simulation reveals mechanism of helix-breaking.

Authors:  Krzysztof Kuczera
Journal:  Biophys J       Date:  2013-08-20       Impact factor: 4.033

3.  Efficient maximum likelihood parameterization of continuous-time Markov processes.

Authors:  Robert T McGibbon; Vijay S Pande
Journal:  J Chem Phys       Date:  2015-07-21       Impact factor: 3.488

4.  Variational cross-validation of slow dynamical modes in molecular kinetics.

Authors:  Robert T McGibbon; Vijay S Pande
Journal:  J Chem Phys       Date:  2015-03-28       Impact factor: 3.488

5.  MSMBuilder: Statistical Models for Biomolecular Dynamics.

Authors:  Matthew P Harrigan; Mohammad M Sultan; Carlos X Hernández; Brooke E Husic; Peter Eastman; Christian R Schwantes; Kyle A Beauchamp; Robert T McGibbon; Vijay S Pande
Journal:  Biophys J       Date:  2017-01-10       Impact factor: 4.033

6.  Exploring Binding Mechanisms in Nuclear Hormone Receptors by Monte Carlo and X-ray-derived Motions.

Authors:  Christoph Grebner; Daniel Lecina; Victor Gil; Johan Ulander; Pia Hansson; Anita Dellsen; Christian Tyrchan; Karl Edman; Anders Hogner; Victor Guallar
Journal:  Biophys J       Date:  2017-03-28       Impact factor: 4.033

7.  Kinetic characterization of the critical step in HIV-1 protease maturation.

Authors:  S Kashif Sadiq; Frank Noé; Gianni De Fabritiis
Journal:  Proc Natl Acad Sci U S A       Date:  2012-11-26       Impact factor: 11.205

Review 8.  To milliseconds and beyond: challenges in the simulation of protein folding.

Authors:  Thomas J Lane; Diwakar Shukla; Kyle A Beauchamp; Vijay S Pande
Journal:  Curr Opin Struct Biol       Date:  2012-12-10       Impact factor: 6.809

9.  Improved coarse-graining of Markov state models via explicit consideration of statistical uncertainty.

Authors:  Gregory R Bowman
Journal:  J Chem Phys       Date:  2012-10-07       Impact factor: 3.488

10.  Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning.

Authors:  Yasuhiro Matsunaga; Yuji Sugita
Journal:  Elife       Date:  2018-05-03       Impact factor: 8.140

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