Literature DB >> 18715051

Building Markov state models along pathways to determine free energies and rates of transitions.

Albert C Pan1, Benoît Roux.   

Abstract

An efficient method is proposed for building Markov models with discrete states able to accurately describe the slow relaxation of a complex system with two stable conformations. First, the reaction pathway described by a set of collective variables between the two stable states is determined using the string method with swarms of trajectories. Then, short trajectories are initiated at different points along this pathway to build the state-to-state transition probability matrix. It is shown, using a model system, how this strategy makes it possible to use trajectories that are significantly shorter than the slowest relaxation time to efficiently build a reliable and accurate Markov model. Extensions of the method to multiple pathways, as well as some common pitfalls arising from poorly relaxed paths or an inappropriate choice of collective variables, are illustrated and discussed.

Mesh:

Year:  2008        PMID: 18715051      PMCID: PMC2674374          DOI: 10.1063/1.2959573

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  20 in total

1.  Transition path sampling: throwing ropes over rough mountain passes, in the dark.

Authors:  Peter G Bolhuis; David Chandler; Christoph Dellago; Phillip L Geissler
Journal:  Annu Rev Phys Chem       Date:  2001-10-04       Impact factor: 12.703

2.  Computing time scales from reaction coordinates by milestoning.

Authors:  Anton K Faradjian; Ron Elber
Journal:  J Chem Phys       Date:  2004-06-15       Impact factor: 3.488

3.  Foldamer dynamics expressed via Markov state models. II. State space decomposition.

Authors:  Sidney P Elmer; Sanghyun Park; Vijay S Pande
Journal:  J Chem Phys       Date:  2005-09-15       Impact factor: 3.488

4.  Error analysis and efficient sampling in Markovian state models for molecular dynamics.

Authors:  Nina Singhal; Vijay S Pande
Journal:  J Chem Phys       Date:  2005-11-22       Impact factor: 3.488

5.  String method in collective variables: minimum free energy paths and isocommittor surfaces.

Authors:  Luca Maragliano; Alexander Fischer; Eric Vanden-Eijnden; Giovanni Ciccotti
Journal:  J Chem Phys       Date:  2006-07-14       Impact factor: 3.488

6.  Finite temperature string method for the study of rare events.

Authors:  Weinan E; Weiqing Ren; Eric Vanden-Eijnden
Journal:  J Phys Chem B       Date:  2005-04-14       Impact factor: 2.991

7.  Finding transition pathways using the string method with swarms of trajectories.

Authors:  Albert C Pan; Deniz Sezer; Benoît Roux
Journal:  J Phys Chem B       Date:  2008-02-22       Impact factor: 2.991

8.  Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics.

Authors:  John D Chodera; Nina Singhal; Vijay S Pande; Ken A Dill; William C Swope
Journal:  J Chem Phys       Date:  2007-04-21       Impact factor: 3.488

9.  Parametrization, molecular dynamics simulation, and calculation of electron spin resonance spectra of a nitroxide spin label on a polyalanine alpha-helix.

Authors:  Deniz Sezer; Jack H Freed; Benoît Roux
Journal:  J Phys Chem B       Date:  2008-04-16       Impact factor: 2.991

10.  Control of membrane fusion mechanism by lipid composition: predictions from ensemble molecular dynamics.

Authors:  Peter M Kasson; Vijay S Pande
Journal:  PLoS Comput Biol       Date:  2007-09-26       Impact factor: 4.475

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  33 in total

Review 1.  Taming the complexity of protein folding.

Authors:  Gregory R Bowman; Vincent A Voelz; Vijay S Pande
Journal:  Curr Opin Struct Biol       Date:  2011-02       Impact factor: 6.809

2.  Mapping L1 ligase ribozyme conformational switch.

Authors:  George M Giambaşu; Tai-Sung Lee; William G Scott; Darrin M York
Journal:  J Mol Biol       Date:  2012-07-03       Impact factor: 5.469

Review 3.  Biomolecularmodeling and simulation: a field coming of age.

Authors:  Tamar Schlick; Rosana Collepardo-Guevara; Leif Arthur Halvorsen; Segun Jung; Xia Xiao
Journal:  Q Rev Biophys       Date:  2011-05       Impact factor: 5.318

4.  A network of molecular switches controls the activation of the two-component response regulator NtrC.

Authors:  Dan K Vanatta; Diwakar Shukla; Morgan Lawrenz; Vijay S Pande
Journal:  Nat Commun       Date:  2015-06-15       Impact factor: 14.919

5.  Simulating rare events using a weighted ensemble-based string method.

Authors:  Joshua L Adelman; Michael Grabe
Journal:  J Chem Phys       Date:  2013-01-28       Impact factor: 3.488

6.  Perspective: Markov models for long-timescale biomolecular dynamics.

Authors:  C R Schwantes; R T McGibbon; V S Pande
Journal:  J Chem Phys       Date:  2014-09-07       Impact factor: 3.488

7.  Transition path theory analysis of c-Src kinase activation.

Authors:  Yilin Meng; Diwakar Shukla; Vijay S Pande; Benoît Roux
Journal:  Proc Natl Acad Sci U S A       Date:  2016-08-01       Impact factor: 11.205

Review 8.  Generative models of conformational dynamics.

Authors:  Christopher James Langmead
Journal:  Adv Exp Med Biol       Date:  2014       Impact factor: 2.622

9.  Free energy and kinetics of conformational transitions from Voronoi tessellated milestoning with restraining potentials.

Authors:  Luca Maragliano; Eric Vanden-Eijnden; Benoît Roux
Journal:  J Chem Theory Comput       Date:  2009-08-31       Impact factor: 6.006

Review 10.  Everything you wanted to know about Markov State Models but were afraid to ask.

Authors:  Vijay S Pande; Kyle Beauchamp; Gregory R Bowman
Journal:  Methods       Date:  2010-06-04       Impact factor: 3.608

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