Variational Approach to Molecular Kinetics

被引:223
作者
Nueske, Feliks [1 ]
Keller, Bettina G. [1 ]
Perez-Hernandez, Guillermo [1 ]
Mey, Antonia S. J. S. [1 ]
Noe, Frank [1 ]
机构
[1] Free Univ Berlin, Dept Math & Comp Sci, D-14195 Berlin, Germany
关键词
CONFORMATIONAL DYNAMICS; TRANSITION NETWORKS; HIDDEN COMPLEXITY; MARKOV-MODELS; STATE MODELS; FINGERPRINTS; SIMULATIONS; PATHWAYS; ENSEMBLE; REVEAL;
D O I
10.1021/ct4009156
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The eigenvalues and eigenvectors of the molecular dynamics propagator (or transfer operator) contain the essential information about the molecular thermodynamics and kinetics. This includes the stationary distribution, the metastable states, and state-to-state transition rates. Here, we present a variational approach for computing these dominant eigenvalues and eigenvectors. This approach is analogous to the variational approach used for computing stationary states in quantum mechanics. A corresponding method of linear variation is formulated. It is shown that the matrices needed for the linear variation method are correlation matrices that can be estimated from simple MD simulations for a given basis set. The method proposed here is thus to first define a basis set able to capture the relevant conformational transitions, then compute the respective correlation matrices, and then to compute their dominant eigenvalues and eigenvectors, thus obtaining the key ingredients of the slow. kinetics.
引用
收藏
页码:1739 / 1752
页数:14
相关论文
共 72 条
  • [1] Dihedral angle principal component analysis of molecular dynamics simulations
    Altis, Alexandros
    Nguyen, Phuong H.
    Hegger, Rainer
    Stock, Gerhard
    [J]. JOURNAL OF CHEMICAL PHYSICS, 2007, 126 (24)
  • [2] [Anonymous], 2004, Molecular Biology of the Cell
  • [3] MSMBuilder2: Modeling Conformational Dynamics on the Picosecond to Millisecond Scale
    Beauchamp, Kyle A.
    Bowman, Gregory R.
    Lane, Thomas J.
    Maibaum, Lutz
    Haque, Imran S.
    Pande, Vijay S.
    [J]. JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2011, 7 (10) : 3412 - 3419
  • [4] Simple few-state models reveal hidden complexity in protein folding
    Beauchamp, Kyle A.
    McGibbon, Robert
    Lin, Yu-Shan
    Pande, Vijay S.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2012, 109 (44) : 17807 - 17813
  • [5] Protein folded states are kinetic hubs
    Bowman, Gregory R.
    Pande, Vijay S.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2010, 107 (24) : 10890 - 10895
  • [6] Progress and challenges in the automated construction of Markov state models for full protein systems
    Bowman, Gregory R.
    Beauchamp, Kyle A.
    Boxer, George
    Pande, Vijay S.
    [J]. JOURNAL OF CHEMICAL PHYSICS, 2009, 131 (12)
  • [7] Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations
    Buch, Ignasi
    Giorgino, Toni
    De Fabritiis, Gianni
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2011, 108 (25) : 10184 - 10189
  • [8] Coarse master equations for peptide folding dynamics
    Buchete, Nicolae-Viorel
    Hummer, Gerhard
    [J]. JOURNAL OF PHYSICAL CHEMISTRY B, 2008, 112 (19) : 6057 - 6069
  • [9] Canonical sampling through velocity rescaling
    Bussi, Giovanni
    Donadio, Davide
    Parrinello, Michele
    [J]. JOURNAL OF CHEMICAL PHYSICS, 2007, 126 (01)
  • [10] Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics
    Chodera, John D.
    Singhal, Nina
    Pande, Vijay S.
    Dill, Ken A.
    Swope, William C.
    [J]. JOURNAL OF CHEMICAL PHYSICS, 2007, 126 (15)