Hierarchical analysis of conformational dynamics in biomolecules: Transition networks of metastable states
Abstract
Molecular dynamics simulation generates large quantities of data that must be interpreted using physically meaningful analysis. A common approach is to describe the system dynamics in terms of transitions between coarse partitions of conformational space. In contrast to previous work that partitions the space according to geometric proximity, the authors examine here clustering based on kinetics, merging configurational microstates together so as to identify longlived, i.e., dynamically metastable, states. As test systems microsecond molecular dynamics simulations of the polyalanines Ala{sub 8} and Ala{sub 12} are analyzed. Both systems clearly exhibit metastability, with some kinetically distinct metastable states being geometrically very similar. Using the backbone torsion rotamer pattern to define the microstates, a definition is obtained of metastable states whose lifetimes considerably exceed the memory associated with interstate dynamics, thus allowing the kinetics to be described by a Markov model. This model is shown to be valid by comparison of its predictions with the kinetics obtained directly from the molecular dynamics simulations. In contrast, clustering based on the hydrogenbonding pattern fails to identify longlived metastable states or a reliable Markov model. Finally, an approach is proposed to generate a hierarchical model of networks, each having a different number of metastable states.more »
 Authors:
 University of Heidelberg
 Freie Universitat Berlin
 ORNL
 Publication Date:
 Research Org.:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 Sponsoring Org.:
 USDOE Laboratory Directed Research and Development (LDRD) Program
 OSTI Identifier:
 932198
 DOE Contract Number:
 DEAC0500OR22725
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Journal of Chemical Physics; Journal Volume: 126; Journal Issue: 15
 Country of Publication:
 United States
 Language:
 English
 Subject:
 59 BASIC BIOLOGICAL SCIENCES; MOLECULAR DYNAMICS METHOD; ALANINES; ORGANIC POLYMERS; KINETICS; METASTABLE STATES; MATHEMATICAL MODELS; BIOLOGICAL MATERIALS
Citation Formats
Noe, F, Horenko, Illia, Schuette, C., and Smith, Jeremy C. Hierarchical analysis of conformational dynamics in biomolecules: Transition networks of metastable states. United States: N. p., 2007.
Web. doi:10.1063/1.2714539.
Noe, F, Horenko, Illia, Schuette, C., & Smith, Jeremy C. Hierarchical analysis of conformational dynamics in biomolecules: Transition networks of metastable states. United States. doi:10.1063/1.2714539.
Noe, F, Horenko, Illia, Schuette, C., and Smith, Jeremy C. Sun .
"Hierarchical analysis of conformational dynamics in biomolecules: Transition networks of metastable states". United States.
doi:10.1063/1.2714539.
@article{osti_932198,
title = {Hierarchical analysis of conformational dynamics in biomolecules: Transition networks of metastable states},
author = {Noe, F and Horenko, Illia and Schuette, C. and Smith, Jeremy C},
abstractNote = {Molecular dynamics simulation generates large quantities of data that must be interpreted using physically meaningful analysis. A common approach is to describe the system dynamics in terms of transitions between coarse partitions of conformational space. In contrast to previous work that partitions the space according to geometric proximity, the authors examine here clustering based on kinetics, merging configurational microstates together so as to identify longlived, i.e., dynamically metastable, states. As test systems microsecond molecular dynamics simulations of the polyalanines Ala{sub 8} and Ala{sub 12} are analyzed. Both systems clearly exhibit metastability, with some kinetically distinct metastable states being geometrically very similar. Using the backbone torsion rotamer pattern to define the microstates, a definition is obtained of metastable states whose lifetimes considerably exceed the memory associated with interstate dynamics, thus allowing the kinetics to be described by a Markov model. This model is shown to be valid by comparison of its predictions with the kinetics obtained directly from the molecular dynamics simulations. In contrast, clustering based on the hydrogenbonding pattern fails to identify longlived metastable states or a reliable Markov model. Finally, an approach is proposed to generate a hierarchical model of networks, each having a different number of metastable states. The model hierarchy yields a qualitative understanding of the multiple time and length scales in the dynamics of biomolecules.},
doi = {10.1063/1.2714539},
journal = {Journal of Chemical Physics},
number = 15,
volume = 126,
place = {United States},
year = {Sun Apr 01 00:00:00 EDT 2007},
month = {Sun Apr 01 00:00:00 EDT 2007}
}

Molecular dynamics simulation generates large quantities of data that must be interpreted using physically meaningful analysis. A common approach is to describe the system dynamics in terms of transitions between coarse partitions of conformational space. In contrast to previous work that partitions the space according to geometric proximity, the authors examine here clustering based on kinetics, merging configurational microstates together so as to identify longlived, i.e., dynamically metastable, states. As test systems microsecond molecular dynamics simulations of the polyalanines Ala{sub 8} and Ala{sub 12} are analyzed. Both systems clearly exhibit metastability, with some kinetically distinct metastable states being geometrically verymore »

Couplings between hierarchical conformational dynamics from multitime correlation functions and twodimensional lifetime spectra: Application to adenylate kinase
An analytical method based on a threetime correlation function and the corresponding twodimensional (2D) lifetime spectrum is developed to elucidate the timedependent couplings between the multitimescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waitingtime dependence of the offdiagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substratefree adenylate kinase (AKE) using longtime coarsegrained molecular dynamics simulations. It is found that the hierarchicalmore » 
Transition Networks for the Comprehensive Characterization of Complex Conformational Change in proteins
Functionally relevant transitions between native conformations of a protein can be complex, involving, for example, the reorganization of parts of the backbone fold, and may occur via a multitude of pathways. Such transitions can be characterized by a transition network (TN), in which the experimentally determined end state structures are connected by a dense network of subtransitions via lowenergy intermediates. We show here how the computation of a TN can be achieved for a complex protein transition. First, an efficient hierarchical procedure is used to uniformly sample the conformational subspace relevant to the transition. Then, the best path which connectsmore »