Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

Christian H. Jensen, Dmitry Nerukh, Robert C. Glen

Research output: Contribution to journalArticle

Abstract

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500 ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100 ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.
Original languageEnglish
Article number115107
Number of pages7
JournalJournal of Chemical Physics
Volume128
Issue number11
DOIs
Publication statusPublished - 21 Mar 2008

Fingerprint

peptides
Molecular dynamics
Trajectories
trajectories
molecular dynamics
Clustering algorithms
Peptides
sensitivity
transition probabilities
Valine
Proline
Leucine
Alanine
leucine
alanine
Water
inclusions
water

Bibliographical note

Copyright (2008) American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.
The following article appeared in Jensen, CH, Nerukh, D & Glen, RC 2008, 'Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory', Journal of chemical physics , vol 128, no. 11 and may be found at http://jcp.aip.org/resource/1/jcpsa6/v128/i11/p115107_s1

Keywords

  • algorithms
  • computer simulation
  • Markov chains
  • mathematical computing
  • chemical models
  • molecular models
  • peptide fragments
  • protein conformation
  • protein folding

Cite this

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abstract = "We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500 ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46{\%}. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814{\%}. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100 ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.",
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Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory. / Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.

In: Journal of Chemical Physics, Vol. 128, No. 11, 115107, 21.03.2008.

Research output: Contribution to journalArticle

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