Identification of biomolecular conformations from incomplete torsion angle observations by hidden Markov models
We present a novel method for the identification of the most important conformations of a biomolecular system from molecular dynamics or Metropolis Monte Carlo time series by means of Hidden Markov Models (HMMs). We show that identification is possible based on the observation sequences of some esse...
| Publié dans: | Journal of computational chemistry. - 1984. - 28(2007), 15 vom: 30. Nov., Seite 2453-64 |
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| Auteur principal: | |
| Autres auteurs: | , , , |
| Format: | Article |
| Langue: | English |
| Publié: |
2007
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| Accès à la collection: | Journal of computational chemistry |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't Peptides DNA 9007-49-2 Alanine OF5P57N2ZX |
| Résumé: | We present a novel method for the identification of the most important conformations of a biomolecular system from molecular dynamics or Metropolis Monte Carlo time series by means of Hidden Markov Models (HMMs). We show that identification is possible based on the observation sequences of some essential torsion or backbone angles. In particular, the method still provides good results even if the conformations do have a strong overlap in these angles. To apply HMMs to angular data, we use von Mises output distributions. The performance of the resulting method is illustrated by numerical tests and by application to a hybrid Monte Carlo time series of trialanine and to MD simulation results of a DNA-oligomer |
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| Description: | Date Completed 16.05.2008 Date Revised 21.11.2013 published: Print Citation Status MEDLINE |
| ISSN: | 1096-987X |