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Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding
Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2855342/ https://www.ncbi.nlm.nih.gov/pubmed/20419160 http://dx.doi.org/10.1371/journal.pone.0009890 |
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author | Rajan, Aruna Freddolino, Peter L. Schulten, Klaus |
author_facet | Rajan, Aruna Freddolino, Peter L. Schulten, Klaus |
author_sort | Rajan, Aruna |
collection | PubMed |
description | Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories suffer from various setbacks, namely (i) they are not data driven, (ii) they are unstable to noise and changes in cut-off parameters such as cluster radius and cluster number, and (iii) they do not reduce the dimensionality of the trajectories, and hence are unsuitable for finding collective coordinates. We advocate the application of principal component analysis (PCA) and a non-metric multidimensional scaling (nMDS) method to reduce MD trajectories and overcome the drawbacks of clustering. To illustrate the superiority of nMDS over other methods in reducing data and reproducing salient features, we analyze three complete villin headpiece folding trajectories. Our analysis suggests that the folding process of the villin headpiece is structurally heterogeneous. |
format | Text |
id | pubmed-2855342 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28553422010-04-23 Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding Rajan, Aruna Freddolino, Peter L. Schulten, Klaus PLoS One Research Article Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories suffer from various setbacks, namely (i) they are not data driven, (ii) they are unstable to noise and changes in cut-off parameters such as cluster radius and cluster number, and (iii) they do not reduce the dimensionality of the trajectories, and hence are unsuitable for finding collective coordinates. We advocate the application of principal component analysis (PCA) and a non-metric multidimensional scaling (nMDS) method to reduce MD trajectories and overcome the drawbacks of clustering. To illustrate the superiority of nMDS over other methods in reducing data and reproducing salient features, we analyze three complete villin headpiece folding trajectories. Our analysis suggests that the folding process of the villin headpiece is structurally heterogeneous. Public Library of Science 2010-04-15 /pmc/articles/PMC2855342/ /pubmed/20419160 http://dx.doi.org/10.1371/journal.pone.0009890 Text en Rajan et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Rajan, Aruna Freddolino, Peter L. Schulten, Klaus Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding |
title | Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding |
title_full | Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding |
title_fullStr | Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding |
title_full_unstemmed | Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding |
title_short | Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding |
title_sort | going beyond clustering in md trajectory analysis: an application to villin headpiece folding |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2855342/ https://www.ncbi.nlm.nih.gov/pubmed/20419160 http://dx.doi.org/10.1371/journal.pone.0009890 |
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