New insights into the meaning and usefulness of principal component analysis of concatenated trajectories

Autores
Pierdominici Sottile, Gustavo; Palma, Juliana Isabel
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A comparison between different conformations of a given protein, relating both structure and dynamics, can be performed in terms of combined principal component analysis (combined-PCA). To that end, a trajectory is obtained by concatenating molecular dynamics trajectories of the individual conformations under comparison. Then, the principal components are calculated by diagonalizing the correlation matrix of the concatenated trajectory. Since the introduction of this approach in 1995 it has had a large number of applications. However, the interpretation of the eigenvectors and eigenvalues so obtained is based on intuitive foundations, because analytical expressions relating the concatenated correlation matrix with those of the individual trajectories under consideration have not been provided yet. In this article, we present such expressions for the cases of two, three, and an arbitrary number of concatenated trajectories. The formulas are simple and show what is to be expected and what is not to be expected from a combined-PCA. Their correctness and usefulness is demonstrated by discussing some representative examples. The results can be summarized in a simple sentence: the correlation matrix of a concatenated trajectory is given by the average of the individual correlation matrices plus the correlation matrix of the individual averages. From this it follows that the combined-PCA of trajectories belonging to different free energy basins provides information that could also be obtained by alternative and more straightforward means.
Fil: Pierdominici Sottile, Gustavo. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Palma, Juliana Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
Materia
Concatenated Trajectories
Conformational Changes
Essential Dynamics
Principal Component Analysis
Protein Dynamics
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/38361

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spelling New insights into the meaning and usefulness of principal component analysis of concatenated trajectoriesPierdominici Sottile, GustavoPalma, Juliana IsabelConcatenated TrajectoriesConformational ChangesEssential DynamicsPrincipal Component AnalysisProtein Dynamicshttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1A comparison between different conformations of a given protein, relating both structure and dynamics, can be performed in terms of combined principal component analysis (combined-PCA). To that end, a trajectory is obtained by concatenating molecular dynamics trajectories of the individual conformations under comparison. Then, the principal components are calculated by diagonalizing the correlation matrix of the concatenated trajectory. Since the introduction of this approach in 1995 it has had a large number of applications. However, the interpretation of the eigenvectors and eigenvalues so obtained is based on intuitive foundations, because analytical expressions relating the concatenated correlation matrix with those of the individual trajectories under consideration have not been provided yet. In this article, we present such expressions for the cases of two, three, and an arbitrary number of concatenated trajectories. The formulas are simple and show what is to be expected and what is not to be expected from a combined-PCA. Their correctness and usefulness is demonstrated by discussing some representative examples. The results can be summarized in a simple sentence: the correlation matrix of a concatenated trajectory is given by the average of the individual correlation matrices plus the correlation matrix of the individual averages. From this it follows that the combined-PCA of trajectories belonging to different free energy basins provides information that could also be obtained by alternative and more straightforward means.Fil: Pierdominici Sottile, Gustavo. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Palma, Juliana Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaJohn Wiley & Sons Inc2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/38361Pierdominici Sottile, Gustavo; Palma, Juliana Isabel; New insights into the meaning and usefulness of principal component analysis of concatenated trajectories; John Wiley & Sons Inc; Journal Of Computational Chemistry; 36; 7; 3-2015; 424-4320192-8651CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1002/jcc.23811/abstractinfo:eu-repo/semantics/altIdentifier/doi/10.1002/jcc.23811info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:49:59Zoai:ri.conicet.gov.ar:11336/38361instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:50:00.112CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv New insights into the meaning and usefulness of principal component analysis of concatenated trajectories
title New insights into the meaning and usefulness of principal component analysis of concatenated trajectories
spellingShingle New insights into the meaning and usefulness of principal component analysis of concatenated trajectories
Pierdominici Sottile, Gustavo
Concatenated Trajectories
Conformational Changes
Essential Dynamics
Principal Component Analysis
Protein Dynamics
title_short New insights into the meaning and usefulness of principal component analysis of concatenated trajectories
title_full New insights into the meaning and usefulness of principal component analysis of concatenated trajectories
title_fullStr New insights into the meaning and usefulness of principal component analysis of concatenated trajectories
title_full_unstemmed New insights into the meaning and usefulness of principal component analysis of concatenated trajectories
title_sort New insights into the meaning and usefulness of principal component analysis of concatenated trajectories
dc.creator.none.fl_str_mv Pierdominici Sottile, Gustavo
Palma, Juliana Isabel
author Pierdominici Sottile, Gustavo
author_facet Pierdominici Sottile, Gustavo
Palma, Juliana Isabel
author_role author
author2 Palma, Juliana Isabel
author2_role author
dc.subject.none.fl_str_mv Concatenated Trajectories
Conformational Changes
Essential Dynamics
Principal Component Analysis
Protein Dynamics
topic Concatenated Trajectories
Conformational Changes
Essential Dynamics
Principal Component Analysis
Protein Dynamics
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A comparison between different conformations of a given protein, relating both structure and dynamics, can be performed in terms of combined principal component analysis (combined-PCA). To that end, a trajectory is obtained by concatenating molecular dynamics trajectories of the individual conformations under comparison. Then, the principal components are calculated by diagonalizing the correlation matrix of the concatenated trajectory. Since the introduction of this approach in 1995 it has had a large number of applications. However, the interpretation of the eigenvectors and eigenvalues so obtained is based on intuitive foundations, because analytical expressions relating the concatenated correlation matrix with those of the individual trajectories under consideration have not been provided yet. In this article, we present such expressions for the cases of two, three, and an arbitrary number of concatenated trajectories. The formulas are simple and show what is to be expected and what is not to be expected from a combined-PCA. Their correctness and usefulness is demonstrated by discussing some representative examples. The results can be summarized in a simple sentence: the correlation matrix of a concatenated trajectory is given by the average of the individual correlation matrices plus the correlation matrix of the individual averages. From this it follows that the combined-PCA of trajectories belonging to different free energy basins provides information that could also be obtained by alternative and more straightforward means.
Fil: Pierdominici Sottile, Gustavo. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Palma, Juliana Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
description A comparison between different conformations of a given protein, relating both structure and dynamics, can be performed in terms of combined principal component analysis (combined-PCA). To that end, a trajectory is obtained by concatenating molecular dynamics trajectories of the individual conformations under comparison. Then, the principal components are calculated by diagonalizing the correlation matrix of the concatenated trajectory. Since the introduction of this approach in 1995 it has had a large number of applications. However, the interpretation of the eigenvectors and eigenvalues so obtained is based on intuitive foundations, because analytical expressions relating the concatenated correlation matrix with those of the individual trajectories under consideration have not been provided yet. In this article, we present such expressions for the cases of two, three, and an arbitrary number of concatenated trajectories. The formulas are simple and show what is to be expected and what is not to be expected from a combined-PCA. Their correctness and usefulness is demonstrated by discussing some representative examples. The results can be summarized in a simple sentence: the correlation matrix of a concatenated trajectory is given by the average of the individual correlation matrices plus the correlation matrix of the individual averages. From this it follows that the combined-PCA of trajectories belonging to different free energy basins provides information that could also be obtained by alternative and more straightforward means.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/38361
Pierdominici Sottile, Gustavo; Palma, Juliana Isabel; New insights into the meaning and usefulness of principal component analysis of concatenated trajectories; John Wiley & Sons Inc; Journal Of Computational Chemistry; 36; 7; 3-2015; 424-432
0192-8651
CONICET Digital
CONICET
url http://hdl.handle.net/11336/38361
identifier_str_mv Pierdominici Sottile, Gustavo; Palma, Juliana Isabel; New insights into the meaning and usefulness of principal component analysis of concatenated trajectories; John Wiley & Sons Inc; Journal Of Computational Chemistry; 36; 7; 3-2015; 424-432
0192-8651
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1002/jcc.23811/abstract
info:eu-repo/semantics/altIdentifier/doi/10.1002/jcc.23811
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons Inc
publisher.none.fl_str_mv John Wiley & Sons Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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