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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/38361
Ver los metadatos del registro completo
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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 |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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13.13397 |