Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features

Autores
Aguilar, Daniel; Oliva, Baldo; Marino, Cristina Ester
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Amino acids committed to a particular function correlate tightly along evolution and tend to form clusters in the 3D structure of the protein. Consequently, a protein can be seen as a network of co-evolving clusters of residues. The goal of this work is two-fold: first, we have combined mutual information and structural data to describe the amino acid networks within a protein and their interactions. Second, we have investigated how this information can be used to improve methods of prediction of functional residues by reducing the search space. As a main result, we found that clusters of co-evolving residues related to the catalytic site of an enzyme have distinguishable topological properties in the network. We also observed that these clusters usually evolve independently, which could be related to a fail-safe mechanism. Finally, we discovered a significant enrichment of functional residues (e.g. metal binding, susceptibility to detrimental mutations) in the clusters, which could be the foundation of new prediction tools.
Fil: Aguilar, Daniel. Universitat Pompeu Fabra; España
Fil: Oliva, Baldo. Universitat Pompeu Fabra; España
Fil: Marino, Cristina Ester. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina
Materia
Coevolution
Mutual Information
coevolution network
Functional prediction
Enzimatic protein
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:11336/97301

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network_name_str CONICET Digital (CONICET)
spelling Mapping the mutual information network of enzymatic families in the protein structure to unveil functional featuresAguilar, DanielOliva, BaldoMarino, Cristina EsterCoevolutionMutual Informationcoevolution networkFunctional predictionEnzimatic proteinhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Amino acids committed to a particular function correlate tightly along evolution and tend to form clusters in the 3D structure of the protein. Consequently, a protein can be seen as a network of co-evolving clusters of residues. The goal of this work is two-fold: first, we have combined mutual information and structural data to describe the amino acid networks within a protein and their interactions. Second, we have investigated how this information can be used to improve methods of prediction of functional residues by reducing the search space. As a main result, we found that clusters of co-evolving residues related to the catalytic site of an enzyme have distinguishable topological properties in the network. We also observed that these clusters usually evolve independently, which could be related to a fail-safe mechanism. Finally, we discovered a significant enrichment of functional residues (e.g. metal binding, susceptibility to detrimental mutations) in the clusters, which could be the foundation of new prediction tools.Fil: Aguilar, Daniel. Universitat Pompeu Fabra; EspañaFil: Oliva, Baldo. Universitat Pompeu Fabra; EspañaFil: Marino, Cristina Ester. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaPublic Library of Science2012-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/97301Aguilar, Daniel; Oliva, Baldo; Marino, Cristina Ester; Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features; Public Library of Science; Plos One; 7; 7; 7-2012; 1-12; e414301932-6203CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0041430info:eu-repo/semantics/altIdentifier/url/https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0041430info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:18:44Zoai:ri.conicet.gov.ar:11336/97301instacron: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:34982025-09-29 10:18:45.267CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features
title Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features
spellingShingle Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features
Aguilar, Daniel
Coevolution
Mutual Information
coevolution network
Functional prediction
Enzimatic protein
title_short Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features
title_full Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features
title_fullStr Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features
title_full_unstemmed Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features
title_sort Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features
dc.creator.none.fl_str_mv Aguilar, Daniel
Oliva, Baldo
Marino, Cristina Ester
author Aguilar, Daniel
author_facet Aguilar, Daniel
Oliva, Baldo
Marino, Cristina Ester
author_role author
author2 Oliva, Baldo
Marino, Cristina Ester
author2_role author
author
dc.subject.none.fl_str_mv Coevolution
Mutual Information
coevolution network
Functional prediction
Enzimatic protein
topic Coevolution
Mutual Information
coevolution network
Functional prediction
Enzimatic protein
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Amino acids committed to a particular function correlate tightly along evolution and tend to form clusters in the 3D structure of the protein. Consequently, a protein can be seen as a network of co-evolving clusters of residues. The goal of this work is two-fold: first, we have combined mutual information and structural data to describe the amino acid networks within a protein and their interactions. Second, we have investigated how this information can be used to improve methods of prediction of functional residues by reducing the search space. As a main result, we found that clusters of co-evolving residues related to the catalytic site of an enzyme have distinguishable topological properties in the network. We also observed that these clusters usually evolve independently, which could be related to a fail-safe mechanism. Finally, we discovered a significant enrichment of functional residues (e.g. metal binding, susceptibility to detrimental mutations) in the clusters, which could be the foundation of new prediction tools.
Fil: Aguilar, Daniel. Universitat Pompeu Fabra; España
Fil: Oliva, Baldo. Universitat Pompeu Fabra; España
Fil: Marino, Cristina Ester. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina
description Amino acids committed to a particular function correlate tightly along evolution and tend to form clusters in the 3D structure of the protein. Consequently, a protein can be seen as a network of co-evolving clusters of residues. The goal of this work is two-fold: first, we have combined mutual information and structural data to describe the amino acid networks within a protein and their interactions. Second, we have investigated how this information can be used to improve methods of prediction of functional residues by reducing the search space. As a main result, we found that clusters of co-evolving residues related to the catalytic site of an enzyme have distinguishable topological properties in the network. We also observed that these clusters usually evolve independently, which could be related to a fail-safe mechanism. Finally, we discovered a significant enrichment of functional residues (e.g. metal binding, susceptibility to detrimental mutations) in the clusters, which could be the foundation of new prediction tools.
publishDate 2012
dc.date.none.fl_str_mv 2012-07
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/11336/97301
Aguilar, Daniel; Oliva, Baldo; Marino, Cristina Ester; Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features; Public Library of Science; Plos One; 7; 7; 7-2012; 1-12; e41430
1932-6203
CONICET Digital
CONICET
url http://hdl.handle.net/11336/97301
identifier_str_mv Aguilar, Daniel; Oliva, Baldo; Marino, Cristina Ester; Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features; Public Library of Science; Plos One; 7; 7; 7-2012; 1-12; e41430
1932-6203
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0041430
info:eu-repo/semantics/altIdentifier/url/https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0041430
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 Public Library of Science
publisher.none.fl_str_mv Public Library of Science
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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