ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs

Autores
Encinar, J. A.; Fernández Ballester, G.; Sánchez Miguel, Ignacio Enrique; Hurtado Gómez, E.; Stricher, F.; Beltrao, P.; Serrano, L.
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Motivation: Most of the structures and functions of proteome globular domains are yet unknown. We can use high-resolution structures from different modular domains in combination with automatic protein design algorithms to predict genome-wide potential interactions of a protein. ADAN database and related web tools are online resources for the predictive analysis of ligand–domain complexes. ADAN database is a collection of different modular protein domains (SH2, SH3, PDZ, WW, etc.). It contains 3505 entries with extensive structural and functional information available, manually integrated, curated and annotated with cross-references to other databases, biochemical and thermodynamical data, simplified coordinate files, sequence files and alignments. Prediadan, a subset of ADAN database, offers position-specific scoring matrices for protein–protein interactions, calculated by FoldX, and predictions of optimum ligands and putative binding partners. Users can also scan a query sequence against selected matrices, or improve a ligand–domain interaction.
Fil: Encinar, J. A.. Universidad de Miguel Hernández; España
Fil: Fernández Ballester, G.. Universidad de Miguel Hernández; España
Fil: Sánchez Miguel, Ignacio Enrique. Fundación Instituto Leloir; Argentina. 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
Fil: Hurtado Gómez, E.. Universidad de Miguel Hernández; España
Fil: Stricher, F.. Universitat Pompeu Fabra; España
Fil: Beltrao, P.. University of California; Estados Unidos
Fil: Serrano, L.. Universitat Pompeu Fabra; España
Materia
Protein-Protein Interaction
Modular Domains
Linear Motifs
Database
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:11336/20664
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifsEncinar, J. A.Fernández Ballester, G.Sánchez Miguel, Ignacio EnriqueHurtado Gómez, E.Stricher, F.Beltrao, P.Serrano, L.Protein-Protein InteractionModular DomainsLinear MotifsDatabasehttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Motivation: Most of the structures and functions of proteome globular domains are yet unknown. We can use high-resolution structures from different modular domains in combination with automatic protein design algorithms to predict genome-wide potential interactions of a protein. ADAN database and related web tools are online resources for the predictive analysis of ligand–domain complexes. ADAN database is a collection of different modular protein domains (SH2, SH3, PDZ, WW, etc.). It contains 3505 entries with extensive structural and functional information available, manually integrated, curated and annotated with cross-references to other databases, biochemical and thermodynamical data, simplified coordinate files, sequence files and alignments. Prediadan, a subset of ADAN database, offers position-specific scoring matrices for protein–protein interactions, calculated by FoldX, and predictions of optimum ligands and putative binding partners. Users can also scan a query sequence against selected matrices, or improve a ligand–domain interaction.Fil: Encinar, J. A.. Universidad de Miguel Hernández; EspañaFil: Fernández Ballester, G.. Universidad de Miguel Hernández; EspañaFil: Sánchez Miguel, Ignacio Enrique. Fundación Instituto Leloir; Argentina. 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; ArgentinaFil: Hurtado Gómez, E.. Universidad de Miguel Hernández; EspañaFil: Stricher, F.. Universitat Pompeu Fabra; EspañaFil: Beltrao, P.. University of California; Estados UnidosFil: Serrano, L.. Universitat Pompeu Fabra; EspañaOxford University Press2009-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/20664Encinar, J. A.; Fernández Ballester, G.; Sánchez Miguel, Ignacio Enrique; Hurtado Gómez, E.; Stricher, F.; et al.; ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs; Oxford University Press; Bioinformatics (oxford, England); 25; 18; 9-2009; 2418-24241367-48031367-4811CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1093/bioinformatics/btp424info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp424info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:03:58Zoai:ri.conicet.gov.ar:11336/20664instacron: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 10:03:59.141CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs
title ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs
spellingShingle ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs
Encinar, J. A.
Protein-Protein Interaction
Modular Domains
Linear Motifs
Database
title_short ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs
title_full ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs
title_fullStr ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs
title_full_unstemmed ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs
title_sort ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs
dc.creator.none.fl_str_mv Encinar, J. A.
Fernández Ballester, G.
Sánchez Miguel, Ignacio Enrique
Hurtado Gómez, E.
Stricher, F.
Beltrao, P.
Serrano, L.
author Encinar, J. A.
author_facet Encinar, J. A.
Fernández Ballester, G.
Sánchez Miguel, Ignacio Enrique
Hurtado Gómez, E.
Stricher, F.
Beltrao, P.
Serrano, L.
author_role author
author2 Fernández Ballester, G.
Sánchez Miguel, Ignacio Enrique
Hurtado Gómez, E.
Stricher, F.
Beltrao, P.
Serrano, L.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Protein-Protein Interaction
Modular Domains
Linear Motifs
Database
topic Protein-Protein Interaction
Modular Domains
Linear Motifs
Database
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Motivation: Most of the structures and functions of proteome globular domains are yet unknown. We can use high-resolution structures from different modular domains in combination with automatic protein design algorithms to predict genome-wide potential interactions of a protein. ADAN database and related web tools are online resources for the predictive analysis of ligand–domain complexes. ADAN database is a collection of different modular protein domains (SH2, SH3, PDZ, WW, etc.). It contains 3505 entries with extensive structural and functional information available, manually integrated, curated and annotated with cross-references to other databases, biochemical and thermodynamical data, simplified coordinate files, sequence files and alignments. Prediadan, a subset of ADAN database, offers position-specific scoring matrices for protein–protein interactions, calculated by FoldX, and predictions of optimum ligands and putative binding partners. Users can also scan a query sequence against selected matrices, or improve a ligand–domain interaction.
Fil: Encinar, J. A.. Universidad de Miguel Hernández; España
Fil: Fernández Ballester, G.. Universidad de Miguel Hernández; España
Fil: Sánchez Miguel, Ignacio Enrique. Fundación Instituto Leloir; Argentina. 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
Fil: Hurtado Gómez, E.. Universidad de Miguel Hernández; España
Fil: Stricher, F.. Universitat Pompeu Fabra; España
Fil: Beltrao, P.. University of California; Estados Unidos
Fil: Serrano, L.. Universitat Pompeu Fabra; España
description Motivation: Most of the structures and functions of proteome globular domains are yet unknown. We can use high-resolution structures from different modular domains in combination with automatic protein design algorithms to predict genome-wide potential interactions of a protein. ADAN database and related web tools are online resources for the predictive analysis of ligand–domain complexes. ADAN database is a collection of different modular protein domains (SH2, SH3, PDZ, WW, etc.). It contains 3505 entries with extensive structural and functional information available, manually integrated, curated and annotated with cross-references to other databases, biochemical and thermodynamical data, simplified coordinate files, sequence files and alignments. Prediadan, a subset of ADAN database, offers position-specific scoring matrices for protein–protein interactions, calculated by FoldX, and predictions of optimum ligands and putative binding partners. Users can also scan a query sequence against selected matrices, or improve a ligand–domain interaction.
publishDate 2009
dc.date.none.fl_str_mv 2009-09
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/11336/20664
Encinar, J. A.; Fernández Ballester, G.; Sánchez Miguel, Ignacio Enrique; Hurtado Gómez, E.; Stricher, F.; et al.; ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs; Oxford University Press; Bioinformatics (oxford, England); 25; 18; 9-2009; 2418-2424
1367-4803
1367-4811
CONICET Digital
CONICET
url http://hdl.handle.net/11336/20664
identifier_str_mv Encinar, J. A.; Fernández Ballester, G.; Sánchez Miguel, Ignacio Enrique; Hurtado Gómez, E.; Stricher, F.; et al.; ADAN: a database for prediction of protein–protein interaction of modular domains mediated by linear motifs; Oxford University Press; Bioinformatics (oxford, England); 25; 18; 9-2009; 2418-2424
1367-4803
1367-4811
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1093/bioinformatics/btp424
info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp424
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 Oxford University Press
publisher.none.fl_str_mv Oxford University Press
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
_version_ 1844613862019563520
score 13.070432

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