PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins

Autores
Ghafouri, Hamidreza; Lazar, Tamas; Del Conte, Alessio; Tenorio Ku, Luiggi G.; Aspromonte, Maria C.; Bernadó, Pau; Chaves Arquero, Belén; Chemes, Lucia Beatriz; Clementel, Damiano; Cordeiro, Tiago N.; Elena Real, Carlos A.; Feig, Michael; Felli, Isabella C.; Ferrari, Carlo; Forman Kay, Julie D.; Gomes, Tiago; Gondelaud, Frank; Gradinaru, Claudiu C.; Ha Duong, Tâp; Head Gordon, Teresa; Heidarsson, Pétur O.; Janson, Giacomo; Jeschke, Gunnar; Leonardi, Emanuela; Liu, Zi Hao; Longhi, Sonia; Lund, Xamuel L.; Macias, Maria J.; Martin Malpartida, Pau; Mercadante, Davide; Mouhand, Assia; Nagy, Gabor; Nugnes, María Victoria; Pérez Cañadillas, José Manuel; Pesce, Giulia; Pierattelli, Roberta; Piovesan, Damiano; Quaglia, Federica; Ricard Blum, Sylvie; Robustelli, Paul; Sagar, Amin; Salladini, Edoardo; Sénicourt, Lucile; Sibille, Nathalie; Teixeira, João M. C.; Tsangaris, Thomas E.; Varadi, Mihaly; Tompa, Peter; Tosatto, Silvio C. E.; Monzon, Alexander Miguel
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.
Fil: Ghafouri, Hamidreza. Università di Padova; Italia
Fil: Lazar, Tamas. Vrije Unviversiteit Brussel; Bélgica
Fil: Del Conte, Alessio. Università di Padova; Italia
Fil: Tenorio Ku, Luiggi G.. Università di Padova; Italia
Fil: Aspromonte, Maria C.. Università di Padova; Italia
Fil: Bernadó, Pau. Vrije Unviversiteit Brussel; Bélgica
Fil: Chaves Arquero, Belén. Università di Padova; Italia
Fil: Chemes, Lucia Beatriz. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; Argentina
Fil: Clementel, Damiano. Università di Padova; Italia
Fil: Cordeiro, Tiago N.. Universidade Nova de Lisboa; Portugal
Fil: Elena Real, Carlos A.. Inserm; Francia
Fil: Feig, Michael. Michigan State University; Estados Unidos
Fil: Felli, Isabella C.. University of Florence; Italia
Fil: Ferrari, Carlo. Università di Padova; Italia
Fil: Forman Kay, Julie D.. University of Toronto; Canadá
Fil: Gomes, Tiago. Universidade Nova de Lisboa; Portugal
Fil: Gondelaud, Frank. Centre National de la Recherche Scientifique; Francia
Fil: Gradinaru, Claudiu C.. University of Toronto; Canadá
Fil: Ha Duong, Tâp. Centre National de la Recherche Scientifique; Francia
Fil: Head Gordon, Teresa. University of California; Estados Unidos
Fil: Heidarsson, Pétur O.. Michigan State University; Estados Unidos
Fil: Janson, Giacomo. No especifíca;
Fil: Jeschke, Gunnar. Università di Padova; Italia
Fil: Leonardi, Emanuela. Università di Padova; Italia
Fil: Liu, Zi Hao. University of Toronto; Canadá
Fil: Longhi, Sonia. Centre National de la Recherche Scientifique; Francia
Fil: Lund, Xamuel L.. Centre National de la Recherche Scientifique; Francia
Fil: Macias, Maria J.. The Barcelona Institute of Science and Technology; España
Fil: Martin Malpartida, Pau. The Barcelona Institute of Science and Technology; España
Fil: Mercadante, Davide. University of Auckland; Nueva Zelanda
Fil: Mouhand, Assia. Centre National de la Recherche Scientifique; Francia
Fil: Nagy, Gabor. Max Planck Institute for Biophysical Chemistry; Alemania
Fil: Nugnes, María Victoria. Università di Padova; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Pérez Cañadillas, José Manuel. Consejo Superior de Investigaciones Científicas; España
Fil: Pesce, Giulia. Centre National de la Recherche Scientifique; Francia
Fil: Pierattelli, Roberta. University of Florence; Italia
Fil: Piovesan, Damiano. Università di Padova; Italia
Fil: Quaglia, Federica. Università di Padova; Italia
Fil: Ricard Blum, Sylvie. Université Claude Bernard Lyon 1; Francia
Fil: Robustelli, Paul. Dartmouth College; Estados Unidos
Fil: Sagar, Amin. Centre National de la Recherche Scientifique; Francia
Fil: Salladini, Edoardo. Università di Torino; Italia
Fil: Sénicourt, Lucile. Centre National de la Recherche Scientifique; Francia
Fil: Sibille, Nathalie. Centre National de la Recherche Scientifique; Francia
Fil: Teixeira, João M. C.. The Hospital for Sick Children; Canadá
Fil: Tsangaris, Thomas E.. University of Toronto; Canadá
Fil: Varadi, Mihaly. No especifíca;
Fil: Tompa, Peter. Vrije Universiteit Amsterdam; Países Bajos
Fil: Tosatto, Silvio C. E.. Università di Padova; Italia
Fil: Monzon, Alexander Miguel. Università di Padova; Italia
Materia
DISORDERED PROTEINS
PROTEIN ENSEMBLE
BIOINFORMATICS
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:11336/265216

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network_name_str CONICET Digital (CONICET)
spelling PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteinsGhafouri, HamidrezaLazar, TamasDel Conte, AlessioTenorio Ku, Luiggi G.Aspromonte, Maria C.Bernadó, PauChaves Arquero, BelénChemes, Lucia BeatrizClementel, DamianoCordeiro, Tiago N.Elena Real, Carlos A.Feig, MichaelFelli, Isabella C.Ferrari, CarloForman Kay, Julie D.Gomes, TiagoGondelaud, FrankGradinaru, Claudiu C.Ha Duong, TâpHead Gordon, TeresaHeidarsson, Pétur O.Janson, GiacomoJeschke, GunnarLeonardi, EmanuelaLiu, Zi HaoLonghi, SoniaLund, Xamuel L.Macias, Maria J.Martin Malpartida, PauMercadante, DavideMouhand, AssiaNagy, GaborNugnes, María VictoriaPérez Cañadillas, José ManuelPesce, GiuliaPierattelli, RobertaPiovesan, DamianoQuaglia, FedericaRicard Blum, SylvieRobustelli, PaulSagar, AminSalladini, EdoardoSénicourt, LucileSibille, NathalieTeixeira, João M. C.Tsangaris, Thomas E.Varadi, MihalyTompa, PeterTosatto, Silvio C. E.Monzon, Alexander MiguelDISORDERED PROTEINSPROTEIN ENSEMBLEBIOINFORMATICShttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.Fil: Ghafouri, Hamidreza. Università di Padova; ItaliaFil: Lazar, Tamas. Vrije Unviversiteit Brussel; BélgicaFil: Del Conte, Alessio. Università di Padova; ItaliaFil: Tenorio Ku, Luiggi G.. Università di Padova; ItaliaFil: Aspromonte, Maria C.. Università di Padova; ItaliaFil: Bernadó, Pau. Vrije Unviversiteit Brussel; BélgicaFil: Chaves Arquero, Belén. Università di Padova; ItaliaFil: Chemes, Lucia Beatriz. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Clementel, Damiano. Università di Padova; ItaliaFil: Cordeiro, Tiago N.. Universidade Nova de Lisboa; PortugalFil: Elena Real, Carlos A.. Inserm; FranciaFil: Feig, Michael. Michigan State University; Estados UnidosFil: Felli, Isabella C.. University of Florence; ItaliaFil: Ferrari, Carlo. Università di Padova; ItaliaFil: Forman Kay, Julie D.. University of Toronto; CanadáFil: Gomes, Tiago. Universidade Nova de Lisboa; PortugalFil: Gondelaud, Frank. Centre National de la Recherche Scientifique; FranciaFil: Gradinaru, Claudiu C.. University of Toronto; CanadáFil: Ha Duong, Tâp. Centre National de la Recherche Scientifique; FranciaFil: Head Gordon, Teresa. University of California; Estados UnidosFil: Heidarsson, Pétur O.. Michigan State University; Estados UnidosFil: Janson, Giacomo. No especifíca;Fil: Jeschke, Gunnar. Università di Padova; ItaliaFil: Leonardi, Emanuela. Università di Padova; ItaliaFil: Liu, Zi Hao. University of Toronto; CanadáFil: Longhi, Sonia. Centre National de la Recherche Scientifique; FranciaFil: Lund, Xamuel L.. Centre National de la Recherche Scientifique; FranciaFil: Macias, Maria J.. The Barcelona Institute of Science and Technology; EspañaFil: Martin Malpartida, Pau. The Barcelona Institute of Science and Technology; EspañaFil: Mercadante, Davide. University of Auckland; Nueva ZelandaFil: Mouhand, Assia. Centre National de la Recherche Scientifique; FranciaFil: Nagy, Gabor. Max Planck Institute for Biophysical Chemistry; AlemaniaFil: Nugnes, María Victoria. Università di Padova; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pérez Cañadillas, José Manuel. Consejo Superior de Investigaciones Científicas; EspañaFil: Pesce, Giulia. Centre National de la Recherche Scientifique; FranciaFil: Pierattelli, Roberta. University of Florence; ItaliaFil: Piovesan, Damiano. Università di Padova; ItaliaFil: Quaglia, Federica. Università di Padova; ItaliaFil: Ricard Blum, Sylvie. Université Claude Bernard Lyon 1; FranciaFil: Robustelli, Paul. Dartmouth College; Estados UnidosFil: Sagar, Amin. Centre National de la Recherche Scientifique; FranciaFil: Salladini, Edoardo. Università di Torino; ItaliaFil: Sénicourt, Lucile. Centre National de la Recherche Scientifique; FranciaFil: Sibille, Nathalie. Centre National de la Recherche Scientifique; FranciaFil: Teixeira, João M. C.. The Hospital for Sick Children; CanadáFil: Tsangaris, Thomas E.. University of Toronto; CanadáFil: Varadi, Mihaly. No especifíca;Fil: Tompa, Peter. Vrije Universiteit Amsterdam; Países BajosFil: Tosatto, Silvio C. E.. Università di Padova; ItaliaFil: Monzon, Alexander Miguel. Università di Padova; ItaliaOxford University Press2024-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/265216Ghafouri, Hamidreza; Lazar, Tamas; Del Conte, Alessio; Tenorio Ku, Luiggi G.; Aspromonte, Maria C.; et al.; PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins; Oxford University Press; Nucleic Acids Research; 52; D1; 1-2024; 536-5441362-4962CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1093/nar/gkad947info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:53:22Zoai:ri.conicet.gov.ar:11336/265216instacron: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 09:53:23.165CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
title PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
spellingShingle PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
Ghafouri, Hamidreza
DISORDERED PROTEINS
PROTEIN ENSEMBLE
BIOINFORMATICS
title_short PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
title_full PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
title_fullStr PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
title_full_unstemmed PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
title_sort PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
dc.creator.none.fl_str_mv Ghafouri, Hamidreza
Lazar, Tamas
Del Conte, Alessio
Tenorio Ku, Luiggi G.
Aspromonte, Maria C.
Bernadó, Pau
Chaves Arquero, Belén
Chemes, Lucia Beatriz
Clementel, Damiano
Cordeiro, Tiago N.
Elena Real, Carlos A.
Feig, Michael
Felli, Isabella C.
Ferrari, Carlo
Forman Kay, Julie D.
Gomes, Tiago
Gondelaud, Frank
Gradinaru, Claudiu C.
Ha Duong, Tâp
Head Gordon, Teresa
Heidarsson, Pétur O.
Janson, Giacomo
Jeschke, Gunnar
Leonardi, Emanuela
Liu, Zi Hao
Longhi, Sonia
Lund, Xamuel L.
Macias, Maria J.
Martin Malpartida, Pau
Mercadante, Davide
Mouhand, Assia
Nagy, Gabor
Nugnes, María Victoria
Pérez Cañadillas, José Manuel
Pesce, Giulia
Pierattelli, Roberta
Piovesan, Damiano
Quaglia, Federica
Ricard Blum, Sylvie
Robustelli, Paul
Sagar, Amin
Salladini, Edoardo
Sénicourt, Lucile
Sibille, Nathalie
Teixeira, João M. C.
Tsangaris, Thomas E.
Varadi, Mihaly
Tompa, Peter
Tosatto, Silvio C. E.
Monzon, Alexander Miguel
author Ghafouri, Hamidreza
author_facet Ghafouri, Hamidreza
Lazar, Tamas
Del Conte, Alessio
Tenorio Ku, Luiggi G.
Aspromonte, Maria C.
Bernadó, Pau
Chaves Arquero, Belén
Chemes, Lucia Beatriz
Clementel, Damiano
Cordeiro, Tiago N.
Elena Real, Carlos A.
Feig, Michael
Felli, Isabella C.
Ferrari, Carlo
Forman Kay, Julie D.
Gomes, Tiago
Gondelaud, Frank
Gradinaru, Claudiu C.
Ha Duong, Tâp
Head Gordon, Teresa
Heidarsson, Pétur O.
Janson, Giacomo
Jeschke, Gunnar
Leonardi, Emanuela
Liu, Zi Hao
Longhi, Sonia
Lund, Xamuel L.
Macias, Maria J.
Martin Malpartida, Pau
Mercadante, Davide
Mouhand, Assia
Nagy, Gabor
Nugnes, María Victoria
Pérez Cañadillas, José Manuel
Pesce, Giulia
Pierattelli, Roberta
Piovesan, Damiano
Quaglia, Federica
Ricard Blum, Sylvie
Robustelli, Paul
Sagar, Amin
Salladini, Edoardo
Sénicourt, Lucile
Sibille, Nathalie
Teixeira, João M. C.
Tsangaris, Thomas E.
Varadi, Mihaly
Tompa, Peter
Tosatto, Silvio C. E.
Monzon, Alexander Miguel
author_role author
author2 Lazar, Tamas
Del Conte, Alessio
Tenorio Ku, Luiggi G.
Aspromonte, Maria C.
Bernadó, Pau
Chaves Arquero, Belén
Chemes, Lucia Beatriz
Clementel, Damiano
Cordeiro, Tiago N.
Elena Real, Carlos A.
Feig, Michael
Felli, Isabella C.
Ferrari, Carlo
Forman Kay, Julie D.
Gomes, Tiago
Gondelaud, Frank
Gradinaru, Claudiu C.
Ha Duong, Tâp
Head Gordon, Teresa
Heidarsson, Pétur O.
Janson, Giacomo
Jeschke, Gunnar
Leonardi, Emanuela
Liu, Zi Hao
Longhi, Sonia
Lund, Xamuel L.
Macias, Maria J.
Martin Malpartida, Pau
Mercadante, Davide
Mouhand, Assia
Nagy, Gabor
Nugnes, María Victoria
Pérez Cañadillas, José Manuel
Pesce, Giulia
Pierattelli, Roberta
Piovesan, Damiano
Quaglia, Federica
Ricard Blum, Sylvie
Robustelli, Paul
Sagar, Amin
Salladini, Edoardo
Sénicourt, Lucile
Sibille, Nathalie
Teixeira, João M. C.
Tsangaris, Thomas E.
Varadi, Mihaly
Tompa, Peter
Tosatto, Silvio C. E.
Monzon, Alexander Miguel
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv DISORDERED PROTEINS
PROTEIN ENSEMBLE
BIOINFORMATICS
topic DISORDERED PROTEINS
PROTEIN ENSEMBLE
BIOINFORMATICS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.
Fil: Ghafouri, Hamidreza. Università di Padova; Italia
Fil: Lazar, Tamas. Vrije Unviversiteit Brussel; Bélgica
Fil: Del Conte, Alessio. Università di Padova; Italia
Fil: Tenorio Ku, Luiggi G.. Università di Padova; Italia
Fil: Aspromonte, Maria C.. Università di Padova; Italia
Fil: Bernadó, Pau. Vrije Unviversiteit Brussel; Bélgica
Fil: Chaves Arquero, Belén. Università di Padova; Italia
Fil: Chemes, Lucia Beatriz. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; Argentina
Fil: Clementel, Damiano. Università di Padova; Italia
Fil: Cordeiro, Tiago N.. Universidade Nova de Lisboa; Portugal
Fil: Elena Real, Carlos A.. Inserm; Francia
Fil: Feig, Michael. Michigan State University; Estados Unidos
Fil: Felli, Isabella C.. University of Florence; Italia
Fil: Ferrari, Carlo. Università di Padova; Italia
Fil: Forman Kay, Julie D.. University of Toronto; Canadá
Fil: Gomes, Tiago. Universidade Nova de Lisboa; Portugal
Fil: Gondelaud, Frank. Centre National de la Recherche Scientifique; Francia
Fil: Gradinaru, Claudiu C.. University of Toronto; Canadá
Fil: Ha Duong, Tâp. Centre National de la Recherche Scientifique; Francia
Fil: Head Gordon, Teresa. University of California; Estados Unidos
Fil: Heidarsson, Pétur O.. Michigan State University; Estados Unidos
Fil: Janson, Giacomo. No especifíca;
Fil: Jeschke, Gunnar. Università di Padova; Italia
Fil: Leonardi, Emanuela. Università di Padova; Italia
Fil: Liu, Zi Hao. University of Toronto; Canadá
Fil: Longhi, Sonia. Centre National de la Recherche Scientifique; Francia
Fil: Lund, Xamuel L.. Centre National de la Recherche Scientifique; Francia
Fil: Macias, Maria J.. The Barcelona Institute of Science and Technology; España
Fil: Martin Malpartida, Pau. The Barcelona Institute of Science and Technology; España
Fil: Mercadante, Davide. University of Auckland; Nueva Zelanda
Fil: Mouhand, Assia. Centre National de la Recherche Scientifique; Francia
Fil: Nagy, Gabor. Max Planck Institute for Biophysical Chemistry; Alemania
Fil: Nugnes, María Victoria. Università di Padova; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Pérez Cañadillas, José Manuel. Consejo Superior de Investigaciones Científicas; España
Fil: Pesce, Giulia. Centre National de la Recherche Scientifique; Francia
Fil: Pierattelli, Roberta. University of Florence; Italia
Fil: Piovesan, Damiano. Università di Padova; Italia
Fil: Quaglia, Federica. Università di Padova; Italia
Fil: Ricard Blum, Sylvie. Université Claude Bernard Lyon 1; Francia
Fil: Robustelli, Paul. Dartmouth College; Estados Unidos
Fil: Sagar, Amin. Centre National de la Recherche Scientifique; Francia
Fil: Salladini, Edoardo. Università di Torino; Italia
Fil: Sénicourt, Lucile. Centre National de la Recherche Scientifique; Francia
Fil: Sibille, Nathalie. Centre National de la Recherche Scientifique; Francia
Fil: Teixeira, João M. C.. The Hospital for Sick Children; Canadá
Fil: Tsangaris, Thomas E.. University of Toronto; Canadá
Fil: Varadi, Mihaly. No especifíca;
Fil: Tompa, Peter. Vrije Universiteit Amsterdam; Países Bajos
Fil: Tosatto, Silvio C. E.. Università di Padova; Italia
Fil: Monzon, Alexander Miguel. Università di Padova; Italia
description The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.
publishDate 2024
dc.date.none.fl_str_mv 2024-01
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/11336/265216
Ghafouri, Hamidreza; Lazar, Tamas; Del Conte, Alessio; Tenorio Ku, Luiggi G.; Aspromonte, Maria C.; et al.; PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins; Oxford University Press; Nucleic Acids Research; 52; D1; 1-2024; 536-544
1362-4962
CONICET Digital
CONICET
url http://hdl.handle.net/11336/265216
identifier_str_mv Ghafouri, Hamidreza; Lazar, Tamas; Del Conte, Alessio; Tenorio Ku, Luiggi G.; Aspromonte, Maria C.; et al.; PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins; Oxford University Press; Nucleic Acids Research; 52; D1; 1-2024; 536-544
1362-4962
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/nar/gkad947
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_ 1842269221568905216
score 13.13397