Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems

A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are spe...

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Detalles Bibliográficos
Autores: Barradas-Bautista, Didier, Rosell, Mireia, Pallara, Chiara, Fernández-Recio, Juan
Tipo de recurso: capítulo de libro
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/115854
Acceso en línea:https://hdl.handle.net/2117/115854
https://dx.doi.org/10.1016/bs.apcsb.2017.06.003
Access Level:acceso abierto
Palabra clave:Protein-protein interactions
Biomedical and health research
Protein–protein interactions
Complex structure
Computational docking
Interface prediction
Hot-spot residues
Drug discovery
Edgetic effect
Pathological mutations
Proteïnes--Investigació
Àrees temàtiques de la UPC::Ciències de la salut
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spelling Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical ProblemsBarradas-Bautista, DidierRosell, MireiaPallara, ChiaraFernández-Recio, JuanProtein-protein interactionsBiomedical and health researchProtein–protein interactionsComplex structureComputational dockingInterface predictionHot-spot residuesDrug discoveryEdgetic effectPathological mutationsProteïnes--InvestigacióÀrees temàtiques de la UPC::Ciències de la salutA huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biomolecules, forming intricate interaction networks that are essential for the majority of cell processes and pathological conditions. Thus, characterizing such interaction networks is an important step in understanding how information flows from gene to phenotype. Indeed, structural characterization of protein–protein interactions at atomic resolution has many applications in biomedicine, from diagnosis and vaccine design, to drug discovery. However, despite the advances of experimental structural determination, the number of interactions for which there is available structural data is still very small. In this context, a complementary approach is computational modeling of protein interactions by docking, which is usually composed of two major phases: (i) sampling of the possible binding modes between the interacting molecules and (ii) scoring for the identification of the correct orientations. In addition, prediction of interface and hot-spot residues is very useful in order to guide and interpret mutagenesis experiments, as well as to understand functional and mechanistic aspects of the interaction. Computational docking is already being applied to specific biomedical problems within the context of personalized medicine, for instance, helping to interpret pathological mutations involved in protein–protein interactions, or providing modeled structural data for drug discovery targeting protein–protein interactions.Spanish Ministry of Economy grant number BIO2016-79960-R; D.B.B. is supported by a predoctoral fellowship from CONACyT; M.R. is supported by an FPI fellowship from the Severo Ochoa program. We are grateful to the Joint BSC-CRG-IRB Programme in Computational Biology.Peer ReviewedAcademic Press20182018-01-0120182018-03-26book parthttp://purl.org/coar/resource_type/c_3248AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/bookPartapplication/pdfhttps://hdl.handle.net/2117/115854https://dx.doi.org/10.1016/bs.apcsb.2017.06.003reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1158542026-05-27T15:37:01Z
dc.title.none.fl_str_mv Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems
title Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems
spellingShingle Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems
Barradas-Bautista, Didier
Protein-protein interactions
Biomedical and health research
Protein–protein interactions
Complex structure
Computational docking
Interface prediction
Hot-spot residues
Drug discovery
Edgetic effect
Pathological mutations
Proteïnes--Investigació
Àrees temàtiques de la UPC::Ciències de la salut
title_short Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems
title_full Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems
title_fullStr Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems
title_full_unstemmed Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems
title_sort Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems
dc.creator.none.fl_str_mv Barradas-Bautista, Didier
Rosell, Mireia
Pallara, Chiara
Fernández-Recio, Juan
author Barradas-Bautista, Didier
author_facet Barradas-Bautista, Didier
Rosell, Mireia
Pallara, Chiara
Fernández-Recio, Juan
author_role author
author2 Rosell, Mireia
Pallara, Chiara
Fernández-Recio, Juan
author2_role author
author
author
dc.subject.none.fl_str_mv Protein-protein interactions
Biomedical and health research
Protein–protein interactions
Complex structure
Computational docking
Interface prediction
Hot-spot residues
Drug discovery
Edgetic effect
Pathological mutations
Proteïnes--Investigació
Àrees temàtiques de la UPC::Ciències de la salut
topic Protein-protein interactions
Biomedical and health research
Protein–protein interactions
Complex structure
Computational docking
Interface prediction
Hot-spot residues
Drug discovery
Edgetic effect
Pathological mutations
Proteïnes--Investigació
Àrees temàtiques de la UPC::Ciències de la salut
description A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biomolecules, forming intricate interaction networks that are essential for the majority of cell processes and pathological conditions. Thus, characterizing such interaction networks is an important step in understanding how information flows from gene to phenotype. Indeed, structural characterization of protein–protein interactions at atomic resolution has many applications in biomedicine, from diagnosis and vaccine design, to drug discovery. However, despite the advances of experimental structural determination, the number of interactions for which there is available structural data is still very small. In this context, a complementary approach is computational modeling of protein interactions by docking, which is usually composed of two major phases: (i) sampling of the possible binding modes between the interacting molecules and (ii) scoring for the identification of the correct orientations. In addition, prediction of interface and hot-spot residues is very useful in order to guide and interpret mutagenesis experiments, as well as to understand functional and mechanistic aspects of the interaction. Computational docking is already being applied to specific biomedical problems within the context of personalized medicine, for instance, helping to interpret pathological mutations involved in protein–protein interactions, or providing modeled structural data for drug discovery targeting protein–protein interactions.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01
2018
2018-03-26
dc.type.none.fl_str_mv book part
http://purl.org/coar/resource_type/c_3248
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/115854
https://dx.doi.org/10.1016/bs.apcsb.2017.06.003
url https://hdl.handle.net/2117/115854
https://dx.doi.org/10.1016/bs.apcsb.2017.06.003
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Academic Press
publisher.none.fl_str_mv Academic Press
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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