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SPServer: split-statistical potentials for the analysis of protein structures and protein-protein interactions

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dc.contributor.author Aguirre Plans, Joaquim, 1993-
dc.contributor.author Meseguer, Alberto
dc.contributor.author Molina Fernández, Rubén
dc.contributor.author Marín López, Manuel Alejandro, 1987-
dc.contributor.author Jumde, Gaurav
dc.contributor.author Casanova, Kevin
dc.contributor.author Bonet Martínez, Jaume, 1982-
dc.contributor.author Fornés Crespo, Oriol, 1983-
dc.contributor.author Fernández Fuentes, Narcís
dc.contributor.author Oliva Miguel, Baldomero
dc.date.accessioned 2021-02-15T06:48:03Z
dc.date.available 2021-02-15T06:48:03Z
dc.date.issued 2021
dc.identifier.citation Aguirre-Plans J, Meseguer A, Molina-Fernandez R, Marín-López MA, Jumde G, Casanova K, Bonet J, Fornes O, Fernandez-Fuentes N, Oliva B. SPServer: split-statistical potentials for the analysis of protein structures and protein-protein interactions. BMC Bioinformatics. 2021; 22(1):4. DOI: 10.1186/s12859-020-03770-5
dc.identifier.issn 1471-2105
dc.identifier.uri http://hdl.handle.net/10230/46469
dc.description.abstract Background: Statistical potentials, also named knowledge-based potentials, are scoring functions derived from empirical data that can be used to evaluate the quality of protein folds and protein-protein interaction (PPI) structures. In previous works we decomposed the statistical potentials in different terms, named Split-Statistical Potentials, accounting for the type of amino acid pairs, their hydrophobicity, solvent accessibility and type of secondary structure. These potentials have been successfully used to identify near-native structures in protein structure prediction, rank protein docking poses, and predict PPI binding affinities. Results: Here, we present the SPServer, a web server that applies the Split-Statistical Potentials to analyze protein folds and protein interfaces. SPServer provides global scores as well as residue/residue-pair profiles presented as score plots and maps. This level of detail allows users to: (1) identify potentially problematic regions on protein structures; (2) identify disrupting amino acid pairs in protein interfaces; and (3) compare and analyze the quality of tertiary and quaternary structural models. Conclusions: While there are many web servers that provide scoring functions to assess the quality of either protein folds or PPI structures, SPServer integrates both aspects in a unique easy-to-use web server. Moreover, the server permits to locally assess the quality of the structures and interfaces at a residue level and provides tools to compare the local assessment between structures. SERVER ADDRESS: https://sbi.upf.edu/spserver/.
dc.description.sponsorship This work was supported by the Spanish Ministry of Science and Innovation (MICINN) [BIO2017-85329-R (co-funded by ERDF,UE)]. BO also acknowledges support from MICINN [ref: MDM-2014-0370]. NFF acknowledges support from [BIO2017-83591-R (co-funded by ERDF, UE)] and [RYC-2015-17519]. We also akcnowledge support from the Spanish National Bioinformatics Institute (INB), PRB2-ISCIII and Grants PT13/0001/0023 of the PEI +D+i 2013–2016, funded by ISCIII and co-funded by ERDF of EU. BO and NFF acknowledge Agència de Gestió d’Ajuts Universitaris I de Recerca de la Generalitat de Catalunya, grant SGR17-1020, and the Council for the Catalan Republic contribution to cover the expenses of publication.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher BioMed Central
dc.relation.ispartof BMC Bioinformatics. 2021; 22(1):4
dc.rights © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data ma
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title SPServer: split-statistical potentials for the analysis of protein structures and protein-protein interactions
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1186/s12859-020-03770-5
dc.subject.keyword Knowledge-based potential
dc.subject.keyword Protein structure evaluation
dc.subject.keyword Protein structure prediction
dc.subject.keyword Protein structure quality assessment
dc.subject.keyword Protein–protein evaluation
dc.subject.keyword Protein–protein interaction
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BIO2017-85329-R
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BIO2017-83591-R
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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