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

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 diffe...

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Autores principales: Aguirre-Plans, Joaquim, Meseguer, Alberto, Molina-Fernandez, Ruben, Marín-López, Manuel Alejandro, Jumde, Gaurav, Casanova, Kevin, Bonet, Jaume, Fornes, Oriol, Fernandez-Fuentes, Narcis, Oliva, Baldo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788957/
https://www.ncbi.nlm.nih.gov/pubmed/33407073
http://dx.doi.org/10.1186/s12859-020-03770-5
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author Aguirre-Plans, Joaquim
Meseguer, Alberto
Molina-Fernandez, Ruben
Marín-López, Manuel Alejandro
Jumde, Gaurav
Casanova, Kevin
Bonet, Jaume
Fornes, Oriol
Fernandez-Fuentes, Narcis
Oliva, Baldo
author_facet Aguirre-Plans, Joaquim
Meseguer, Alberto
Molina-Fernandez, Ruben
Marín-López, Manuel Alejandro
Jumde, Gaurav
Casanova, Kevin
Bonet, Jaume
Fornes, Oriol
Fernandez-Fuentes, Narcis
Oliva, Baldo
author_sort Aguirre-Plans, Joaquim
collection PubMed
description 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/.
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spelling pubmed-77889572021-01-07 SPServer: split-statistical potentials for the analysis of protein structures and protein–protein interactions Aguirre-Plans, Joaquim Meseguer, Alberto Molina-Fernandez, Ruben Marín-López, Manuel Alejandro Jumde, Gaurav Casanova, Kevin Bonet, Jaume Fornes, Oriol Fernandez-Fuentes, Narcis Oliva, Baldo BMC Bioinformatics Software 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/. BioMed Central 2021-01-06 /pmc/articles/PMC7788957/ /pubmed/33407073 http://dx.doi.org/10.1186/s12859-020-03770-5 Text en © The Author(s) 2020 Open AccessThis 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 made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Aguirre-Plans, Joaquim
Meseguer, Alberto
Molina-Fernandez, Ruben
Marín-López, Manuel Alejandro
Jumde, Gaurav
Casanova, Kevin
Bonet, Jaume
Fornes, Oriol
Fernandez-Fuentes, Narcis
Oliva, Baldo
SPServer: split-statistical potentials for the analysis of protein structures and protein–protein interactions
title SPServer: split-statistical potentials for the analysis of protein structures and protein–protein interactions
title_full SPServer: split-statistical potentials for the analysis of protein structures and protein–protein interactions
title_fullStr SPServer: split-statistical potentials for the analysis of protein structures and protein–protein interactions
title_full_unstemmed SPServer: split-statistical potentials for the analysis of protein structures and protein–protein interactions
title_short SPServer: split-statistical potentials for the analysis of protein structures and protein–protein interactions
title_sort spserver: split-statistical potentials for the analysis of protein structures and protein–protein interactions
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788957/
https://www.ncbi.nlm.nih.gov/pubmed/33407073
http://dx.doi.org/10.1186/s12859-020-03770-5
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