SPServerSplit-statistical potentials for the analysis of protein structures and protein–protein interactions

Authors Organisations
  • Joaquim Aguirre-Plans(Author)
    Universitat Pompeu Fabra Barcelona
  • Alberto Meseguer(Author)
    Universitat Pompeu Fabra Barcelona
  • Ruben Molina-Fernandez(Author)
    Universitat Pompeu Fabra Barcelona
  • Manuel Alejandro Marín-López(Author)
    Universitat Pompeu Fabra Barcelona
  • Gaurav Jumde(Author)
    Universitat Pompeu Fabra Barcelona
  • Kevin Casanova(Author)
    Universitat Pompeu Fabra Barcelona
  • Jaume Bonet(Author)
    École Polytechnique Fédérale de Lausanne
  • Oriol Fornes(Author)
    University of British Columbia
  • Narcis Fernandez Fuentes(Author)
    University of Vic - Central University of Catalonia
  • Baldo Oliva(Author)
    Universitat Pompeu Fabra Barcelona
Type Article
Original languageEnglish
Article number4
Number of pages13
JournalBMC Bioinformatics
Volume22
Issue number1
DOI
Publication statusPublished - 06 Jan 2021
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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/.

Keywords

  • Knowledge-based potential, Protein structure evaluation, Protein structure prediction, Protein structure quality assessment, Protein–protein evaluation, Protein–protein interaction

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