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

• Published in: BMC bioinformatics Vol. 22; no. 1; pp. 4 - 13
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 06.01.2021; BioMed Central; BMC
• Subjects: Amino acids; Amino Acids - chemistry; Amino Acids - metabolism; Empirical analysis; File servers; Hydrophobicity; Interfaces; Internet; Knowledge Bases; Knowledge-based potential; Methods; Models, Statistical; Osteoprotegerin; Protein interaction; Protein Interaction Maps - physiology; Protein research; Protein structure; Protein structure evaluation; Protein structure prediction; Protein structure quality assessment; Protein Structure, Secondary; Protein-protein interactions; Proteins; Proteins - chemistry; Proteins - metabolism; Protein–protein evaluation; Protein–protein interaction; Quality assessment; Residues; Secondary structure; Servers; Software; Statistics; Structural models; Spain; Protein structure quality assessment; Protein structure prediction; Knowledge-based potential; Protein–protein evaluation; Protein structure evaluation; Protein–protein interaction
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-020-03770-5

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. 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. 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/ .