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SPServer: split-statistical potentials for the analysis of protein structures and protein–protein interactions
BMC Bioinformatics ( IF 2.9 ) Pub Date : 2021-01-06 , DOI: 10.1186/s12859-020-03770-5
Joaquim Aguirre-Plans 1 , Alberto Meseguer 1 , Ruben Molina-Fernandez 1 , Manuel Alejandro Marín-López 1 , Gaurav Jumde 1 , Kevin Casanova 1 , Jaume Bonet 2 , Oriol Fornes 3 , Narcis Fernandez-Fuentes 4, 5 , Baldo Oliva 1
Affiliation  

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. https://sbi.upf.edu/spserver/ .

中文翻译:


SPServer:用于分析蛋白质结构和蛋白质-蛋白质相互作用的分割统计势



统计势,也称为基于知识的势,是源自经验数据的评分函数,可用于评估蛋白质折叠和蛋白质-蛋白质相互作用 (PPI) 结构的质量。在之前的工作中,我们用不同的术语分解了统计势,称为分割统计势,考虑了氨基酸对的类型、它们的疏水性、溶剂可及性和二级结构的类型。这些势已成功用于识别蛋白质结构预测中的近天然结构、对蛋白质对接姿势进行排序以及预测 PPI 结合亲和力。在这里,我们展示了 SPServer,一个应用分割统计势来分析蛋白质折叠和蛋白质界面的 Web 服务器。 SPServer 提供全局分数以及以分数图和地图形式呈现的残基/残基对概况。这种详细程度允许用户:(1)识别蛋白质结构上潜在问题的区域; (2) 识别蛋白质界面中的破坏性氨基酸对; (3)对三级和四级构造模型的质量进行比较和分析。虽然有许多 Web 服务器提供评分功能来评估蛋白质折叠或 PPI 结构的质量,但 SPServer 将这两个方面集成在一个独特的易于使用的 Web 服务器中。此外,服务器允许在残留水平上本地评估结构和界面的质量,并提供工具来比较结构之间的本地评估。 https://sbi.upf.edu/spserver/。
更新日期:2021-01-06
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