Institute of Chemistry, Slovak Academy of Sciences, Bratislava, Slovakia.
Department of Chemistry, Rikkyo University, Nishi-Ikebukuro, Tokyo, Japan.
PLoS One. 2021 Jul 30;16(7):e0255167. doi: 10.1371/journal.pone.0255167. eCollection 2021.
The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga.
蛋白质残基网络(PRN)研究领域为蛋白质和蛋白质复合物的结构分析带来了一些有用的方法和技术。其中许多方法已经成熟,可供 PRN 专家以外的蛋白质组学社区使用。在本文中,我们介绍了一款软件,该软件收集了一组(网络)方法,专门用于分析蛋白质-蛋白质相互作用(PPI)和/或蛋白质与其他类型配体(如核酸、寡糖等)的相互作用。同时,我们提出将网络差异分析用作识别介导蛋白质之间关键相互作用的残基的方法。我们使用模型系统来说明,结合其他已发表的方法,也包括在 pyProGA 中,它可以用于进行此类预测。这种扩展的方法组合允许与其他方法进行交叉检查预测,正如我们在这里展示的那样。此外,从各种输入构建 PRN 模型的可能性到目前为止是我们代码的独特优势。可以使用 PDB 文件中定义的结构数据和/或残基对相互作用能的数据,这些数据可以来自力场参数或片段分子轨道(FMO)计算。pyProGA 是一款免费的开源软件,可从 https://gitlab.com/Vlado_S/pyproga 获得。