Institute of Protein Research, Russian Academy of Sciences, Pushchino, 142290 Moscow, Russia.
Institute of Mathematical Problems of Biology, Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Vitkevicha str.1, Pushchino, 142290 Moscow, Russia.
Molecules. 2020 Mar 27;25(7):1522. doi: 10.3390/molecules25071522.
We created a new library of disordered patterns and disordered residues in the Protein Data Bank (PDB). To obtain such datasets, we clustered the PDB and obtained the groups of chains with different identities and marked disordered residues. We elaborated a new procedure for finding disordered patterns and created a new version of the library. This library includes three sets of patterns: unique patterns, patterns consisting of two kinds of amino acids, and homo-repeats. Using this database, the user can: (1) find homologues in the entire Protein Data Bank; (2) perform a statistical analysis of disordered residues in protein structures; (3) search for disordered patterns and homo-repeats; (4) search for disordered regions in different chains of the same protein; (5) download clusters of protein chains with different identity from our database and library of disordered patterns; and (6) observe 3D structure interactively using MView. A new library of disordered patterns will help improve the accuracy of predictions for residues that will be structured or unstructured in a given region.
我们创建了一个新的蛋白质数据库(PDB)中无序模式和无序残基的库。为了获得这样的数据集,我们对 PDB 进行了聚类,并获得了具有不同身份的链组,并标记了无序残基。我们详细描述了一种寻找无序模式的新方法,并创建了该库的新版本。该库包括三组模式:独特模式、由两种氨基酸组成的模式和同源重复。使用这个数据库,用户可以:(1)在整个蛋白质数据库中查找同源物;(2)对蛋白质结构中的无序残基进行统计分析;(3)搜索无序模式和同源重复;(4)在同一蛋白质的不同链中搜索无序区域;(5)从我们的数据库和无序模式库中下载具有不同身份的蛋白质链簇;(6)使用 MView 进行交互式观察 3D 结构。无序模式的新库将有助于提高对给定区域中结构或非结构残基的预测准确性。