Suppr超能文献

分析互作网络中的内在离散蛋白。

Analyzing IDPs in Interactomes.

机构信息

Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.

USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.

出版信息

Methods Mol Biol. 2020;2141:895-945. doi: 10.1007/978-1-0716-0524-0_46.

Abstract

Intrinsically disordered proteins (IDPs) and regions (IDRs) are commonly found in all proteomes analyzed so far. These proteins/regions are subject to numerous posttranslational modifications (PTMs) and alternative splicing, are involved in a wide range of cellular functions, and often facilitate protein-protein interactions (PPIs). Some of these proteins contain molecular recognition features (MoRFs), which are IDRs that bind to partner proteins and undergo disorder-to-order transitions. Although many IDPs/IDRs can fold upon binding, a large fraction of these proteins are known to maintain significant amounts of disorder in their bound states. Being well-recognized interaction specialists, IDPs/IDRs can participate in one-to-many and many-to-one interactions, where one IDP/IDR binds to multiple partners potentially gaining very different structures in the bound state, or where multiple unrelated IDPs/IDRs bind to one partner. As a result, IDPs frequently serve as hubs (i.e., proteins with many links) in complex PPI networks. The goal of this chapter is to describe computational and bioinformatics tools that can be used to look at the disorder status of proteins within a given PPI network and also to gain some knowledge on the disorder-based functionality of the members of this network. To this end, description is provided for some of the use of UniProt and DisProt databases, several databases generating PPI networks (BioGRID, IntAct, DIP, MINT, HPRD, APID, KEGG, and STRING), Composition profiler, some tools for the per-residue disorder predictions (PONDR VLXT, PONDR VL3, PONDR VSL2, PONDR-FIT, and IUPred), binary disorder classifiers CH-plot and CDF-plot and their combined CH-CDF analysis, web-based tools for the visualization of disorder distribution in a query protein (DP and MobiDB), as well as some tools for evaluation disorder-based functionality of proteins (ANCHOR, MoRFpred, DEPP, and ModPred).

摘要

目前分析的所有蛋白质组中都普遍存在无规则蛋白质 (IDP) 和区域 (IDR)。这些蛋白质/区域受到许多翻译后修饰 (PTM) 和选择性剪接的影响,参与了广泛的细胞功能,并且通常促进蛋白质-蛋白质相互作用 (PPI)。其中一些蛋白质含有分子识别特征 (MoRF),这是与伴侣蛋白结合并发生无序到有序转变的 IDR。虽然许多 IDP/IDR 在结合时可以折叠,但已知这些蛋白质中的很大一部分在结合状态下仍保持大量无序。作为公认的相互作用专家,IDP/IDR 可以参与一对一和多对一的相互作用,其中一个 IDP/IDR 与多个伴侣结合,在结合状态下可能获得非常不同的结构,或者多个不相关的 IDP/IDR 与一个伴侣结合。因此,IDP 经常在复杂的 PPI 网络中充当枢纽(即具有许多连接的蛋白质)。本章的目的是描述可用于查看给定 PPI 网络中蛋白质无序状态的计算和生物信息学工具,并获得有关该网络成员基于无序功能的一些知识。为此,提供了对 UniProt 和 DisProt 数据库、生成 PPI 网络的几个数据库(BioGRID、IntAct、DIP、MINT、HPRD、APID、KEGG 和 STRING)、Composition profiler 的一些用途的描述,以及一些用于残基无序预测的工具(PONDR VLXT、PONDR VL3、PONDR VSL2、PONDR-FIT 和 IUPred)、二进制无序分类器 CH-plot 和 CDF-plot 及其组合的 CH-CDF 分析、用于查询蛋白质中无序分布可视化的基于网络的工具 (DP 和 MobiDB) 以及一些用于评估蛋白质基于无序功能的工具 (ANCHOR、MoRFpred、DEPP 和 ModPred)。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验