Prediction of interactions involving intrinsically disordered proteins

预测涉及本质无序蛋白质的相互作用

• 批准号: RGPIN-2015-05412
• 负责人: Gsponer, Joerg
• 金额: $ 2.55万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=613536
• 关键词: Prediction; interactions; involving; intrinsically; disordered

Intrinsically disordered (ID) proteins play a central role in protein interactomes because their ID segments often mediate large numbers of interactions. We have shown previously that interactions mediated by ID protein segments are characterized by features that distinguish them from other protein interactions. We hypothesize that these features can be used to (i) identify interaction sites on globular proteins that preferentially bind ID proteins and (ii) determine the structures that ID protein segments adopt upon binding. Based on this hypothesis, we propose the following aims:    Aim 1: Development of a predictor that identifies surface regions on globular proteins that bind ID proteins. Aim 2: Development of a method to determine the structure of binary complexes in which one member is an ID protein. Aim 3: Application of these methods on autoinhibited proteins. Aim1: Using specific features that distinguish ID protein-binding surfaces from other protein surfaces (including flexibility, electrostatic potential or residue conservation), we will train a classifier to distinguish the two types of surfaces. The performance of the classifier will be tested by ten-fold cross-validation as well as on a test set of structures not used in the training. Aim 2: We will extend a recently published docking protocol such that it can be used for the determination of the structure of complexes in which one member is an ID protein. The protocol uses multiple steps of low- and high-resolution docking and the Rosetta potential for the scoring of generated structures. The developed protocol will be benchmarked on a set of known high-resolution structures of complexes that contain ID proteins. Aim 3: Here, we will test whether the methods developed in Aim 1 and 2 can be used to determine the structure of proteins in which an ID segments interacts in cis with a domain of the same polypeptide chain, i.e., acts as an autoinhibitory switch. We will first benchmark the approach on a set of autoinhibited proteins for which the structure is known, and then use it to determine the structure of the autoinhibited state of the ABC transporter Rv1747 from Mycobacterium tuberculosis that we predict to be autoinhibited. We are confident that the tools developed in this research program will constitute a solid base for the future development of computational methods used in the design of therapeutic peptides and proteins that inhibit, respectively, mimic interactions mediated by ID proteins.

本质无序 (ID) 蛋白质在蛋白质相互作用组中发挥着核心作用，因为它们的 ID 片段通常介导大量相互作用。我们之前已经表明，由 ID 蛋白片段介导的相互作用具有区别于其他蛋白质相互作用的特征。我们假设这些特征可用于 (i) 识别球状蛋白上优先结合 ID 蛋白的相互作用位点，以及 (ii) 确定 ID 蛋白片段在结合后采用的结构。基于这一假设，我们提出以下目标：    目标 1：开发一种预测器，用于识别与 ID 蛋白结合的球状蛋白的表面区域。 目标 2：开发一种方法来确定二元复合物的结构，其中一个成员是 ID 蛋白。 目标 3：将这些方法应用于自抑制蛋白。 目标 1：利用区分 ID 蛋白质结合表面与其他蛋白质表面的特定特征（包括灵活性、静电势或残基守恒），我们将训练一个分类器来区分这两种类型的表面。分类器的性能将通过十倍交叉验证以及训练中未使用的结构测试集进行测试。 目标 2：我们将扩展最近发布的对接方案，使其可用于确定其中一个成员是 ID 蛋白的复合物的结构。该协议使用低分辨率和高分辨率对接的多个步骤以及 Rosetta 电位对生成的结构进行评分。所开发的方案将以一组已知的含有 ID 蛋白的复合物的高分辨率结构为基准。 目标 3：在这里，我们将测试目标 1 和 2 中开发的方法是否可用于确定蛋白质结构，其中 ID 片段与同一多肽链的结构域顺式相互作用，即充当自抑制开关。我们将首先在一组已知结构的自抑制蛋白上对该方法进行基准测试，然后用它来确定来自结核分枝杆菌的 ABC 转运蛋白 Rv1747 的自抑制状态的结构，我们预测该转运蛋白会发生自抑制。 我们相信，本研究项目中开发的工具将为未来开发用于设计治疗性肽和蛋白质的计算方法奠定坚实的基础，这些治疗性肽和蛋白质分别抑制模拟 ID 蛋白质介导的相互作用。