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.

蛋白质内部无序（ID）蛋白质在蛋白质相互作用组中起着核心作用，因为它们的ID片段通常介导大量的相互作用。我们以前已经表明，由ID蛋白片段介导的相互作用的特征在于将它们与其他蛋白质相互作用区分开来。我们假设这些特征可用于（i）鉴定优先结合ID蛋白的球状蛋白上的相互作用位点，以及（ii）确定ID蛋白片段在结合时采用的结构。基于这一假设，我们提出以下目标：    目的1：开发一种预测器，识别结合ID蛋白的球状蛋白的表面区域。 目的2：发展一种确定其中一个成员是ID蛋白质的二元复合物结构的方法。 目的3：这些方法在自抑制蛋白研究中的应用。 目标1：使用将ID蛋白质结合表面与其他蛋白质表面区分开的特定特征（包括柔性、静电势或残基守恒），我们将训练分类器来区分这两种类型的表面。分类器的性能将通过十重交叉验证以及训练中未使用的结构测试集进行测试。 目标二：我们将扩展最近发表的对接协议，使其可用于确定其中一个成员是ID蛋白的复合物的结构。该协议使用多个低分辨率和高分辨率对接步骤以及罗塞塔势对生成的结构进行评分。开发的协议将基准上的一组已知的高分辨率结构的复合物，包含ID蛋白。 目标3：在这里，我们将测试在目标1和2中开发的方法是否可以用于确定其中ID区段与相同多肽链的结构域顺式相互作用的蛋白质的结构，即，就像一个自动抑制开关我们将首先基准的方法上的一组autoinhibited蛋白质的结构是已知的，然后用它来确定结构的autoinhibited状态的ABC转运蛋白Rv1747从结核分枝杆菌，我们预测将autoinhibited。 我们有信心，在这项研究计划中开发的工具将构成一个坚实的基础，用于治疗性肽和蛋白质的设计，分别抑制，模拟ID蛋白介导的相互作用的计算方法的未来发展。