A multistage approach to protein-protein docking

蛋白质-蛋白质对接的多阶段方法

• 批准号: 8608536
• 负责人: SANDOR VAJDA
• 金额: $ 28.47万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2017-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8608536
• 关键词: Address; Algorithms; Back; Benchmarking; Binding; Biological; Complex; Deposition; Discrimination; Disease; Dissociation; Docking; Fourier Transform; Free Energy; Goals; Grant; Homology Modeling; Hot Spot; Laboratories; Ligands; Methods; Modeling; Molecular Conformation; Morphologic artifacts; Pathway interactions; Peptides; Probability; Proteins; Protocols documentation; Request for Proposals; Rest; Running; Side; Site; Solutions; Staging; Structure; Vertebral column; base; experimental analysis; flexibility; method development; novel; protein complex; protein protein interaction; receptor; research study; simulation; success

Protein-protein interactions are integral to virtually all biological pathways. Many important interactions occur in weak, transient complexes that will not be amenable to direct experimental analysis, even when both proteins can be isolated and their structures determined. Thus, it is important to develop computational docking methods which, starting from the structures of component proteins, can determine the structure of their complexes. We have developed a multistage docking algorithm that provided the best results in the latest rounds of the CAPRI (Critical Assessment of Predicted Interactions) worldwide docking experiment. In addition, our docking server ClusPro was the best among automated servers. Although the CAPRI results demonstrate progress, a number of major problems remain unsolved. First, docking homology models is a challenge and all methods used in CAPRI performed poorly for such targets. Docking unbound structures is also difficult if binding is accompanied by substantial backbone conformational change. Second, it is not clear whether a model generated by docking represents a specific and stable complex. Third, the interface may include regions that are disordered in the separate proteins, challenging docking methods. We address these problems by pursuing three specific aims. First, we develop a novel algorithm for docking homology models and proteins with substantial backbone flexibility. The method is based on the hypothesis that the interface in complexes is sequentially and structurally more conserved than the rest of the proteins. Since such regions are frequently sufficient for recognition, identification and correct docking of the key segments can yield near-native docked structures. For homology models this implies that one can dock the regions that can be reliably modeled, and then expand the models by adding back the removed parts using the docked structures as constraints. The problem of docking "difficult cases" with substantial backbone conformational change can also be addressed by identifying and docking the structurally most conserved regions. Once clusters of the docked rigid fragments are obtained, the models are expanded by rebuilding the more flexible parts. Second, we use a two-step approach to examine the stability of protein complexes, first by removing small and hence unlikely clusters of low energy docked structures, and then by calculating dissociation rates by stochastic roadmap simulation. The method will be validated on a benchmark set that includes models of real protein complexes and decoys generated by docking non-interacting protein pairs. The approach will also be used to determine whether complex structures deposited to the PDB are biologically relevant. Third, we consider the problem of determining the structure of flexible loops and/or disordered regions when they become parts of a protein- protein interface. Rather than attempting to predict and to dock the most likely conformation of the flexible fragment, we build their bound structure directly into binding hot spots of the partner protein. Flexible peptide docking methods will be used to expand the docked fragments by adding further residues.

蛋白质-蛋白质相互作用是几乎所有生物途径的组成部分。许多重要的相互作用发生在 弱的，短暂的复合物，将不服从直接实验分析，即使两种蛋白质 可以分离并确定其结构。因此，发展计算对接技术具有重要意义 方法，从组分蛋白质的结构出发，可以确定其结构， 配合物我们已经开发了一个多级对接算法，提供了最好的结果在最新的 卡普里（Critical Assessment of Predicted Interactions）全球对接实验此外，本发明还提供了一种方法， 我们的对接服务器是自动化服务器中最好的。尽管卡普里的结果表明， 尽管取得了进展，但一些重大问题仍未解决。首先，对接同源模型是一个挑战， 卡普里中使用的方法对这些目标表现不佳。对接未绑定结构也很困难， 结合伴随着大量的骨架构象变化。第二，不清楚A 通过对接产生的模型代表特定的和稳定的复合物。第三，界面可以包括区域 在分离的蛋白质中是无序的，这挑战了对接方法。我们通过以下方式解决这些问题： 追求三个具体目标。首先，我们开发了一个新的算法对接同源模型和蛋白质 具有相当大的骨架柔性。该方法基于复合物中的界面是 序列和结构上比其他蛋白质更保守。由于这些地区经常 足以识别、识别和正确对接的关键段可以产生接近本地的对接 结构.对于同源性模型，这意味着可以对接可以可靠建模的区域，并且 然后使用停靠的结构作为约束，通过添加回移除的部分来扩展模型。的 也可以解决具有实质性骨架构象变化的对接“困难情况”的问题 通过识别和对接结构上最保守的区域。一旦这些固定的刚性碎片 通过重构柔性较大的零件来扩展模型。其次，我们使用两步 一种检查蛋白质复合物稳定性的方法，首先通过去除小的，因此不太可能的簇， 低能对接结构，然后通过随机路线图模拟计算解离速率。 该方法将在包括真实的蛋白质复合物和诱饵模型的基准集上进行验证 通过对接非相互作用的蛋白质对产生。该方法还将用于确定是否 沉积在PDB上的复杂结构是生物相关的。第三，我们考虑以下问题： 当它们成为蛋白质的一部分时，确定柔性环和/或无序区域的结构- 蛋白质界面而不是试图预测和对接最有可能的构象的柔性 片段，我们将它们的结合结构直接构建到伴侣蛋白的结合热点中。柔性肽 对接方法将用于通过添加另外的残基来扩增对接的片段。