Analysis and Design of Coiled Coil Partnering

描述（由申请人提供）：拟议工作的广泛，长期目标是了解蛋白质如何在单个结构域水平上建立相互作用特异性，并在可用于计算预测和设计的模型中捕获这一点。这个问题是人类健康问题的核心。突变或错误调节的蛋白质之间的不适当相互作用可能导致疾病，深入了解这种情况是很重要的。此外，设计特异性抑制天然蛋白质复合物的新型蛋白质或肽将为未来的治疗提供途径。相互作用特异性问题可以通过关注一个普遍存在但结构简单的蛋白质-蛋白质相互作用基序来简化：α-螺旋卷曲螺旋。卷曲螺旋出现在所有物种的蛋白质组中，并与各种各样的功能相关。它们的序列和结构特性使它们易于进行计算分析，卷曲螺旋也便于使用生物物理方法进行实验研究。拟议的研究涉及收集系统的实验相互作用数据，并使用它来开发和测试各种计算技术，以预测相互作用。计算方法也将开发用于设计卷曲螺旋样肽，并提出实验来表征设计。这项建议的具体目标是：（1）测试和改进用于预测卷曲螺旋结构、能量和相互作用的方法，（2）扩展现有的卷曲螺旋设计能力以治疗更广泛的靶标，（3）测量广泛跨动物物种的bZIP卷曲螺旋相互作用并开发蛋白质-蛋白质相互作用特异性如何进化的模型，和（4）鉴定2-组分受体组氨酸激酶的相互作用特异性决定簇，并操纵这些决定簇以产生异特异性激酶。目标1和2的预测和设计方法将主要使用基于结构的技术。物理激励的能量函数将用于评估，并结合更多的经验方法进行测试。目标3涉及开发一种新的蛋白质-蛋白质相互作用测定法，并使用其测量> 10，000种可能的关联。这些数据将被应用于分析bZIP转录因子相互作用的演变，也将是有价值的目标1的计算方法进行测试。目的4检验原核组氨酸激酶主要同源缔合的假设，并提出确定其相互作用特异性的决定因素的计算和实验技术。总之，这四个目标包括一个综合方案的结构建模，生物物理和生物信息学分析和实验测试，旨在了解卷曲螺旋相互作用的特异性。 公共卫生相关性：蛋白质之间的相互作用对细胞的正常功能至关重要。重要的是，正确的复合形式和不正确的，即使存在许多密切相关的可能性。该项目解决了卷曲螺旋蛋白质的序列和结构如何决定其相互作用特性，并提出了使用计算技术预测和修改卷曲螺旋相互作用的方法。

DESCRIPTION (provided by applicant): The broad, long-term objectives of the proposed work are to understand how proteins establish interaction specificity at the level of individual domains and to capture this in models that can be used for computational prediction and design. The problem is central to issues of human health. Improper interactions among mutated or mis-regulated proteins can lead to disease, and achieving a deeper understanding of how this occurs is important. Further, the design of novel proteins or peptides to specifically inhibit native protein complexes would provide a route to future therapies. The interaction specificity problem can be simplified by focusing on a ubiquitous yet structurally simple protein-protein interaction motif: the alpha-helical coiled coil. Coiled coils occur throughout the proteomes of all species and are associated with a wide variety of functions. Their sequence and structural properties make them tractable for computational analysis, and coiled coils are also convenient for experimental study using biophysical methods. The proposed research involves collecting systematic experimental interaction data and using it to develop and test diverse computational techniques for predicting interactions. Computational methods will also be developed for designing coiled-coil-like peptides, and experiments are proposed to characterize the designs. The specific aims of this proposal are: (1) To test and improve methods for predicting coiled-coil structures, energies and interactions, (2) To extend existing coiled-coil design capabilities to treat a broader range of targets, (3) To measure bZIP coiled-coil interactions broadly across animal species and to develop a model of how protein- protein interaction specificity can evolve, and (4) To identify interaction specificity determinants of 2- component receptor histidine kinases and manipulate these to generate heterospecific kinases. The prediction and design methods of Aims 1 and 2 will use primarily structure-based techniques. Physically motivated energy functions will be used for evaluation, and also tested in conjunction with more empirical approaches. Aim 3 involves the development of a new protein-protein interaction assay and its use to measure >10,000 possible associations. These data will be applied to analyze the evolution of bZIP transcription factor interactions and will also be valuable for testing the computational methods of Aim 1. Aim 4 tests the hypothesis that prokaryotic histidine kinases primarily homoassociate, and proposes computational and experimental techniques for identifying determinants of their interaction specificity. Together, the four aims comprise an integrated program of structural modeling, biophysical and bioinformatic analysis and experimental testing aimed at understanding coiled-coil interaction specificity. PUBLIC HEALTH RELEVANCE: Interactions between proteins are essential to the proper functioning of cells. It is important that the correct complexes form and the incorrect ones do not, even when many closely related possibilities exist. This project addresses how the sequences and structures of coiled-coil proteins determine their interaction properties, and proposes methods for predicting and modifying coiled-coil interactions using computational techniques.