The Role of 'Dynamics Motifs' in Modulating Specificity in PDZ Domains

描述(申请人提供)：PDZ结构域是人类蛋白质组中含量最丰富的蛋白质之一，是正常细胞生理所必需的。毫不奇怪，序列或表达上的错误会导致一系列疾病，从罕见的亚瑟氏综合征到结肠癌。然而，我们很难理解PDZ结构域驱动的杂乱的蛋白质-蛋白质相互作用，也没有明确的分子机制来详细说明PDZ结构域的配体识别。结构域表现出比预期更高的伙伴多样性，获得广泛的亲和力，并可能参与以前未知的变构信号。随着我们对PDZ结构域结合偏好的了解增加，从X射线结构中关于PDZ结构域特异性的想法被证明是不完整的。这是因为蛋白质不是静态结构，功能可能会立即从这些结构派生出来。相反，折叠的蛋白质是围绕一个平均结构动态变化的，从而产生一系列天然状态的构象。越来越多的证据表明，自然状态的运动或动力学对于功能是必不可少的。与蛋白质结构的其他方面一样，蛋白质动力学可能面临着优化或微调特定任务的进化压力。在这项提议中，我们的目标是将结构-功能轴的传统概念扩展到包括动力学。我们提出了以下假设：PDZ结构域配体的识别受其结构的侧链动力学(SCD)的特定分布，即其‘动力学基序’的调控。我们用三个目标来检验我们的假设。在目标1中，我们将了解SCD的进化压力，并将其与观察到的整个PDZ结构域家族的功能差异联系起来。在目标2中，我们试图找到相关的运动，因为它们是蛋白质中一种看似合理的机制，不需要构象变化就可以进行远程通讯。最后，在目标#3中，我们设计了一个“混合”的PDZ域，并测试动态中的长距离变化可能会如何改变接口绑定偏好。在这项提案中，我们希望确定SCD是否在确定PDZ结构域特异性方面发挥作用，并进一步确定动力学传递特异性的机制。更好地了解PDZ结构域结合可以进行合理的药物设计和蛋白质设计，这一基本原理推动了我们的研究。此外，PDZ结构域相互作用可以作为许多混杂蛋白质-蛋白质相互作用的模型系统。 公共卫生相关性：“动力学基序”在调节PDZ领域的特异性中的作用项目叙述--成功的药物靶向蛋白质-蛋白质相互作用的基础是理解这些界面的混杂性质的能力。这一拟议的研究路线解决了可以说是细胞最重要的一类蛋白质-蛋白质相互作用的混杂问题，即PDZ结构域家族的蛋白质相互作用。我们希望定义侧链动力学在决定PDZ结构域家族特异性中的作用，从而为改进药物和整体配体结合的理论预测提供一个框架。

DESCRIPTION (provided by applicant): PDZ domains are one of the most abundant proteins in the human proteome and are essential to normal cellular physiology. Not surprisingly, errors in either sequence or expression lead to a number of disease states ranging from the rare Usher's Syndrome to Colon Cancer. Yet, we struggle to understand the promiscuous protein-protein interactions which PDZ domains drive and there remains no clear molecular mechanism which details PDZ domain ligand recognition. Domains show a higher diversity in partners than predicted, access a wide range of affinities, and might engage in previously unknown allosteric signaling. As our knowledge of PDZ domain binding preferences increases, ideas about PDZ domains specificity from x-ray structure prove incomplete. This is because proteins are not static structures from which function might be immediately derived. Instead, folded proteins are dynamic around an average structure producing an ensemble of native state conformations. Increasing evidence demonstrates that the motions, or dynamics, of the native state are essential for function. Like other facets of protein architecture, protein dynamics may be under evolutionary pressure to optimize or fine tune a specific task. In this proposal, we have the objective of expanding the traditional notion of a structure-function axis to include dynamics. We put forth the following hypothesis: PDZ domain ligand recognition is modulated by the specific distribution of side-chain dynamics (SCD) of its structure, i.e. its 'dynamics motif'. We test our hypothesis with three aims. In Aim #1, we will access the evolutionary pressure on SCD and relate this to functional differences observed across the PDZ domain family. In Aim #2, we seek to find correlated motions as they are a plausible mechanism for long distance communication in proteins without the need for conformational change. And finally, in Aim #3, we design a 'hybrid' PDZ domain and test how long distance alterations in dynamics may alter the interface binding preferences. In this proposal, we expect to determine if SCD have a role in determining PDZ domain specificity, and further, the mechanism with which dynamics convey specificity. We are driven by the rationale that better understanding of PDZ domain binding allows for rational drug design and protein design. And further, PDZ domain interaction may serve as a model system for many promiscuous protein-protein interactions. PUBLIC HEALTH RELEVANCE: The Role of 'Dynamics Motifs' in Modulating Specificity in PDZ Domains Project Narrative - Fundamental to successful drug targeting of protein-protein interactions is the ability to understand the promiscuous nature of these interfaces. This proposed line of research addresses the promiscuity of arguably one of the cells' most important class of protein-protein interactions, those of the PDZ domain family. We expect to define a role for side-chain dynamics in determining specificity in the PDZ domain family, thus providing a framework for improved theoretical prediction of drug and overall ligand binding.