Functional Annotation of Natural and Disease Variants in Tryosine Kinases

 说明(申请人提供)：蛋白酪氨酸激酶是一种动态的分子开关，在催化的“开”和“关”状态之间切换，开启和关闭负责细胞生长和存活的信号。虽然在正常状态下，酪氨酸激酶开关受到多种结构机制的严格调控，但在许多疾病状态下，该开关是永久开启或关闭的，部分原因是酪氨酸激酶域的突变。尽管基因组测序研究揭示了许多不同疾病类型的酪氨酸激酶的突变模式，但理解这些突变对结构和功能的影响是一个挑战，因为许多重复的突变发生在远离活性部位的地方(远端突变)，而且导致酪氨酸激酶变构调节复杂模式的残基网络还不完全清楚。我们的长期目标是使用计算和实验相结合的方法来理解蛋白激酶中序列、结构、功能、调节和疾病之间的联系。我们在这项提案中的目标是描绘有助于酪氨酸激酶变构调节的独特模式的残基相互作用网络，并开发一个利用三维结构中编码的进化和变构特性来预测突变影响的计算框架。中心假设是，远端突变改变了酪氨酸激酶进化上保守的变构网络，而描绘酪氨酸激酶特有的变构网络将为预测和测试疾病突变的影响提供背景。具体目标是：*识别和表征与严格变构控制有关的自然序列和结构变体 为建立预测突变对酪氨酸激酶活性的影响的计算框架，并以选定的受体酪氨酸激酶作为模型系统，通过实验验证计算预测，这些目标的成功完成有望揭示酪氨酸激酶结构域中可能的变构位点上的新的激活突变，并精确定位关键残基和相互作用，用于功能研究。这些结果反过来有望通过加速突变的酪氨酸蛋白激酶的功能特征产生重大的生物医学影响，突变的酪氨酸蛋白激酶正成为个性化药物的主要靶点。最后，通过提供基因组测序研究中确定的突变的详细机械注释，该提案将解决NIH将基因组发现转化为治疗策略的翻译医学中的一个基本路线图问题。

 DESCRIPTION (provided by applicant): Protein tyrosine kinases are dynamic molecular switches that toggle between a catalytically "on" and "off" state to turn on and off signals responsible for cell growth and survival. While the tyrosine kinase switch is tightly regulated by diverse array of structural mechanisms in normal states, in many disease states, the switch is permanently turned on or off due, in part, to mutations in the tyrosine kinase domain. Although genome sequencing studies have revealed the mutational patterns of tyrosine kinases from many different disease types, understanding the structural and functional impact of these mutations is a challenge because many recurrent mutations occur far from the active site (distal mutations) and the residue networks that contribute to the complex modes of tyrosine kinase allosteric regulation are not fully understood. Our long term goal is to understand the relationships connecting sequence, structure, function, regulation and disease in protein kinases using a combination of computational and experimental approaches. Our objective in this proposal, which is the next logical step toward attainment of our long-term goal, is to delineate the residue interaction networks that contribute to the unique modes of allosteric regulation in tyrosine kinases, and to develop a computational framework for predicting mutation impact using the evolutionary and allosteric properties encoded in three dimensional structures. The central hypothesis is that distal mutations alter evolutionarily conserved allosteric networks in tyrosine kinases, and delineating the allosteric networks unique to tyrosine kinases will provide context for predicting and testing disease mutation impact. The specific aims are: * To identify and characterize natural sequence and structural variants associated with tight allosteric control of tyrosine kinase activity * To develop a computational framework for predicting mutation impact on kinase activation and to experimentally validate computational predictions using selected receptor tyrosine kinases as model systems Successful completion of these aims is expected to reveal novel activating mutations in putative allosteric sites in the tyrosine kinase domain, and pinpoint key residues and interactions for functional studies. These outcomes, in turn, are expected to have major biomedical impact by accelerating the functional characterization of the mutated tyrosine kinome, which is emerging as a major target for personalized medicine. Finally, by providing detailed mechanistic annotation of mutations identified in genome sequencing studies, this proposal will address a fundamental NIH roadmap problem in translational medicine of converting genomic discoveries into therapeutic strategies.