Functional Annotation of Natural and Disease Variants in Tryosine Kinases

 描述（由申请人提供）：蛋白酪氨酸激酶是动态分子开关，其在催化“开”和“关”状态之间切换以打开和关闭负责细胞生长和存活的信号。虽然酪氨酸激酶开关在正常状态下受到多种结构机制的严格调节，但在许多疾病状态下，开关部分由于酪氨酸激酶结构域中的突变而永久打开或关闭。虽然基因组测序研究已经揭示了许多不同疾病类型的酪氨酸激酶的突变模式，但理解这些突变的结构和功能影响是一个挑战，因为许多复发性突变发生在远离活性位点（远端突变）的地方，并且导致酪氨酸激酶变构调控复杂模式的残基网络尚未完全理解。我们的长期目标是使用计算和实验方法的组合来了解蛋白激酶中连接序列，结构，功能，调节和疾病的关系。我们的目标在这个建议，这是下一个合乎逻辑的步骤，实现我们的长期目标，是描绘的残基相互作用网络，有助于酪氨酸激酶的变构调节的独特模式，并开发一个计算框架，预测突变的影响，使用编码在三维结构中的进化和变构特性。中心假设是远端突变改变酪氨酸激酶中进化上保守的变构网络，并且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影响提供背景。具体目标是：* 识别和表征与紧密变构控制相关的天然序列和结构变体 为了开发一个预测突变对激酶激活的影响的计算框架，并使用选定的受体酪氨酸激酶作为模型系统来实验验证计算预测，这些目标的成功完成有望揭示酪氨酸激酶结构域中推定的变构位点中的新型激活突变，并为功能研究确定关键残基和相互作用。反过来，这些结果预计将通过加速突变酪氨酸激酶组的功能表征产生重大的生物医学影响，突变酪氨酸激酶组正在成为个性化医疗的主要目标。最后，通过提供基因组测序研究中发现的突变的详细机制注释，该提案将解决转化医学中将基因组发现转化为治疗策略的基本NIH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.