CAREER: Unraveling the Design Principles of Protein Kinases using an Evolutionary Systems Approach

智力优势：蛋白质磷酸化是细胞对环境信号做出反应的基本机制。在真核生物中，蛋白质磷酸化是由一个庞大而多样的蛋白激酶家族进行的，这些蛋白激酶在其调节模式中显示出显着的多样性和复杂性。蛋白激酶调控的复杂模式是数十亿年来自然选择作用于基因组序列的结果。尽管有超过100，000个来自不同生物体的蛋白激酶序列，但是，很少有人利用基因组序列中嵌入的进化信息来理解蛋白激酶机制的复杂性和多样性。该项目的总体目标是通过对蛋白激酶序列、结构和功能数据的定量和综合分析，生成可测试的蛋白激酶进化和调控模型。具体目标是（i）定量原核生物中真核生物和远缘真核生物样激酶之间的序列和结构相似性和差异，（ii）鉴定和实验表征作用于主要蛋白激酶组，特别是酪氨酸激酶的进化约束，酪氨酸激酶代表激酶结构域进化中的重要过渡态，和（iii）以本体论的形式提供蛋白激酶序列、结构和功能数据的概念表示。为了实现这些目标，该项目将使用一种新的进化系统方法，其中蛋白激酶调节和进化的机制模型将通过序列，结构和功能数据的定量和综合分析来建立和测试。该项目的完成将为实验研究提供新的可检验假设/模型，为蛋白激酶数据的大规模综合分析提供计算资源，并为理解其他信号传导领域调控的演变提供概念框架，从而产生重大影响。这个项目的主要教育目标是帮助学生了解生物学中进化和综合方法的重要性。为了实现这一目标，研究人员将开发和评估新的教育工具，用于教授本科生和研究生有关数据集成和数据挖掘。 这些工具将通过网络资源和出版物进行试点、评估、修订并广泛传播给本科教育工作者。研究人员将通过格鲁吉亚大学现有的培训计划为本科生和高中生提供研究培训，并通过与NSF REU真菌基因组学和计算生物学计划合作，将代表性不足的少数民族纳入教育和研究活动。 该项目的教育活动将促进高中和本科阶段的探究式学习，并为下一代科学家在综合生物学领域的职业生涯做好准备。

Intellectual Merit: Protein phosphorylation is a fundamental mechanism by which cells respond to environmental signals. In eukaryotes, protein phosphorylation is carried out by a large and diverse family of protein kinases, which display remarkable diversity and complexity in their modes of regulation. The complex modes of protein kinase regulation have evolved as a consequence of natural selection operating on genomic sequences for billions of years. Despite the availability of over 100,000 protein kinase sequences from diverse organisms, however, very little has been done to use the evolutionary information embedded in genomic sequences to understand the complexity and diversity of the protein kinase machinery. The overall goal of this project is to generate testable models of protein kinase evolution and regulation through quantitative and integrative analysis of protein kinase sequence, structure and functional data. Specific goals are to (i) quantify the sequence and structural similarities and differences between eukaryotic and distantly related eukaryotic-like kinases in prokaryotes, (ii) identify and experimentally characterize the evolutionary constraints acting on major protein kinase groups, in particular tyrosine kinases, which represent an important transition state in the evolution of the kinase domain, and (iii) provide conceptual representation of protein kinase sequence, structure and functional data in the form of an ontology. In order to accomplish these aims this project will use a novel evolutionary-systems approach in which mechanistic models of protein kinase regulation and evolution will be built and tested through quantitative and integrative analysis of sequence, structure and functional data. Accomplishing this project is expected to have a major impact by providing new testable hypotheses/models for experimental studies, a computational resource for large-scale integrative analysis of protein kinase data, and a conceptual framework for understanding the evolution of regulation in other signaling domains.Broader Impacts: The major educational goal of this project is to help students develop an understanding of the importance of evolutionary and integrative approaches in biology. To accomplish this goal, the investigator will develop and assess new educational tools useful for teaching undergraduate and graduate students about data integration and data mining. These tools will be piloted, assessed, revised and broadly disseminated to undergraduate educators through web-resources and publications. The investigator will provide research training for undergraduate and high school students through existing training programs at the University of Georgia, and incorporate under-represented minorities in educational and research activities by partnering with the NSF REU Fungal Genomics and Computational Biology program. The educational activities of this project will promote inquiry-based learning at the high school and undergraduate level, and prepare the next generation of scientists for careers in integrative biology.