Lipchik Andrew M, Perez Minervo, Bolton Scott, Dumrongprechachan Vasin, Ouellette Steven B, Cui Wei, Parker Laurie L
Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Center for Cancer Research, Purdue University , West Lafayette, Indiana 47907.
J Am Chem Soc. 2015 Feb 25;137(7):2484-94. doi: 10.1021/ja507164a. Epub 2015 Feb 17.
Nonreceptor protein tyrosine kinases (NRTKs) are essential for cellular homeostasis and thus are a major focus of current drug discovery efforts. Peptide substrates that can enhance lanthanide ion luminescence upon tyrosine phosphorylation enable rapid, sensitive screening of kinase activity, however design of suitable substrates that can distinguish between tyrosine kinase families is a huge challenge. Despite their different substrate preferences, many NRTKs are structurally similar even between families. Furthermore, the development of lanthanide-based kinase assays is hampered by incomplete understanding of how to integrate sequence selectivity with metal ion binding, necessitating laborious iterative substrate optimization. We used curated proteomic data from endogenous kinase substrates and known Tb(3+)-binding sequences to build a generalizable in silico pipeline with tools to generate, screen, align, and select potential phosphorylation-dependent Tb(3+)-sensitizing substrates that are most likely to be kinase specific. We demonstrated the approach by developing several substrates that are selective within kinase families and amenable to high-throughput screening (HTS) applications. Overall, this strategy represents a pipeline for developing efficient and specific assays for virtually any tyrosine kinase that use HTS-compatible lanthanide-based detection. The tools provided in the pipeline also have the potential to be adapted to identify peptides for other purposes, including other enzyme assays or protein-binding ligands.
非受体蛋白酪氨酸激酶(NRTKs)对于细胞稳态至关重要,因此是当前药物研发工作的主要重点。酪氨酸磷酸化后能增强镧系离子发光的肽底物可实现激酶活性的快速、灵敏筛选,然而设计能区分酪氨酸激酶家族的合适底物是一项巨大挑战。尽管它们的底物偏好不同,但许多NRTKs在结构上即使在家族之间也很相似。此外,由于对如何将序列选择性与金属离子结合整合的理解不完整,基于镧系元素的激酶分析方法的开发受到阻碍,这就需要进行费力的迭代底物优化。我们利用来自内源性激酶底物的经过整理的蛋白质组学数据和已知的Tb(3+)结合序列,构建了一个通用的计算机模拟流程,使用工具来生成、筛选、比对和选择最有可能具有激酶特异性的潜在磷酸化依赖性Tb(3+)敏化底物。我们通过开发几种在激酶家族内具有选择性且适用于高通量筛选(HTS)应用的底物来证明了该方法。总体而言,该策略代表了一种为几乎任何酪氨酸激酶开发高效且特异的分析方法的流程,这些方法使用与HTS兼容的基于镧系元素的检测。该流程中提供的工具还有可能被改编用于识别其他用途的肽,包括其他酶分析或蛋白质结合配体。