KINATEST-ID: A Pipeline To Develop Phosphorylation-Dependent Terbium Sensitizing Kinase Assays
datasetposted on 2015-02-25, 00:00 authored by Andrew M. Lipchik, Minervo Perez, Scott Bolton, Vasin Dumrongprechachan, Steven B. Ouellette, Wei Cui, Laurie L. Parker
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 Tb3+-binding sequences to build a generalizable in silico pipeline with tools to generate, screen, align, and select potential phosphorylation-dependent Tb3+-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.
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sequence selectivitylanthanide ion luminescenceiterative substrate optimizationtyrosine kinasekinase substratestyrosine phosphorylationkinase activitytyrosine kinase familiesNRTKcurated proteomic dataenzyme assayskinase familiesPeptide substratesHTSsilico pipelinesubstrate preferencesmetal ion bindingdrug discovery efforts