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KINATEST-ID: A Pipeline To Develop Phosphorylation-Dependent Terbium Sensitizing Kinase Assays

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NIAID Data Ecosystem2026-03-08 收录
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https://figshare.com/articles/dataset/KINATEST_ID_A_Pipeline_To_Develop_Phosphorylation_Dependent_Terbium_Sensitizing_Kinase_Assays/2192638
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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.

非受体型蛋白酪氨酸激酶(Nonreceptor protein tyrosine kinases, NRTKs)对细胞稳态的维持至关重要,因此是当前药物研发的核心研究方向。可在酪氨酸磷酸化后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,但设计可区分不同酪氨酸激酶家族的适配底物仍是一项巨大挑战。尽管不同家族的非受体型蛋白酪氨酸激酶的底物偏好存在差异,但多数激酶的结构在家族间仍具有高度相似性。此外,由于尚未明确如何将序列选择性与金属离子结合特性相结合,基于镧系元素的激酶检测方法的开发受到阻碍,致使底物优化不得不依赖繁琐的迭代流程。我们借助来自内源性激酶底物的经人工整理注释的蛋白质组学数据,以及已知的铽离子(Tb³⁺)结合序列,构建了一套可推广的计算机模拟流程(in silico pipeline),该流程集成了生成、筛选、比对以及筛选最具激酶特异性的磷酸化依赖型铽离子增敏底物的工具。我们通过开发数种在激酶家族内具有选择性且适用于高通量筛选(high-throughput screening, HTS)的底物,验证了该方法的有效性。总体而言,该策略为几乎所有酪氨酸激酶开发高效、特异性的检测方法提供了一套标准化流程,这类检测方法可兼容基于镧系元素的高通量筛选检测技术。本流程集成的工具还具备被适配用于其他场景的肽段筛选的潜力,例如其他酶学检测或蛋白质结合配体的开发。
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2016-02-14
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