Multiplexed proteomics-based kinase assay development

激酶是多种疾病环境中信号传导的中心枢纽，包括癌症、自身免疫性疾病、心脏病、 疾病，超越。对于可以简化多路复用测量的技术存在显著需求 使用高通量筛选和临床实验室兼容的读数， 翻译.我们开发了这些基于细胞的检测方法，设计了新的底物， 特定的读出技术，并在体外和基于细胞的测定中对其进行表征。通过前期工作，我们 建立了一个名为KINATEST-ID的计算机管道的原型，在该管道中识别激酶底物偏好， 对照其他“脱靶”激酶，然后基于预测的相容性设计新的肽 用一种读出技术并进行了实验测试。我们最初的迭代这个管道集中在酪氨酸 激酶和体外镧系元素荧光测定读出，其具有有限的多重性。质量 报告活细胞中激酶活性的细胞可递送激酶底物的光谱检测将提供 更高的多重性，但在以前的工作中，我们遇到了一个基本的物理化学限制，我们的 设计流水线：选择Tb 3+螯合序列产生偏向酸性氨基酸的底物 (e.g. D，E），其在标准MS分析中表现非常差。我们还发现，虽然我们可以预测生化 尽管对于具有高质量偏好数据的激酶而言，选择性的预测仍然是不充分的 因为大多数激酶缺乏这样的数据来相互交叉参照。这些障碍进一步限制了 开发用于基于细胞的激酶谱分析的底物的进展，特别是使用多重MS 侦测此外，为了更稳健地进行更高通量分析，测定的工作流程， 样品处理和MS检测需要简化。在目标1中，我们将扩展KINATEST-ID平台 功能，重点是MS检测。在目标2中，我们将开发多路复用的基于细胞的可递送基质 与同事合作，使用靶向平行反应监测（PRM）MS方法进行激酶测定， Cedars Sinai正在开发尖端的高通量蛋白质组学方法，这些方法是临床实验室- 兼容.这项工作将产生一个优化的平台，用于开发和实施MS兼容， 基于细胞的测定，使激酶活性谱在活细胞中，以及一个路径，以新的工具， 激酶。总的来说，这些工具将有很大的潜力影响基础研究，快速分析信号 活性和激酶抑制剂药物发现，最终转化为临床。

Kinases are a central hub for signaling in multiple disease settings, including cancer, autoimmune disease, heart disease, and beyond. There is significant need for technologies that could streamline multiplexed measurement of kinase activities in live cells using high throughput screening and clinical lab-compatible read-outs for future translation. We develop these kinds of cell-based assay approaches, designing novel substrates tuned to particular read-out technologies and characterize them in vitro and in cell-based assays. Through prior work, we prototyped an in silico pipeline called KINATEST-ID, in which kinase substrate preferences are identified, cross- checked against other “off-target” kinases, then novel peptides are designed based on predicted compatibility with a read-out technique and tested empirically. Our initial iterations of this pipeline have focused on tyrosine kinases and in vitro lanthanide fluorescence assay read-outs, which have limited multiplexability. Mass spectrometry detection of cell-deliverable kinase substrates that report kinase activity in live cells would provide far higher multiplexability, but in prior work we ran up against a fundamental physiochemical limitation of our design pipeline: selecting sequences for Tb3+ chelation produces substrates biased towards acidic amino acids (e.g. D, E) that ionize very poorly in standard MS analyses. We also found that while we could predict biochemical efficiency for kinases that had high-quality preference data available, prediction of selectivity is still inadequate because most kinases lack such data for cross-referencing against each other. These barriers have limited further progress on developing substrates for cell-based kinase profiling assays, particularly with multiplexed MS detection. Further, in order to be more robust for higher throughput analyses, the workflows for the assay, sample processing, and MS detection need to be simplified. In Aim 1, we will expand the KINATEST-ID platform functionality with a focus on MS detection. In Aim 2, we will develop multiplexed cell-based deliverable substrate kinase assays using targeted parallel reaction monitoring (PRM) MS methods in collaboration with colleagues at Cedars Sinai who are developing cutting edge, high throughput proteomics methods that are clinical lab- compatible. This work will produce an optimized platform for developing and implementing MS-compatible, cell-based assays enabling kinase activity profiling in live cells, as well as a path to new tools for understudied kinases. Overall, these tools will have high potential to impact both basic research for rapid profiling of signaling activities, and kinase inhibitor drug discovery with eventual translation to the clinic.