Multiplexed proteomics-based kinase assay development

激酶是多种疾病的信号中枢，包括癌症、自身免疫性疾病、心脏 疾病，甚至更多。对能够简化多路传输测量的技术的需求非常大 使用高通量筛选和临床实验室兼容读数来研究活细胞中的激酶活性以供将来使用 翻译。我们开发了这些基于细胞的分析方法，设计了新的底物来调整 具体的读出技术，并在体外和基于细胞的分析中对其进行表征。通过之前的工作，我们 建立了名为KINATEST-ID的电子管道中的原型，在该管道中，确定了激酶底物的偏好，交叉- 对照其他“非靶标”的蛋白激酶，然后根据预测的兼容性设计新的多肽 一种读出技术，并进行了经验测试。我们对这条流水线的最初迭代集中在酪氨酸上 激酶和体外镧系元素荧光分析读出，这些都限制了多重性。质量 报告活细胞中的激酶活性的细胞递送激酶底物的光谱检测将提供 更高的多工性，但在之前的工作中，我们遇到了我们 设计流水线：选择Tb3螯合序列产生偏向酸性氨基酸的底物 (例如，D、E)在标准的MS分析中电离很差。我们还发现，虽然我们可以预测生化 对于拥有高质量偏好数据的激酶来说，选择性的预测仍然是不够的 因为大多数激酶缺乏这样的数据来相互对照。这些障碍进一步限制了 基于细胞的激酶图谱分析底物的开发进展，特别是多重MS分析 侦测。此外，为了更稳健地进行更高吞吐量的分析，用于分析的工作流， 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 侧重于MS检测的功能。在目标2中，我们将开发基于细胞的多路传输底物 与同事合作，使用靶向平行反应监测(PRM)MS方法进行激酶分析，网址为 Cedars Sinai正在开发尖端的、高通量的蛋白质组学方法，这些方法正在进行临床实验室- 兼容。这项工作将为开发和实现MS兼容提供一个优化的平台， 基于细胞的分析，使活细胞中的激酶活性谱，以及为未被研究的新工具的途径 激活剂。总体而言，这些工具将对快速分析信令的基础研究产生很大影响 活性，以及激酶抑制剂药物的发现，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.