Multiplexed proteomics-based kinase assay development

基于多重蛋白质组学的激酶测定开发

基本信息

批准号：
10615893
负责人：
Laurie L. Parker
金额：
$ 31.38万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-05-01 至 2026-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10615893
关键词：
Acetylesterase Acidic Amino Acids Autoimmune Diseases Basic Science Biochemical Biological Biological Assay Biological Models Biology Cells Clinic Clinical Clinical Chemistry Collaborations Complex Data Detection Development Disease Drug Combinations Drug Targeting Enzymes Face Fluorescence Future Goals Heart Diseases In Vitro Lanthanoid Series Elements Malignant Neoplasms Mass Spectrum Analysis Measurement Measures Methods Methyltransferase Mixed Function Oxygenases Monitor Mutation Patients Peptides Performance Pharmaceutical Preparations Phosphopeptides Phosphotransferases Post-Translational Protein Processing Process Protein Tyrosine Kinase Proteomics Protocols documentation Publishing Ramp Reaction Reporting Resistance Running Sampling Signal Transduction Techniques Technology Testing Therapeutic Time Translations Treatment Effectiveness Treatment outcome Work assay development base chelation companion diagnostics design drug development drug discovery experimental study flexibility genomic biomarker high throughput analysis high throughput screening improved in silico inhibitor therapy instrumentation ionization kinase inhibitor novel novel therapeutics overexpression phosphoproteomics prediction algorithm preference protein biomarkers prototype screening tool

项目摘要

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.

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、心脏疾病迫切需要能够简化多重测量的技术。使用高通量筛选和临床实验室兼容的读数来分析活细胞中的激酶活性，以供未来使用我们开发了这些基于细胞的检测方法，设计了适合的新型底物。通过之前的工作，我们对特定的读出技术进行了体外和基于细胞的测定的表征。制作了一个名为 KINATEST-ID 的计算机管道原型，其中确定了激酶底物偏好、交叉与其他“脱靶”激酶进行检查，然后根据预测的兼容性设计新的肽我们对该管道的初始迭代主要集中在酪氨酸上。激酶和体外镧系元素荧光测定读数，其多重性有限。报告活细胞中激酶活性的细胞可传递激酶底物的光谱检测将提供更高的多重性，但在之前的工作中，我们遇到了我们的基本理化限制设计流程：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 MS 分析中电离效果非常差我们还发现，虽然我们可以预测生化。具有高质量偏好数据的激酶的效率，选择性的预测仍然不足因为大多数激酶缺乏相互交叉引用的数据，这些障碍进一步限制了这一点。开发基于细胞的激酶谱分析底物的进展，特别是多重 MS 此外，为了更稳健地进行更高通量的分析，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。在目标 2 中，我们将开发多种基于细胞的可交付底物。与同事合作，使用靶向平行反应监测 (PRM) MS 方法进行激酶测定 Cedars Sinai 正在开发尖端的、高通量的蛋白质组学方法，这些方法是临床实验室- 这项工作将产生一个用于开发和实施 MS 兼容的优化平台。基于细胞的检测能够在活细胞中进行激酶活性分析，并为尚未充分研究的人提供新工具的途径总的来说，这些工具将具有很大的潜力影响信号快速分析的基础研究。活动和激酶抑制剂药物发现并最终转化为临床。