蛋白质组学
仿形(计算机编程)
质谱法
定量蛋白质组学
小分子
计算生物学
化学
化学生物学
代谢组学
半胱氨酸
工作流程
计算机科学
色谱法
生物
生物化学
操作系统
基因
酶
数据库
出处
期刊:Methods in Enzymology
日期:2022-09-07
卷期号:: 295-322
标识
DOI:10.1016/bs.mie.2022.07.037
摘要
Chemical proteomics methods, such as activity-based protein profiling, have emerged as powerful and versatile tools to annotate the protein functions and targets of bioactive small molecules in complex biological systems. Incorporated with mass spectrometry (MS)-based quantitative proteomics method, changes of protein activities could be captured and investigated with site-specific precision. However, the semi-stochastic nature of data-dependent acquisition and high cost of the isotopic-labeled reagents make it challenging for chemical biology research to systematically and reproducibly analyze a large number of samples in multidimensional analysis and high-throughput screening. In this chapter, we describe an efficient quantitative chemical proteomic strategy, termed DIA-ABPP, with good reproducibility and high quantification accuracy. Cysteinome profiling was used as a proof-of-concept example with the detailed protocol to demonstrate the workflow of the DIA-ABPP method, including dose-dependent analysis of cysteines that are sensitive to modification by a reactive metabolite, screening of a cysteine-reactive fragment library, and profiling of circadian cysteinome fluctuation. This quantitative chemoproteomic strategy would provide an opportunity for in-depth multi-dimensional chemical proteomic profiling and illuminate the function of bioactive small molecules and proteins in complex biological systems.
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