Activity-based protein profiling (ABPP) has emerged as a powerful and versatile tool to enable annotation of protein functions and discovery of targets of bioactive ligands in complex biological systems. It utilizes chemical probes to covalently label functional sites in proteins so that they can be enriched for mass spectrometry (MS)-based quantitative proteomics analysis. However, the semistochastic nature of datadependent acquisition and high cost associated with isotopically encoded quantification reagents compromise the power of ABPP in multidimensional analysis and high-throughput screening, when a large number of samples need to be quantified in parallel. Here, we combine the data-independent acquisition (DIA) MS with ABPP to develop an efficient label-free quantitative chemical proteomic method, DIA-ABPP, with good reproducibility and high accuracy for high-throughput quantification. We demonstrated the power of DIA-ABPP for comprehensive profiling of functional cysteineome in three distinct applications, including dosedependent quantification of cysteines' sensitivity toward a reactive metabolite, screening of ligandable cysteines with a covalent fragment library, and profiling of cysteinome fluctuation in circadian clock cycles. DIA-ABPP will open new opportunities for indepth and multidimensional profiling of functional proteomes and interactions with bioactive small molecules in complex biological systems.
Activity-based protein profiling (ABPP) has emerged as a powerful functional chemoproteomic strategy which enables global profiling of proteome reactivity toward bioactive small molecules in complex biological and/or pathological processes. To quantify the degree of reactivity in a site-specific manner, an isotopic tandem orthogonal proteolysis (isoTOP)-ABPP strategy has been developed; however, the high cost and long workflow associated with the synthesis of isotopically labeled cleavable tags limit its wide use. Herein, we combined reductive dimethyl labeling with TOP-ABPP to develop a fast, affordable, and efficient method, termed "rdTOP-ABPP", for quantitative chemical proteomics with site-specific precision and triplex quantification. The rdTOP-ABPP method shows high accuracy and precision, good reproducibility, and better capacity for site identification and quantification and is highly compatible with many commercially available cleavable tags. We demonstrated the power of rdTOP-ABPP by profiling the target of (1 S,3 R)-RSL3, a canonical inducer for cell ferroptosis, and provided the first global portrait of its proteome reactivity in a quantitative and site-specific manner.
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