Abstract
Activity-based protein profiling (ABPP) is a chemoproteomic technique that uses chemical probes to label active enzymes selectively and covalently in complex proteomes. Competitive ABPP, which involves treatment of the active proteome with an analyte of interest, is especially powerful for profiling how small molecules impact specific protein activities. Advances in higher throughput workflows have made it possible to generate extensive competitive ABPP data across various biological systems and treatments, making this approach highly appealing for characterizing shared and unique proteins affected by perturbations such as drug or chemical exposures. To use the competitive ABPP approach effectively to understand potential adverse effects of chemicals of concern, a wide range of concentrations may be needed, particularly for chemicals that may lack toxicity data. In this work, we present an integral competitive ABPP method that enables target sensitivity differentiation across a wide range of concentrations for the model organophosphate (OP), paraoxon. Using previously developed OP-ABPs, we optimized conditions for tandem mass tag (TMT) multiplexing of ABPP samples and compared conventional competitive ABPP involving discrete samples at various paraoxon concentrations with pooling of samples across that same concentration range. The results show that small vs. large differences in integral intensities for the competitive sample can be used to distinguish low vs. high sensitivity proteins, respectively, without increasing the overall number of samples. We envision the integral ABPP method will provides a means to screen diverse chemicals more rapidly to identify both highly sensitive and less sensitive protein targets.
Supplementary materials
Title
Supporting Information
Description
Supporting figures including gel image of pooled competitive ABPP samples, additional conventional ABPP results for individual proteins, ABPP-TMT optimization results, and supporting methods for sample preparation and data analysis.
Actions