An Integral Activity-Based Protein Profiling Method for Higher Throughput Determination of Protein Target Sensitivity to Small Molecules

Activity-based
protein profiling (ABPP) is a chemoproteomic technique
that uses small molecule 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 diverse biological
samples, 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 (CoC),
a wide range of concentrations may be needed, particularly for chemicals
that lack potency or toxicity data. In this work, we present an integral
competitive ABPP method that enables target sensitivity determination
for different organophosphate (OP) pesticides as model toxicants.
Using previously developed OP-ABPs, we optimized conditions for tandem
mass tag (TMT) multiplexing of ABPP samples and compared conventional
competitive ABPP involving samples at discrete paraoxon concentrations
to pooled samples across that same concentration range. We then expanded
our approach to compare protein target sensitivities toward two additional
OP pesticides, chlorpyrifos oxon and malaoxon. The results showed
that differences in integral intensities for the pooled competition
sample can be used to evaluate the relative sensitivity of specific
proteins without increasing the overall number of samples. For 8 CoC
concentrations of interest, this strategy reduced the number of TMT
plexes and the corresponding number of LC–MS/MS analyses 3-fold.
We envision the integral ABPP (IABPP) method will provide a means
to screen diverse chemicals more rapidly to identify both high and
low sensitivity protein targets.