End-to-End Throughput Chemical Proteomics for Photoaffinity Labeling Target Engagement and Deconvolution

Photoaffinity labeling (PAL) methodologies have proven
to be instrumental
for the unbiased deconvolution of protein–ligand binding events
in physiologically relevant systems. However, like other chemical
proteomic workflows, they are limited in many ways by time-intensive
sample manipulations and data acquisition techniques. Here, we describe
an approach to address this challenge through the innovation of a
carboxylate bead-based protein cleanup procedure to remove excess
small-molecule contaminants and couple it to plate-based, proteomic
sample processing as a semiautomated solution. The analysis of samples
via label-free, data-independent acquisition (DIA) techniques led
to significant improvements on a workflow time per sample basis over
current standard practices. Experiments utilizing three established
PAL ligands with known targets, (+)-JQ-1, lenalidomide, and dasatinib,
demonstrated the utility of having the flexibility to design experiments
with a myriad of variables. Data revealed that this workflow can enable
the confident identification and rank ordering of known and putative
targets with outstanding protein signal-to-background enrichment sensitivity.
This unified end-to-end throughput strategy for processing and analyzing
these complex samples could greatly facilitate efficient drug discovery
efforts and open up new opportunities in the chemical proteomics field.