End-to-End\nThroughput Chemical Proteomics for Photoaffinity\nLabeling Target Engagement and Deconvolution

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