Chemoproteomics has enabled the rapid and proteome-wide discovery of functional, redox-sensitive, and ligandable cysteine residues. Despite widespread adoption and considerable advances in both sample-preparation workflows and MS instrumentation, chemoproteomics experiments still typically only identify a small fraction of all cysteines encoded by the human genome. Here, we develop an optimized sample-preparation workflow that combines enhanced peptide labeling with singlepot, solid-phase-enhanced sample-preparation (SP3) to improve the recovery of biotinylated peptides, even from small sample sizes. By combining this improved workflow with on-line highfield asymmetric waveform ion mobility spectrometry (FAIMS) separation of labeled peptides, we achieve unprecedented coverage of > 14000 unique cysteines in a single-shot 70 min experiment. Showcasing the wide utility of the SP3-FAIMS chemoproteomic method, we find that it is also compatible with competitive small-molecule screening by isotopic tandem orthogonal proteolysis-activity-based protein profiling (isoTOP-ABPP). In aggregate, our analysis of 18 samples from seven cell lines identified 34225 unique cysteines using only~28 h of instrument time. The comprehensive spectral library and improved coverage provided by the SP3-FAIMS chemoproteomics method will provide the technical foundation for future studies aimed at deciphering the functions and druggability of the human cysteineome.

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Mass-spectrometry-based chemoproteomics has enabled the rapid and proteome-wide discovery of functional and potentially ’druggable’ hotspots in proteins. While numerous transformations are now available, chemoproteomic studies still rely overwhelmingly on copper­(I)-catalyzed azide–alkyne cycloaddition (CuAAC) or ’click’ chemistry. The absence of bio-orthogonal chemistries that are functionally equivalent and complementary to CuAAC for chemoproteomic applications has hindered the development of multiplexed chemoproteomic platforms capable of assaying multiple amino acid side chains in parallel. Here, we identify and optimize Suzuki–Miyaura cross-coupling conditions for activity-based protein profiling and mass-spectrometry-based chemoproteomics, including for target deconvolution and labeling site identification. Uniquely enabled by the observed orthogonality of palladium-catalyzed cross-coupling and CuAAC, we combine both reactions to achieve dual labeling. Multiplexed targeted deconvolution identified the protein targets of bifunctional cysteine- and lysine-reactive probes.

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The integration of proteomic, transcriptomic, and genetic variant annotation data will improve our understanding of genotypephenotype associations. Due, in part, to challenges associated with accurate inter-database mapping, such multi-omic studies have not extended to chemoproteomics, a method that measures the intrinsic reactivity and potential "druggability" of nucleophilic amino acid side chains. Here, we evaluated mapping approaches to match chemoproteomic-detected cysteine and lysine residues with their genetic coordinates. Our analysis revealed that database update cycles and reliance on stable identifiers can lead to pervasive misidentification of labeled residues. Enabled by this examination of mapping strategies, we then integrated our chemoproteomics data with computational methods for predicting genetic variant pathogenicity, which revealed that codons of highly reactive cysteines are enriched for genetic variants that are predicted to be more deleterious and allowed us to identify and functionally characterize a new damaging residue in the cysteine protease caspase-8. Our study provides a roadmap for more precise inter-database mapping and points to untapped opportunities to improve the predictive power of pathogenicity scores and to advance prioritization of putative druggable sites.