High throughput multidimensional chemoproteomics for function-directed covalent target discovery - PROJECT SUMMARY/ABSTRACT Cysteine-reactive drugs are an exciting class of therapeutics that offer the benefits of high potency, occupancy and increased selectivity. Motivated by the clinical success of recent cancer therapeutics that engage specific cysteines, including neratinib and ibrutinib, the discovery of additional targets amenable to covalency is a burgeoning area for drug development. One strategy to find such targets is cysteine chemoproteomics, which uses mass spectrometry-based proteomics to mine the cellular proteome for potentially targetable cysteine residues. While cysteine chemoproteomic platforms are increasingly adopted for target discovery and mode of action studies, two unmet needs remain that together will increase the utility of this technology for cancer drug discovery applications: (1) improved sample throughput and (2) enhanced discovery of actionable cysteines, for which covalent labeling will clearly impact protein function. To this end, our team has already made substantial inroads into both of these challenges by establishing high throughput and low cost screening platforms and novel multi-dimensional chemoproteomic platforms that report cysteine-dependent changes in protein thermal stability, which provides a high throughput metric of likely cysteine functionality. Here we will build on this exciting proof- of-concept data by establishing enhanced sample preparation reagents that will further increase screening throughput by enhancing multiplexing capabilities compared to state of the art technology. Enabled by these custom reagents, we will establish a custom proteomics platform to pinpoint covalent labeling sites that alter protein thermal stability, which will provide a roadmap for prioritizing high value targets for further mode of action studies. To ensure the rigor of our technology, the proposed methods will be assessed relative to the state of the art, using rigorous performance metrics. Thus, our work will solve the bottleneck of cysteine prioritization, which will increase the conversion of initial hits to leads. More broadly, our unprecedented ultra-high coverage chemoproteomic platform will be paradigm shifting both for cysteine chemoproteomic sample processing, and more broadly for many proteomic applications that require analysis of many samples in parallel.
