Copper(I)-nitrene platform for chemoproteomic profiling of methionine.

Methionine plays a critical role in various biological and cell regulatory processes, making its chemoproteomic profiling indispensable for exploring its functions and potential in protein therapeutics. Building on the principle of rapid oxidation of methionine, we report Copper(I)-Nitrene Platform for robust, and selective labeling of methionine to generate stable sulfonyl sulfimide conjugates under physiological conditions. We demonstrate the versatility of this platform to label methionine in bioactive peptides, intact proteins (6.5-79.5 kDa), and proteins in complex cell lysate mixtures with varying payloads. We discover ligandable proteins and sites harboring hyperreactive methionine within the human proteome. Furthermore, this has been utilized to profile oxidation-sensitive methionine residues, which might increase our understanding of the protective role of methionine in diseases associated with elevated levels of reactive oxygen species. The Copper(I)-Nitrene Platform allows labeling methionine residues in live cancer cells, observing minimal cytotoxic effects and achieving dose-dependent labeling. Confocal imaging further reveals the spatial distribution of modified proteins within the cell membrane, cytoplasm, and nucleus, underscoring the platform's potential in profiling the cellular interactome.

ProTargetMiner as a proteome signature library of anticancer molecules for functional discovery.

Deconvolution of targets and action mechanisms of anticancer compounds is fundamental in drug development. Here, we report on ProTargetMiner as a publicly available expandable proteome signature library of anticancer molecules in cancer cell lines. Based on 287 A549 adenocarcinoma proteomes affected by 56 compounds, the main dataset contains 7,328 proteins and 1,307,859 refined protein-drug pairs. These proteomic signatures cluster by compound targets and action mechanisms. The targets and mechanistic proteins are deconvoluted by partial least square modeling, provided through the website http://protargetminer.genexplain.com. For 9 molecules representing the most diverse mechanisms and the common cancer cell lines MCF-7, RKO and A549, deep proteome datasets are obtained. Combining data from the three cell lines highlights common drug targets and cell-specific differences. The database can be easily extended and merged with new compound signatures. ProTargetMiner serves as a chemical proteomics resource for the cancer research community, and can become a valuable tool in drug discovery.