Improvement of Capture Compound Mass Spectrometry Technology (CCMS) for the Profiling of Human Kinases by Combination with 2D LC-MS/MS

An increasingly popular and promising field in functional proteomics is the isolation of proteome subsets based on small molecule-protein interactions. One platform approach in this field are Capture Compounds that contain a small molecule of interest to bind target proteins, a photo-activatable reactivity function to covalently trap bound proteins, and a sorting function to isolate captured protein conjugates from complex biological samples for direct protein identification by liquid chromatography/mass spectrometry (nLC-MS/MS). In this study we used staurosporine as a selectivity group for analysis in HepG2 cells derived from human liver. In the present study, we combined the functional isolation of kinases with different separation workflows of automated split-free nanoflow liquid chromatography prior to mass spectrometric analysis. Two different CCMS setups, CCMS technology combined with 1D LC-MS and 2D LC-MS, were compared regarding the total number of kinase identifications. By extending the chromatographic separation of the tryptic digested captured proteins from 1D LC linear gradients to 2D LC we were able to identify 97 kinases. This result is similar to the 1D LC setup we previously reported but this time 4 times less input material was needed. This makes CCMS of kinases an even more powerful tool for the proteomic profiling of this important protein family

Identification of Potential Off-target Toxicity Liabilities of Catechol‑<i>O</i>‑methyltransferase Inhibitors by Differential Competition Capture Compound Mass Spectrometry

Structurally related inhibitors of a shared therapeutic target may differ regarding potential toxicity issues that are caused by different off-target bindings. We devised a differential competition capture compound mass spectrometry (dCCMS) strategy to effectively differentiate off-target profiles. Tolcapone and entacapone are potent inhibitors of catechol-<i>O</i>-methyl transferase (COMT) for the treatment of Parkinson’s disease. Tolcapone is also known for its hepatotoxic side effects even though it is therapeutically more potent than entacapone. Here, we identified 3-hydroxyisobutyryl-CoA hydrolase (HIBCH) as a possible toxicity-causing off-target of tolcapone, and this protein is not bound by the less toxic COMT inhibitor entacapone. Moreover, two novel compounds from a focused library synthesized in-house, <i>N</i>²,<i>N</i>²,<i>N</i>³,<i>N</i>³-tetraethyl-6,7-dihydroxy-5-nitronaphthalene-2,3-dicarboxamide and 5-(3,4-dihydroxy-5-nitrobenzylidene)-3-ethylthiazolidine-2,4-dione, were utilized to gain insight into the structure–activity relationships in binding to COMT and the novel off-target HIBCH. These compounds, especially <i>N</i>²,<i>N</i>²,<i>N</i>³,<i>N</i>³-tetraethyl-6,7-dihydroxy-5-nitronaphthalene-2,3-dicarboxamide, could serve as starting point for the development of improved and more specific COMT inhibitors

Dabigatran and Dabigatran Ethyl Ester: Potent Inhibitors of Ribosyldihydronicotinamide Dehydrogenase (NQO2)

Recent studies have revealed that compounds believed to be highly selective frequently address multiple target proteins. We investigated the protein interaction profile of the widely prescribed thrombin inhibitor dabigatran (<b>1</b>), resulting in the identification and subsequent characterization of an additional target enzyme. Our findings are based on an unbiased functional proteomics approach called capture compound mass spectrometry (CCMS) and were confirmed by independent biological assays. <b>1</b> was shown to specifically bind ribosyldihydronicotinamide dehydrogenase (NQO2), a detoxification oxidoreductase. Molecular dockings predicted and biological experiments confirmed that dabigatran ethyl ester (<b>2</b>) inhibits NQO2 even more effectively than the parent <b>1</b> itself. Our data show that <b>1</b> and <b>2</b> are inhibitors of NQO2, thereby revealing a possible new aspect in the mode of action of <b>1</b>. We present a workflow employing chemical proteomics, molecular modeling, and functional assays by which a compound’s protein-interaction profile can be determined and used to tune the binding affinity