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Issue 3, 2014
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Rapid profiling of protein kinase inhibitors by quantitative proteomics

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Abstract

The ability to determine structure–activity relationships (SAR) and identify cellular targets from cell lysates and tissues is of great utility for kinase inhibitor drug discovery. We describe a streamlined mass spectrometry-based chemoproteomics workflow to examine the SAR and target profiles of a small library of kinase inhibitors that consists of the drug dasatinib and a panel of general type II inhibitors. By combining a simplified affinity enrichment and on-bead protein digestion workflow with quantitative proteomics, we achieved sensitive and specific enrichment of target kinases using our small molecule probes. We applied the affinity matrices in competition experiments with soluble probes in HeLa cell lysates using less than 1 mg of protein per experiment. Each pull-down experiment was analyzed in a single nanoLC-MS run. Stringent selection criteria for target identification were applied to deduce 28 protein targets for dasatinib and 31 protein targets for our general type II kinase inhibitor in HeLa cell lysate. Additional kinase and protein targets were identified with the general type II inhibitor analogs, with small structural changes leading to divergent target profiles. We observed surprisingly high sequence coverage on some proteins, enabling further analyses of phosphorylation sites for several target kinases without additional sample processing. Our rapid workflow profiled cellular targets for six small molecules within a week, demonstrating that an unbiased proteomics screen of cellular targets yields valuable SAR information and may be incorporated at an early stage in kinase inhibitor development.

Graphical abstract: Rapid profiling of protein kinase inhibitors by quantitative proteomics

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Supplementary files

Article information


Submitted
23 Oct 2013
Accepted
06 Dec 2013
First published
11 Dec 2013

Med. Chem. Commun., 2014,5, 363-369
Article type
Concise Article

Rapid profiling of protein kinase inhibitors by quantitative proteomics

M. Golkowski, J. L. Brigham, B. G. K. Perera, G. S. Romano, D. J. Maly and S. Ong, Med. Chem. Commun., 2014, 5, 363
DOI: 10.1039/C3MD00315A

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