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Molecular & Cellular Proteomics 6:537-547, 2007.
© 2007 by The American Society for Biochemistry and Molecular Biology, Inc.

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Technology

Proteomics Analysis of Protein Kinases by Target Class-selective Prefractionation and Tandem Mass Spectrometry ^*,S

Josef Wissing^,, Lothar Jänsch^,, Manfred Nimtz, Guido Dieterich, Renate Hornberger^¶, György Kéri^||,**, Jürgen Wehland and Henrik Daub^¶,

From the Department of Cell Biology, Helmholtz Centre for Infection Research (HZI), Inhoffenstrasse 7, 38124 Braunschweig, Germany, ^¶ Cell Signalling Group, Department of Molecular Biology, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany, ^|| Vichem Chemie Ltd., Herman Ottó u. 15, Budapest 1022, Hungary, and ^** Department of Medicinal Chemistry, Peptide Biochemistry Research Group, Semmelweis University, Puskin u. 9, Budapest 1088, Hungary

Protein kinases constitute a large superfamily of enzymes with key regulatory functions in nearly all signal transmission processes of eukaryotic cells. However, due to their relatively low abundance compared with the vast majority of cellular proteins, currently available proteomics techniques do not permit the comprehensive biochemical characterization of protein kinases. To address these limitations, we have developed a prefractionation strategy that uses a combination of immobilized low molecular weight inhibitors for the selective affinity capture of protein kinases. This approach resulted in the direct purification of cell type-specific sets of expressed protein kinases, and more than 140 different members of this enzyme family could be detected by LC-MS/MS. Furthermore the enrichment technique combined with phosphopeptide fractionation led to the identification of more than 200 different phosphorylation sites on protein kinases, which often remain occluded in global phosphoproteome analysis. As the phosphorylation states of protein kinases can provide a readout for the signaling activities within a cellular system, kinase-selective phosphoproteomics based on the procedures described here has the potential to become an important tool in signal transduction analysis.

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