PhosphoPep-a phosphoproteome resource for systems biology research in Drosophila Kc167 cells

被引:154
作者
Bodenmiller, Bernd
Malmstrom, Johan
Gerrits, Bertran
Campbell, David
Lam, Henry
Schmidt, Alexander
Rinner, Oliver
Mueller, Lukas N.
Shannon, Paul T.
Pedrioli, Patrick G.
Panse, Christian
Lee, Hoo-Keun
Schlapbach, Ralph
Aebersold, Ruedi
机构
[1] Swiss Fed Inst Technol, Inst Mol Syst Biol, CH-8093 Zurich, Switzerland
[2] Zurich PhD Program Mol Life Sci, Zurich, Switzerland
[3] Swiss Fed Inst Technol, UZH, Funct Genom Ctr Zurich, Zurich, Switzerland
[4] Inst Syst Biol, Seattle, WA USA
[5] Swiss Fed Inst Technol, Competence Ctr Syst Physiol & Metab Dis, Zurich, Switzerland
[6] Swiss Fed Inst Technol, Inst Biochem, Zurich, Switzerland
[7] Univ Zurich, Fac Sci, Zurich, Switzerland
关键词
data integration; drosophila; interactive database; phosphoproteomics; systems biology;
D O I
10.1038/msb4100182
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The ability to analyze and understand the mechanisms by which cells process information is a key question of systems biology research. Such mechanisms critically depend on reversible phosphorylation of cellular proteins, a process that is catalyzed by protein kinases and phosphatases. Here, we present PhosphoPep, a database containing more than 10 000 unique high-confidence phosphorylation sites mapping to nearly 3500 gene models and 4600 distinct phosphoproteins of the Drosophila melanogaster Kc167 cell line. This constitutes the most comprehensive phosphorylation map of any single source to date. To enhance the utility of PhosphoPep, we also provide an array of software tools that allow users to browse through phosphorylation sites on single proteins or pathways, to easily integrate the data with other, external data types such as protein-protein interactions and to search the database via spectral matching. Finally, all data can be readily exported, for example, for targeted proteomics approaches and the data thus generated can be again validated using PhosphoPep, supporting iterative cycles of experimentation and analysis that are typical for systems biology research.
引用
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页数:11
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