This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Protein phosphorylation, mediated by a family of enzymes called cyclin-dependent kinases (Cdks), plays a central role in the cell-division cycle of eukaryotes. Phosphorylation by Cdks directs the cell cycle by modifying the function of regulators of key processes such as DNA replication and mitotic progression. Here, we present a novel computational procedure to predict substrates of the cyclin-dependent kinase Cdc28 (Cdk1) in the Saccharomyces cerevisiae. Currently, most computational phosphorylation site prediction procedures focus solely on local sequence characteristics. In the present procedure, we model Cdk substrates based on both local and global characteristics of the substrates. Thus, we define the local sequence motifs that represent the Cdc28 phosphorylation sites and subsequently model clustering of these motifs within the protein sequences. This restraint reflects the observation that many known Cdk substrates contain multiple clustered phosphorylation sites. The present strategy defines a subset of the proteome that is highly enriched for Cdk substrates, as validated by comparing it to a set of bona fide, published, experimentally characterized Cdk substrates which was to our knowledge, comprehensive at the time of writing. To corroborate our model, we compared its predictions with three experimentally independent Cdk proteomic datasets and found significant overlap. Finally, we directly detected in vivo phosphorylation at Cdk motifs for selected putative substrates using mass spectrometry. A manuscript describing this work has been published: Prediction of cyclin-dependent kinase phosphorylation substrates. Chang EJ, Begum R, Chait BT, Gaasterland T. PLoS ONE. 2007 Aug 1;2(7):e656

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR000862-36
Application #
7954087
Study Section
Special Emphasis Panel (ZRG1-BCMB-Q (40))
Project Start
2009-03-01
Project End
2010-02-28
Budget Start
2009-03-01
Budget End
2010-02-28
Support Year
36
Fiscal Year
2009
Total Cost
$1,190
Indirect Cost
Name
Rockefeller University
Department
Miscellaneous
Type
Other Domestic Higher Education
DUNS #
071037113
City
New York
State
NY
Country
United States
Zip Code
10065
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