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Updated: Jul 13, 2026
12:26
Identification of Cyclin-dependent Kinase 1 Specific Phosphorylation Sites by an In Vitro Kinase Assay
Published on: May 3, 2018
Prediction of cyclin-dependent kinase phosphorylation substrates
Emmanuel J Chang1, Rashida Begum, Brian T Chait
1Department of Chemistry, York College of the City University of New York, Jamaica, New York, United States of America; Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, Rockefeller University, New York, New York, United States of America. echang@york.cuny
Plos One
|August 2, 2007
Summary
This study introduces a new computational method to identify cyclin-dependent kinase (Cdk) substrates in yeast. The approach combines local and global protein features, improving predictions of phosphorylation sites critical for cell division.
Area of Science:
- Molecular Biology
- Computational Biology
- Biochemistry
Background:
- Cyclin-dependent kinases (Cdks) regulate eukaryotic cell division through protein phosphorylation.
- Accurate identification of Cdk substrates is crucial for understanding cell cycle control.
Purpose of the Study:
- To develop a novel computational procedure for predicting cyclin-dependent kinase Cdc28 (Cdk1) substrates in Saccharomyces cerevisiae.
- To improve substrate prediction by integrating both local and global protein characteristics.
Main Methods:
- Defined local sequence motifs for Cdc28 phosphorylation sites.
- Modeled clustering of these motifs within protein sequences.
- Validated predictions against known Cdk substrates and independent proteomic datasets.
- Confirmed in vivo phosphorylation using mass spectrometry.
Main Results:
- The novel procedure identified a proteome subset highly enriched for Cdk substrates.
- Predictions showed significant overlap with three independent Cdk proteomic datasets.
- Directly detected in vivo phosphorylation at predicted Cdk motifs in selected proteins.
Conclusions:
- The developed computational strategy effectively predicts Cdk substrates by considering both local and global protein features.
- This method enhances the understanding of cell cycle regulation by identifying key phosphorylation targets.
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