Predicting Cyclin-Dependent Kinase Phosphorylation Substrates
Author Information
Author(s): Chang Emmanuel J., Begum Rashida, Chait Brian T., Gaasterland Terry
Primary Institution: Department of Chemistry, York College of the City University of New York
Hypothesis
Cdk substrates might contain clusters of phosphorylation sites, and therefore that Cdk substrate prediction could be improved by optimizing the consensus motif sequence and selecting proteins whose sequences are enriched for repeats of that motif.
Conclusion
The study presents a model for predicting Cdk substrates that incorporates both local and global sequence characteristics, successfully identifying a significant number of putative substrates.
Supporting Evidence
- The model predicts a set of 91 candidate Cdk substrate proteins comprising 1.5% of the yeast proteome.
- 46 of the candidate substrates were defined as strong candidates, detected using the canonical-motif scoring method.
- 22 of the 35 candidates matched the top scoring in vitro substrates.
- Many of the candidate substrates were also predicted to contain Cdk phosphorylation sites using other leading phosphorylation detection algorithms.
Takeaway
The researchers created a computer program to find proteins that can be changed by a special process called phosphorylation, which helps cells divide properly.
Methodology
The study used a computational procedure to model Cdk substrates based on both local and global characteristics of the substrates, incorporating clustering of phosphorylation sites.
Potential Biases
The known set of phosphorylation sites for a particular kinase may be systematically biased, potentially leading to false negatives.
Limitations
The method may miss certain known substrates and is less comprehensive, yielding a set of likely candidate substrates rather than a complete list.
Digital Object Identifier (DOI)
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