Predicting CDK Targets Using Phosphorylation Clusters
Author Information
Author(s): Moses Alan M, Hériché Jean-Karim, Durbin Richard
Primary Institution: Wellcome Trust Sanger Institute
Hypothesis
Can clustering of phosphorylation site recognition motifs predict the targets of cyclin-dependent kinases?
Conclusion
The study introduces a computational strategy that successfully predicts cyclin-dependent kinase targets by identifying clusters of consensus motifs in protein sequences.
Supporting Evidence
- CDK consensus motifs are frequently clustered in substrate proteins.
- The method predicts new biologically interesting candidates.
- Statistical tests show significant enrichment of strong consensus matches in known CDK targets.
Takeaway
Scientists found that certain patterns in proteins can help guess which ones are affected by specific enzymes that control cell functions.
Methodology
The study used computational methods to analyze protein sequences for clusters of CDK consensus motifs.
Potential Biases
Potential bias in identifying known targets may affect the results.
Limitations
The method cannot distinguish between targets of different cyclins or other kinases.
Participant Demographics
The study focused on Saccharomyces cerevisiae proteins.
Statistical Information
P-Value
1.2 × 10-9
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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