ArticleBMC bioinformatics2010
Modular composition predicts kinase/substrate interactions.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A Proteome-wide Domain-centric Perspective on Protein Phosphorylation.Molecular & cellular proteomics : MCP · 2014Article
- Human protein reference database and human proteinpedia as discovery resources for molecular biotechnology.Molecular biotechnology · 2011Article
- Article
- Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components.PLoS computational biology · 2010Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPhosphorylation events direct the flow of signals and metabolites along cellular protein networks. Current annotations of kinase-substrate binding events are far from complete. In this study, we scanned the entire human protein sequences using the PROSITE domain annotation tool to identify patterns of domain composition in kinases and their substrates. We identified statistically enriched pairs of strings of domains (signature pairs) in kinase-substrate couples presented in the 2006 version of the PTM database.
resultsThe signature pairs enriched in kinase - substrate binding interactions turned out to be highly specific to kinase subtypes. The resulting list of signature pairs predicted kinase-substrate interactions in validation dataset not used in learning with high statistical accuracy.
conclusionsThe method presented here produces predictions of protein phosphorylation events with high accuracy and mid-level coverage. Our method can be used in expanding the currently available drafts of cell signaling pathways and thus will be an important tool in the development of combination drug therapies targeting complex diseases.
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