Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase

Background: The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the experimentally-derived data are sufficiently not complete for the reconstruction of signaling pathways. This problem can be solved by the network enrichment with predicted protein interactions. The previously published in silico method PAAS was applied for prediction of interactions between protein kinases and their substrates. Results: We used the method for recognition of the protein classes defined by the interaction with the same protein partners. 1021 protein kinase substrates classified by 45 kinases were extracted from the Phospho.ELM database and used as a training set. The reasonable accuracy of prediction calculated by leave-one-out cross validation procedure was observed in the majority of kinase-specificity classes. The random multiple splitting of the studied set onto the test and training set had a...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Boris Sobolev, Dmitry Filimonov, Alexey Lagunin, Alexey Zakharov, Olga Koborova, Alexander E. Kel, Vladimir Poroikov
• Keywords: BMCBI 2010, Kinase, Protein, Protein Partners