Prediction of functional phosphorylation sites by incorporating evolutionary information.
Protein phosphorylation is a ubiquitous protein post-translational modification, which plays an important role in cellular signaling systems underlying various physiological and pathological processes. Current in silico methods mainly focused on the prediction of phosphorylation sites, but rare methods considered whether a phosphorylation site is functional or not. Since functional phosphorylation sites are more valuable for further experimental research and a proportion of phosphorylation sites have no direct functional effects, the prediction of functional phosphorylation sites is quite necessary for this research area. Previous studies have shown that functional phosphorylation sites are more conserved than non-functional phosphorylation sites in evolution. Thus, in our method, we developed a web server by integrating existing phosphorylation site prediction methods, as well as both absolute and relative evolutionary conservation scores to predict the most likely functional phosphorylation sites. Using our method, we predicted the most likely functional sites of the human, rat and mouse proteomes and built a database for the predicted sites. By the analysis of overall prediction results, we demonstrated that protein phosphorylation plays an important role in all the enriched KEGG pathways. By the analysis of protein-specific prediction results, we demonstrated the usefulness of our method for individual protein studies. Our method would help to characterize the most likely functional phosphorylation sites for further studies in this research area.
Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
Shen
S
Niu
Zhen
Z
Wang
Dongya
D
Ge
Guoqing
G
Zhang
Yixue
Y
Li
D000818:Animals; D050760:Cyclin-Dependent Kinase Inhibitor p27 / Q000378:metabolism; D030562:Databases, Protein; D006801:Humans; D051379:Mice; D010766:Phosphorylation; D011506:Proteins / Q000378:metabolism*; D051381:Rats; D012984:Software; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism
D011506:Proteins; D016159:Tumor Suppressor Protein p53; D050760:Cyclin-Dependent Kinase Inhibitor p27