Prediction of substrate sites for protein phosphatases 1B, SHP-1, and SHP-2 based on sequence features.

Tyrosine phosphorylation plays crucial roles in numerous physiological processes. The level of phosphorylation state depends on the combined action of protein tyrosine kinases and protein tyrosine phosphatases. Detection of possible phosphorylation and dephosphorylation sites can provide useful information to the functional studies of relevant proteins. Several studies have focused on the identification of protein tyrosine kinase substrates. However, compared with protein tyrosine kinases, the prediction of protein tyrosine phosphatase substrates involved in the balance of protein phosphorylation level falls behind. This paper described a method that utilized the k-nearest neighbor algorithm to identity the substrate sites of three protein tyrosine phosphatases based on the sequence features of manually collected dephosphorylation sites. In the performance evaluation, both sensitivities and specificities could reach above 75% for all three protein tyrosine phosphatases. Finally, the method was applied on a set of known tyrosine phosphorylation sites to search for candidate substrates.