Protein phosphorylation, which is an important reversible mechanism in post-translational modifications, is involved in many essential cellular processes including cellular regulation, cellular signal pathways, metabolism, growth, differentiation and membrane transport (1). Phosphorylation of substrate sites at serine, threonine and tyrosine residues of eukaryotic proteins is performed by members of the protein kinase family. Additionally, phosphorylation on histidine plays an important role in signal transduction in prokaryotes known as two-component histidine kinase (2). It is estimated that one-third of proteins are phosphorylated and around half of kinome are disease- or cancer-related by chromosomal mapping (3). Experimental identifications of kinase-specific phosphorylation sites on substrates in vivo and in vitro are the foundation of understanding the mechanisms of phosphorylation dynamics and important for the biomedical drug design (4). However, these experiments are often time-consuming, labor-intensive and expensive. Therefore, in silico prediction of phosphorylation sites with high predictive performance could be a promising strategy to conduct preliminary analyses and could heavily reduce the number of potential targets that need further in vivo or in vitro confirmation.
