We are entering the era of personalized genomics as breakthroughs in sequencing technology has made it possible to sequence or genotype individual person in an efficient and accurate manner. Preliminary results from HapMap and other similar projects have revealed the existence of tremendous genetic variations among world populations and among individuals. It is important to delineate the functional implication of such variations, i.e. whether they affect the stability and biochemical properties of proteins. It is also generally believed that the genetic variation is the main cause for different susceptibility to certain diseases or different response to therapeutic treatments. Understanding genetic variation in the context of human diseases thus holds the promise for "Personalized Medicine".

    We hypothesized that some non-synonymous variations might influence post-translational modifications (PTMs) of proteins (eg., phosphorylation), by changing the residue types of the target sites or key flanking amino acids. To address the issue, we carried out a genome-wide analysis of single nucleotide polymorphisms (SNPs) that could potentially influence protein phosphorylation characteristics in human. Here, we defined a phosSNP (Phosphorylation- related SNP) as a non-synonymous SNP (nsSNP) that affects the protein phosphorylation status. Due to the experimental data limitation, accurate prediction of phosphorylation sites is important for this study. During the past several years, we took great efforts on developing novel, accurate and fast-speed algorithms for prediction of kinase-specific phosphorylation sites. One of them is the GPS (Group-based Prediction System) series algorithm. The current GPS 2.0 software can predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. With this powerful tool, we computationally detected that approximately 70% of the reported nsSNPs are potential phosSNPs. More interestingly, ~74.6% of these potential phosSNPs might induce changes in protein kinase (PK) types in adjacent phosphorylation sites, rather than creating or removing phosphorylation sites directly. Taken together, we proposed that a large proportion of the nsSNPs might affect protein phosphorylation characteristics and play important roles in rewiring biological pathways.