Prediction of kinase-specific phosphorylation sites through an integrative model of protein context and sequence

Abstract

Identifying kinase substrates and the specific phosphorylation sites they regulate is an important factor in understanding protein function regulation and signalling pathways. Computational prediction of kinase targets – assigning kinases to putative substrates, and selecting from protein sequence the sites that kinases can phosphorylate – requires the consideration of both the cellular context that kinases operate in, as well as their binding affinity. This consideration enables investigation of how phosphorylation influences a range of biological processes. We report here a novel probabilistic model for classifying kinase-specific phosphorylation sites from sequence across three model orga..