Uncovering Phosphorylation-Based Specificities through Functional Interaction Networks.

ABSTRACT: Protein kinases are an important class of enzymes involved in the phosphorylation of their targets, which regulate key cellular processes and are typically mediated by a specificity for certain residues around the target phospho-acceptor residue. While efforts have been made to identify such specificities, only ∼30% of human kinases have a significant number of known binding sites. We describe a computational method that utilizes functional interaction data and phosphorylation data to predict specificities of kinases. We applied this method to human kinases to predict substrate preferences for 57% of all known kinases and show that we are able to reconstruct well-known specificities. We used an in vitro mass spectrometry approach to validate four understudied kinases and show that predicte

SUBMITTER: Wagih O 

PROVIDER: S-EPMC4762521 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature