Structural basis and prediction of substrate specificity in protein serine/threonine kinases

Abstract

The large number of protein kinases makes it impractical to determine their specificities and substrates experimentally. Using the available crystal structures, molecular modeling, and sequence analyses of kinases and substrates, we developed a set of rules governing the binding of a heptapeptide substrate motif (surrounding the phosphorylation site) to the kinase and implemented these rules in a web-interfaced program for automated prediction of optimal substrate peptides, taking only the amino acid sequence of a protein kinase as input. We show the utility of the method by analyzing yeast cell cycle control and DNA damage checkpoint pathways. Our method is the only available predictive method generally applicable for identifying possible substrate proteins for protein serine͞threonine kinases and helps in silico construction of signaling pathways. The accuracy of prediction is comparable to the accuracy of data from systematic large-scale experimental approaches.

Amino acids determining enzyme-substrate specificity in prokaryotic and eukaryotic protein kinases

“…Our method also assumes similar binding geometries in most PKsubstrate pairs. This assumption is supported by available crystal structures (22,32), experiments with peptide libraries (16)(17)(18), and recent computational studies (33).…”

Kinase peptide specificity: Improved determination and relevance to protein phosphorylation

“…The results provide powerful validation that PSSMs can accurately describe the kinase specificity of PKC-␦ and - (Fig. 3) and that PSSMs derived by our PS-OPL method are more accurate than the corresponding PSSMs derived by other available methods (12,17). Because the difference between our predictions and the ASP-OPL-based predictions is the experimentally determined data in the corresponding PSSM, the superior predictions for PKC-␦ and -must reflect greater accuracy of the PS-OPLbased PSSMs.…”

Navigating cancer network attractors for tumor-specific therapy

“…In line with their importance, network-attacking mutations have attracted more attention in recent years [43][44][45][46][47][48] . Moreover, information has been accumulating steadily about how specificity in signaling networks and modular protein domains emerges [49][50][51] , leading to the definition of determinants of specificity in protein domains 52,53 . These determinants, sometimes referred to as specificitydetermining residues, are residues that can lead to substrate specificity changes after mutation.…”