Structural basis and prediction of substrate specificity in protein serine/threonine kinases.
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 serinethreonine 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.
Brinkworth
Ross I
RI
Department of Biochemistry and Molecular Biology and Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia.
Breinl
Robert A
RA
Kobe
Bostjan
B
D000595:Amino Acid Sequence; D001665:Binding Sites; D002453:Cell Cycle; D016384:Consensus Sequence; D017868:Cyclic AMP-Dependent Protein Kinases / Q000737:chemistry / Q000378:metabolism; D004249:DNA Damage; D030562:Databases, Protein; D008954:Models, Biological; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009842:Oligopeptides / Q000737:chemistry / Q000378:metabolism*; D017346:Protein Serine-Threonine Kinases / Q000737:chemistry* / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000166:cytology / Q000201:enzymology / Q000235:genetics; D015398:Signal Transduction; D012984:Software; D013379:Substrate Specificity
D009842:Oligopeptides; D017346:Protein Serine-Threonine Kinases; D017868:Cyclic AMP-Dependent Protein Kinases