![]() ![]() Furthermore, it is possible that in certain cases, different kinases may have partially overlapping specificity, so that a single acceptor residue can be phosphorylated by more than one kinase. Other kinases require restraints that may be distal to the recognition site, or consensus motif. In some cases a particular kinase may require its substrate to have a highly stringent recognition site, whereas other kinases may be relatively promiscuous. A major difficulty in protein phosphorylation prediction stems from the fact that each kinase has its own particular specificity determinants. The somewhat limited success of current phosphorylation prediction algorithms likely arises from the very large number and variety of both kinases and potential phosphate acceptors (Ser, Thr and Tyr residues). Phosphorylation prediction algorithms must select, from all amino acid sequence space, a subset of amino acid sequences that are able to interact with one or more kinases as phosphate acceptors. Therefore, a computational tool that accurately predicts phosphorylation events could contribute to a more complete understanding of cell function. Networks of phosphorylation-induced signaling can result in complex effects such as signal amplification, feedback inhibition or induction of cyclical oscillation between different cellular states –. For example, phosphorylation can create docking sites to mediate protein interactions, modify signal sequences on proteins to regulate their subcellular localization, or activate enzymes by bringing their active sites into proper alignment. The addition of phosphate, which is a sterically bulky and negatively charged moiety, can alter a protein's biochemical properties and affect its structure and activity. The reversible modification of proteins by covalent addition and removal of phosphate is a major means by which cellular function is regulated. Finally, we directly detected in vivo phosphorylation at Cdk motifs for selected putative substrates using mass spectrometry. To corroborate our model, we compared its predictions with three experimentally independent Cdk proteomic datasets and found significant overlap. The present strategy defines a subset of the proteome that is highly enriched for Cdk substrates, as validated by comparing it to a set of bona fide, published, experimentally characterized Cdk substrates which was to our knowledge, comprehensive at the time of writing. This restraint reflects the observation that many known Cdk substrates contain multiple clustered phosphorylation sites. Thus, we define the local sequence motifs that represent the Cdc28 phosphorylation sites and subsequently model clustering of these motifs within the protein sequences. In the present procedure, we model Cdk substrates based on both local and global characteristics of the substrates. Currently, most computational phosphorylation site prediction procedures focus solely on local sequence characteristics. Here, we present a novel computational procedure to predict substrates of the cyclin-dependent kinase Cdc28 (Cdk1) in the Saccharomyces cerevisiae. Phosphorylation by Cdks directs the cell cycle by modifying the function of regulators of key processes such as DNA replication and mitotic progression. Protein phosphorylation, mediated by a family of enzymes called cyclin-dependent kinases (Cdks), plays a central role in the cell-division cycle of eukaryotes. ![]()
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