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. 1994 Nov 1;4(11):973-82.
doi: 10.1016/s0960-9822(00)00221-9.

Use of an oriented peptide library to determine the optimal substrates of protein kinases

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Use of an oriented peptide library to determine the optimal substrates of protein kinases

Z Songyang et al. Curr Biol. .

Abstract

Background: Phosphorylation by protein kinases is an important general mechanism for controlling intracellular processes, and plays an essential part in the signal transduction pathways that regulate cell growth in response to extracellular signals. A great number of protein kinases have been discovered, and the identification of their biological targets is still a very active research area. Protein kinases must have the appropriate substrate specificity to ensure that signals are transmitted correctly. Previous studies have demonstrated the importance of primary sequences within substrate proteins in determining protein kinase specificity, but efficient ways of identifying these sequences are lacking.

Results: We have developed a new technique for determining the substrate specificity of protein kinases, using an oriented library of more than 2.5 billion peptide substrates. In this approach, the consensus sequence of optimal substrates is determined by sequencing the mixture of products generated during a brief reaction with the kinase of interest. The optimal substrate predicted for cAMP-dependent protein kinase (PKA) by this technique is consistent with the sequences of known PKA substrates. The optimal sequences predicted for cyclin-dependent kinases (CDKs) cyclin B-Cdc2 and cyclin A-CDK2 also agree well with sites thought to be phosphorylated in vivo by these kinases. In addition, we determined the optimal substrate for SLK1, a homologue of the STE20 protein serine kinase of hitherto unknown substrate specificity. We also discuss a model incorporating the optimal cyclin B-Cdc2 substrate into the known crystal structure of this kinase.

Conclusions: Using the new technique we have developed, the sequence specificity of protein kinases can rapidly be predicted and, from this information, potential targets of the kinases can be identified.

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