Dataset Information

Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs.

ABSTRACT: Phosphorylation is a universal mechanism for regulating cell behavior in eukaryotes. Although protein kinases target short linear sequence motifs on their substrates, the rules for kinase substrate recognition are not completely understood. We used a rapid peptide screening approach to determine consensus phosphorylation site motifs targeted by 61 of the 122 kinases in Saccharomyces cerevisiae. By correlating these motifs with kinase primary sequence, we uncovered previously unappreciated rules for determining specificity within the kinase family, including a residue determining P-3 arginine specificity among members of the CMGC [CDK (cyclin-dependent kinase), MAPK (mitogen-activated protein kinase), GSK (glycogen synthase kinase), and CDK-like] group of kinases. Furthermore, computational scanning of the yeast proteome enabled the prediction of thousands of new kinase-substrate relationships. We experimentally verified several candidate substrates of the Prk1 family of kinases in vitro and in vivo and identified a protein substrate of the kinase Vhs1. Together, these results elucidate how kinase catalytic domains recognize their phosphorylation targets and suggest general avenues for the identification of previously unknown kinase substrates across eukaryotes.

SUBMITTER: Mok J

PROVIDER: S-EPMC2846625 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs.

Mok Janine J Kim Philip M PM Lam Hugo Y K HY Piccirillo Stacy S Zhou Xiuqiong X Jeschke Grace R GR Sheridan Douglas L DL Parker Sirlester A SA Desai Ved V Jwa Miri M Cameroni Elisabetta E Niu Hengyao H Good Matthew M Remenyi Attila A Ma Jia-Lin Nianhan JL Sheu Yi-Jun YJ Sassi Holly E HE Sopko Richelle R Chan Clarence S M CS De Virgilio Claudio C Hollingsworth Nancy M NM Lim Wendell A WA Stern David F DF Stillman Bruce B Andrews Brenda J BJ Gerstein Mark B MB Snyder Michael M Turk Benjamin E BE

Science signaling 20100216 109

Phosphorylation is a universal mechanism for regulating cell behavior in eukaryotes. Although protein kinases target short linear sequence motifs on their substrates, the rules for kinase substrate recognition are not completely understood. We used a rapid peptide screening approach to determine consensus phosphorylation site motifs targeted by 61 of the 122 kinases in Saccharomyces cerevisiae. By correlating these motifs with kinase primary sequence, we uncovered previously unappreciated rules ...[more]

PMID: 20159853

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Project description:BACKGROUND: Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. RESULTS: We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. CONCLUSION: While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structure-based P-site prediction method has been made available at (http://phos3d.mpimp-golm.mpg.de).

Dataset Information

Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs.

Publications

Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs.

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