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Bioinformatics Advance Access published online on November 7, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn569
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© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Discovery of Phosphorylation Motif Mixtures in Phosphoproteomics Data

Anna Ritz 1,*, Gregory Shakhnarovich 2, Arthur R. Salomon 3 and Benjamin J. Raphael 1,4,*

1Department of Computer Science, Brown University
2Toyota Technological Institute at Chicago
3Department of Chemistry and Molecular Biology, Cell Biology, and Biochemistry, Brown University
4Center for Computational Molecular Biology, Brown University

*To whom correspondence should be addressed. Anna Ritz, E-mail: aritz{at}cs.brown.edu, Benjamin J. Raphael, E-mail: braphael{at}cs.brown.edu


  Abstract

Motivation: Modification of proteins via phosphorylation is a primary mechanism for signal transduction in cells. Phosphorylation sites on proteins are determined in part through particular patterns, or motifs, present in the amino acid sequence.

Results: We describe an algorithm that simultaneously discovers multiple motifs in a set of peptides that were phosphorylated by several different kinases. Such sets of peptides are routinely produced in proteomics experiments. Our motif-finding algorithm uses the principle of minimum description length to determine a mixture of sequence motifs that distinguish a foreground set of phosphopeptides from a background set of unphosphorylated peptides. We show that our algorithm outperforms existing motif-finding algorithms on synthetic datasets consisting of mixtures of known phosphorylation sites. We also derive a motif specificity score that quantifies whether or not the phosphoproteins containing an instance of a motif have a significant number of known interactions with a specific kinase or phosphatase. Application of our motif-finding algorithm to recently published human and mouse proteomic studies recovers several known phosphorylation motifs and reveals a number of novel motifs that are enriched for interactions. Our tools provide a new approach for uncovering the sequence specificities of uncharacterized kinases or phosphatase.

Availability: Software is available at http:/cs.brown.edu/people/braphael/software.html

Contact: aritz{at}cs.brown.edu, braphael{at}cs.brown.edu

Associate Editor: Prof. Burkhard Rost

Received on August 1, 2008; revised on October 24, 2008; accepted on October 28, 2008

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