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  Discovery of candidate KEN-box motifs using cell cycle keyword enrichment combined with native disorder prediction and motif conservation

Sushama, M., Gilles, T., Chenna, R., Chica, C., & Gibson, T. J. (2008). Discovery of candidate KEN-box motifs using cell cycle keyword enrichment combined with native disorder prediction and motif conservation. Bioinformatics, 24(4), 453-457. doi:10.1093/bioinformatics/btm624.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-808E-D Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-808F-B
Genre: Journal Article

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 Creators:
Sushama, Michael, Author
Gilles, Travé, Author
Chenna, Ramu1, Author              
Chica, Claudia, Author
Gibson, Toby J., Author
Affiliations:
1Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              

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 Abstract: Motivation: KEN-box-mediated target selection is one of the mechanisms used in the proteasomal destruction of mitotic cell cycle proteins via the APC/C complex. While annotating the Eukaryotic Linear Motif resource (ELM, http://elm.eu.org/), we found that KEN motifs were significantly enriched in human protein entries with cell cycle keywords in the UniProt/Swiss-Prot database—implying that KEN-boxes might be more common than reported. Results: Matches to short linear motifs in protein database searches are not, per se, significant. KEN-box enrichment with cell cycle Gene Ontology terms suggests that collectively these motifs are functional but does not prove that any given instance is so. Candidates were surveyed for native disorder prediction using GlobPlot and IUPred and for motif conservation in homologues. Among >25 strong new candidates, the most notable are human HIPK2, CHFR, CDC27, Dab2, Upf2, kinesin Eg5, DNA Topoisomerase 1 and yeast Cdc5 and Swi5. A similar number of weaker candidates were present. These proteins have yet to be tested for APC/C targeted destruction, providing potential new avenues of research.

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Language(s): eng - English
 Dates: 2008-01-09
 Publication Status: Published in print
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Title: Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 24 (4) Sequence Number: - Start / End Page: 453 - 457 Identifier: ISSN: 1367-4803