Large-Scale Discovery and Characterization of Protein Regulatory Motifs in Eukaryotes

Lieber, Daniel S.; Elemento, Olivier; Tavazoie, Saeed

doi:10.1371/journal.pone.0014444

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Large-Scale Discovery and Characterization of Protein Regulatory Motifs in Eukaryotes

Published Date:

Dec 29 2010

Publisher's site:

http://dx.doi.org/10.1371/journal.pone.0014444 New Site Icon

Source:

PLoS One. 5(12).

[PDF-856.95 KB]

Details:

Alternative Title:

PLoS One

Personal Author:

Lieber, Daniel S. ; Elemento, Olivier ; Tavazoie, Saeed ;

Description:

The increasing ability to generate large-scale, quantitative proteomic data has brought with it the challenge of analyzing such data to discover the sequence elements that underlie systems-level protein behavior. Here we show that short, linear protein motifs can be efficiently recovered from proteome-scale datasets such as sub-cellular localization, molecular function, half-life, and protein abundance data using an information theoretic approach. Using this approach, we have identified many known protein motifs, such as phosphorylation sites and localization signals, and discovered a large number of candidate elements. We estimate that ~80% of these are novel predictions in that they do not match a known motif in both sequence and biological context, suggesting that post-translational regulation of protein behavior is still largely unexplored. These predicted motifs, many of which display preferential association with specific biological pathways and non-random positioning in the linear protein sequence, provide focused hypotheses for experimental validation.

Subject:

[+]

Pubmed ID:

21206902

Pubmed Central ID:

PMC3012054

Document Type:

Journal Article

Funding:

1DP10D003787-01/DP/NCCDPHP CDC HHS/United States ; 2R01HG003219/HG/NHGRI NIH HHS/United States ; P50 GM071508/GM/NIGMS NIH HHS/United States ; R01 HG003219/HG/NHGRI NIH HHS/United States ;

Collection(s):

CDC Public Access

Main Document Checksum:

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