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PLoS One. 2010 Dec 29;5(12):e14444. doi: 10.1371/journal.pone.0014444.

Large-scale discovery and characterization of protein regulatory motifs in eukaryotes.

Author information

  • 1Department of Molecular Biology, Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America.

Abstract

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.

PMID:
21206902
[PubMed - indexed for MEDLINE]
PMCID:
PMC3012054
Free PMC Article

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