Exploiting publicly available biological and biochemical information for the discovery of novel short linear motifs.
KAUST Grant NumberKUK-I1-012-43
Permanent link to this recordhttp://hdl.handle.net/10754/596841
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AbstractThe function of proteins is often mediated by short linear segments of their amino acid sequence, called Short Linear Motifs or SLiMs, the identification of which can provide important information about a protein function. However, the short length of the motifs and their variable degree of conservation makes their identification hard since it is difficult to correctly estimate the statistical significance of their occurrence. Consequently, only a small fraction of them have been discovered so far. We describe here an approach for the discovery of SLiMs based on their occurrence in evolutionarily unrelated proteins belonging to the same biological, signalling or metabolic pathway and give specific examples of its effectiveness in both rediscovering known motifs and in discovering novel ones. An automatic implementation of the procedure, available for download, allows significant motifs to be identified, automatically annotated with functional, evolutionary and structural information and organized in a database that can be inspected and queried. An instance of the database populated with pre-computed data on seven organisms is accessible through a publicly available server and we believe it constitutes by itself a useful resource for the life sciences (http://www.biocomputing.it/modipath).
CitationSayadi A, Briganti L, Tramontano A, Via A (2011) Exploiting Publicly Available Biological and Biochemical Information for the Discovery of Novel Short Linear Motifs. PLoS ONE 6: e22270. Available: http://dx.doi.org/10.1371/journal.pone.0022270.
SponsorsThis work was partially supported by Award No. KUK-I1-012-43 made by King Abdullah University of Science and Technology (KAUST: http://www.kaust.edu.sa/), by Fondazione Roma (http://www.fondazioneroma.it/it/index.html) and by the Italian Ministry of Health (http://www.salute.gov.it/), contract no. onc_ord 25/07, FIRB ITALBIONET and PROTEOMICA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
PublisherPublic Library of Science (PLoS)
PubMed Central IDPMC3140502
CollectionsPublications Acknowledging KAUST Support
- SLiMFinder: a probabilistic method for identifying over-represented, convergently evolved, short linear motifs in proteins.
- Authors: Edwards RJ, Davey NE, Shields DC
- Issue date: 2007 Oct 3
- The SLiMDisc server: short, linear motif discovery in proteins.
- Authors: Davey NE, Edwards RJ, Shields DC
- Issue date: 2007 Jul
- Computational prediction of short linear motifs from protein sequences.
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- D-SLIMMER: domain-SLiM interaction motifs miner for sequence based protein-protein interaction data.
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- Exploring Short Linear Motifs Using the ELM Database and Tools.
- Authors: Gouw M, Sámano-Sánchez H, Van Roey K, Diella F, Gibson TJ, Dinkel H
- Issue date: 2017 Jun 27