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Holger Dinkel, Sushama Michael,
Robert J Weatheritt,
Norman E Davey,
Kim Van Roey,
Brigitte Altenberg,
Grischa Toedt,
Bora Uyar,
Markus Seiler,
Aidan Budd, [......],
Katja Luck,
Allegra Via,
Andrew Chatr-Aryamontri,
Niall Haslam,
Gleb Grebnev,
Richard J Edwards,
Michel O Steinmetz,
Heike Meiselbach,
Francesca Diella,
Toby J Gibson
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ABSTRACT: Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instances.
Nucleic Acids Research 11/2011; 40(Database issue):D242-51. · 8.03 Impact Factor
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Cathryn M Gould,
Francesca Diella,
Allegra Via,
Pål Puntervoll,
Christine Gemünd,
Sophie Chabanis-Davidson, Sushama Michael,
Ahmed Sayadi,
Jan Christian Bryne,
Claudia Chica, [......],
Robert J Weatheritt,
Aidan Budd,
Tim Hughes,
Jakub Pas,
Leszek Rychlewski,
Gilles Travé,
Rein Aasland,
Manuela Helmer-Citterich,
Rune Linding,
Toby J Gibson
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ABSTRACT: Linear motifs are short segments of multidomain proteins that provide regulatory functions independently of protein tertiary structure. Much of intracellular signalling passes through protein modifications at linear motifs. Many thousands of linear motif instances, most notably phosphorylation sites, have now been reported. Although clearly very abundant, linear motifs are difficult to predict de novo in protein sequences due to the difficulty of obtaining robust statistical assessments. The ELM resource at http://elm.eu.org/ provides an expanding knowledge base, currently covering 146 known motifs, with annotation that includes >1300 experimentally reported instances. ELM is also an exploratory tool for suggesting new candidates of known linear motifs in proteins of interest. Information about protein domains, protein structure and native disorder, cellular and taxonomic contexts is used to reduce or deprecate false positive matches. Results are graphically displayed in a 'Bar Code' format, which also displays known instances from homologous proteins through a novel 'Instance Mapper' protocol based on PHI-BLAST. ELM server output provides links to the ELM annotation as well as to a number of remote resources. Using the links, researchers can explore the motifs, proteins, complex structures and associated literature to evaluate whether candidate motifs might be worth experimental investigation.
Nucleic Acids Research 11/2009; 38(Database issue):D167-80. · 8.03 Impact Factor
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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.
Bioinformatics 02/2008; 24(4):453-7. · 5.47 Impact Factor
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ABSTRACT: It is now clear that a detailed picture of cell regulation requires a comprehensive understanding of the abundant short protein motifs through which signaling is channeled. The current body of knowledge has slowly accumulated through piecemeal experimental investigation of individual motifs in signaling. Computational methods contributed little to this process. A new generation of bioinformatics tools will aid the future investigation of motifs in regulatory proteins, and the disordered polypeptide regions in which they frequently reside. Allied to high throughput methods such as phosphoproteomics, signaling networks are becoming amenable to experimental deconstruction. In this review, we summarise the current state of linear motif biology, which uses low affinity interactions to create cooperative, combinatorial and highly dynamic regulatory protein complexes. The discrete deterministic properties implicit to these assemblies suggest that models for cell regulatory networks in systems biology should neither be overly dependent on stochastic nor on smooth deterministic approximations.
Frontiers in Bioscience 02/2008; 13:6580-603. · 3.52 Impact Factor
