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iLIR: A web resource for prediction of Atg8-family interacting proteins.

TitleiLIR: A web resource for prediction of Atg8-family interacting proteins.
Publication TypeJournal Article
Year of Publication2014
AuthorsKalvari, Ioanna, Stelios Tsompanis, Nitha C. Mulakkal, Richard Osgood, Terje Johansen, Ioannis P. Nezis, and V. J. Promponas
Date Published2014 May
KeywordsAdaptor Proteins, Signal Transducing, Amino Acid Sequence, Animals, Arabidopsis, Autophagy-Related Protein 8 Family, Databases, Protein, Drosophila melanogaster, Humans, Internet, Microfilament Proteins, Microtubule-Associated Proteins, Multigene Family, Plasmodium falciparum, Protein Binding, Protein Interaction Domains and Motifs, Protein Interaction Maps, Saccharomyces cerevisiae

Macroautophagy was initially considered to be a nonselective process for bulk breakdown of cytosolic material. However, recent evidence points toward a selective mode of autophagy mediated by the so-called selective autophagy receptors (SARs). SARs act by recognizing and sorting diverse cargo substrates (e.g., proteins, organelles, pathogens) to the autophagic machinery. Known SARs are characterized by a short linear sequence motif (LIR-, LRS-, or AIM-motif) responsible for the interaction between SARs and proteins of the Atg8 family. Interestingly, many LIR-containing proteins (LIRCPs) are also involved in autophagosome formation and maturation and a few of them in regulating signaling pathways. Despite recent research efforts to experimentally identify LIRCPs, only a few dozen of this class of-often unrelated-proteins have been characterized so far using tedious cell biological, biochemical, and crystallographic approaches. The availability of an ever-increasing number of complete eukaryotic genomes provides a grand challenge for characterizing novel LIRCPs throughout the eukaryotes. Along these lines, we developed iLIR, a freely available web resource, which provides in silico tools for assisting the identification of novel LIRCPs. Given an amino acid sequence as input, iLIR searches for instances of short sequences compliant with a refined sensitive regular expression pattern of the extended LIR motif (xLIR-motif) and retrieves characterized protein domains from the SMART database for the query. Additionally, iLIR scores xLIRs against a custom position-specific scoring matrix (PSSM) and identifies potentially disordered subsequences with protein interaction potential overlapping with detected xLIR-motifs. Here we demonstrate that proteins satisfying these criteria make good LIRCP candidates for further experimental verification. Domain architecture is displayed in an informative graphic, and detailed results are also available in tabular form. We anticipate that iLIR will assist with elucidating the full complement of LIRCPs in eukaryotes.

Alternate JournalAutophagy

by Dr. Radut.