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iLIR : a web resource for prediction of Atg8-family interacting proteins
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Kalvari, Ioanna, Tsompanis, Stelios, Mulakkal, Nitha Charles, Osgood, Richard, Johansen, Terje, Nezis, I. P. and Promponas, Vasilis J. (2014) iLIR : a web resource for prediction of Atg8-family interacting proteins. Autophagy, Volume 10 (Number 5). doi:10.4161/auto.28260 ISSN 1554-8627.
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Official URL: https://www.landesbioscience.com/journals/autophag...
Abstract
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.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > QH Natural history | ||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | ||||||||
Library of Congress Subject Headings (LCSH): | Autophagic vacuoles, Proteins -- Analysis -- Computer programs, Computational biology | ||||||||
Journal or Publication Title: | Autophagy | ||||||||
Publisher: | Landes Bioscience | ||||||||
ISSN: | 1554-8627 | ||||||||
Official Date: | 26 February 2014 | ||||||||
Dates: |
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Volume: | Volume 10 | ||||||||
Number: | Number 5 | ||||||||
Number of Pages: | 12 | ||||||||
DOI: | 10.4161/auto.28260 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Funder: | Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC) | ||||||||
Grant number: | BB/L006324/1 (BBSRC) |
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