Literature DB >> 21385787

Agos--a universal web tool for GW Argonaute-binding domain prediction.

Andrzej Zielezinski1, Wojciech M Karlowski.   

Abstract

MOTIVATION: AGO(Argonaute)-binding domains, composed of repeated motifs, in which only binary combinations of tryptophan and glycine are conserved, bind AGO proteins and are essential during RNAi-mediated gene silencing. The amino acid sequence of this domain is extremely divergent and therefore very difficult to detect. Commonly used bioinformatic tools fail to identify tryptophan-glycine and/or glycine-tryptophan motifs (WG/GW) domains and currently there is no publicly available software which can detect these weakly conserved, but functional AGO-binding segments.
RESULTS: Recently, we have developed an algorithm based on compositional analysis of the amino acid content of the domain. We have demonstrated that the algorithm can be successfully applied for the identification of the new WG/GW proteins in the Arabidopsis genome. Here we introduce Agos (Argonaute-binding domain screener), a novel universal web service for de novo identification of WG/GW domains in protein sequences. The web implementation of the algorithm contains several new features and enhancements: (i) one universal scoring matrix which allows identification of AGO-binding proteins in sequences representing all organisms; (ii) reduction of false positive predictions by improved selectivity of the algorithm; (iii) graphical interface to easily browse the prediction results; and (iv) the option to submit a DNA sequence which will be automatically translated in six frames before running the prediction algorithm. AVAILABILITY: Freely available at: http://bioinfo.amu.edu.pl/agos/.

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Year:  2011        PMID: 21385787     DOI: 10.1093/bioinformatics/btr128

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  2 in total

1.  The potyviral silencing suppressor HCPro recruits and employs host ARGONAUTE1 in pro-viral functions.

Authors:  Maija Pollari; Swarnalok De; Aiming Wang; Kristiina Mäkinen
Journal:  PLoS Pathog       Date:  2020-10-08       Impact factor: 6.823

2.  Comparison of Surface Proteomes of Adherence Variants of Listeria Monocytogenes Using LC-MS/MS for Identification of Potential Surface Adhesins.

Authors:  Hung King Tiong; Steven D Hartson; Peter M Muriana
Journal:  Pathogens       Date:  2016-05-17
  2 in total

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