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/.