The mining of toxin-like polypeptides from EST database by single residue distribution analysis

Novel high throughput sequencing technologies require permanent development of bioinformatics data processing methods. Among them, rapid and reliable identification of encoded proteins plays a pivotal role. To search for particular protein families, the amino acid sequence motifs suitable for selective screening of nucleotide sequence databases may be used. In this work, we suggest a novel method for simplified representation of protein amino acid sequences named Single Residue Distribution Analysis, which is applicable both for homology search and database screening.

Using the procedure developed, a search for amino acid sequence motifs in sea anemone polypeptides was performed, and 14 different motifs with broad and low specificity were discriminated. The adequacy of motifs for mining toxin-like sequences was confirmed by their ability to identify 100% toxin-like anemone polypeptides in the reference polypeptide database. The employment of novel motifs for the search of polypeptide toxins in Anemonia viridis EST dataset allowed us to identify 89 putative toxin precursors. The translated and modified ESTs were scanned using a special algorithm. In addition to direct comparison with the motifs developed, the putative signal peptides were predicted and homology with known structures was examined.

The suggested method may be used to retrieve structures of interest from the EST databases using simple amino acid sequence motifs as templates. The efficiency of the procedure for directed search of polypeptides is higher than that of most currently used methods. Analysis of 39939 ESTs of sea anemone Anemonia viridis resulted in identification of five protein precursors of earlier described toxins, discovery of 43 novel polypeptide toxins, and prediction of 39 putative polypeptide toxin sequences. In addition, two precursors of novel peptides presumably displaying neuronal function were disclosed.