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Open Access Highly Accessed Open Badges Research article

Bioinformatic characterizations and prediction of K+ and Na+ ion channels effector toxins

Rima Soli1, Belhassen Kaabi13*, Mourad Barhoumi1, Mohamed El-Ayeb2 and Najet Srairi-Abid2

Author Affiliations

1 Laboratory of Epidemiology and Ecology of Parasites, Institut Pasteur de Tunis, Tunis, Tunisia

2 Laboratory of Venom and Toxins, Institut Pasteur de Tunis, Tunis, Tunisia

3 Research and Teaching Building, Institut Pasteur de Tunis, 13 Place Pasteur, BP 74, 1002 Belvedere-Tunis, Tunisia

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BMC Pharmacology 2009, 9:4  doi:10.1186/1471-2210-9-4

Published: 10 March 2009



K+ and Na+ channel toxins constitute a large set of polypeptides, which interact with their ion channel targets. These polypeptides are classified in two different structural groups. Recently a new structural group called birtoxin-like appeared to contain both types of toxins has been described. We hypothesized that peptides of this group may contain two conserved structural motifs in K+ and/or Na+ channels scorpion toxins, allowing these birtoxin-like peptides to be active on K+ and/or Na+ channels.


Four multilevel motifs, overrepresented and specific to each group of K+ and/or Na+ ion channel toxins have been identified, using GIBBS and MEME and based on a training dataset of 79 sequences judged as representative of K+ and Na+ toxins.

Unexpectedly birtoxin-like peptides appeared to present a new structural motif distinct from those present in K+ and Na+ channels Toxins. This result, supported by previous experimental data, suggests that birtoxin-like peptides may exert their activity on different sites than those targeted by classic K+ or Na+ toxins.

Searching, the nr database with these newly identified motifs using MAST, retrieved several sequences (116 with e-value < 1) from various scorpion species (test dataset). The filtering process left 30 new and highly likely ion channel effectors.

Phylogenetic analysis was used to classify the newly found sequences. Alternatively, classification tree analysis, using CART algorithm adjusted with the training dataset, using the motifs and their 2D structure as explanatory variables, provided a model for prediction of the activity of the new sequences.


The phylogenetic results were in perfect agreement with those obtained by the CART algorithm.

Our results may be used as criteria for a new classification of scorpion toxins based on functional motifs.