Journal of Computational Biology and Bioinformatics Research
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Article Number - 19EC4499816

Vol.5(1), pp. 6-14 , April 2013
DOI: 10.5897/JCBBR12.013
ISSN: 2141-2227

Full Length Research Paper

Annotation of virulence factors in schistosomes for the development of a SchistoVir database

Adewale S. Adebayo1 and Chiaka I. Anumudu2*

1Cell Biology and Genetics Unit, Department of Zoology, University of Ibadan, Oyo State, Nigeria

2Cellular Parasitology Programme, Department of Zoology, University of Ibadan, Oyo State, Nigeria.


 Accepted: 08 March 2013  Published: 30 April 2013

Copyright © 2013 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0

Scientific efforts in the eradication of neglected tropical diseases, such as those caused by the parasitic helminthes, can be improved if a database of key virulence factors directly implicated in pathogenesis is available. As a first step towards creating SchistoVir, a database of virulence protein factors in schistosomes, in this study, we curated, annotated and aligned sequences of twenty virulence factors identified from the literature, using several bioinformatics tools including UniProtKB, SchistoDB, VirulentPred, InterProScan, ProtScale, MotifScan, TDRtarget, SignalP, MODBASE, PDB and MUSCLE. Among the protein entries, the most frequently occurring amino acid residues were lysine, serine, leucine, glutamine, glycine and cysteine in order of magnitude. Although sequence repeat regions (SRRs) of significant value were identified manually in fifty percent of the proteins (while dipeptide repeats (DiPs) and single amino acid repeats (SAARs) were not), nevertheless, seventy-two percent of the protein entries were classified as virulent by the prediction model, VirulentPred. Most of the entries (eighty percent) did not have target compounds based on the database of available chemical compounds at TDRtargets. Fourteen of the twenty entries (seventy percent) had more than 30 consecutively negative amino acid residues based on the ProtScale’s Kyte and Doolittle hydrophobicity plot. Hence, they would be hydrophobic enough to be transmembrane in location or secretory in nature. Only 7 (tyrosinase, serine protease1, Tspan-1, VAL4, cathepsin b and L and calreticulin) had cleavage sites and signal peptides, while none had a significant signal anchor probability. The annotations and characterization provided by this work and the development of a SchistoVir database will aid in further research of schistosome pathogenesis and control.


Key words: Protein database, bioinformatics tools, virulence proteins/factors, annotation, schistosomes.

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APA (2013). Annotation of virulence factors in schistosomes for the development of a SchistoVir database. Journal of Computational Biology and Bioinformatics Research, 5(1), 6-14.
Chicago Adewale S. Adebayo and Chiaka I. Anumudu. "Annotation of virulence factors in schistosomes for the development of a SchistoVir database." Journal of Computational Biology and Bioinformatics Research 5, no. 1 (2013): 6-14.
MLA Adewale S. Adebayo and Chiaka I. Anumudu. "Annotation of virulence factors in schistosomes for the development of a SchistoVir database." Journal of Computational Biology and Bioinformatics Research 5.1 (2013): 6-14.
DOI 10.5897/JCBBR12.013

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