Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates:E coli 536

Rai, Jade, Lok, Ka In, Mok, Chun Yin, Mann, Harvinder, Noor, Mohammed, Patel, Pritesh and Flower, Darren R (2012). Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates:E coli 536. Bioinformation, 8 (6), pp. 272-275.

Abstract

Epitope prediction is becoming a key tool for vaccine discovery. Prospective analysis of bacterial and viral genomes can identify antigenic epitopes encoded within individual genes that may act as effective vaccines against specific pathogens. Since B-cell epitope prediction remains unreliable, we concentrate on T-cell epitopes, peptides which bind with high affinity to Major Histacompatibility Complexes (MHC). In this report, we evaluate the veracity of identified T-cell epitope ensembles, as generated by a cascade of predictive algorithms (SignalP, Vaxijen, MHCPred, IDEB, EpiJen), as a candidate vaccine against the model pathogen uropathogenic gram negative bacteria Escherichia coli (E-coli) strain 536 (O6:K15:H31). An immunoinformatic approach was used to identify 23 epitopes within the E-coli proteome. These epitopes constitute the most promiscuous antigenic sequences that bind across more than one HLA allele with high affinity (IC50 <50nM). The reliability of software programmes used, polymorphic nature of genes encoding MHC and what this means for population coverage of this potential vaccine are discussed.

Publication DOI: https://doi.org/10.6026/97320630008272
Divisions: Life & Health Sciences > Pharmacy
Life & Health Sciences
Life & Health Sciences > Chronic and Communicable Conditions
Additional Information: This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
Full Text Link: http://www.bioi ... 20630008272.htm
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Published Date: 2012-03-31
Authors: Rai, Jade
Lok, Ka In
Mok, Chun Yin
Mann, Harvinder
Noor, Mohammed
Patel, Pritesh
Flower, Darren R ( 0000-0002-8542-7067)

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