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- Title
Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates: E coli 536.
- Authors
Rai, Jade; Lok, Ka In; Mok, Chun Yin; Mann, Harvinder; Noor, Mohammed; Patel, Pritesh; Flower, Darren R
- 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
Bioinformation, 2012, Vol 8, Issue 6, p272
- ISSN
0973-2063
- Publication type
Journal Article
- DOI
10.6026/97320630008272