Dataset Information

Evolutionary Analysis and Prediction of Peptide Vaccine Candidates for Foot-and-Mouth-Disease Virus Types A and O in Bangladesh.

ABSTRACT: Foot-and-mouth disease (FMD), an endemic disease of cloven-hoofed animals, causes an annual economic loss of US$60-150 million in Bangladesh. There is no cross-protection among the foot-and-mouth disease virus (FMDV) serotypes and vaccination escape mutation may happen. Peptide vaccine is a safer alternative. The aim of this study is to predict and map the B and T cell epitopes of VP1 proteins of FMDV serotypes O and A that were circulating in Bangladesh from 2011 to 2013. Using evolutionary and computational approach (BCPred, BepiPred, DiscoTope, ElliPro, and ProPred-I, IEDB analysis for MHC-I prediction), a total of 11 B and T cell epitopes were predicted. Also, the three-dimensional (3D) structure of VP1 protein showed that the predicted five epitopes residing on N- and C-termini can be considered as good vaccine candidates, and epitopes on the G-H loop can serve as receptor recognition sites for vaccine design. The scores of predicted epitopes of one method were cross-checked with other one for potential epitope mining. Within the VP1 antigenic sites, significant evidence of positive selection was present indicating evolution of VP1 under high immune surveillance.

SUBMITTER: Momtaz S

PROVIDER: S-EPMC4219755 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Evolutionary Analysis and Prediction of Peptide Vaccine Candidates for Foot-and-Mouth-Disease Virus Types A and O in Bangladesh.

Momtaz Samina S Rahman Arafat A Sultana Munawar M Hossain M Anwar MA

Evolutionary bioinformatics online 20141103

Foot-and-mouth disease (FMD), an endemic disease of cloven-hoofed animals, causes an annual economic loss of US$60-150 million in Bangladesh. There is no cross-protection among the foot-and-mouth disease virus (FMDV) serotypes and vaccination escape mutation may happen. Peptide vaccine is a safer alternative. The aim of this study is to predict and map the B and T cell epitopes of VP1 proteins of FMDV serotypes O and A that were circulating in Bangladesh from 2011 to 2013. Using evolutionary and ...[more]

PMID: 25452681

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Project description:Identifying when past exposure to an infectious disease will protect against newly emerging strains is central to understanding the spread and the severity of epidemics, but the prediction of viral cross-protection remains an important unsolved problem. For foot-and-mouth disease virus (FMDV) research in particular, improved methods for predicting this cross-protection are critical for predicting the severity of outbreaks within endemic settings where multiple serotypes and subtypes commonly co-circulate, as well as for deciding whether appropriate vaccine(s) exist and how much they could mitigate the effects of any outbreak. To identify antigenic relationships and their predictors, we used linear mixed effects models to account for variation in pairwise cross-neutralization titres using only viral sequences and structural data. We identified those substitutions in surface-exposed structural proteins that are correlates of loss of cross-reactivity. These allowed prediction of both the best vaccine match for any single virus and the breadth of coverage of new vaccine candidates from their capsid sequences as effectively as or better than serology. Sub-sequences chosen by the model-building process all contained sites that are known epitopes on other serotypes. Furthermore, for the SAT1 serotype, for which epitopes have never previously been identified, we provide strong evidence--by controlling for phylogenetic structure--for the presence of three epitopes across a panel of viruses and quantify the relative significance of some individual residues in determining cross-neutralization. Identifying and quantifying the importance of sites that predict viral strain cross-reactivity not just for single viruses but across entire serotypes can help in the design of vaccines with better targeting and broader coverage. These techniques can be generalized to any infectious agents where cross-reactivity assays have been carried out. As the parameterization uses pre-existing datasets, this approach quickly and cheaply increases both our understanding of antigenic relationships and our power to control disease.

Dataset Information

Evolutionary Analysis and Prediction of Peptide Vaccine Candidates for Foot-and-Mouth-Disease Virus Types A and O in Bangladesh.

Publications

Evolutionary Analysis and Prediction of Peptide Vaccine Candidates for Foot-and-Mouth-Disease Virus Types A and O in Bangladesh.

Similar Datasets

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