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The in silico prediction of foot-and-mouth disease virus (FMDV) epitopes on the South African territories (SAT)1, SAT2 and SAT3 serotypes

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dc.contributor.advisor Rees, D. J. G.
dc.contributor.advisor Maree, F. F.
dc.contributor.author Mukonyora, Michelle
dc.date.accessioned 2017-01-24T06:09:26Z
dc.date.available 2017-01-24T06:09:26Z
dc.date.issued 2015-08
dc.date.submitted 2017-01-24
dc.identifier.citation Mukonyora, Michelle (2015) The in silico prediction of foot-and-mouth disease virus (FMDV) epitopes on the South African territories (SAT)1, SAT2 and SAT3 serotypes, University of South Africa, Pretoria, <http://hdl.handle.net/10500/21942> en
dc.identifier.uri http://hdl.handle.net/10500/21942
dc.description.abstract Foot-and-mouth disease (FMD) is a highly contagious and economically important disease that affects even-toed hoofed mammals. The FMD virus (FMDV) is the causative agent of FMD, of which there are seven clinically indistinguishable serotypes. Three serotypes, namely, South African Territories (SAT)1, SAT2 and SAT3 are endemic to southern Africa and are the most antigenically diverse among the FMDV serotypes. A negative consequence of this antigenic variation is that infection or vaccination with one virus may not provide immune protection from other strains or it may only confer partial protection. The identification of B-cell epitopes is therefore key to rationally designing cross-reactive vaccines that recognize the immunologically distinct serotypes present within the population. Computational epitope prediction methods that exploit the inherent physicochemical properties of epitopes in their algorithms have been proposed as a cost and time-effective alternative to the classical experimental methods. The aim of this project is to employ in silico epitope prediction programmes to predict B-cell epitopes on the capsids of the SAT serotypes. Sequence data for 18 immunologically distinct SAT1, SAT2 and SAT3 strains from across southern Africa were collated. Since, only one SAT1 virus has had its structure elucidated by X-ray crystallography (PDB ID: 2WZR), homology models of the 18 virus capsids were built computationally using Modeller v9.12. They were then subjected to energy minimizations using the AMBER force field. The quality of the models was evaluated and validated stereochemically and energetically using the PROMOTIF and ANOLEA servers respectively. The homology models were subsequently used as input to two different epitope prediction servers, namely Discotope1.0 and Ellipro. Only those epitopes predicted by both programmes were defined as epitopes. Both previously characterised and novel epitopes were predicted on the SAT strains. Some of the novel epitopes are located on the same loops as experimentally derived epitopes, while others are located on a putative novel antigenic site, which is located close to the five-fold axis of symmetry. A consensus set of 11 epitopes that are common on at least 15 out of 18 SAT strains was collated. In future work, the epitopes predicted in this study will be experimentally validated using mutagenesis studies. Those found to be true epitopes may be used in the rational design of broadly reactive SAT vaccines en
dc.format.extent 1 online resource (203 leaves) : color illustrations
dc.language.iso en en
dc.subject Foot-and-mouth-disease en
dc.subject Foot-and-mouth disease virus (FMDV) en
dc.subject South African territories (SAT) en
dc.subject Viral protein (VP) en
dc.subject Epitope en
dc.subject Epitope prediction en
dc.subject Immunoinformatics en
dc.subject Homology Model en
dc.subject Discotope en
dc.subject Ellipro en
dc.subject.ddc 636.08969100968
dc.subject.lcsh Homology theory en
dc.subject.lcsh Foot-and-mouth disease virus -- South Africa en
dc.subject.lcsh Viral proteins -- South Africa en
dc.subject.lcsh Antigenic determinants -- South Africa en
dc.subject.lcsh Immunoinformatics -- South Africa en
dc.title The in silico prediction of foot-and-mouth disease virus (FMDV) epitopes on the South African territories (SAT)1, SAT2 and SAT3 serotypes en
dc.type Dissertation en
dc.description.department Life and Consumer Sciences en
dc.description.degree M. Sc. (Life Sciences)


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