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A computational study of Ebola virus pathogenicity and a modeling approach for human non-synonymous variants

Recent advances in genome sequencing are improving our better understanding of genetic variation. However, the investigation of the genotype-phenotype relationship is still challenging, especially for the interpretation of the myriad of discovered genetic variants that weakly relate to disease. Recently, researchers have confirmed that disease causing genetic variants typically occur at functional sites, such as protein-protein or protein-ligand interaction sites. Giving this observation, several bioinformatics tools have been developed. This thesis first details VarMod (Variant Modeller), an algorithm that predicts whether nonsynonymous single nucleotide variants (nsSNVs) affect protein function. The recent Ebola virus outbreak in West Africa demonstrated the potential for the virus to cause edipdemics and highlighted our limited understanding of Ebola virus biology. The second part of this thesis focuses on the investigation of the molecular determinants of Ebolavirus pathogenicity. In two related analyses knowledge of differing pathogenicity of Ebolavirus species is used. Firstly, comparison of the sequences of Reston viruses (the only Ebolavirus species that is not pathogenic in humans) with the four pathogenic Ebolavirus species, enabled the identification of Specificity Determining Positions (SDPs) that are differentially conserved between these two groups. These SDPs were further investigated using analysis of protein structure and identified variation in the Ebola virus VP24 as likely to have a role in determining species-specific pathogenicity. The second approach investigated rodent-adapted Ebola virus. Ebola virus is not pathogenic in rodents but it can be passaged to induce pathogenicity. Analysis of the mutations identified in four adaption studies identified that very few mutations are required for adaptation to a new species and once again the VP24 is likely to have a central role. Subsequent molecular dynamics simulations compared the interaction of Ebola and Reston virus VP24 with human karyopherin alpha5. The analysis suggests that Reston virus VP24 has weaker binding with karyopherins and we propose that this change in binding may reduce the ability of Reston VP24 to inhibit human interferon signaling.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:693839
Date January 2016
CreatorsPappalardo, Morena
PublisherUniversity of Kent
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttps://kar.kent.ac.uk/57320/

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