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A Computational study of Ebolavirus Pathogenicity and a Modeling approach for human non-synonymous variants

Pappalardo, Morena (2016) A Computational study of Ebolavirus Pathogenicity and a Modeling approach for human non-synonymous variants. Doctor of Philosophy (PhD) thesis, University of Kent,. (KAR id:57320)

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Recent advances in genome sequencing are improving our better understanding of

is still challenging, especially for the interpretation of the myriad of discovered

Recently, researchers have confirmed that disease causing genetic variants typically

Giving this observation, several bioinformatics tools have been developed. This

nonsynonymous single nucleotide variants (nsSNVs) affect protein function.

virus to cause edipdemics and highlighted our limited understanding of Ebola virus

determinants of Ebolavirus pathogenicity. In two related analyses knowledge of

sequences of Reston viruses (the only Ebolavirus species that is not pathogenic in

Specificity Determining Positions (SDPs) that are differentially conserved between

structure and identified variation in the Ebola virus VP24 as likely to have a role in

rodent-adapted Ebola virus. Ebola virus is not pathogenic in rodents but it can be

adaption studies identified that very few mutations are required for adaptation to a

molecular dynamics simulations compared the interaction of Ebola and Reston virus

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.

Item Type: Thesis (Doctor of Philosophy (PhD))
Uncontrolled keywords: nsSNV, varMod, Ebolavirus pathogenicity, Reston
Subjects: Q Science > QP Physiology (Living systems)
Q Science > QR Microbiology
R Medicine > RB Pathology
Divisions: Divisions > Division of Natural Sciences > School of Biosciences
Depositing User: Users 1 not found.
Date Deposited: 16 Sep 2016 11:00 UTC
Last Modified: 20 May 2021 13:31 UTC
Resource URI: (The current URI for this page, for reference purposes)
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