Document Type

Thesis

Publication Date

4-2022

Advisor

Lisa Gentile

Abstract

An unexpected outbreak of SARS-CoV-2 caused a worldwide pandemic in 2020. Many repurposed drugs were tested, but there are currently only three FDA approved antivirals (Merck’s antiviral Molnupiravir, Pfizer’s antiviral Paxlovid, and Remdisivir).1 Most of the antiviral drugs tested SARS-CoV-2 main protease and RNA-dependent RNA polymerase. However, it is important to explore different drug targets of SARS-CoV-2 to prepare for the virus mutations of the future. This research looks at an alternative approach in which SARSCoV- 2 Open Reading Frame 8 (ORF8), which has been shown to be a rapidly evolving hypervariable gene, was chosen to be the protein of interest. A series of computational strategies were developed to generate pharmacophores and identify lead compounds. In addition to the lead compound identification pipeline, this thesis also presents an automated method for generating pharmacophore models from molecular docking output. The pharmacophore-based models resulted in four potential FDA-approved compounds. This thesis focuses on the binding activity of one of the four compounds, novobiocin. To collect data on the binding activity, the ORF8 protein was expressed and purified. Results suggest that novobiocin binds to ORF8, and it might be a potential inhibitor for further developments of an antiviral for SARS-CoV-2. 1

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