Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/129524
Title: Drug design at the HIV capsid hexamer using the inhibitor GS-6207 as a lead
Authors: Cassar, Matthew Jonathan (2024)
Keywords: HIV infections -- Malta
Capsid proteins -- Malta
Capsids (Virology)
Issue Date: 2024
Citation: Cassar, M. J. (2024). Drug design at the HIV capsid hexamer using the inhibitor GS-6207 as a lead (Master's dissertation).
Abstract: HIV and AIDS-related illnesses have been the cause for roughly 40 million deaths since the first case of HIV was diagnosed over 4 decades ago, with the HIV-1 capsid hexamer receptor emerging as a potential target for novel drugs to use as a new mechanism of action. This study aimed to identify novel modulators of the HIV-1 capsid hexamer with better physicochemical properties and bioavailability than GS-6207, which was employed as a lead molecule scaffold, using virtual screening and de novo drug design methods. A consensus pharmacophore was generated using the GS-6207 scaffold. This consensus pharmacophore was then employed to create novel high-affinity molecules that adhere to Lipinski’s rules and have the potential to bind to and modulate the HIV-1 capsid hexamer. Virtual screening using this consensus pharmacophore yielded over 900 potential hit molecules. These hits were filtered according to Lipinski’s Rules, and the top ten molecules, with docking scores ranging from 4.78 and 6.40, were selected for in-depth analysis based on their favourable affinities. An extensive software suite was used for this study, including SYBYL-X®, MONA®, LigBuilder®, BIOVIA Discovery Studio®, and ZINCPharmer. These programs were used to discover and optimise novel antagonists with high binding affinity for the HIV-1 capsid hexamer. These programs were used to analyse critical interactions between the lead molecules and the target receptors, computationally edit and modify molecules, and create seed structures. These seed structures were then utilised to generate novel ligand candidates. These novel structures were then filtered according to Lipinski’s rules, with the best amongst them being chosen for further analysis.
Description: M.Pharm.(Melit.)
URI: https://www.um.edu.mt/library/oar/handle/123456789/129524
Appears in Collections:Dissertations - FacM&S - 2024
Dissertations - FacM&SPha - 2024

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