Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah

Dengue virus (DENV) infection is a rising health concern worldwide. Despite the alarming situation, there is no effective antiviral for DENV infections. With the increasing number of NS3 viral inhibitors developed for other diseases, the development of drugs targeting dengue NS3 protein is an intere...

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Main Author:	Abdullah, Zafirah Liyana
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Dengue
Online Access:	https://ir.uitm.edu.my/id/eprint/102179/1/102179.pdf
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id	my-uitm-ir.102179
record_format	uketd_dc
spelling	my-uitm-ir.1021792024-12-09T09:25:15Z Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah 2024 Abdullah, Zafirah Liyana Dengue Dengue virus (DENV) infection is a rising health concern worldwide. Despite the alarming situation, there is no effective antiviral for DENV infections. With the increasing number of NS3 viral inhibitors developed for other diseases, the development of drugs targeting dengue NS3 protein is an interesting venture. Thus, this study is set forth to identify potential DENV inhibitors by building a prediction model of NS3 dengue antiviral. Initially, the models were built using bioactivity data of 62,354 compounds using ligand-based (L-B), and proteochemometric (PCM) modelling approaches. For the L-B approach, a Random Forest (RF) one-vs-one classification model was utilized while the PCM model employed the Parzen-Rosenblatt Windows (PRW) algorithm. Subsequently, the validated predictive models were used to screen marketed drugs, and in vitro assays were conducted to validate the drug’s viral inhibitory potential. Finally, the interactions that are responsible for the observed in vitro results were validated using molecular docking. The in silico studies revealed that both L-B and PCM models performed well in the internal and external validations. However, the L-B model showed better accuracy in the external validation, in terms of its sensitivity (0.671). 2024 Thesis https://ir.uitm.edu.my/id/eprint/102179/ https://ir.uitm.edu.my/id/eprint/102179/1/102179.pdf text en public phd doctoral Universiti Teknologi MARA (UiTM) Faculty of Pharmacy
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Dengue
spellingShingle	Dengue Abdullah, Zafirah Liyana Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah
description	Dengue virus (DENV) infection is a rising health concern worldwide. Despite the alarming situation, there is no effective antiviral for DENV infections. With the increasing number of NS3 viral inhibitors developed for other diseases, the development of drugs targeting dengue NS3 protein is an interesting venture. Thus, this study is set forth to identify potential DENV inhibitors by building a prediction model of NS3 dengue antiviral. Initially, the models were built using bioactivity data of 62,354 compounds using ligand-based (L-B), and proteochemometric (PCM) modelling approaches. For the L-B approach, a Random Forest (RF) one-vs-one classification model was utilized while the PCM model employed the Parzen-Rosenblatt Windows (PRW) algorithm. Subsequently, the validated predictive models were used to screen marketed drugs, and in vitro assays were conducted to validate the drug’s viral inhibitory potential. Finally, the interactions that are responsible for the observed in vitro results were validated using molecular docking. The in silico studies revealed that both L-B and PCM models performed well in the internal and external validations. However, the L-B model showed better accuracy in the external validation, in terms of its sensitivity (0.671).
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abdullah, Zafirah Liyana
author_facet	Abdullah, Zafirah Liyana
author_sort	Abdullah, Zafirah Liyana
title	Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah
title_short	Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah
title_full	Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah
title_fullStr	Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah
title_full_unstemmed	Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah
title_sort	revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / zafirah liyana abdullah
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Pharmacy
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/102179/1/102179.pdf
_version_	1818588032433913856

Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah

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