Computational insight of dexamethasone against potential targets of SARS-CoV-2

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dc.contributor.authorFadaka, Adewale Oluwaseun
dc.contributor.authorSibuyi, Nicole Remaliah Samantha
dc.contributor.authorMadiehe, Abram Madimabe
dc.date.accessioned2023-02-08T07:35:39Z
dc.date.available2023-02-08T07:35:39Z
dc.date.issued2022
dc.description.abstractThe health sector has been on the race to find a potent therapy for coronavirus disease (COVID)-19, a diseases caused by severe acute respiratory syndrome coronavirus (SARS-CoV)-2. Repurposed anti-viral drugs have played a huge role in combating the virus, and most recently, dexamethasone (Dex) have shown its therapeutic activity in severe cases of COVID-19 patients. The study sought to provide insights on the anti-COVID-19 mechanism of Dex at both atomic and molecular level against SARSCoV-2 targets. Computational methods were employed to predict the binding affinity of Dex to SARSCoV-2 using the Schrodinger suite (v2020-2). The target molecules and ligand (Dex) were retrieved from PDB and PubChem, respectively. The selected targets were SARS-CoV-2 main protease (Mpro), and host secreted molecules glucocorticoid receptor, and Interleukin-6 (IL-6). Critical analyses such as Protein and ligand preparation, molecular docking, molecular dynamic (MD) simulations, and absorption, distribution, metabolism, excretion (ADME), and toxicity analyses were performed using the targets and the ligand as inputs.en_US
dc.identifier.citationFadaka, A. O. et al. (2022). Computational insight of dexamethasone against potential targets of SARS-CoV-2. JOURNAL OF BIOMOLECULAR STRUCTURE AND DYNAMICS, 40 (2). 875-885. 10.1080/07391102.2020.1819880en_US
dc.identifier.issn1538-0254
dc.identifier.uri10.1080/07391102.2020.1819880
dc.identifier.urihttp://hdl.handle.net/10566/8376
dc.language.isoenen_US
dc.publisherTaylor and Francis Groupen_US
dc.subjectDexamethasoneen_US
dc.subjectCovid-19en_US
dc.subjectPublic healthen_US
dc.subjectWorld Health Organization (WHO)en_US
dc.subjectBiotechnologyen_US
dc.titleComputational insight of dexamethasone against potential targets of SARS-CoV-2en_US
dc.typeArticleen_US

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