Discovery of potential FDA-approved SARS-CoV-2 Papain-like protease inhibitors: A multi-phase in silico approach

Papain-like protease (PLpro) is a crucial enzyme for SARS-CoV-2 replication and immune evasion. Inhibiting PLpro could be a promising strategy to fight against COVID-19. This study aimed to identify potent inhibitors of PLpro among FDA-approved drugs using an in silico approach. The study also aimed to examine and confirm the binding of the selected compounds to the active pocket of PLpro using a multi-phased in silico approach, involving the screening of 3009 FDA-approved drugs to pinpoint the most similar compounds to, TTT, the co-crystallized ligand TTT of PLpro. The selected compounds were subjected to further analysis, including molecular docking, molecular dynamics simulations, MM-GPSA (molecular mechanics generalized Born surface area), and PLIP (Protein-Ligand Interaction Profiler) studies, to examine and confirm their binding to the active pocket of PLpro. Seven candidates (Vismodegib, Celecoxib, Ketoprofen, Indomethacin, Naphazoline, Valdecoxib, and Eslicarbazepine) showed promising in silico activities against the PLpro. The computational analysis confirmed the binding of Celecoxib to the active pocket of PLpro, suggesting its potential in the fight against COVID-19. This study identified seven FDA-approved drugs as potential inhibitors of PLpro, providing a feasible approach for drug repurposing against COVID-19. The results obtained from the in silico approach hold promise, but further in vitro and in vivo studies are warranted to validate the potential of these compounds.

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Publication Details

Journal
Journal of Chemical Research
Published
2024-11-01
DOI
https://doi.org/10.1177/17475198241298547
Citations
3
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.08

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article

Discovery of potential FDA-approved SARS-CoV-2 Papain-like protease inhibitors: A multi-phase in silico approach

Ibrahim H. Eissa, Aisha A. Alsfouk, Mohamed M. Khalifa, Eslam B. Elkaeed et al.
3 citations
Journal of Chemical Research
Computational Drug Discovery Methods
1.08
article

Discovery of potential FDA-approved SARS-CoV-2 Papain-like protease inhibitors: A multi-phase in silico approach

Ibrahim H. Eissa, Aisha A. Alsfouk, Mohamed M. Khalifa, Eslam B. Elkaeed, Ahmed M. Metwaly, Fatma G. Amin, Ibrahim M. Ibrahim
article en
3 citations

Abstract

Papain-like protease (PLpro) is a crucial enzyme for SARS-CoV-2 replication and immune evasion. Inhibiting PLpro could be a promising strategy to fight against COVID-19. This study aimed to identify potent inhibitors of PLpro among FDA-approved drugs using an in silico approach. The study also aimed to examine and confirm the binding of the selected compounds to the active pocket of PLpro using a multi-phased in silico approach, involving the screening of 3009 FDA-approved drugs to pinpoint the most similar compounds to, TTT, the co-crystallized ligand TTT of PLpro. The selected compounds were subjected to further analysis, including molecular docking, molecular dynamics simulations, MM-GPSA (molecular mechanics generalized Born surface area), and PLIP (Protein-Ligand Interaction Profiler) studies, to examine and confirm their binding to the active pocket of PLpro. Seven candidates (Vismodegib, Celecoxib, Ketoprofen, Indomethacin, Naphazoline, Valdecoxib, and Eslicarbazepine) showed promising in silico activities against the PLpro. The computational analysis confirmed the binding of Celecoxib to the active pocket of PLpro, suggesting its potential in the fight against COVID-19. This study identified seven FDA-approved drugs as potential inhibitors of PLpro, providing a feasible approach for drug repurposing against COVID-19. The results obtained from the in silico approach hold promise, but further in vitro and in vivo studies are warranted to validate the potential of these compounds.

Journal of Chemical ResearchVol. 48(6)
Princess Nourah bint Abdulrahman University (SA), Alfaisal University (SA), Cairo University (EG), Al-Azhar University (EG), Almaarefa University, Alexandria University (EG)
Princess Nourah Bint Abdulrahman University
Openalex Percentile: Top 19%
Computational Drug Discovery Methods
1.08
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