In silico evaluation of FDA-approved antivirals and corticosteroids against SARS-CoV-2

The work provides computational insights into the binding mechanisms of pharmaceutical drugs Baloxavir Marboxil (BM), Dexamethasone (DM), and Remdesivir (RD) with SARS-CoV-2 protein using molecular docking, molecular dynamics (MD) simulations, and density functional theory (DFT) analyses. The aim is to identify strong inhibitors that can be repurposed as antiviral drugs. Molecular docking results indicate that BM exhibits the highest binding affinity (- 8.88 ± 0.57 kcal/mol), followed by DM and RD. According to ADMET profile, DM has better absorption and clearance, while BM and RD have hepatotoxicity issues that call for more experimental verification. While DFT-based reactivity descriptors highlight BM as the most suitable ligand for drug development due to its high reactivity and balanced electronic properties, MD simulations study confirms DM as the best binding candidate showing stable binding with very small RMSD 0.78 ± 0.12 Å, followed by RD and BM. MD simulations study along with binding free energy computations confirms the stability of all three ligand-protein complexes with root mean square deviation (RMSD) values of ligands below 3.0 Å. Many regulatory bodies, including the U.S. FDA, have authorized RD for the treatment of COVID-19 under emergency use authorization (EUA). The remaining medications, BM and DM can be said to show promise as antiviral treatments in the context of RD. All metrics form MD simulations and molecular docking, DFT, and ADMET evaluations confirm their appropriateness, highlighting their potential for additional research.

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Publication Details

Journal
Scientific Reports
Published
2026-03-24
DOI
https://doi.org/10.1038/s41598-026-44640-z
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

In silico evaluation of FDA-approved antivirals and corticosteroids against SARS-CoV-2

Scientific Reports
Computational Drug Discovery Methods
article

In silico evaluation of FDA-approved antivirals and corticosteroids against SARS-CoV-2

article en

Abstract

The work provides computational insights into the binding mechanisms of pharmaceutical drugs Baloxavir Marboxil (BM), Dexamethasone (DM), and Remdesivir (RD) with SARS-CoV-2 protein using molecular docking, molecular dynamics (MD) simulations, and density functional theory (DFT) analyses. The aim is to identify strong inhibitors that can be repurposed as antiviral drugs. Molecular docking results indicate that BM exhibits the highest binding affinity (- 8.88 ± 0.57 kcal/mol), followed by DM and RD. According to ADMET profile, DM has better absorption and clearance, while BM and RD have hepatotoxicity issues that call for more experimental verification. While DFT-based reactivity descriptors highlight BM as the most suitable ligand for drug development due to its high reactivity and balanced electronic properties, MD simulations study confirms DM as the best binding candidate showing stable binding with very small RMSD 0.78 ± 0.12 Å, followed by RD and BM. MD simulations study along with binding free energy computations confirms the stability of all three ligand-protein complexes with root mean square deviation (RMSD) values of ligands below 3.0 Å. Many regulatory bodies, including the U.S. FDA, have authorized RD for the treatment of COVID-19 under emergency use authorization (EUA). The remaining medications, BM and DM can be said to show promise as antiviral treatments in the context of RD. All metrics form MD simulations and molecular docking, DFT, and ADMET evaluations confirm their appropriateness, highlighting their potential for additional research.

Scientific Reports
Tribhuvan University (NP)
Affordable and clean energy
Openalex Percentile: Top 9%
Computational Drug Discovery Methods
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