Identification of Natural Inhibitors of SARS-CoV-2 Main Protease (Mpro) via Structure-Based Virtual Screening and Molecular Dynamics Simulations

The ongoing COVID-19 pandemic has highlighted the urgent need for effective antiviral treatments to combat the spread of the virus. Natural products have emerged as a valuable source of potential drug candidates, given their diverse chemical structures and ability to inhibit viral replication. In this study, we selected a dataset of 356 antiviral natural products from the Ambinter chemical library and screened them for their ability to inhibit the main protease (Mpro), a key target for drug development against SARS-CoV-2 using molecular docking in order to estimate their potential pharmacological activity. Furthermore, we evaluated the selected compounds' physicochemical properties and pharmacokinetic parameters to assess their drug-likeness. Finally, molecular dynamics simulations were conducted on the highest-ranking compounds to assess their stability and molecular interactions over time. Our findings indicate that the compounds Amb18482894 and Amb1953578 belonging to the flavones and the flavonolignans chemical classes exhibit strong affinity towards Mpro with binding scores of −8.4 and −8.0 kcal/mol, respectively, which were found to be higher than the reference compound, masitinib. Moreover, better stability was observed in the studied natural compounds in complex with Mpro, suggesting their potential as future drug candidates for COVID-19. This study contributes to the ongoing efforts to identify safe and effective treatments for this global health crisis.

Publication Details

Journal
Letters in Applied NanoBioScience
Published
2024-12-30
DOI
https://doi.org/10.33263/lianbs134.176
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Identification of Natural Inhibitors of SARS-CoV-2 Main Protease (Mpro) via Structure-Based Virtual Screening and Molecular Dynamics Simulations

Letters in Applied NanoBioScience
Computational Drug Discovery Methods
article

Identification of Natural Inhibitors of SARS-CoV-2 Main Protease (Mpro) via Structure-Based Virtual Screening and Molecular Dynamics Simulations

article en

Abstract

The ongoing COVID-19 pandemic has highlighted the urgent need for effective antiviral treatments to combat the spread of the virus. Natural products have emerged as a valuable source of potential drug candidates, given their diverse chemical structures and ability to inhibit viral replication. In this study, we selected a dataset of 356 antiviral natural products from the Ambinter chemical library and screened them for their ability to inhibit the main protease (Mpro), a key target for drug development against SARS-CoV-2 using molecular docking in order to estimate their potential pharmacological activity. Furthermore, we evaluated the selected compounds' physicochemical properties and pharmacokinetic parameters to assess their drug-likeness. Finally, molecular dynamics simulations were conducted on the highest-ranking compounds to assess their stability and molecular interactions over time. Our findings indicate that the compounds Amb18482894 and Amb1953578 belonging to the flavones and the flavonolignans chemical classes exhibit strong affinity towards Mpro with binding scores of −8.4 and −8.0 kcal/mol, respectively, which were found to be higher than the reference compound, masitinib. Moreover, better stability was observed in the studied natural compounds in complex with Mpro, suggesting their potential as future drug candidates for COVID-19. This study contributes to the ongoing efforts to identify safe and effective treatments for this global health crisis.

Letters in Applied NanoBioScienceVol. 13(4)
Universitat de Barcelona
Good health and well-being
Openalex Percentile: Top 70%
Computational Drug Discovery Methods
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