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2000
Volume 31, Issue 18
  • ISSN: 1381-6128
  • E-ISSN: 1873-4286

Abstract

Introduction

The emergence of SARS-CoV-2 and the COVID-19 pandemic highlighted the urgent need for novel antiviral therapies. The main protease (Mpro) of SARS-CoV-2 is a key enzyme in viral replication and a promising therapeutic target.

Methods

This study employed virtual screening approaches to identify potential Mpro inhibitors, leveraging both structure- and ligand-based methods.

Results

Two optimum pharmacophore models were built from hundreds of crystallographic structures of Mpro, validated through ROC curve analysis and Dynophores dynamic simulations. These models captured ≈ 60K hits from six diverse compound libraries made of more than 3 million compounds. Additionally, a ligand-based similarity search using ROCS software identified 1024 potential hits based on shape and atom-based comparisons with co-crystallized ligands. Subsequent molecular docking and filtering based on physicochemical properties and structural diversity yielded 16 and 6 hits from structure- and ligand-based screening, respectively. Molecular dynamics simulations were conducted on the top-scoring hits to assess their binding stability within the Mpro active site. SCR00943 demonstrated stable binding, interacting favorably with key residues, including the catalytic dyad, resulting in a binding affinity of -61.2 kcal/mol.

Conclusion

This virtual screening campaign identified promising Mpro inhibitors, showcasing the potential of computational approaches to accelerate drug discovery efforts against COVID-19.

© 2025 Bentham Science Publishers
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Virtual Screening Identifies Inhibitors of SARS-CoV-2 Main Protease through Pharmacophore and Similarity Approaches
Curr. Pharm. Des. 31, 1461 (2025); https://doi.org/10.2174/0113816128358219241210101947
/content/journals/cpd/10.2174/0113816128358219241210101947
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  • Article Type:     Research Article
Keyword(s): COVID-19; docking; dynophores; Mpro; pharmacophore; virtual screening

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