The COVID-19 pandemic, driven by the SARS-CoV-2 virus, necessitates the development of effective therapeutics. The main protease of the virus, Mpro, is a key target due to its crucial role in viral replication. Our study presents a novel approach combining ligand-based pharmacophore modeling with structure-based advanced virtual screening to identify potential inhibitors of Mpro. We screened around 200 million compounds using this integrated methodology, resulting in a shortlist of promising compounds. These were further scrutinized through molecular dynamics simulations, revealing their interaction dynamics with Mpro. Subsequent in vitro assays using the Mpro enzyme identified two compounds exhibiting significant micromolar inhibitory activity. These findings provide valuable scaffolds for the development of advanced therapeutics targeting Mpro. The comprehensive nature of our approach, spanning computational predictions to experimental validations, offers a robust pathway for rapid and efficient identification of potential drug candidates against COVID-19.

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http://dx.doi.org/10.1186/s12985-024-02607-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11662536PMC

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