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Free energy perturbation–based large-scale virtual screening for effective drug discovery against COVID-19
International Journal of High Performance Computing Applications ; 37(1):45-57, 2023.
Article in English | Scopus | ID: covidwho-2242698
ABSTRACT
As a theoretically rigorous and accurate method, FEP-ABFE (Free Energy Perturbation-Absolute Binding Free Energy) calculations showed great potential in drug discovery, but its practical application was difficult due to high computational cost. To rapidly discover antiviral drugs targeting SARS-CoV-2 Mpro and TMPRSS2, we performed FEP-ABFE–based virtual screening for ∼12,000 protein-ligand binding systems on a new generation of Tianhe supercomputer. A task management tool was specifically developed for automating the whole process involving more than 500,000 MD tasks. In further experimental validation, 50 out of 98 tested compounds showed significant inhibitory activity towards Mpro, and one representative inhibitor, dipyridamole, showed remarkable outcomes in subsequent clinical trials. This work not only demonstrates the potential of FEP-ABFE in drug discovery but also provides an excellent starting point for further development of anti-SARS-CoV-2 drugs. Besides, ∼500 TB of data generated in this work will also accelerate the further development of FEP-related methods. © The Author(s) 2022.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies Language: English Journal: International Journal of High Performance Computing Applications Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies Language: English Journal: International Journal of High Performance Computing Applications Year: 2023 Document Type: Article