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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 ; 2022.
Article in English | Web of Science | ID: covidwho-2005565
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 M- pro and TMPRSS2, we performed FEP-ABFE-based virtual screening for similar to 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 M- pro , 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, similar to 500 TB of data generated in this work will also accelerate the further development of FEP-related methods.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Experimental Studies Language: English Journal: International Journal of High Performance Computing Applications Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Experimental Studies Language: English Journal: International Journal of High Performance Computing Applications Year: 2022 Document Type: Article