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To rapidly discover antiviral drugs targeting SARS-CoV-2 M<jats:sup> pro<\/jats:sup> and TMPRSS2, we performed FEP-ABFE\u2013based virtual screening for \u223c12,000 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<jats:sup> pro<\/jats:sup>, 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, \u223c500\u00a0TB of data generated in this work will also accelerate the further development of FEP-related methods. <\/jats:p>","DOI":"10.1177\/10943420221117797","type":"journal-article","created":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T11:03:41Z","timestamp":1661166221000},"page":"45-57","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":12,"title":["Free energy perturbation\u2013based large-scale virtual screening for effective drug discovery against COVID-19"],"prefix":"10.1177","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9357-6839","authenticated-orcid":false,"given":"Zhe","family":"Li","sequence":"first","affiliation":[{"name":"School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, P. R. 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