The coronavirus disease (COVID-19) pandemic caused by a severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread worldwide recently, leading to
a global social and economic disruption. Although the emergently approved vaccine
programs against SARS-CoV-2 have been rolled out globally, the number of COVID-19
daily cases and deaths has remained significantly high. Here, we attempted to
computationally screen for possible medications for COVID-19 via rapidly estimate the
highly potential inhibitors from an FDA-approved drug database against the main
protease (Mpro) of SARS-CoV-2. The approach combined molecular docking and fast
pulling of ligand (FPL) simulations that were demonstrated to be accurate and suitable
for quick prediction of SARS-CoV-2 Mpro inhibitors. The results suggested that twentyseven compounds were capable of strongly associating with SARS-CoV-2 Mpro. Among
them, the seven top leads are daclatasvir, teniposide, etoposide, levoleucovorin,
naldemedine, cabozantinib, and irinotecan. The potential application of these drugs in
COVID-19 therapy has thus been discussed.