Computational drug repurposing for the identification of SARS-CoV-2 main protease inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for the known COVID-19 disease. Since currently no definitive therapies or vaccines for the SARS-CoV-2 virus are avail- able, there is an urgent need to identify effective drugs against SARS-CoV-2 infection. One of the best- known targets available is the main protease of this virus, crucial for the processing of polyproteins codified by viral RNA. In this work, we used a computational virtual screening procedure for the repur- posing of commercial drugs available in the DrugBank database as inhibitors of the SARS-CoV-2 main protease. Molecular docking calculations and molecular dynamics (MD) simulations have been applied. The computational model was validated through a self-docking procedure. The screening procedure highlighted five interesting drugs that showed a comparable or higher docking score compared to the crystallographic compound and maintained the protein binding during the MD runs. Amongst these drugs, Ritonavir has been used in clinical trials with patients affected by COVID-19 and Nelfinavir showed anti-SARS-CoV-2 activity. The five identified drugs could be evaluated experimentally as inhibi- tors of the SARS-CoV-2 main protease in view of a possible COVID-19 treatment.