QSAR Modeling of SARS-CoV Mpro Inhibitors Identifies Drugs as Candidates for  Repurposing against SARS-CoV-2 

The SARS-CoV-2 main protease (Mpro) has been proposed as one of the major drug targets for  COVID-19. We have collected experimental data on the inhibitory activity of compounds tested  against the closely related Mpro of SARS-CoV (96 % sequence identity, 100 % active site  conservation). After rigorous data curation, we developed QSAR models of these inhibitors and  employed the models for virtual screening of all drugs in the DrugBank database. Similarity searching and molecular docking were explored in parallel, but docking failed to correctly  discriminate between experimentally active and inactive compounds, so it was not relied upon for  prospective virtual screening. Forty-two compounds were identified by our models as consensus computational hits. Subsequent to our computational studies, NCATS reported the results of  experimental screening of their drug collection in SARS-CoV-2 cytopathic effect assay (https://opendata.ncats.nih.gov/covid19/). Coincidentally, NCATS tested 11 of our 42  computational hits, and three of them, cenicriviroc (AC50 of 8.9 µM), proglumetacin (tested twice independently, with AC50 of 8.9 µM and 12.5 µM), and sufugolix (AC50 of 12.6 µM), were shown  to be active. These observations support the value of our modeling approaches and models for  guiding the experimental investigations of putative anti-COVID-19 drug candidates. All data and models used in this study are publicly available on GitHub (https://github.com/alvesvm/sars-cov mpro), and Chembench web portal (https://chembench.mml.unc.edu/).