Computational models identify several FDA approved or experimental drugs as putative agents against SARS-CoV-2

The outbreak of a novel human coronavirus (SARS-CoV-2) has evolved into global health emergency, infecting hundreds of thousands of people worldwide. In an effort to find antiviral medications, many computational groups have pursued the 3C-like protease of the virus, also known as main protease (M(pro)), as a drug target. We have identified experimental data on the inhibitory activity of compounds tested against closely related (96% sequence identity, 100% active site conservation) protease of SARS-CoV and employed this data to build Quantitative Structure-Activity Relationships (QSAR) models for this dataset. We employed these models for virtual screening of all marketed, withdrawn, experimental, and investigational drugs from DrugBank, including compounds in clinical trials. Molecular docking and similarity search approaches were explored in parallel with QSAR modeling, but molecular docking failed to correctly discriminate between experimentally active and inactive compounds, so we did not rely on this approach in prospective virtual screening. As a result of our studies, we recommended 41 approved, experimental, or investigational drugs as potential agents against SARS-CoV-2 acting as putative inhibitors of M(pro)>. Ten compounds with feasible prices were purchased and are awaiting the experimental validation. This manuscript will be updated once results are available and submitted for peer-review publication if compounds are found to be active in SARS-CoV-2 phenotypic screen.