Framycetin for COVID-19

The total cases of novel corona virus (SARS-CoV-2) infections is more than one million and total deaths recorded is more than fifty thousand. The research for developing vaccines and drugs against SARS-CoV-2 is going on in different parts of the world. Aim of the present study was to identify potential drug candidates against SARS-CoV-2 from existing drugs using in silico molecular modeling and docking. The targets for the present study was the spike protein and the main protease of SARS-CoV-2. The study was able to identify some drugs that can either bind to the spike protein receptor binding domain or the main protease of SARS-CoV-2. These include some of the antiviral drugs. These drugs might have the potential to inhibit the infection and viral replication.

Abstract Using as a template the crystal structure of the SARS-CoV-2 main protease, we developed a pharmacophore model of functional centers of the protease inhibitor-binding pocket. With this model, we conducted data mining of the conformational database of FDA-approved drugs. This search brought 64 compounds that can be potential inhibitors of the SARS-CoV-2 protease. The conformations of these compounds undergone 3D fingerprint similarity clusterization. Then we conducted docking of possible conformers of these drugs to the binding pocket of the protease. We also conducted the same docking of random compounds. Free energies of the docking interaction for the selected compounds were clearly lower than random compounds. Three of the selected compounds were carfilzomib, cyclosporine A, and azithromycin—the drugs that already are tested for COVID-19 treatment. Among the selected compounds are two HIV protease inhibitors and two hepatitis C protease inhibitors. We recommend testing of the selected compounds for treatment of COVID-19.