Theoretical and Computational Chemistry

Fast Identification of Possible Drug Treatment of Coronavirus Disease -19 (COVID-19) Through Computational Drug Repurposing Study



The recent outbreak of novel coronavirus disease -19 (COVID-19) calls for and welcomes possible treatment strategies using drugs on the market. It is very efficient to apply computer-aided drug design techniques to quickly identify promising drug repurposing candidates, especially after the detailed 3D-structures of key virous proteins are resolved. Taking the advantage of a recently released crystal structure of COVID-19 protease in complex with a covalently-bonded inhibitor, N3,1 I conducted virtual docking screening of approved drugs and drug candidates in clinical trials. For the top docking hits, I then performed molecular dynamics simulations followed by binding free energy calculations using an endpoint method called MM-PBSA-WSAS.2-4 Several promising known drugs stand out as potential inhibitors of COVID-19 protease, including Carfilzomib, Eravacycline, Valrubicin, Lopinavir and Elbasvir. Carfilzomib, an approved anti-cancer drug acting as a proteasome inhibitor, has the best MM-PBSA-WSAS binding free energy, -13.82 kcal/mol. Streptomycin, an antibiotic and a charged molecule, also demonstrates some inhibitory effect, even though the predicted binding free energy of the charged form (-3.82 kcal/mol) is not nearly as low as that of the neutral form (-7.92 kcal/mol). One bioactive, PubChem 23727975, has a binding free energy of -12.86 kcal/mol. Detailed receptor-ligand interactions were analyzed and hot spots for the receptor-ligand binding were identified. I found that one hotspot residue HIS41, is a conserved residue across many viruses including COVID-19, SARS, MERS, and HCV. The findings of this study can facilitate rational drug design targeting the COVID-19 protease.


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