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Computational Target-Based Drug Repurposing of Elbasvir, an Antiviral Drug Predicted to Bind Multiple SARS-CoV-2 Proteins
preprintrevised on 07.04.2020, 16:49 and posted on 08.04.2020, 10:12 by Meenakshisundaram Balasubramaniam, Robert Shmookler Reis
Coronavirus disease 19 (COVID-19) is a severe acute respiratory syndrome caused by SARS-CoV-2 (2019-nCoV). While no drugs have yet been approved to treat this disease, small molecules effective against other viral infections are under clinical evaluation for therapeutic abatement of SARS-CoV-2 infections. Ongoing clinical trials include Kaletra (a combination of two protease inhibitors approved for HIV treatment), remdesivir (an investigational drug targeting RNA-dependent RNA polymerase [RdRP] of SARS-CoV-2), and hydroxychloroquine (an approved anti-malarial and immuno-modulatory drug). Since SARS-CoV-2 replication depends on three virally encoded proteins (RdRP, papain-like proteinase, and helicase), we screened 54 FDA-approved antiviral drugs and ~3300 investigational drugs for binding to these proteins using targeted and unbiased docking simulations and computational modeling. Elbasvir, a drug approved for treating hepatitis C, is predicted to bind stably and preferentially to all three proteins. At the therapeutic dosage, elbasvir has low toxicity (liver enzymes transiently elevated in 1% of subjects) and well-characterized drug-drug interactions. We predict that treatment with elbasvir, alone or in combination with other drugs such as grazoprevir, could efficiently block SARS-CoV-2 replication. The concerted action of elbasvir on at least three targets essential for viral replication renders viral mutation to drug resistance extremely unlikely.