Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation

Abstract

New affordable therapeutic protocols for COVID-19 are urgently needed despite the increasing number of effective vaccines and monoclonal antibodies. To this end, there is increasing attention towards computational methods for drug repositioning and de novo drug design. Here, we systematically integrated multiple data-driven computational approaches to perform virtual screening and prioritize candidate drugs for the treatment of COVID-19. From the set of prioritized drugs, we selected a subset of representative candidates to test in human cells. Two compounds, 7-hydroxystaurosporine and bafetinib, showed synergistic antiviral effects in our in vitro experiments, and strongly inhibited viral-induced syncytia formation. Moreover, since existing drug repositioning methods provide limited usable information for de novo drug design, we extracted and prioritized the chemical substructures of the identified drugs, providing a chemical vocabulary that may help to design new effective drugs.

Antidepressant and Antipsychotic Drugs Reduce Viral Infection by SARS-CoV-2 and Fluoxetine Shows Antiviral Activity Against the Novel Variants in vitro

“…The strategy of drug repurposing has been used as a method of searching novel treatments for virus-related diseases ( Dyall et al, 2014 ; Mercorelli et al, 2018 ; Serra et al, 2021 ). A pre-clinical study has shown that the antidepressant drugs, such as sertraline, paroxetine, and clomipramine, can reduce the Zaire Ebola virus (EBOV) entry to target cells ( Johansen et al, 2015 ).…”