A chemotherapy medication originally developed to treat cancer could potentially be repurposed to inhibit the replication of the novel coronavirus and treat Covid-19, according to a study based on computer simulations and lab experiments. The research, published in the publication PLOS Computational Biology, combined a couple of computational techniques that simulate drug-virus interactions from different, complimentary perspectives. The use of this hybrid approach, scientists from the Shenzhen Institutes of Advanced Technology in China, screened 1,906 existing drugs for their potential ability to inhibit replication of the coronavirus by targeting a viral protein called RNA-dependent RNA polymerase (RdRP).
The researchers identified four promising drugs, that have been then tested against the SARS-CoV-2 virus in lab experiments. They said two of the drugs, pralatrexate and azithromycin, successfully inhibited replication of the virus, and further lab experiments showed that pralatrexate more strongly inhibited viral replication than did remdesivir — a drug that is currently used to treat some Covid-19 patients.
According to the scientists, the findings propose that pralatrexate could potentially be repurposed to treat Covid-19. Then again, the researchers said the chemotherapy drug may immediate remarkable side effects and is used for people with terminal lymphoma, so they added that instant use for Covid-19 patients isn’t guaranteed. But the research highlighted the importance of the new screening strategy to identify drugs which may be repurposed.
“We have demonstrated the value of our novel hybrid approach that combines deep-learning technologies with more traditional simulations of molecular dynamics,” said study writer Haiping Zhang of the Shenzhen Institutes of Advanced Technology.
The researchers are now developing extra computational methods for generating novel molecular structures which may be developed into new drugs to treat Covid-19.
(This story has been published from a wire agency feed without modifications to the text. )
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