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The research, published in the journal PLOS Computational Biology, combined multiple computational techniques that simulate drug-virus interactions from different, complementary perspectives.
Using 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 novel coronavirus by targeting a viral protein called RNA-dependent RNA polymerase (RdRP).
The researchers identified four promising drugs, which were then tested against the SARS-CoV-2 virus in lab experiments.
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However, the researchers said the chemotherapy drug may prompt significant side effects and is used for people with terminal lymphoma, so they added that immediate use for COVID-19 patients is not guaranteed.
But the research highlighted the importance of the new screening strategy to identify drugs that could 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 author Haiping Zhang of the Shenzhen Institutes of Advanced Technology.
The researchers are now developing additional computational methods for generating novel molecular structures that could be developed into new drugs to treat COVID-19.