New virtual screening strategy identifies existing drug that inhibits Covid-19 virus

A new computer drug screening strategy combined with laboratory experiments suggests that pralatrexate, a chemotherapy drug originally developed to treat lymphoma, could potentially be reused to treat Covid-19. Haiping Zhang of the Shenzhen Institutes of Advanced Technology in Shenzhen, China, and colleagues present these findings in the open access journal Computational Biology PLOS.

With the Covid-19 pandemic causing illness and death around the world, better treatment is urgently needed. One shortcut could be to reuse existing drugs that were originally developed to treat other conditions. Computer methods can help identify these drugs by simulating how different drugs would interact with SARS-CoV-2, the virus that causes Covid-19.

To facilitate virtual screening for existing drugs, Zhang and his colleagues combined several computational techniques that simulate drug-virus interactions from different and complementary perspectives. They used this hybrid approach to screen 1,906 existing drugs for their potential ability to inhibit SARS-CoV-2 replication by targeting a viral protein called RNA-dependent RNA polymerase (RdRP).

The new screening approach identified four promising drugs, which were then tested against SARS-CoV-2 in lab experiments. Two of the drugs, pralatrexate and azithromycin, were successful in inhibiting virus replication. Other laboratory experiments have shown that pralatrexate inhibits viral replication more strongly than remdesivir, a drug currently used to treat some patients with Covid-19.

These results suggest that pralatrexate could potentially be reused to treat Covid-19. However, this chemotherapy drug can cause significant side effects and is used for people with terminal lymphoma, so its immediate use in Covid-19 patients is not guaranteed. Still, the results support the use of the new screening strategy to identify drugs that could be reused.

“We have demonstrated the value of our new hybrid approach which combines deep learning technologies with more traditional simulations of molecular dynamics,” says Zhang. He and his colleagues are currently developing additional computational methods to generate new molecular structures that could be developed into new drugs to treat Covid-19.