The COVID-19 pandemic has caused more than 1.84 million deaths and there have been over 84.3 million confirmed cases worldwide, according to the World Health Organization. Remdesivir has been approved by the FDA to treat COVID-19 in certain patients; however, according to the study, pralatrexate outperformed it in lab experiments. More treatments for COVID-19 are urgently needed and computational methods may be able to identify drugs that can be repurposed to treat the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19.
Investigators from the Shenzhen Institutes of Advanced Technology in Shenzhen, China combined multiple computational techniques that stimulate drug-virus interaction from different, complimentary perspectives, according to the study. More than 1900 drugs were screened for their potential use against the SARS-CoV-2 virus by targeting RNA-dependent RNA polymerase (RdRP).
The screening process identified 4 potential drugs that were then tested against SARS-CoV-2 in lab experiments. Of the 4 drugs, pralatrexate and azithromycin successfully inhibited the replication of the virus. According to the study, further experimentation found that pralatrexate was more effective at viral inhibition than remdesivir.
“We have demonstrated the value of our novel hybrid approach that combines deep-learning technologies with more traditional simulations of molecular dynamics,” said researcher Haiping Zhang, PhD, in a press release.
Although the findings indicating that pralatrexate could potentially be repurposed to treat COVID-19 are promising, the drug poses significant adverse effects, according to the study. Additionally, the drug is used to treat those with terminal lymphoma, so immediate use for patients with COVID-19 cannot be guaranteed.
New virtual screening strategy identifies existing drug that inhibits COVID-19 virus [News Release] December 31, 2020; Shenzhen, China. Accessed January 5, 2021. https://www.sciencedaily.com/releases/2020/12/201231141456.htm.