Hybrid screening finds that pralatrexate inhibits COVID-19

In lab experiments, pralatrexate outperformed remdesivir against SARS-CoV-2

Dec 31, 2020
Mel J. Yeates
Hybrid screening finds that pralatrexate inhibits COVID-19

SHENZHEN, China—A novel computational drug screening strategy has suggested that pralatrexate — a chemotherapy medication originally developed for treating lymphoma — has the potential to be repurposed as a COVID-19 treatment. Haiping Zhang of the Shenzhen Institutes of Advanced Technology and colleagues have presented their findings in PLOS Computational Biology.

Zhang and his colleagues combined multiple computational techniques that simulate drug-virus interactions from different, complementary perspectives. They used this hybrid approach to screen 1,906 existing drugs for the potential ability to inhibit replication of SARS-CoV-2 by targeting RNA-dependent RNA polymerase (RdRP).

“Previously, we have developed two deep learning-based models to estimate protein-ligand interactions: DFCNN [15] and DeepBindBC (http://cbblab.siat.ac.cn/DeepBindBC/index.php),” notes the article. “DFCNN uses molecular vector data of protein pocket and ligand, instead of spatial information at interaction site, to estimate the protein-ligand pair as binding or non-binding with a probability value between 0 and 1. DeepBindBC estimates the binding possibility from atom contact information at interaction surface of a modeled 3D protein-ligand complex. The input of DeepBindBC contains spatial information of the protein-ligand interface, thus it strongly complements DFCNN.”

“We propose a hybrid screening procedure, based on deep learning and molecular simulation, consisting of DFCNN [15], DeepBindBC, Autodock Vina [16], pocket localized molecular dynamics simulation, and metadynamics, as well as our in-house developed tools, to explore the binding potential of drugs,” the article continues.

The researchers’ screening approach identified four promising drugs, which were tested against SARS-CoV-2 in lab experiments. Two of the drugs — pralatrexate and azithromycin — successfully inhibited virus replication. Further in vitro experiments showed that pralatrexate inhibited viral replication more strongly than remdesivir, a drug currently in use for treating COVID-19.

“Pralatrexate is a folate analogue metabolic inhibitor, which was approved by FDA in 2009 for the treatment of patients with relapsed or refractory peripheral T cell lymphoma (PTCL). Pralatrexate inhibits the folate metabolism pathway through inhibition of dihydrofolate reductase (DHFR) [23],” says the article. 

“Pralatrexate was selected by the virtual screening pipeline based on its potential acts of inhibiting the RdRp enzyme, whereas its extremely low EC50 for the virus replication compared to Remdesivir (RdRp inhibitor) may have multiple mechanism of action involved as well,” the article adds. “Pralatrexate is known to be an antifolate that efficiently prevents synthesis of DNA and presumably also RNA [25], which may explain inhibition of SARS-CoV-2 replication.” 

The findings suggest that pralatrexate has the potential to be repurposed for treating COVID-19. The chemotherapy drug can have significant side effects, so its effectiveness in COVID-19 patients isn’t guaranteed. However, the findings do support the use of this 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,” Zhang stated. He and his colleagues now plan to develop additional computational methods, in the hopes of generating novel molecular structures for development into new drugs to treat COVID-19.

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