New flagship screening strategy identifies existing drug that prevents Covid-19 virus

A state-of-the-art computer drug screening strategy combined with laboratory tests suggests that pralatrexate, a chemotherapy drug originally developed to treat lymphoma, could be replicated to treat Covid-19 . Haiping Zhang of Shenzhen Institute of Advanced Technology in Shenzhen, China, and colleagues will present these findings in the open access journal PLOS Computing Biology.

With the Covid-19 pandemic causing disease and death worldwide, better treatments are urgently needed. One shortcoming could be in the replacement of drugs that were originally developed to treat other conditions. Computational methods can help identify such drugs by simulating how different drugs would interact with SARS-CoV-2, the virus that causes Covid-19.

To help with meaningful screening of existing drugs, Zhang and colleagues developed several computational techniques that are similar to drug virus interactions from different perspectives. They used this hybrid method to screen 1,906 existing drugs for their ability to inhibit the reproduction of SARS-CoV-2 by targeting a viral protein called RNA polymerase RNA which is dependent on RNA (RdRP).

The novel screening method identified four promising drugs, which were then tested against SARS-CoV-2 in laboratory experiments. Two of the drugs, pralatrexate and azithromycin, successfully inhibited the reproduction of the virus. Further laboratory tests showed that pralatrexate significantly inhibited viral replication than remdesivir, a drug currently used to treat some Covid-19 patients.

These findings suggest that pralatrexate may be replicated to treat Covid-19. However, this chemotherapy drug can induce serious side effects and is used for people with terminal lymphoma, so immediate use is not guaranteed for Covid-19 patients. However, the findings support the use of the new screening strategy to identify drugs that may be transplanted.

“We have demonstrated the value of our novel hybrid approach that combines deep learning technologies with more traditional simulations of molecular dynamics,” says Zhang. He and his colleagues are now developing techniques additional computing to generate new molecular structures that could be upgraded to new drugs to handle Covid-19.

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Peer review; Simulation / modeling

In your cover use this URL to access the article which is freely available in PLOS Computing Biology:
magazines http: //.plos.org /ploscompbiol /article? id =10.1371 /iris.pcbi.1008489

Citation: Zhang H, Yang Y, Li J, Wang M, Saravanan KM, Wei J, et al. (2020) A novel diagnostic screening method identifies Pralatrexate as an inhibitor of SARS-CoV-2 RdRp and reduces viral replication in vitro. PLoS Comput Biol 16 (12): e1008489.
https: //doi.org /10.1371 /iris.pcbi.1008489

Funding: This work was partly supported by China’s National Research and Development Program under Grant No. 2018YFB0204403 (YW) and 2019YFA0906100 (XW); CAS Project Strategic Priority XDB38000000 to YW, National Science and Technology Project under Grant No. 2018ZX10101004 (YY), China National Science Foundation under Grant no. U1813203 (YW); National Trust for Natural Youth Science of China (Grant number 31601028: YP); Shenzhen Basic Research Fund under Grant no. JCYJ20190807170801656 (JL), JCYJ20180507182818013 (YW), JCYJ20170413093358429 (YW), and SIAT Innovation Program for Outstanding Young Researchers (JL). The funders were not involved in the research design, data collection and analysis, publication decision, or preparation of the manuscript.

Competing interests: No authors have competing interests.