Pralatrexate is superior to remdesivir versus SARS-CoV-2 in laboratory experiments.
Combined with laboratory studies, a new computer-assisted drug screening technique indicates that pralatrexate, a chemotherapeutic agent that was initially developed to treat lymphoma, may theoretically be used to treat covid-19. In the open-access journal PLOS Computational Biology, Haiping Zhang of the Shenzhen Institutes of Advanced Technology in Shenzhen, China, and colleagues present these results.
With the worldwide Covid 19 pandemic causing disease and death, improved therapies are desperately required. Reuse of existing medicines initially designed to treat other diseases may be one shortcut.
By simulating how different drugs can interact with SARS-CoV-2, the virus that causes covid-19, computational methods will help classify certain drugs.
Zhang and colleagues combined many computational strategies that model drug-virus interactions from distinct, complementary viewpoints to assist in the virtual screening of existing drugs.
Using this hybrid method, 1,906 existing drugs were tested for their potential ability to inhibit replication of SARS-CoV-2 by targeting a viral protein called RNA-dependent RNA polymerase (RdRP).
Four promising drugs were established by the novel screening technique, which were then tested in laboratory trials against SARS-CoV-2.
Viral replication was successfully blocked by two of the drugs, pralatrexate and azithromycin.
Further laboratory studies have shown that pralatrexate has more significantly inhibited viral replication than remdesivir, a medication commonly used to treat certain patients with Covid-19.
These findings indicate that for the treatment of covid-19, pralatrexate may theoretically be used. This chemotherapy agent can, however, cause severe side effects and is used in people with end-stage lymphoma, so immediate use is not warranted in patients with Covid-19. Nevertheless, the findings support the use of the latest screening method to classify drugs that could be repurposed.
“We have demonstrated the value of our novel hybrid approach that combines deep learning technologies with more traditional molecular dynamics simulations,” Zhang says. In order to produce new molecular structures that could be transformed into new drugs to treat covid-19, he and his colleagues are now developing additional computational methods.
Zhang H, Yang Y, Li J, Wang M, Saravanan KM, Wei J, et al, December 31, 2020, PLOS Computational Biology.DOI: 10.1371/journal.pcbi.10084899 Reference: “A novel virtual screening procedure identifies Pralatrexate as inhibitor of SARS-CoV-2 RdRp and it reduces viral replication in vitro”
Funding: this study was partly funded under Grant No. 2018YFB0204403 (Y.W.) and 2019YFA0906100 (X.W.) by China’s National Key Research and Development Program; Strategic Priority CAS Project XDB380000 to Y.W., National Main Project for Science and Technology under Grant No. 2018ZX10101004 (Y.Y.), China National Science Foundation under Grant No. U1813203 (Y.W.); China’s National Foundation of Natural Youth Science (Grant No. 31601028: Y.P.); the Shenzhen Fundamental Research Fund under Grant No. JCYJ20190807170801656 (J.L.), JCYJ20180507182818013 (Y.W.), JCYJ20170413093358429 (Y.W.); and the Excellent Young Researchers Innovation Program at SIAT (J.L.).
The funders had no impact on the design of the report, the collection and analysis of data, the decision to publish, or the manuscript preparation.