A novel computational drug screening strategy combined with lab experiments suggest that pralatrexate, a chemotherapy medication originally developed to treat lymphoma, could potentially be repurposed 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 PLOS Computational Biology.
With the Covid-19 pandemic causing illness and death worldwide, better treatments are urgently needed.
One shortcut could be to repurpose existing 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 aid virtual screening of existing drugs, Zhang and colleagues combined multiple computational techniques that simulate drug-virus interactions from different, complimentary perspectives.
They used this hybrid approach to screen 1,906 existing drugs for their potential ability to inhibit replication of SARS-CoV-2 by targeting a viral protein called RNA-dependent RNA polymerase (RdRP).
The novel screening approach identified four promising drugs, which were then tested against SARS-CoV-2 in lab experiments. Two of the drugs, pralatrexate and azithromycin, successfully inhibited replication of the virus. Further lab experiments showed that pralatrexate more strongly inhibited viral replication than did remdesivir, a drug that is currently used to treat some Covid-19 patients.
However, this chemotherapy drug can prompt significant side effects and is used for people with terminal lymphoma, so immediate use for Covid-19 patients is not guaranteed.
Still, the findings support the use of the 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 says. He and his colleagues are now developing additional computational methods for generating novel molecular structures that could be developed into new drugs to treat Covid-19.
Pralatrexate is a folate analogue inhibitor of dihydrofolate reductase (DHFR) exhibiting high affinity for reduced folate carrier-1 (RFC-1) with antineoplastic and immunosuppressive activities. Pralatrexate selectively enters cells expressing RFC-1; intracellularly, this agent is highly polyglutamylated and competes for the folate binding site of DHFR, blocking tetrahydrofolate synthesis, which may result in depletion of nucleotide precursors; inhibition of DNA, RNA and protein synthesis; and apoptotic tumor cell death.
Efficient intracellular polyglutamylation of pralatrexate results in higher intracellular concentrations compared to non-polyglutamylated pralatrexate, which is more readily effuxed by the MRP (multidrug resistance protein) drug efflux pump. RFC-1, an oncofetal protein expressed at highest levels during embryonic development, may be over-expressed on the cell surfaces of various cancer cell types.
Pralatrexate and Azithromycin inhibit the replication of SARS-CoV-2 in vitro
To further confirm the efficiency of the hits from the virtual screening, we tested the antiviral activity of Azithromycin, Pralatrexate, Amoxicillin and Sofosbuvir in vitro. Experiments were performed in a biosafety level 3 laboratory where regulation requires.
Vero cells were infected with SARS-CoV-2 (BetaCoV/Shenzhen/SZTH-003/2020, GISAID No. EPI_ISL_406594) at a MOI(multiplicity of infection, which represents the ratio of the numbers of virus particles to the numbers of the host cells in a given infection medium.) of 0.02 (the cytopathic effect was mild at 48 hours post-infection with this MOI) in the presence of varying concentrations of the tested drugs, and the inhibition rates were evaluated by quantification of viral copy numbers in the cell supernatant via quantitative reverse transcription polymerase chain reaction reverse transcription polymerase chain reaction (qRT-PCR) and confirmed with immunofluorescence assay (Fig 2).
The results showed that Pralatrexate and Azithromycin could efficiently inhibit the replication of SARS-CoV-2, with half-maximal effective concentration (EC50) values of 0.008 and 9.453 μM (Fig 2A), whereas Remdesivir achieved an inhibitory activity with EC50 value of 8.777 μM within the same experimental system (S5 Fig).
Indirect immunofluorescence assay (IFA) showed similar results with qRT-PCR assay (Fig 2B). CCK-8 assay of the two drugs showed that the half-cytotoxic concentration (CC50) values of Pralatrexate and Azithromycin on Vero cells were 0.167 μM and > 100 μM, respectively, and the calculated the selectivity indexes (SI) of Pralatrexate and Azithromycin were 20.878 and >10.579, respectively.
Whether the two drugs worked at the stage of viral entry or post entry was analyzed using time-of-addition assay as previously reported . The results showed that Pralatrexate functioned at a stage post virus entry, while Azithromycin functioned at both entry and post-entry stages of the SARS-COV-2 infection in Vero cells (Fig 2C).
Furthermore, surface plasmon resonance (SPR) experiments were performed to test the in vitro binding of Pralatrexate and Azithromycin with immobilized RdRp protein of SARS-CoV-2. Both drugs showed expected binding response in S6 Fig.
reference link: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008489#pcbi.1008489.s006
More information: Zhang H, Yang Y, Li J, Wang M, Saravanan KM, Wei J, et al. (2020) A novel virtual screening procedure identifies Pralatrexate as inhibitor of SARS-CoV-2 RdRp and it reduces viral replication in vitro. PLoS Comput Biol 16(12): e1008489. DOI: 10.1371/journal.pcbi.1008489