Enisamium Inhibits SARS-CoV-2 RNA Synthesis

  1. Stefano Elli
  2. Denisa Bojkova
  3. Marco Bechtel
  4. Thomas Vial
  5. David Boltz
  6. Miguel Muzzio
  7. Xinjian Peng
  8. Federico Sala
  9. Cesare Cosentino
  10. Andrew Goy
  11. Marco Guerrini
  12. Lutz Müller
  13. Jindrich Cinatl
  14. Victor Margitich
  15. Aartjan J. W. te Velthuis

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Pandemic SARS-CoV-2 causes a mild to severe respiratory disease called coronavirus disease 2019 (COVID-19). While control of the SARS-CoV-2 spread partly depends on vaccine-induced or naturally acquired protective herd immunity, antiviral strategies are still needed to manage COVID-19. Enisamium is an inhibitor of influenza A and B viruses in cell culture and clinically approved in countries of the Commonwealth of Independent States. In vitro, enisamium acts through metabolite VR17-04 and inhibits the activity of the influenza A virus RNA polymerase. Here we show that enisamium can inhibit coronavirus infections in NHBE and Caco-2 cells, and the activity of the SARS-CoV-2 RNA polymerase in vitro. Docking and molecular dynamics simulations provide insight into the mechanism of action and indicate that enisamium metabolite VR17-04 prevents GTP and UTP incorporation. Overall, these results suggest that enisamium is an inhibitor of SARS-CoV-2 RNA synthesis in vitro.

Article activity feed

  1. Version published to 10.3390/biomedicines9091254
  2. Version published to 10.1101/2021.01.05.21249237v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.01.05.21249237: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Staining was detected using a peroxidase conjugated anti-rabbit secondary antibody (1:1000, Dianova) and the addition of AEC substrate.
    anti-rabbit
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    SARS-CoV-2 infections: Confluent layers of Caco-2 cells in 96-well plates were treated with serial dilutions of FAV00A or FAV00B 6 hours prior to infection.
    Caco-2
    suggested: None
    HCoV-NL63 NHBE infections: MatTek’s EpiAirway System (MatTek; Ashland, MA) consisted of differentiated NHBE cells that were cultured to form a multilayered, highly differentiated model that closely resembles the epithelial tissue of the respiratory tract.
    HCoV-NL63
    suggested: RRID:CVCL_RW88)
    Software and Algorithms
    SentencesResources
    Data were analysed using ImageJ and Prism 9 (GraphPad).
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Molecular docking: The docking simulation was performed using Autodock 4.2 software (21).
    Autodock
    suggested: (AutoDock, RRID:SCR_012746)
    The unpaired uracil base was subsequently mutated in cytosine (Cyt) or adenine (Ade) in Pymol 2.3.4 (Schrodinger LLC), generating two different complexes, identified as nsp12/7/8(Cyt) and nsp12/7/8(Ade) respectively.
    Pymol
    suggested: (PyMOL, RRID:SCR_000305)
    Molecular dynamic simulation: Explicit solvent MD simulation were run using NAMD 2.12 (24) software, applying the Amber force field (ff14SB) (25).
    NAMD
    suggested: (NAMD, RRID:SCR_014894)
    The t-leap application of the Ambertools 14.0 package (25) was applied to generate the topology, the parameters, and the coordinate files of the macromolecular complex simulated.
    Ambertools
    suggested: (AmberTools, RRID:SCR_018497)
    The quantum chemistry software GAMESS (27) was used for this stage.
    GAMESS
    suggested: (Gamess, RRID:SCR_014896)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04682873RecruitingA Clinical Study to Assess the Efficacy and Safety of Amizon…

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2021.01.05.21249237v1 on medRxiv