Identification of five antiviral compounds from the Pandemic Response Box targeting SARS-CoV-2

  1. Melle Holwerda
  2. Philip V’kovski
  3. Manon Wider
  4. Volker Thiel
  5. Ronald Dijkman

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Abstract

With currently over 4 million confirmed cases worldwide, including more than 300’000 deaths, the current Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic has a major impact on the economy and health care system. Currently, a limited amount of prophylactic or therapeutic intervention options are available against SARS-CoV-2. In this study, we screened 400 compounds from the antimicrobial ‘Pandemic Response Box’ library for inhibiting properties against SARS-CoV-2. We identified sixteen compounds that potently inhibited SARS-CoV-2 replication, of which five compounds displayed equal or even higher antiviral activity compared to Remdesivir. These results show that five compounds should be further investigated for their mode of action, safety and efficacy against SARS-CoV-2.

Highlights

  • 400 compounds from the pandemic response box were tested for antiviral activity against SARS-CoV-2.

  • 5 compounds had an equal or higher antiviral efficacy towards SARS-CoV-2, compared to the nucleoside analogue Remdesivir.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.17.100404: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    IC50 determination of selected compounds: Vero-E6 cells were seeded in 96-well clear bottom, black plates (Costar), 20’000 cells per well one day prior to the experiment.
    Vero-E6
    suggested: None
    Experimental Models: Organisms/Strains
    SentencesResources
    SARS-CoV-2 (SARS-CoV-2/München-1.1/2020/929 [15], stocks were produced on Vero-E6 cells, aliquoted and stored at - 80°C.
    SARS-CoV-2 (SARS-CoV-2/München-1.1/2020/929
    suggested: None
    Software and Algorithms
    SentencesResources
    Four images per well were acquired to cover the entire surface of the well and processed and stitched using the Gen5 Image prime software package (v3.08.01).
    Gen5
    suggested: (Gen5, RRID:SCR_017317)
    Data representation: Graphs were generated using GraphPad Prism software version 8.4.2 and the final figures were assembled in Adobe Illustrator CS6.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Adobe Illustrator
    suggested: (Adobe Illustrator, RRID:SCR_010279)
    Brightness and contrast of microscopy picture were minimally adjusted and processed identically to their corresponding control using FIJI.
    FIJI
    suggested: (Fiji, RRID:SCR_002285)

    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: No clinical trial numbers were referenced.

    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.

  2. Version published to 10.1101/2020.05.17.100404v1 on bioRxiv