A Large-scale Drug Repositioning Survey for SARS-CoV-2 Antivirals

This article has been Reviewed by the following groups

Read the full article

Abstract

The emergence of novel SARS coronavirus 2 (SARS-CoV-2) in 2019 has triggered an ongoing global pandemic of severe pneumonia-like disease designated as coronavirus disease 2019 (COVID-19). To date, more than 2.1 million confirmed cases and 139,500 deaths have been reported worldwide, and there are currently no medical countermeasures available to prevent or treat the disease. As the development of a vaccine could require at least 12-18 months, and the typical timeline from hit finding to drug registration of an antiviral is >10 years, repositioning of known drugs can significantly accelerate the development and deployment of therapies for COVID-19. To identify therapeutics that can be repurposed as SARS-CoV-2 antivirals, we profiled a library of known drugs encompassing approximately 12,000 clinical-stage or FDA-approved small molecules. Here, we report the identification of 30 known drugs that inhibit viral replication. Of these, six were characterized for cellular dose-activity relationships, and showed effective concentrations likely to be commensurate with therapeutic doses in patients. These include the PIKfyve kinase inhibitor Apilimod, cysteine protease inhibitors MDL-28170, Z LVG CHN2, VBY-825, and ONO 5334, and the CCR1 antagonist MLN-3897. Since many of these molecules have advanced into the clinic, the known pharmacological and human safety profiles of these compounds will accelerate their preclinical and clinical evaluation for COVID-19 treatment.

Article activity feed

  1. SciScore for 10.1101/2020.04.16.044016: (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
    Vero E6 and Huh-7 cells (Apath LLC, Brooklyn) were maintained in Dulbecco’s modified eagle medium (DMEM, Gibco) supplemented with 10 % heat-inactivated fetal bovine serum (FBS, Gibco), 50 U/mL penicillin, 50 µg/mL streptomycin, 1 mM sodium pyruvate (Gibco), 10 mM HEPES (Gibco), and 1X MEM non-essential amino acids solution (
    Vero E6
    suggested: RRID:CVCL_XD71)
    Huh-7
    suggested: None
    Software and Algorithms
    SentencesResources
    Each annotation property was tested for enrichment among the screening hits using the GSEA software38,39.
    GSEA
    suggested: (SeqGSEA, RRID:SCR_005724)

    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: We detected the following sentences addressing limitations in the study:
    Of note, one potential limitation of Vero cells is that, due to species differences, pro-drugs that require the human host cell machinery for processing into their active form, such as some nucleoside inhibitors, may not harbor the same potency as in human cells. Consistently, we found that remdesivir inhibits SARS-CoV-2 replication ∼60-fold more potently in human cells in comparison to Vero E6 cells (Figure 3A and Figure S5; data not shown). The dynamic range of the viral-induced CPE in the assay was small (∼2-2.5 fold), but robust and reproducible (Figure 1B). Both the optimization using the LOPAC® 1280library and the first ReFRAME collection screen displayed acceptable Z’ factors (0.4 and 0.51, respectively). The duplicate ReFRAME screen, had a reduced dynamic range (1.5-fold) and corresponding Z’ factor (0.19). Although the correlation between the two ReFRAME replications was high (R2=0.68), there were compounds that were found active in replicate 1, but not replicate 2 (Figure 1C, bottom right of middle panel). While we leveraged all datasets to select molecules for further validation, compound selection was weighted for replicate 1. Specifically, in addition to 28 molecules from the LOPAC®1280 library, 250 drugs were selected based on their activity. 48 additional ones, belonging to enriched target/MOA sets based on GSEA analysis, were also included. These selected compounds were tested in an orthogonal assay that directly measures viral replication, in contrast to the ...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    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.