Evaluation of 19 antiviral drugs against SARS-CoV-2 Infection

  1. Shufeng Liu
  2. Christopher Z. Lien
  3. Prabhuanand Selvaraj
  4. Tony T. Wang

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

The global pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or 2019-nCoV) has prompted multiple clinical trials to jumpstart search for anti-SARS-CoV-2 therapies from existing drugs, including those with reported in vitro efficacies as well as those ones that are not known to inhibit SARS-CoV-2, such as ritonavir/lopinavir and favilavir. Here we report that after screening 19 antiviral drugs that are either in clinical trials or with proposed activity against SARS-CoV-2, remdesivir was the most effective. Chloroquine only effectively protected virus-induced cytopathic effect at around 30 µM with a therapeutic index of 1.5. Our findings also suggest that velpatasvir, ledipasvir, ritonavir, litonavir, lopinavir, favilavir, sofosbuvir, danoprevir, and pocapavir do not have direct antiviral effect.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.29.067983: (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
    The SARS-CoV-2 strain WA1-2020 was obtained from BEI Resources, NIAID, NIH, and had been passed three times on Vero cells and 1 time on Vero E6 cells prior to acquisition.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Vero cells were plated the day before infection into 96 well plates at 1.5 × 104 cells/well.
    Vero
    suggested: RRID:CVCL_ZW93)
    Software and Algorithms
    SentencesResources
    Both IC50 and CC50 were calculated using Prism 7.0 (Graphpad).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    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 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.
    • No funding statement was detected.
    • 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 10.1101/2020.04.29.067983v3 on bioRxiv
  3. Version published to 10.1101/2020.04.29.067983v2 on bioRxiv
  4. Version published to 10.1101/2020.04.29.067983v1 on bioRxiv