Identification of Potent and Safe Antiviral Therapeutic Candidates Against SARS-CoV-2

  1. Xia Xiao
  2. Conghui Wang
  3. De Chang
  4. Ying Wang
  5. Xiaojing Dong
  6. Tao Jiao
  7. Zhendong Zhao
  8. Lili Ren
  9. Charles S. Dela Cruz
  10. Lokesh Sharma
  11. Xiaobo Lei
  12. Jianwei Wang

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Abstract

COVID-19 pandemic has infected millions of people with mortality exceeding >1 million. There is an urgent need to find therapeutic agents that can help clear the virus to prevent severe disease and death. Identifying effective and safer drugs can provide more options to treat COVID-19 infections either alone or in combination. Here, we performed a high throughput screening of approximately 1,700 US FDA-approved compounds to identify novel therapeutic agents that can effectively inhibit replication of coronaviruses including SARS-CoV-2. Our two-step screen first used a human coronavirus strain OC43 to identify compounds with anti-coronaviral activities. The effective compounds were then screened for their effectiveness in inhibiting SARS-CoV-2. These screens have identified 20 anti-SARS-CoV-2 drugs including previously reported compounds such as hydroxychloroquine, amlodipine besylate, arbidol hydrochloride, tilorone 2HCl, dronedarone hydrochloride, mefloquine, and thioridazine hydrochloride. Five of the newly identified drugs had a safety index (cytotoxic/effective concentration) of >600, indicating a wide therapeutic window compared to hydroxychloroquine which had a safety index of 22 in similar experiments. Mechanistically, five of the effective compounds (fendiline HCl, monensin sodium salt, vortioxetine, sertraline HCl, and salifungin) were found to block SARS-CoV-2 S protein-mediated cell fusion. These FDA-approved compounds can provide much needed therapeutic options that we urgently need during the midst of the pandemic.

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  1. Version published to 10.3389/fimmu.2020.586572
  2. ScreenIT

    SciScore for 10.1101/2020.07.06.188953: (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

    Antibodies
    SentencesResources
    Rabbit polyclonal against SARS-CoV-2 N protein antibody was purchased from Sino Biological (Beijing, China)
    SARS-CoV-2 N protein antibody
    suggested: (ABclonal Cat# A20021, RRID:AB_2862924)
    SARS-CoV-2 N protein
    suggested: None
    Immunofluorescence staining was performed using mouse anti-OC43 NP antibody, followed by anti-mouse Alexa Flour 488 and DAPI (Sigma, St. Louis, MO).
    anti-OC43 NP
    suggested: None
    anti-mouse
    suggested: None
    Immunofluorescence was conducted with mouse anti-OC43 N protein antibody, or rabbit anti-SARS-CoV-2-NP antibody, and followed by anti-mouse, or anti-rabbit Alexa Flour 488 and DAPI.
    anti-OC43 N protein
    suggested: None
    anti-SARS-CoV-2-NP
    suggested: None
    anti-rabbit
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    HEK293T cells stably expressing recombinant human ACE2 (293T/hACE2) were maintained in Dulbecco’s MEM containing 10% fetal bovine serum and 100 unit penicillin, and 100μg streptomycin per milliliter.
    HEK293T
    suggested: None
    The next day, LLC-MK2 cells were treated with the compounds at a concentration of 10μM.
    LLC-MK2
    suggested: None
    IC50 (The half maximal Inhibitory concentration), CC50 (The half maximal cytotoxic concentration) and SI (Selectivity index) determination: LLC-MK2 cells (for OC43 infection) or Vero cells (for SARS-CoV-2 infection) were seeded in 96 wells plate one day before infection at the concentration of 2×104 cells /well or 1.4×104 cells /well, respectively.
    Vero
    suggested: RRID:CVCL_ZW93)
    Briefly, HEK-293T cells were co-transfected with SARS-CoV-2-S glycoprotein and eGFP.
    HEK-293T
    suggested: None
    Software and Algorithms
    SentencesResources
    The data were nonlinear fitting by graphpad 7.0 software to calculate IC50 of each drug.
    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.
    • 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.

  3. Version published to 10.1101/2020.07.06.188953v1 on bioRxiv