Discovery of clinically approved drugs capable of inhibiting SARS-CoV-2 in vitro infection using a phenotypic screening strategy and network-analysis to predict their potential to treat covid-19

  1. Douglas Ferreira Sales-Medina
  2. Ludmila Rodrigues Pinto Ferreira
  3. Lavínia M. D. Romera
  4. Karolina Ribeiro Gonçalves
  5. Rafael V. C. Guido
  6. Gilles Courtemanche
  7. Marcos S. Buckeridge
  8. Édison L. Durigon
  9. Carolina B. Moraes
  10. Lucio H. Freitas-Junior

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The disease caused by SARS-CoV2, covid-19, rapidly spreads worldwide, causing the greatest threat to global public health in the last 100 years. This scenario has become catastrophic as there are no approved vaccines to prevent the disease, and the main measures to contain the virus transmission are confinement and social distancing. One priority strategy is based on drug repurposing by pursuing antiviral chemotherapy that can control transmission and prevent complications associated with covid-19. With this aim, we performed a high content screening assay for the discovery of anti-SARS-CoV-2 compounds. From the 65 screened compounds, we have found four drugs capable to selectively inhibit SARS-CoV-2 in vitro infection: brequinar, abiraterone acetate, neomycin, and the extract of Hedera helix . Brequinar and abiraterone acetate had higher inhibition potency against SARS-CoV-2 than neomycin and Hedera helix extract, respectively. Drugs with reported antiviral activity and in clinical trials for covid-19, chloroquine, ivermectin, and nitazoxanide, were also included in the screening, and the last two were found to be non-selective. We used a data mining approach to build drug-host molecules-biological function-disease networks to show in a holistic way how each compound is interconnected with host node molecules and virus infection, replication, inflammatory response, and cell apoptosis. In summary, the present manuscript identified four drugs with active inhibition effect on SARS-CoV-2 in vitro infection, and by network analysis, we provided new insights and starting points for the clinical evaluation and repurposing process to treat SARS-CoV-2 infection.

Summary sentence

Discovery of drug repurposing candidates, inhibitors of SARS-CoV-2 infection in vitro , using a phenotypic screening strategy and network analysis.

Article activity feed

  1. Version published to 10.1101/2020.07.09.196337v2 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.07.09.196337: (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
    As a primary antibody, either serum from a convalescent covid-19 Brazilian patient diluted 1:500 in PBS or a polyclonal rabbit antibody anti-SARS-CoV-2 nucleocapside protein (GeneTex) at 2 μg/mL in PBS were used to detect SARS-CoV-2 infection in Vero cells.
    PBS or a polyclonal rabbit antibody anti-SARS-CoV-2 nucleocapside protein ( GeneTex ) at 2 μg/mL in PBS
    suggested: None
    anti-SARS-CoV-2 nucleocapside protein
    suggested: None
    As secondary antibodies, goat anti-human IgG labeled with FITC (Chemicon) or goat anti-rabbit IgG labeled with Alexa 488 (Thermo Scientific) was used diluted at 4 μg/mL in PBS and incubated for 30 min with 5 μg/mL 4’,6-Diamidine-2’-phenylindole dihydrochloride (DAPI, Sigma-Aldrich) in PBS to stain nuclei.
    anti-human IgG
    suggested: None
    anti-rabbit IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    1×105 Vero CCL-81 cells were seeded on each well of a 24-well plate in DMEM High Glucose supplemented as described above at 37° C with 5% CO2.
    Vero CCL-81
    suggested: None
    Phenotypic screening assay: An amount of 2000 Vero E6 cells were seeded on each well of a 384-well assay plate (Greiner Bio-One) in 40 μL of DMEM High Glucose (Sigma-Aldrich) supplemented with 10% heat-inactivated Fetal Bovine Serum (Thermo Scientific), 100 U/mL of penicillin and 100 μg/mL of streptomycin (Thermo Scientific) at 37 °C, 5% CO2 for 24 h.
    Vero E6
    suggested: RRID:CVCL_XD71)
    As a primary antibody, either serum from a convalescent covid-19 Brazilian patient diluted 1:500 in PBS or a polyclonal rabbit antibody anti-SARS-CoV-2 nucleocapside protein (GeneTex) at 2 μg/mL in PBS were used to detect SARS-CoV-2 infection in Vero cells.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)
    Software and Algorithms
    SentencesResources
    These two parameters were used to calculate the concentration of EC50 and CC50, compounds concentrations that reduce the infection ratio, and cell survival in 50%, respectively, compared to non-treated infected controls of each compound using GraphPad Prism version 7.0 (GraphPad Software, USA)
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Functional and network analysis: Functional and network analysis was performed with Ingenuity Pathway Analysis (IPA, Qiagen).
    Ingenuity Pathway Analysis
    suggested: (Ingenuity Pathway Analysis, RRID:SCR_008653)

    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 10.1101/2020.07.09.196337v1 on bioRxiv