Discovery of Triple Inhibitors of Both SARS-CoV-2 Proteases and Human Cathepsin L

  1. Ittipat Meewan
  2. Jacob Kattoula
  3. Julius Y. Kattoula
  4. Danielle Skinner
  5. Pavla Fajtová
  6. Miriam A. Giardini
  7. Brendon Woodworth
  8. James H. McKerrow
  9. Jair Lage de Siqueira-Neto
  10. Anthony J. O’Donoghue
  11. Ruben Abagyan

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Abstract

One inhibitor of the main SARS-CoV-2 protease has been approved recently by the FDA, yet it targets only SARS-CoV-2 main protease (Mpro). Here, we discovered inhibitors containing thiuram disulfide or dithiobis-(thioformate) tested against three key proteases involved in SARS-CoV-2 replication, including Mpro, SARS-CoV-2 papain-like protease (PLpro), and human cathepsin L. The use of thiuram disulfide and dithiobis-(thioformate) covalent inhibitor warheads was inspired by an idea to find a better alternative than disulfiram, an approved treatment for chronic alcoholism that is currently in phase 2 clinical trials against SARS-CoV-2. Our goal was to find more potent inhibitors that target both viral proteases and one essential human protease to reduce the dosage, improve the efficacy, and minimize the adverse effects associated with these agents. We found that compounds coded as RI175, RI173, and RI172 were the most potent inhibitors in an enzymatic assay against SARS-CoV-2 Mpro, SARS-CoV-2 PLpro, and human cathepsin L, with IC50s of 300, 200, and 200 nM, which is about 5-, 19-, and 11-fold more potent than disulfiram, respectively. In addition, RI173 was tested against SARS-CoV-2 in a cell-based and toxicity assay and was shown to have a greater antiviral effect than disulfiram. The identified compounds demonstrated the promising potential of thiuram disulfide or dithiobis-(thioformate) as a reactive functional group in small molecules that could be further developed for treatment of the COVID-19 virus or related variants.

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  1. Version published to 10.3390/ph15060744
  2. ScreenIT

    SciScore for 10.1101/2021.10.19.465036: (What is this?)

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

    Table 1: Rigor

    EthicsEuthanasia Agents: Cells were incubated overnight at 37 °C with 5% of CO2.
    Sex as a biological variablenot detected.
    RandomizationThe algorithm for sampling 3D conformation of ligands and pockets was generated randomly based on biased probability Monte Carlo.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The plates were then fixed with 4% PFA evaluated immunofluorescence signal for viral detection using Rabbit anti-nucleocapsid (GeneTex, cat# GTX135357) and anti-Rabbit Alexa488 as a secondary antibody.
    anti-nucleocapsid
    suggested: (GeneTex Cat# GTX135357, RRID:AB_2868464)
    anti-Rabbit
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Cells culture and immunofluorescence assay: For infectivity assay, Vero-E6 cells (2,000 cells/well, 384 well plate format) were used as host cells, infected with SARS-CoV-2 in an ‘multiplicity-of-infection’ value (MOI) of 1.0.
    Vero-E6
    suggested: None
    Certain concentrations of compounds were spotted in the plates, followed by the Vero cells.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)
    Software and Algorithms
    SentencesResources
    All fluorescence signals were detected using Synergy HTX Multi-Mode Microplate Reader (BioTek) and data were visualized using Gen5 Software (BioTek).
    Gen5
    suggested: (Gen5, RRID:SCR_017317)
    Dose response curves of each compound against all selected proteases were performed on 10 concentrations in triplicate ranging from 50 mM to 100 nM and IC50 values of each compound were calculated accordingly using SciPy and Matplotlib Python packages.
    SciPy
    suggested: (SciPy, RRID:SCR_008058)
    Matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)
    Python
    suggested: (IPython, RRID:SCR_001658)
    The image signals were analyzed using MetaXpress software to quantify individual cells and infected cells.
    MetaXpress
    suggested: (MetaXpress, RRID:SCR_016654)

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.10.19.465036v1 on bioRxiv