Suite of TMPRSS2 Assays for Screening Drug Repurposing Candidates as Potential Treatments of COVID-19

  1. Jonathan H. Shrimp
  2. John Janiszewski
  3. Catherine Z. Chen
  4. Miao Xu
  5. Kelli M. Wilson
  6. Stephen C. Kales
  7. Philip E. Sanderson
  8. Paul Shinn
  9. Rick Schneider
  10. Zina Itkin
  11. Hui Guo
  12. Min Shen
  13. Carleen Klumpp-Thomas
  14. Samuel G. Michael
  15. Wei Zheng
  16. Anton Simeonov
  17. Matthew D. Hall

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Abstract

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  1. Version published to 10.1021/acsinfecdis.2c00172
  2. ScreenIT

    SciScore for 10.1101/2022.02.04.479134: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Pseudotyped Particle Entry Assays: A SARS-CoV-2 Spike pseudotyped particle (PP) entry assay was performed as previously described (Chen et. al.) In short, 40,000 cells/well Calu3 cells (catalog HTB-55, ATCC) were seeded in white, solid bottom 96-well microplates
    HTB-55
    suggested: None
    Software and Algorithms
    SentencesResources
    The unlabeled peptide substrate, Cbz-SKPSKRSFIED was custom ordered from LifeTein.
    LifeTein
    suggested: (LifeTein, RRID:SCR_012626)
    Data normalization, visualization, and curve fitting were performed using Prism (GraphPad, San Diego, CA).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    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 10.1101/2022.02.04.479134v1 on bioRxiv