TMPRSS2 Inhibitor Discovery Facilitated through an In Silico and Biochemical Screening Platform

  1. Amanda L. Peiffer
  2. Julie M. Garlick
  3. Yujin Wu
  4. Jesse W. Wotring
  5. Sahil Arora
  6. Alexander S. Harmata
  7. Daniel A. Bochar
  8. Corey J. Stephenson
  9. Matthew B. Soellner
  10. Jonathan Z. Sexton
  11. Charles L. Brooks
  12. Anna K. Mapp

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Abstract

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  1. Version published to 10.1021/acsmedchemlett.3c00035
  2. Version published to 10.1101/2021.03.22.436465v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.03.22.436465: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    TMPRSS2 antibody (Novus biologicals, NBP1-20984) was added to membrane (1:1000 dilution in Super Block) and incubated overnight at 4C with gentle shaking.
    TMPRSS2
    suggested: (Novus Cat# NBP1-20984, RRID:AB_1643199)
    Software and Algorithms
    SentencesResources
    Raw data was deconvoluted (intact protein of 20,000-25,000 Da) using BioConfirm software with background subtraction.
    BioConfirm
    suggested: None
    V0 was plotted vs substrate concentration and the data was fit to the Michaelis Menten equation using GraphPad Prism.
    GraphPad Prism
    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.
    • 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.

  4. Version published to 10.1101/2021.03.22.436465v1 on bioRxiv