Graph Convolutional Network-Based Screening Strategy for Rapid Identification of SARS-CoV-2 Cell-Entry Inhibitors

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Abstract

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  1. SciScore for 10.1101/2021.12.08.471787: (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

    Experimental Models: Cell Lines
    SentencesResources
    13 HEK293T cells were dispensed into black, clear-bottom 1536-well microplates (Greiner BioOne, # 789092-F)) at 5000cells/well in 5L media with 200nM pHrodo red-labeled a-Syn fibrils and incubated at 37°C, 5% CO2,
    HEK293T
    suggested: None
    SARS-CoV-2 PP assay: HEK293T-ACE2-GFP cells seeded in white, solid bottom 384-well microplates
    HEK293T-ACE2-GFP
    suggested: None
    Software and Algorithms
    SentencesResources
    Image processing and statistical analyses: Confocal images were processed using the Zeiss Zen software.
    Zeiss Zen
    suggested: None
    To measure fluorescence intensity, we used the Fiji software.
    Fiji
    suggested: (Fiji, RRID:SCR_002285)
    Statistical analyses were performed using either Excel or GraphPad Prism 9.
    Excel
    suggested: None
    Nonlinear curve fitting and IC50 calculation was done with GraphPad Prism 9 using the inhibitor response three variable model or the exponential decay model.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Images were prepared with Adobe Photoshop and assembled in Adobe Illustrator.
    Adobe Photoshop
    suggested: (Adobe Photoshop, RRID:SCR_014199)
    Adobe Illustrator
    suggested: (Adobe Illustrator, RRID:SCR_010279)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 28. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.


    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.