A cyclic peptide inhibitor of the SARS-CoV-2 main protease

  1. Adam G. Kreutzer
  2. Maj Krumberger
  3. Elizabeth M. Diessner
  4. Chelsea Marie T. Parrocha
  5. Michael A. Morris
  6. Gretchen Guaglianone
  7. Carter T. Butts
  8. James S. Nowick

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Abstract

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  1. Version published to 10.1016/j.ejmech.2021.113530
  2. ScreenIT

    SciScore for 10.1101/2020.08.03.234872: (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

    Experimental Models: Cell Lines
    SentencesResources
    HEK-293 cells were plated in a 96-well plate at 15,000 cells per well.
    HEK-293
    suggested: None
    Software and Algorithms
    SentencesResources
    The IC50 value for UCI-1 was determined using the GraphPad Prism 8.4.3 software (GraphPad) by plotting the initial rates.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    :

    Docking of UCI-1 to SARS-CoV-2 Mpro: The model of the SARS-CoV-2 Mpro was generated as follows: Starting coordinates of SARS-CoV-2 Mpro were generated from the SARS-CoV-2 Mpro crystallographic structure (PDB 6YB7) using PyMOL and saved as a new PDB file.

    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)
    The lowest energy cluster, as determined by AutoDock Vina was chosen to represent the SARS-CoV-2 Mpro UCI-1 interaction model in Figure 7C.
    AutoDock
    suggested: (AutoDock, RRID:SCR_012746)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

  3. Version published to 10.1101/2020.08.03.234872v2 on bioRxiv
  4. Version published to 10.1101/2020.08.03.234872v1 on bioRxiv