Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor

  1. Jun Lan
  2. Jiwan Ge
  3. Jinfang Yu
  4. Sisi Shan
  5. Huan Zhou
  6. Shilong Fan
  7. Qi Zhang
  8. Xuanling Shi
  9. Qisheng Wang
  10. Linqi Zhang
  11. Xinquan Wang

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  1. ScreenIT

    SciScore for 10.1101/2020.02.19.956235: (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.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Diffraction data were auto-processed with aquarium pipeline and the data processing statistics are listed in Table S121.
    aquarium
    suggested: (AQUARIUM, RRID:SCR_015760)
    Structural determination and refinement: The structure was determined by the molecular replacement method with PHASER in CCP4 suite22.
    CCP4
    suggested: (CCP4, RRID:SCR_007255)
    Subsequent model building and refinement were performed using COOT and PHENIX, respectively24,25.
    COOT
    suggested: (Coot, RRID:SCR_014222)
    PHENIX
    suggested: (Phenix, RRID:SCR_014224)

    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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • 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.

    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.

  2. Version published to 10.1038/s41586-020-2180-5
  3. Version published to 10.1101/2020.02.19.956235v1 on bioRxiv