Structural basis of a public antibody response to SARS-CoV-2

  1. Meng Yuan
  2. Hejun Liu
  3. Nicholas C. Wu
  4. Chang-Chun D. Lee
  5. Xueyong Zhu
  6. Fangzhu Zhao
  7. Deli Huang
  8. Wenli Yu
  9. Yuanzi Hua
  10. Henry Tien
  11. Thomas F. Rogers
  12. Elise Landais
  13. Devin Sok
  14. Joseph G. Jardine
  15. Dennis R. Burton
  16. Ian A. Wilson

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Abstract

Molecular-level understanding of human neutralizing antibody responses to SARS-CoV-2 could accelerate vaccine design and facilitate drug discovery. We analyzed 294 SARS-CoV-2 antibodies and found that IGHV3-53 is the most frequently used IGHV gene for targeting the receptor binding domain (RBD) of the spike (S) protein. We determined crystal structures of two IGHV3-53 neutralizing antibodies +/- Fab CR3022 ranging from 2.33 to 3.11 Å resolution. The germline-encoded residues of IGHV3-53 dominate binding to the ACE2 binding site epitope with no overlap with the CR3022 epitope. Moreover, IGHV3-53 is used in combination with a very short CDR H3 and different light chains. Overall, IGHV3-53 represents a versatile public VH in neutralizing SARS-CoV-2 antibodies, where their specific germline features and minimal affinity maturation provide important insights for vaccine design and assessing outcomes.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.08.141267: (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
    Iterative model building and refinement were carried out in COOT (45) and PHENIX (46), respectively.
    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:
    • 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.

    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 10.1101/2020.06.08.141267 on bioRxiv