Structure-Based Design, Synthesis and Biological Evaluation of Peptidomimetic Aldehydes as a Novel Series of Antiviral Drug Candidates Targeting the SARS-CoV-2 Main Protease

  1. Wenhao Dai
  2. Bing Zhang
  3. Xia-Ming Jiang
  4. Haixia Su
  5. Jian Li
  6. Yao Zhao
  7. Xiong Xie
  8. Zhenming Jin
  9. Jingjing Peng
  10. Fengjiang Liu
  11. Chunpu Li
  12. You Li
  13. Fang Bai
  14. Haofeng Wang
  15. Xi Chen
  16. Xiaobo Cen
  17. Shulei Hu
  18. Xiuna Yang
  19. Jiang Wang
  20. Xiang Liu
  21. Gengfu Xiao
  22. Hualiang Jiang
  23. Zihe Rao
  24. Lei-Ke Zhang
  25. Yechun Xu
  26. Haitao Yang
  27. Hong Liu

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

SARS-CoV-2 is the etiological agent responsible for the COVID-19 outbreak in Wuhan. Specific antiviral drug are urgently needed to treat COVID-19 infections. The main protease (M pro ) of SARS-CoV-2 is a key CoV enzyme that plays a pivotal role in mediating viral replication and transcription, which makes it an attractive drug target. In an effort to rapidly discover lead compounds targeting M pro , two compounds ( 11a and 11b ) were designed and synthesized, both of which exhibited excellent inhibitory activity with an IC50 value of 0.05 μM and 0.04 μM respectively. Significantly, both compounds exhibited potent anti-SARS-CoV-2 infection activity in a cell-based assay with an EC50 value of 0.42 μM and 0.33 μM, respectively. The X-ray crystal structures of SARS-CoV-2 M pro in complex with 11a and 11b were determined at 1.5 Å resolution, respectively. The crystal structures showed that 11a and 11b are covalent inhibitors, the aldehyde groups of which are bound covalently to Cys145 of M pro . Both compounds showed good PK properties in vivo , and 11a also exhibited low toxicity which is promising drug leads with clinical potential that merits further studies.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.03.25.996348: (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

    No key resources detected.

    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 10.1101/2020.03.25.996348v1 on bioRxiv