A repurposed drug screen identifies compounds that inhibit the binding of the COVID-19 spike protein to ACE2

  1. Kaleb B. Tsegay
  2. Christiana M. Adeyemi
  3. Edward P. Gniffke
  4. D. Noah Sather
  5. John K. Walker
  6. Stephen E. P. Smith

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Abstract

Repurposed drugs that block the interaction between the SARS-CoV-2 spike protein and its receptor ACE2 could offer a rapid route to novel COVID-19 treatments or prophylactics. Here, we screened 2701 compounds from a commercial library of drugs approved by international regulatory agencies for their ability to inhibit the binding of recombinant, trimeric SARS-CoV-2 spike protein to recombinant human ACE2. We identified 56 compounds that inhibited binding by <90%, measured the EC 50 of binding inhibition, and computationally modeled the docking of the best inhibitors to both Spike and ACE2. These results highlight an effective screening approach to identify compounds capable of disrupting the Spike-ACE2 interaction as well as identifying several potential inhibitors that could serve as templates for future drug discovery efforts.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.08.439071: (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
    In Silico Modeling: The S1 subunit of SARS-CoV-2 spike protein comprising the receptor binding domain (RBD) was modelled using the SWISS-MODEL server11, the FASTA sequence (residues 316-530) was retrieved from UniProtKB - P0DTC2 and used as a query sequence, PDB ID: 6VSB with 100% sequence identity was used as a template12,13.
    UniProtKB
    suggested: (UniProtKB, RRID:SCR_004426)
    The SDF structures of the selected FDA-approved drugs were downloaded from Selleck chemicals and PubChem.
    PubChem
    suggested: (PubChem, RRID:SCR_004284)
    Ligand and protein preparation was performed using the Ligprep and protein preparation wizard tool on Schrödinger Maestro version 12.2.
    Maestro
    suggested: (Maestro, RRID:SCR_016748)

    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 10.1101/2021.04.08.439071 on bioRxiv