The neutralization effect of Montelukast on SARS-CoV-2 is shown by multiscale in silico simulations and combined in vitro studies

  1. Serdar Durdagi
  2. Timucin Avsar
  3. Muge Didem Orhan
  4. Muge Serhatli
  5. Bertan Koray Balcioglu
  6. Hasan Umit Ozturk
  7. Alisan Kayabolen
  8. Yuksel Cetin
  9. Seyma Aydinlik
  10. Tugba Bagci-Onder
  11. Saban Tekin
  12. Hasan Demirci
  13. Mustafa Guzel
  14. Atilla Akdemir
  15. Seyma Calis
  16. Lalehan Oktay
  17. Ilayda Tolu
  18. Yasar Enes Butun
  19. Ece Erdemoglu
  20. Alpsu Olkan
  21. Nurettin Tokay
  22. Şeyma Işık
  23. Aysenur Ozcan
  24. Elif Acar
  25. Sehriban Buyukkilic
  26. Yesim Yumak

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Small molecule inhibitors have previously been investigated in different studies as possible therapeutics in the treatment of SARS-CoV-2. In the current drug repurposing study, we identified the leukotriene (D4) receptor antagonist Montelukast as a novel agent that simultaneously targets two important drug targets of SARS-CoV-2. We initially demonstrated the dual inhibition profile of Montelukast through multiscale molecular modeling studies. Next, we characterized its effect on both targets by different in vitro experiments including the Fluorescent Resonance Energy Transfer (FRET)-based main protease enzyme inhibition assay, surface plasmon resonance (SPR) spectroscopy, pseudovirus neutralization on HEK293T / hACE2, and virus neutralization assay using xCELLigence MP real time cell analyzer. Our integrated in silico and in vitro results confirmed the dual potential effect of the Montelukast both on virus entry into the host cell (Spike/ACE2) and on the main protease enzyme inhibition. The virus neutralization assay results showed that while no cytotoxicity of the Montelukast was observed at 12 μM concentration, the cell index time 50 (CIT 50 ) value was delayed for 12 hours. Moreover, it was also shown that Favipiravir, a well-known antiviral used in COVID-19 therapy, should be used by 16-fold higher concentrations than Montelukast in order to have the same effect of Montelukast. The rapid use of new small molecules in the pandemic is very important today. Montelukast, whose pharmacokinetic and pharmacodynamic properties are very well characterized and has been widely used in the treatment of asthma since 1998, should urgently be completed in clinical phase studies and if its effect is proven in clinical phase studies, it should be used against COVID-19.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.12.26.424423: (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
    It is expected that VERO E6 cells in the presence of the SARS-CoV2 virus will demonstrate a decrease in CI values.
    VERO E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    Montelukast structure was downloaded from PubChem (https://pubchem.ncbi.nlm.nih.gov/) and LigPrep module of the Maestro molecular modeling package was used in ligand preparation with OPLS3e force field.
    PubChem
    suggested: (PubChem, RRID:SCR_004284)
    https://pubchem.ncbi.nlm.nih.gov/
    suggested: (PubChem BioAssay, RRID:SCR_010734)
    Protein preparation tool of Maestro was used in both targets at physiological pH.
    Maestro
    suggested: (Maestro, RRID:SCR_016748)
    The results were plotted with GraphPad Prism 8.0 software (GraphPad, San Diego CA, USA).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.
    • 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 10.1101/2020.12.26.424423 on bioRxiv