Targeting CoV-2 Spike RBD and ACE-2 Interaction with Flavonoids of Anatolian Propolis by in silico and in vitro Studies in terms of possible COVID-19 therapeutics

  1. Halil Ibrahim Guler
  2. Fulya Ay Sal
  3. Zehra Can
  4. Yakup Kara
  5. Oktay Yildiz
  6. Ali Osman Belduz
  7. Sabriye Çanakci
  8. Sevgi Kolayli

Reviewed by

Read the full article

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Propolis is a multi-functional bee product with a rich in polyphenols. In this study, the inhibition effect of Anatolian propolis against SARS coronavirus-2 (SARS CoV-2) was investigated as in vitro and in silico . Raw and commercial of propolis samples were used in the study and it was found that both of were rich in caffeic acid, p-coumaric acid, ferulic acid, t-cinnamic acid, hesperetin, chrysin, pinocembrin and caffeic acid phenethyl ester (CAPE) by HPLC-UV analysis. The ethanolic propolis extracts (EPE) were used in the screening ELISA test against the spike S1 protein (SARS Cov-2): ACE-2 inhibition KIT for in vitro study. Binding energy constants of these polyphenols to the CoV-2 Spike S1 RBD and ACE-2proteinwere calculated separately as molecular docking study using AutoDock 4.2 molecular docking software. In addition, pharmacokinetics and drug-likeness properties of these eight polyphenols were calculated according to the SwissADME tool. Binding energy constant of pinocembrin was the highest for both of the receptors, followed by chrysin, CAPE and hesperetin. In silico ADME behavior of the eight polyphenols were found potential ability to work effectively as novel drugs. The findings of both studies showed that propolis has a high inhibitory potential against Covid-19 virus. However, further studies are needed.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.02.22.432207: (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
    Molecular Docking Studies: AutoDock 4.2 software for performing molecular docking studies was used to investigate the possible interactions of eight ligands and reference molecule with the target proteins.
    AutoDock
    suggested: (AutoDock, RRID:SCR_012746)
    The 3-D structure of all ligands (pinocembrin, chrysin, cape, hesperetin, ferulic acid, t-cinnamic acid, p-coumaric acid, caffeic acid) and reference molecule (Hydroxychloroquine) were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/
    https://pubchem.ncbi.nlm.nih.gov/
    suggested: (PubChem BioAssay, RRID:SCR_010734)
    The SMILES format retrieved from PubChem Database of the interested ligands were used as input for analysis tool (Daina et al., 2017).
    PubChem
    suggested: (PubChem, RRID:SCR_004284)
    2.7 Statistical analyses: The statistical evaluations were carried out with the SPSS Statistic 11.5 (IBM SPSS Statistics, Armonk
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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 10.1101/2021.02.22.432207 on bioRxiv