The discovery of potential natural products for targeting SARS-CoV-2 spike protein by virtual screening

  1. Guan-Yu Chen
  2. Tsung-You Yao
  3. Azaj Ahmed
  4. Yi-Cheng Pan
  5. Juan-Cheng Yang
  6. Yang-Chang Wu

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters into the cells through its spike proteins binding to human angiotensin-converting enzyme 2 (ACE2) protein and causes virus infection in host cells. Until now, there are no available antiviral drugs have been reported that can effectively block virus infection. The study aimed to discover the potential compounds to prevent viral spike proteins to bind to the human ACE2 proteins from Taiwan Database of Extracts and Compounds (TDEC) by structure-based virtual screening. In this study, to rapidly discover potential inhibitors against SARS-CoV-2 spike proteins, the molecular docking calculation was performed by AutoDock Vina program. Herein, we found that 39 potential compounds may have good binding affinities and can respectively bind to the viral receptor-binding domain (RBD) of spike protein in the prefusion conformation and spike-ACE2 complex protein in silico . Among those compounds, especially natural products thioflexibilolide A and candidine that were respectively isolated from the soft corals Sinularia flexibilis and Phaius mishmensis may have better binding affinity than others. This study provided the predictions that these compounds may have the potential to prevent SARS-CoV-2 spike protein from entry into cells.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.25.170639: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Structure-based virtual screening: The virtual screenings with molecular docking calculations were performed by AutoDock Vina (version 1.1.2) program within PyRx (version 0.8) software to discover the potential compounds binding into the viral spike protein from the compound database [23, 24].
    AutoDock Vina
    suggested: (AutoDock Vina, RRID:SCR_011958)
    PyRx
    suggested: (PyRx, RRID:SCR_018548)
    Finally, the results of the docking simulations were shown and analyzed by PyMOL and DS 2019 software.
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)

    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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • 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 10.1101/2020.06.25.170639v1 on bioRxiv