An artificial intelligence system reveals liquiritin inhibits SARS-CoV-2 by mimicking type I interferon

  1. Jie Zhu
  2. Yong-Qiang Deng
  3. Xin Wang
  4. Xiao-Feng Li
  5. Na-Na Zhang
  6. Zurui Liu
  7. Bowen Zhang
  8. Cheng-Feng Qin
  9. Zhengwei Xie

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Abstract

The pandemic COVID-19 has spread to all over the world and greatly threatens safety and health of people. COVID-19 is highly infectious and with high mortality rate. As no effective antiviral treatment is currently available, new drugs are urgently needed. We employed transcriptional analysis to uncover potential antiviral drugs from natural products or FDA approved drugs. We found liquiritin significantly inhibit replication of SARS-CoV-2 in Vero E6 cells with EC 50 = 2.39 μM. Mechanistically, we found liquiritin exerts anti-viral function by mimicking type I interferon. Upregulated genes induced by liquiritin are enriched in GO categories including type I interferon signaling pathway, negative regulation of viral genome replication and etc. In toxicity experiment, no death was observed when treated at dose of 300 mg/kg for a week in ICR mice. All the organ indexes but liver and serum biochemical indexes were normal after treatment. Liquiritin is abundant in licorice tablet (~0.2% by mass), a traditional Chinese medicine. Together, we recommend liquiritin as a competitive candidate for treating COVID-19. We also expect liquiritin to have a broad and potent antiviral function to other viral pathogens, like HBV, HIV and etc.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.02.074021: (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 variableThirty-Six ICR male and female mice were purchased from the Peking University Animal Department.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    The virus was amplified and titerated by standard plaque forming assay on Vero cells.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)
    The in vitro antiviral activity: The in vitro antiviral efficacy of the tested drug on Vero E6 Cell was performed as we previously described [Jin, et al., 2020].
    Vero E6
    suggested: None
    The DEGs between normal and liquirintin-treated MCF7 cells were also screened by the limma package.
    MCF7
    suggested: NCI-DTP Cat# MCF7, RRID:CVCL_0031)
    Software and Algorithms
    SentencesResources
    After adjusting the absorbance for background and comparing to untreated controls, the cytotoxic concentration CC50 was calculated using a sigmoidal nonlinear regression function to fit the dose-response curve using the GraphPad Prism 7.0 software.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Transcriptional analysis: Microarray data on gene expression (GSE85871) was downloaded from Gene Expression Omnibus (GEO).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    The DEGs between normal and liquirintin-treated MCF7 cells were also screened by the limma package.
    limma
    suggested: (LIMMA, RRID:SCR_010943)
    To elucidate potential biological process associated with the DEGs, we performed GO enrichment analysis utilizing the Database for Annotation, Visualization and Integrated Discovery (DAVID).
    DAVID
    suggested: (DAVID, RRID:SCR_001881)
    The upregulated DEGs were mapped to STRING to evaluate the PPI information and set confidence score > 0.4 as the cut-off standard.
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Cytoscape was used to visualize the PPI network, a practical open–source software tool for the visual exploration of biomolecule interaction networks consisting of protein, gene and other types of interaction.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)

    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 10.1101/2020.05.02.074021v1 on bioRxiv