CAT, AGTR2, L-SIGN and DC-SIGN are potential receptors for the entry of SARS-CoV-2 into human cells

  1. Dongjie Guo
  2. Ruifang Guo
  3. Zhaoyang Li
  4. Yuyang Zhang
  5. Wei Zheng
  6. Xiaoqiang Huang
  7. Tursunjan Aziz
  8. Yang Zhang
  9. Lijun Liu

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Abstract

Since December 2019, the COVID-19 caused by SARS-CoV-2 has been widely spread all over the world. It is reported that SARS-CoV-2 infection affects a series of human tissues, including lung, gastrointestinal tract, kidney, etc. ACE2 has been identified as the primary receptor of the SARS-CoV-2 Spike (S) protein. The relatively low expression level of this known receptor in the lungs, which is the predominantly infected organ in COVID-19, indicates that there may be some other co-receptors or alternative receptors of SARS-CoV-2 to work in coordination with ACE2. Here, we identified twenty-one candidate receptors of SARS-CoV-2, including ACE2-interactor proteins and SARS-CoV receptors. Then we investigated the protein expression levels of these twenty-one candidate receptors in different human tissues and found that five of which CAT, MME, L-SIGN, DC-SIGN, and AGTR2 were specifically expressed in SARS-CoV-2 affected tissues. Next, we performed molecular simulations of the above five candidate receptors with SARS-CoV-2 S protein, and found that the binding affinities of CAT, AGTR2, L-SIGN and DC-SIGN to S protein were even higher than ACE2. Interestingly, we also observed that CAT and AGTR2 bound to S protein in different regions with ACE2 conformationally, suggesting that these two proteins are likely capable of the co-receptors of ACE2. Conclusively, we considered that CAT, AGTR2, L-SIGN and DC-SIGN were the potential receptors of SARS-CoV-2. Moreover, AGTR2 and DC-SIGN tend to be highly expressed in the lungs of smokers, which is consistent with clinical phenomena of COVID-19, and further confirmed our conclusion. Besides, we also predicted the binding hot spots for these putative protein-protein interactions, which would help develop drugs against SARS-CoV-2.

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  1. ScreenIT

    SciScore for 10.1101/2021.07.07.451411: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Online resources: Two databases, BioGRID [18] and STRING [19] were searched to identify potential ACE2-interacting proteins.
    BioGRID
    suggested: (BioGrid Australia, RRID:SCR_006334)
    STRING
    suggested: (STRING, RRID:SCR_005223)
    The data of normal lung tissues in microarray datasets GSE10072, GSE123352, and GSE32863 from Gene Expression Omnibus (GEO) were analyzed for exploring the correlations between the expression levels of potential receptors and smoking status.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    The protein and mRNA expression data of potential receptors were obtained from the Human Protein Atlas (HPA) portal (https://www.proteinatlas.org/).
    https://www.proteinatlas.org/
    suggested: (HPA, RRID:SCR_006710)
    The subcellular locations of potential receptors were acquired from UniProt (https://www.uniprot.org/).
    UniProt
    suggested: (UniProtKB, RRID:SCR_004426)
    https://www.uniprot.org/
    suggested: (Universal Protein Resource, RRID:SCR_002380)
    The amino acid sequences of all proteins were obtained from Ensembl (https://asia.ensembl.org/index.html).
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Data management using R 4.0.0, statistical analysis and data visualization using GraphPad Prism 8.0.2. 2.2.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    The structures of potential receptors other than AGTR2 were predicted by I-TASSER [20] (Table S1).
    I-TASSER
    suggested: (I-TASSER, RRID:SCR_014627)
    Data visualization was accomplished using PyMOL. 2.4.
    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:
    • 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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2021.07.07.451411v1 on bioRxiv