Interaction of the spike protein RBD from SARS-CoV-2 with ACE2: similarity with SARS-CoV, hot-spot analysis and effect of the receptor polymorphism

  1. Houcemeddine Othman
  2. Zied Bouslama
  3. Jean-Tristan Brandenburg
  4. Jorge da Rocha
  5. Yosr Hamdi
  6. Kais Ghedira
  7. Najet Srairi-Abid
  8. Scott Hazelhurst

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

The spread of COVID-19 caused by the SARS-CoV-2 outbreak has been growing since its first identification in December 2019. The publishing of the first SARS-CoV-2 genome made a valuable source of data to study the details about its phylogeny, evolution, and interaction with the host. Protein-protein binding assays have confirmed that Angiotensin-converting enzyme 2 (ACE2) is more likely to be the cell receptor through which the virus invades the host cell. In the present work, we provide an insight into the interaction of the viral spike Receptor Binding Domain (RBD) from different coronavirus isolates with host ACE2 protein. By calculating the binding energy score between RBD and ACE2, we highlighted the putative jump in the affinity from a progenitor form of SARS-CoV-2 to the current virus responsible for COVID-19 outbreak. Our result was consistent with previously reported phylogenetic analysis and corroborates the opinion that the interface segment of the spike protein RBD might be acquired by SARS-CoV-2 via a complex evolutionary process rather than a progressive accumulation of mutations. We also highlighted the relevance of Q493 and P499 amino acid residues of SARS-CoV-2 RBD for binding to human ACE2 and maintaining the stability of the interface. Moreover, we show from the structural analysis that it is unlikely for the interface residues to be the result of genetic engineering. Finally, we studied the impact of eight different variants located at the interaction surface of ACE2, on the complex formation with SARS-CoV-2 RBD. We found that none of them is likely to disrupt the interaction with the viral RBD of SARS-CoV-2.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.03.04.976027: (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
    2.2 Sequence analysis and phylogenetic tree calculation: MAFFT 7.450 was used to align the whole genome sequences and the protein sequences of viral RBDs [5] (Supplementary Materials 1).
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Prediction of the N-Glycosylation sites was made for all studied ACE2 sequences using NetNGlyc server (https://www.cbs.dtu.dk/services/NetNGlyc/).
    NetNGlyc
    suggested: (NetNGlyc, RRID:SCR_001570)
    For the RBD sequences, the best substitution model for maximum likelihood (ML) calculation was selected using a model selection tool implemented on MEGA 6 software based on the lowest BIC score.
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    The template sequences of the ligand (spike protein) and the receptor (ACE2) were aligned locally with the target sequences using the program Water from the EMBOSS package [12]
    EMBOSS
    suggested: (EMBOSS, RRID:SCR_008493)
    Modeller version 9.22 [14] was then used to predict the complex model of each spike protein with the ACE2 using a slow refining protocol.
    Modeller
    suggested: (MODELLER, RRID:SCR_008395)

    Results from OddPub: Thank you for sharing your data.

    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 10.1101/2020.03.04.976027 on bioRxiv