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Journal of Medical Virology
Article . 2020 . Peer-reviewed
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In silico studies on the comparative characterization of the interactions of SARS‐CoV‐2 spike glycoprotein with ACE‐2 receptor homologs and human TLRs

Authors: Choudhury, Abhigyan; Mukherjee, Suprabhat;

In silico studies on the comparative characterization of the interactions of SARS‐CoV‐2 spike glycoprotein with ACE‐2 receptor homologs and human TLRs

Abstract

AbstractCoronavirus disease‐2019 (COVID‐19) outbreak due to novel coronavirus or severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection has come out as a major threat for mankind in recent times. It is continually taking an enormous toll on mankind by means of increasing number of deaths, associated comorbidities, and socioeconomic loss around the globe. Unavailability of chemotherapeutics/vaccine has posed tremendous challenges to scientists and doctors for developing an urgent therapeutic strategy. In this connection, the present in silico study aims to understand the sequence divergence of spike protein (the major infective protein of SARS‐CoV‐2), its mode of interaction with the angiotensin‐converting enzyme‐2 receptor (ACE2) receptor of human and related animal hosts/reservoir. Moreover, the involvement of the human Toll‐like receptors (TLRs) against the spike protein has also been demonstrated. Our data indicated that the spike glycoprotein of SARS‐CoV‐2 is phylogenetically close to bat coronavirus and strongly binds with ACE2 receptor protein from both human and bat origin. We have also found that cell surface TLRs, especially TLR4 is most likely to be involved in recognizing molecular patterns from SARS‐CoV‐2 to induce inflammatory responses. The present study supported the zoonotic origin of SARS‐CoV‐2 from a bat and also revealed that TLR4 may have a crucial role in the virus‐induced inflammatory consequences associated with COVID‐19. Therefore, selective targeting of TLR4‐spike protein interaction by designing competitive TLR4‐antagonists could pave a new way to treat COVID‐19. Finally, this study is expected to improve our understanding on the immunobiology of SARS‐CoV‐2 and could be useful in adopting spike protein, ACE2, or TLR‐guided intervention strategy against COVID‐19 shortly.

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Keywords

Models, Molecular, Protein Conformation, alpha-Helical, Binding Sites, Eutheria, SARS-CoV-2, Alphacoronavirus, COVID-19, Infectious Diseases, Virology, Chiroptera, Host-Pathogen Interactions, Spike Glycoprotein, Coronavirus, Animals, Data Mining, Humans, Receptors, Virus, Thermodynamics, Protein Conformation, beta-Strand, Protein Interaction Domains and Motifs, Angiotensin-Converting Enzyme 2, Phylogeny, Protein Binding

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    432
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
432
Top 0.1%
Top 1%
Top 0.1%
hybrid