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Cited by 585

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Emerging COVID-19 coronavirus: glycan shield and structure prediction of spike glycoprotein and its interaction with human CD26

Open access
Vankadari, Naveen, Wilce, Jacqueline A.·2020·Emerging Microbes & Infections

Abstract

The recent outbreak of pneumonia-causing COVID-19 in China is an urgent global public health issue with an increase in mortality and morbidity. Here we report our modelled homo-trimer structure of COVID-19 spike glycoprotein in both closed (ligand-free) and open (ligand-bound) conformation, which is involved in host cell adhesion. We also predict the unique N- and O-linked glycosylation sites of spike glycoprotein that distinguish it from the SARS and underlines shielding and camouflage of COVID-19 from the host the defence system. Furthermore, our study also highlights the key finding that the S1 domain of COVID-19 spike glycoprotein potentially interacts with the human CD26, a key immunoregulatory factor for hijacking and virulence. These findings accentuate the unique features of COVID-19 and assist in the development of new therapeutics.

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Metadata

Authors
Vankadari, N., & Wilce, J. A.
Venue
Emerging Microbes & Infections
Published
2020-01
Volume
9
Issue
1
Pages
601-604
ISSN
2222-1751 (ISSN-L)
OpenAlex
W3012088820
Cited by
585
References
10
FWCI
16.27
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Emerging COVID-19 coronavirus: glycan shield and structure prediction of spike glycoprotein and its interaction with human CD26. https://app.cochat.ai/papers/10.1080/22221751.2020.1739565
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Vankadari, N., & Wilce, J. A. (2020). Emerging COVID-19 coronavirus: glycan shield and structure prediction of spike glycoprotein and its interaction with human CD26. Emerging Microbes & Infections. https://doi.org/10.1080/22221751.2020.1739565

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.