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Cell Reports
Article . 2021 . Peer-reviewed
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Cell Reports
Article
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Cell Reports
Article . 2021
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PubMed Central
Other literature type . 2021
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Landscape of human antibody recognition of the SARS-CoV-2 receptor binding domain

Authors: Adam K. Wheatley; Phillip Pymm; Robyn Esterbauer; Melanie H. Dietrich; Wen Shi Lee; Damien Drew; Hannah G. Kelly; +26 Authors

Landscape of human antibody recognition of the SARS-CoV-2 receptor binding domain

Abstract

Potent neutralizing monoclonal antibodies are one of the few agents currently available to treat COVID-19. SARS-CoV-2 variants of concern (VOCs) that carry multiple mutations in the viral spike protein can exhibit neutralization resistance, potentially affecting the effectiveness of some antibody-based therapeutics. Here, the generation of a diverse panel of 91 human, neutralizing monoclonal antibodies provides an in-depth structural and phenotypic definition of receptor binding domain (RBD) antigenic sites on the viral spike. These RBD antibodies ameliorate SARS-CoV-2 infection in mice and hamster models in a dose-dependent manner and in proportion to in vitro, neutralizing potency. Assessing the effect of mutations in the spike protein on antibody recognition and neutralization highlights both potent single antibodies and stereotypic classes of antibodies that are unaffected by currently circulating VOCs, such as B.1.351 and P.1. These neutralizing monoclonal antibodies and others that bind analogous epitopes represent potentially useful future anti-SARS-CoV-2 therapeutics.

Country
Australia
Keywords

Male, 570, 610, Antibodies, Viral, Article, Epitopes, Mice, Neutralization Tests, Cricetinae, Animals, Humans, SARS-CoV-2, Cryoelectron Microscopy, Antibodies, Monoclonal, COVID-19, Middle Aged, Antibodies, Neutralizing, Mice, Inbred C57BL, Spike Glycoprotein, Coronavirus, Receptors, Virus, Female, Angiotensin-Converting Enzyme 2, 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).
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    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 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).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
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!
47
Top 1%
Top 10%
Top 1%
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gold