An antibody-escape calculator for mutations to the SARS-CoV-2 receptor-binding domain

Mapping Intimacies ◽

10.1101/2021.12.04.471236 ◽

2021 ◽

Author(s):

Allison J Greaney ◽

Tyler N Starr ◽

Jesse D Bloom

Keyword(s):

Receptor Binding ◽

Polyclonal Antibody ◽

Polyclonal Antibodies ◽

Binding Domain ◽

Receptor Binding Domain ◽

Experimental Characterization ◽

Antibody Recognition ◽

Antigenic Properties ◽

Interactive Version

A key goal of SARS-CoV-2 surveillance is to rapidly identify viral variants with mutations that reduce neutralization by polyclonal antibodies elicited by vaccination or infection. Unfortunately, direct experimental characterization of new viral variants lags their sequence-based identification. Here we help address this challenge by aggregating deep mutational scanning data into an "escape calculator" that estimates the antigenic effects of arbitrary combinations of mutations to the virus's spike receptor-binding domain (RBD). The calculator can be used to intuitively visualize how mutations impact polyclonal antibody recognition, and score the expected antigenic effect of combinations of mutations. These scores correlate with neutralization assays performed on SARS-CoV-2 variants, and emphasize the ominous antigenic properties of the recently described Omicron variant. An interactive version of the calculator is at https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/escape-calc/, and we provide a Python module for batch processing.

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Computational Prediction of the Epitopes of HA1 Protein of Influenza Viruses to its Neutralizing Antibodies

Antibodies ◽

10.3390/antib8010002 ◽

2018 ◽

Vol 8 (1) ◽

pp. 2

Author(s):

Xiaoyan Zeng ◽

Fiona Legge ◽

Chao Huang ◽

Xiao Zhang ◽

Yongjun Jiao ◽

...

Keyword(s):

Influenza Virus ◽

Crystal Structures ◽

Receptor Binding ◽

Neutralizing Antibodies ◽

Computational Prediction ◽

Binding Domain ◽

Influenza Viruses ◽

New Method ◽

Receptor Binding Domain ◽

Antibody Recognition

In this work, we have used a new method to predict the epitopes of HA1 protein of influenza virus to several antibodies HC19, CR9114, BH151 and 4F5. While our results reproduced the binding epitopes of H3N2 or H5N1 for the neutralizing antibodies HC19, CR9114, and BH151 as revealed from the available crystal structures, additional epitopes for these antibodies were also suggested. Moreover, the predicted epitopes of H5N1 HA1 for the newly developed antibody 4F5 are located at the receptor binding domain, while previous study identified a region 76-WLLGNP-81 as the epitope. The possibility of antibody recognition of influenza virus via different mechanism by binding to different epitopes of an antigen is also discussed.

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Expression, purification and characterization of the receptor-binding domain of botulinum neurotoxin serotype B as a vaccine candidate

Protein Expression and Purification ◽

10.1016/j.pep.2015.02.008 ◽

2015 ◽

Vol 110 ◽

pp. 122-129 ◽

Cited By ~ 6

Author(s):

Alon Ben David ◽

Amram Torgeman ◽

Ada Barnea ◽

Ran Zichel

Keyword(s):

Receptor Binding ◽

Botulinum Neurotoxin ◽

Vaccine Candidate ◽

Binding Domain ◽

Receptor Binding Domain ◽

Purification And Characterization ◽

Serotype B

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Receptor-binding domain of human α2-macroglobulin Expression, folding and biochemical characterization of a high-affinity recombinant derivative

FEBS Letters ◽

10.1016/0014-5793(94)00349-1 ◽

1994 ◽

Vol 344 (2-3) ◽

pp. 242-246 ◽

Cited By ~ 16

Author(s):

Thor Las Holtet ◽

Kåre Lehmann Nielsen ◽

Michael Etzerodt ◽

Søren Kragh Moestrup ◽

Jørgen Gliemann ◽

...

Keyword(s):

Receptor Binding ◽

Biochemical Characterization ◽

Binding Domain ◽

Receptor Binding Domain ◽

High Affinity ◽

Α2 Macroglobulin

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Landscape of human antibody recognition of the SARS-CoV-2 Receptor Binding Domain

Cell Reports ◽

10.1016/j.celrep.2021.109822 ◽

2021 ◽

pp. 109822

Author(s):

Adam K. Wheatley ◽

Phillip Pymm ◽

Robyn Esterbauer ◽

Melanie H. Dietrich ◽

Wen Shi Lee ◽

...

Keyword(s):

Receptor Binding ◽

Binding Domain ◽

Human Antibody ◽

Receptor Binding Domain ◽

Antibody Recognition

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A COVID-19 vaccine candidate using SpyCatcher multimerization of the SARS-CoV-2 spike protein receptor-binding domain induces potent neutralising antibody responses

10.1101/2020.08.31.275701 ◽

2020 ◽

Author(s):

Tiong Kit Tan ◽

Pramila Rijal ◽

Rolle Rahikainen ◽

Anthony H. Keeble ◽

Lisa Schimanski ◽

...

Keyword(s):

Antibody Response ◽

Receptor Binding ◽

Polyclonal Antibody ◽

Vaccine Candidate ◽

Binding Domain ◽

Antibody Responses ◽

Cold Chain ◽

Receptor Binding Domain ◽

Cell Infection ◽

Protein Receptor

ABSTRACTThere is dire need for an effective and affordable vaccine against SARS-CoV-2 to tackle the ongoing pandemic. In this study, we describe a modular virus-like particle vaccine candidate displaying the SARS-CoV-2 spike glycoprotein receptor-binding domain (RBD) using SpyTag/SpyCatcher technology (RBD-SpyVLP). Low doses of RBD-SpyVLP in a prime-boost regimen induced a strong neutralising antibody response in mice and pigs that was superior to convalescent human sera. We evaluated antibody quality using ACE2 blocking and neutralisation of cell infection by pseudovirus or wild-type SARS-CoV-2. Using competition assays with a monoclonal antibody panel, we showed that RBD-SpyVLP induced a polyclonal antibody response that recognised all key epitopes on the RBD, reducing the likelihood of selecting neutralisation-escape mutants. The induction of potent and polyclonal antibody responses by RBD-SpyVLP provides strong potential to address clinical and logistic challenges of the COVID-19 pandemic. Moreover, RBD-SpyVLP is highly resilient, thermostable and can be lyophilised without losing immunogenicity, to facilitate global distribution and reduce cold-chain dependence.

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