Characterization of the diphtheria toxin receptor-binding domain

1993 ◽  
Vol 7 (4) ◽  
pp. 585-591 ◽  
Author(s):  
John M. Rolf ◽  
Leon Eidels
Toxicon ◽  
2012 ◽  
Vol 60 (2) ◽  
pp. 106-107
Author(s):  
Benoit Villiers ◽  
Sylvain Pichard ◽  
Alain Sanson ◽  
Stephanie Delluc ◽  
Bernard Maillere ◽  
...  

FEBS Letters ◽  
1994 ◽  
Vol 344 (2-3) ◽  
pp. 242-246 ◽  
Author(s):  
Thor Las Holtet ◽  
Kåre Lehmann Nielsen ◽  
Michael Etzerodt ◽  
Søren Kragh Moestrup ◽  
Jørgen Gliemann ◽  
...  

2002 ◽  
Vol 74 (6) ◽  
pp. 2528-2536 ◽  
Author(s):  
Jonathan W. Francis ◽  
Robert H. Brown ◽  
Dayse Figueiredo ◽  
Mary P. Remington ◽  
Orlando Castillo ◽  
...  

2021 ◽  
Author(s):  
Allison J Greaney ◽  
Tyler N Starr ◽  
Jesse D Bloom

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.


1998 ◽  
Vol 66 (2) ◽  
pp. 418-423 ◽  
Author(s):  
Karin Lobeck ◽  
Pascal Drevet ◽  
Michel Léonetti ◽  
Cécile Fromen-Romano ◽  
Frédéric Ducancel ◽  
...  

ABSTRACT Two recombinant fragments of diphtheria toxin (DT) were fused to an engineered tandem repeat of the immunoglobulin (Ig) binding domain of protein A, called ZZ. These fragments are (i) the receptor binding domain (DTR), which comprises amino acids 382 to 535 of DT, and (ii) a linear peptide (DT168–220) which comprises residues 168 to 220 of the loop between fragment A and fragment B of DT. The fusion proteins were produced in Escherichia coli and purified by affinity chromatography. In vitro experiments showed that the DTR domain is responsible for the capacity of ZZ-DTR to bind to Vero cells and is capable of inhibiting the cytotoxicity of DT for these cells. These findings suggest that DTR binds to the cell surface receptors of DT and hence adopts a conformation that is similar to that of the receptor binding domain of DT. We compared the capacities of ZZ-DTR, ZZ-DT168–220, and a chemically detoxified form of DT currently used for vaccination to elicit antibodies in rabbits. The toxoid was more immunogenic than ZZ-DT168–220, which in turn was more immunogenic than ZZ-DTR. However, ZZ-DT168–220 antiserum was poorly efficient at neutralizing DT cytotoxicity on Vero cells, whereas ZZ-DTR antiserum was only 15-fold less potent than anti-DT antisera.


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