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An antibody-escape calculator for mutations to the SARS-CoV-2 receptor-binding domain
Allison J Greaney; Tyler N Starr; Jesse D Bloom.
Afiliación
  • Allison J Greaney; University of Washington
  • Tyler N Starr; Fred Hutch Cancer Center
  • Jesse D Bloom; Fred Hutch Cancer Center
Preprint en En | PREPRINT-BIORXIV | ID: ppbiorxiv-471236
ABSTRACT
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 viruss 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.
Licencia
cc_by
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-BIORXIV Tipo de estudio: Prognostic_studies Idioma: En Año: 2021 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-BIORXIV Tipo de estudio: Prognostic_studies Idioma: En Año: 2021 Tipo del documento: Preprint