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Article

Mutational analysis of SARS-CoV-2 variants of concern reveals key tradeoffs between receptor affinity and antibody escape.

PLoS computational biology - 1 May 2022

Makowski Emily K, Schardt John S, Smith Matthew D, Tessier Peter M

Abstract excerpt

SARS-CoV-2 variants with enhanced transmissibility represent a serious threat to global health. Here we report machine learning models that can predict the impact of receptor-binding domain (RBD) mutations on receptor (ACE2) affinity, which is linked to infectivity, and escape from human serum antibodies, which is linked to viral neutralization. Importantly, the models predict many of the known impacts of RBD...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 35639784
DOI: 10.1371/journal.pcbi.1010160
PMCID: PMC9223403

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