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Predicting changes in neutralizing antibody activity for SARS-CoV-2 XBB.1.5 using in silico protein modeling

Colby T. Ford, Shirish Yasa, Denis Jacob Machado, Richard White, Daniel Janies

2023Frontiers in Virology13 citationsDOIOpen Access PDF

Abstract

The SARS-CoV-2 variant XBB.1.5 is of concern as it has high transmissibility. XBB.1.5 currently accounts for upwards of 30% of new infections in the United States. One year after our group published the predicted structure of the Omicron (B.1.1.529) variant’s receptor binding domain (RBD) and antibody binding affinity, we return to investigate the new mutations seen in XBB.1.5 which is a descendant of Omicron. Using in silico modeling approaches against newer neutralizing antibodies that are shown effective against B.1.1.529, we predict the immune consequences of XBB.1.5’s mutations and show that there is no statistically significant difference in overall antibody evasion when comparing to the B.1.1.529 and other related variants (e.g., BJ.1 andBM.1.1.1). However, noticeable changes in antibody binding affinity were seen due to specific amino acid changes of interest in the newer variants.

Topics & Concepts

In silicoAntibodySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Transmissibility (structural dynamics)Computational biologyNeutralizing antibodyBiologyVirologyCoronavirus disease 2019 (COVID-19)ChemistryGeneticsGeneMedicineDiseaseQuantum mechanicsInfectious disease (medical specialty)PhysicsVibration isolationVibrationPathologySARS-CoV-2 and COVID-19 ResearchMonoclonal and Polyclonal Antibodies Researchvaccines and immunoinformatics approaches
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