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

IF 2 Q4 VIROLOGY Frontiers in virology Pub Date : 2023-04-26 DOI:10.3389/fviro.2023.1172027
Colby T. Ford, Shirish Yasa, Denis Jacob Machado, Richard Allen White, Daniel A. Janies
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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.
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利用硅蛋白模型预测SARS-CoV-2 XBB.1.5中和抗体活性的变化
SARS-CoV-2变体XBB.1.5具有高传播性,值得关注。XBB.1.5目前占美国新感染病例的30%以上。在我们小组发表了预测的Omicron (B.1.1.529)变体的受体结合域(RBD)结构和抗体结合亲和力一年后,我们回到研究在Omicron的后代XBB.1.5中发现的新突变。使用针对新的中和抗体的计算机建模方法,对B.1.1.529有效,我们预测了XBB.1.5突变的免疫后果,并表明与B.1.1.529和其他相关变体(例如,BJ.1和bm .1.1.1)相比,总体抗体逃避没有统计学上的显著差异。然而,抗体结合亲和力的显著变化是由于新变异中感兴趣的特定氨基酸的变化。
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