Computational Analysis of Receptor-Binding Domains of SARS-CoV-2 to Reveal the Mechanism of Immune Escape

Mengxu Zhu, Kongyan Li, Hong Yan
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Abstract

Covid-19 has become a world pandemic for years. With the appearance of mutations, immune escape has become a problem, reducing the effectiveness of vaccines and antibodies. To reveal the mechanism of immune escape, we analyze the geometrical properties of the receptor-binding domain in the SARS-CoV-2 spike protein, which plays a vital role in the immune reaction. Several important variants are taken as examples, and the wild type model is prepared as a reference. The computational method is applied to simulate the behaviors of the models, and alpha shape algorithm is employed to extract geometrical data of the protein surface. Average moving distance of the surface atoms is used to quantify their activity. Our results show that the mutations changed the properties of the protein. The variants have different distributions of active sites, which may change the specific antigenicity and influence the binding abilities of drugs and antibodies. This study explains the mechanism of immune escape of SARS-CoV-2, and provides a geometrical method to find potential new target sites for the design of drugs and vaccines.
SARS-CoV-2受体结合域的计算分析揭示免疫逃逸机制
2019冠状病毒病多年来一直是世界大流行病。随着突变的出现,免疫逃逸已经成为一个问题,降低了疫苗和抗体的有效性。为了揭示免疫逃逸的机制,我们分析了在免疫反应中起重要作用的SARS-CoV-2刺突蛋白受体结合域的几何特性。以几种重要的变异体为例,准备了野生型模型作为参考。采用计算方法模拟模型的行为,并采用alpha形状算法提取蛋白质表面的几何数据。表面原子的平均移动距离被用来量化它们的活性。我们的研究结果表明,突变改变了蛋白质的特性。这些变异具有不同的活性位点分布,可能改变特异性抗原性,影响药物和抗体的结合能力。该研究解释了SARS-CoV-2的免疫逃逸机制,为药物和疫苗的设计提供了一种寻找潜在新靶点的几何方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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