Emerging Dominant SARS-CoV-2 Variants
Emerging Dominant SARS-CoV-2 Variants
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DOI：
10.1021/acs.jcim.2c01352
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发表时间：
2023-01-09
影响因子：
5.6
通讯作者：
Wei, Guo-Wei
中科院分区：
文献类型：
--
作者：
Chen, Jiahui;Wang, Rui;Wei, Guo-Wei
对新出现的主要严重急性呼吸综合征冠状病毒2（SARS-CoV-2）变体的准确和可靠预测使政策制定者和疫苗制造商能够为未来的感染浪潮做好准备。由优势变体Omicron（BA.1），BA.2和BA.4/BA.5引起的SARS-CoV-2感染的最后三波，是由我们的人工智能（AI）模型准确预测的，这些模型是用生物物理学，病毒基因组的基因分型，实验数据，代数拓扑和深度学习构建的。基于最新的实验数据，我们分析了所有可能的病毒刺突蛋白受体结合域（RBD）突变对SARS-CoV-2感染性的影响。我们的分析揭示了病毒的进化机制，即，通过传染性增强和抗体抗性的自然选择。我们预测，BP.1、BL*、BA.2.75*、BQ.1*，特别是BN. 1 *，很有可能成为新的主导变体，推动下一次激增。我们在2022年10月18日做出的关于这些变体优势的关键预测（见arXiv：2210.09485）在2022年11月下旬成为现实。
Accurate and reliable forecasting of emerging dominant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants enables policymakers and vaccine makers to get prepared for future waves of infections. The last three waves of SARS-CoV-2 infections caused by dominant variants, Omicron (BA.1), BA.2, and BA.4/BA.5, were accurately foretold by our artificial intelligence (AI) models built with biophysics, genotyping of viral genomes, experimental data, algebraic topology, and deep learning. On the basis of newly available experimental data, we analyzed the impacts of all possible viral spike (S) protein receptor-binding domain (RBD) mutations on the SARS-CoV-2 infectivity. Our analysis sheds light on viral evolutionary mechanisms, i.e., natural selection through infectivity strengthening and antibody resistance. We forecast that BP.1, BL*, BA.2.75*, BQ.1*, and particularly BN.1* have a high potential to become the new dominant variants to drive the next surge. Our key projection about these variants dominance made on Oct. 18, 2022 (see arXiv:2210.09485) became reality in late November 2022.