中和
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
传递率(结构动力学)
抗体
病毒
2019年冠状病毒病(COVID-19)
2019-20冠状病毒爆发
定向分子进化
定向进化
积极选择
免疫逃逸
病毒学
免疫系统
生物
计算生物学
遗传学
医学
基因
传染病(医学专业)
突变体
振动
爆发
隔振
量子力学
病理
疾病
物理
作者
Sisi Shan,Shitong Luo,Ziqing Yang,Junxian Hong,Yufeng Su,Fan Ding,Lili Fu,Chenyu Li,Peng Chen,Jianzhu Ma,Xuanling Shi,Qi Zhang,Bonnie Berger,Linqi Zhang,Jian Peng
标识
DOI:10.1073/pnas.2122954119
摘要
Significance SARS-CoV-2 continues to evolve through emerging variants, more frequently observed with higher transmissibility. Despite the wide application of vaccines and antibodies, the selection pressure on the Spike protein may lead to further evolution of variants that include mutations that can evade immune response. To catch up with the virus’s evolution, we introduced a deep learning approach to redesign the complementarity-determining regions (CDRs) to target multiple virus variants and obtained an antibody that broadly neutralizes SARS-CoV-2 variants.
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