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Viral evolution prediction identifies broadly neutralizing antibodies to existing and rospective SARS-CoV-2 variants

Nature microbiology. 2025-08; 
Fanchong Jian, Anna Z Wec, Leilei Feng, Yuanling Yu, Lei Wang, Peng Wang, Lingling Yu, Jing Wang, Jacob Hou, Daniela Montes Berrueta, Diana Lee, Tessa Speidel, LingZhi Ma, Thu Kim, Ayijiang Yisimayi, Weiliang Song, Lu Liu, Sijie Yang, Xiao Niu, Tianhe Xiao, Ran An, Yao Wang, Fei Shao, Youchun Wang, Simone Pecetta, Xiangxi Wang, Laura M Walker, Yunlong Cao
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摘要

Monoclonal antibodies (mAbs) targeting the SARS-CoV-2 receptor-binding domain are used to treat and prevent COVID-19. However, the rapid evolution of SARS-CoV-2 drives continuous escape from therapeutic mAbs. Therefore, the ability to identify broadly neutralizing antibodies (bnAbs) to future variants is needed. Here we use deep mutational scanning to predict viral receptor-binding domain evolution and to select for mAbs neutralizing both existing and prospective variants. A retrospective analysis of 1,103 SARS-CoV-2 wild-type-elicited mAbs shows that this method can increase the probability of identifying effective bnAbs to the XBB.1.5 strain from 1% to 40% in an early pandemic set-up. Among these bnAbs, BD55-... More

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