Volume 33, No 1, Jan 2023

ISSN: 1001-0602 
EISSN: 1748-7838 2018 
impact factor 17.848* 
(Clarivate Analytics, 2019)

Volume 33 Issue 1, January 2023: 80-82

LETTERS TO THE EDITOR

Deep learning-based rapid generation of broadly reactive antibodies against SARS-CoV-2 and its Omicron variant

Hantao Lou^1,2,†,* , Jianqing Zheng^3,4,† , Xiaohang (Leo) Fang⁵ , Zhu Liang^2,6 , Meihan Zhang¹ , Yu Chen¹ , Chunmei Wang^7,8 , Xuetao Cao^1,7,8,*

¹Frontier Research Center for Cell Response, Nankai-Oxford International Advanced Research Institute, College of Life Sciences, Nankai University, Tianjin, China
²Ludwig Institute for Cancer Research, University of Oxford, Oxford, UK
³The Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
⁴Big Data Institute, University of Oxford, Oxford, UK
⁵Department of Engineering Science, University of Oxford, Oxford, UK
⁶Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
⁷Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
⁸Department of Immunology, Centre for Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China
^†These authors contributed equally: Hantao Lou, Jianqing Zheng
Correspondence: Hantao Lou(hantao.lou@nankai.edu.cn)Xuetao Cao(caoxt@immunol.org)

Dear Editor,

The COVID-19 pandemic has been ongoing for nearly two and half years, and new variants of concern (VOCs) of SARS-CoV-2 continue to emerge, which urges the development of broadly neutralizing antibodies.1,2 Variants such as the delta (B.1.617.2 lineage) and Omicron (BA.1 and BA.2) were reported to exhibit immune evasion to some of the current therapeutic antibodies.2,3

https://doi.org/10.1038/s41422-022-00727-6

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