Public antibody clonotypes and deep learning identify SARS-CoV-2 and HIV broadly neutralizing antibodies in immune repertoires.
Zhou, L., Yu, Z., Lin, S., Jiang, Y., Gao, J., Ma, Y., Jiang, W., Liang, S., Chen, Y., Zhang, Y., Lin, Y., Liang, M., Dai, J., Zhang, L., Xiao, Y., Li, T., Kong, Z., Liu, Q., He, S., Wu, Y., Yuan, Q., Liu, F., Zhang, J., Zheng, Q., Yu, H., Gu, Y., Li, S., Xia, N.(2026) Cell Rep 45: 117582-117582
- PubMed: 42319828 Search on PubMed
- DOI: https://doi.org/10.1016/j.celrep.2026.117582
- Primary Citation Related Structures: 
9WLA, 9WLB - PubMed Abstract: 
Broadly neutralizing antibodies (bnAbs) are essential for the development of vaccines and therapeutics against rapidly evolving pathogens like HIV and SARS-CoV-2, yet traditional discovery methods remain technically challenging and time consuming. Here, we introduce ClonoDeep, an AI-powered platform that integrates public antibody clonotypes with a sequence-based deep learning model to directly identify bnAbs from a large-scale immune repertoire, independent of antigen-specific immunization. Applied to SARS-CoV-2 repertoires, ClonoDeep identified 18 clonotype-derived antibody candidates; 83% of the candidates were neutralizing antibodies, and 8 of these antibodies demonstrated broad neutralization across variants. Structural analysis revealed that somatic hypermutations at HCDR3 His107/Gly109 are key enhancers of the binding affinity and neutralizing breadth. Extending to HIV, ClonoDeep uncovered three previously unreported bnAbs from non-HIV cohorts, indicating that rare bnAb-like precursors exist in non-HIV cohort repertoires. ClonoDeep establishes a high-throughput computational approach for mining neutralizing antibodies from antibody repertoires shaped by non-pathogen-specific immunity and provides design principles to guide vaccine strategies against genetically diverse pathogens.
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Fujian 361102, China; National Institute of Diagnostics and Vaccine Development in Infectious Diseases, National Innovation Platform for Industry-Education Integration in Vaccine Research, Xiamen University, Fujian 361102, China. Electronic address: zhoulizhi@xmu.edu.cn.
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