Mining antibody functionality via AI-guided structural landscape profiling
Despite substantial progress in single-cell screening techniques, antibody (Ab) repertoires still remain enigmatic. Here we show that Ab sequences can be linked to their functionality by using big data obtained from high-throughput sequencing. Using the expansive SARS-CoV-2 pandemic data, we develop an AI-based method to reveal the neutralization potential of Ab repertoires. We employ machine learning to process public 3D structural data of Ab-RBD complexes and create a comprehensive tool, RBD-AIM (https://rbdaim.2a2i.org/), for high-throughput prediction of structural Ab epitopes based on Ab sequence. Using RBD-AIM, we analyze the local big data sources to evaluate the functional biodiversity of native B cell repertoires raised after vaccination and reconstructed in a yeast display system using single-cell microfluidics. This pipeline allows for rapid isolation of neutralizing Abs that promote the survival of transgenic hACE2+ mice in lethal models of SARS-CoV-2 infection. We believe that the AI-guided sequence-functionality link can be successfully employed for further high-throughput discovery of therapeutic Abs and functional analysis of Ab repertoires.
Authors
- Roman G. Efremov (ORCID: https://orcid.org/0000-0002-5474-4721)
- Leyla A. Ovchinnikova (ORCID: https://orcid.org/0000-0002-3086-0728)
- Stanislav S. Terekhov (ORCID: https://orcid.org/0000-0003-2220-0452)
- Arthur O. Zalevsky (ORCID: https://orcid.org/0000-0001-6987-8119)
- Igor A. Yaroshevich (ORCID: https://orcid.org/0000-0002-8525-5568)
- Alexey Stepanov
- Tatiana Shashkova (ORCID: https://orcid.org/0000-0002-8754-8727)
- Sergey V. Duga (ORCID: https://orcid.org/0000-0002-5894-9855)
- N. N. Kostin (ORCID: https://orcid.org/0000-0001-9447-9961)
- Olga Kardymon (ORCID: https://orcid.org/0000-0002-4827-8891)
- Yakov A. Lomakin (ORCID: https://orcid.org/0000-0002-3514-5395)
- Yuliana A. Mokrushina (ORCID: https://orcid.org/0000-0002-4669-9545)
- Roger D. Kornberg (ORCID: https://orcid.org/0000-0002-2425-7519)
- Anastasia Smirnova (ORCID: https://orcid.org/0000-0002-7546-7436)
- Ilgar Z. Mamedov (ORCID: https://orcid.org/0000-0002-3992-9285)
- Margarita N. Baranova (ORCID: https://orcid.org/0000-0002-1759-9836)
- Nikita V. Ivanisenko (ORCID: https://orcid.org/0000-0002-0333-8117)
- Elena T. Aliper (ORCID: https://orcid.org/0000-0002-5842-5322)
- Igor E. Eliseev (ORCID: https://orcid.org/0000-0002-3344-2513)
- Nikolay Akhmetyanov
- Stepan Mamontov
- Hongkai Zhang (ORCID: https://orcid.org/0000-0002-1786-1574)
- Yuhong Guo (ORCID: https://orcid.org/0000-0001-9589-1747)
- Diana M. Malabuiok
- Aleksandr S. Chernov
- Dmitry Nolde
- Vitali M Boitsov
- Tatiana V. Bobik
- Ding Zhang
- Mingxiu Zhang
- Kun Guo
- Richard Lerner
- Alexander G. Gabibov
- Ivan V. Smirnov
- Nan Zhang
Institutions
- Scripps Research Institute (US)
- Nankai University (CN)
- ShanghaiTech University (CN)
- Institute of Bioorganic Chemistry (RU)
- Stanford Medicine (US)
- Bioinformatics Institute (SG)
- Stanford University (US)
Publication Details
- Journal
- Nature Communications
- Published
- 2026-03-15
- DOI
- https://doi.org/10.1038/s41467-026-70553-6
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00