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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mining antibody functionality via AI-guided structural landscape profiling

Roman G. Efremov, Leyla A. Ovchinnikova, Stanislav S. Terekhov, Arthur O. Zalevsky et al.
Nature Communications
Single-cell and spatial transcriptomics
article

Mining antibody functionality via AI-guided structural landscape profiling

Roman G. Efremov, Leyla A. Ovchinnikova, Stanislav S. Terekhov, Arthur O. Zalevsky, Igor A. Yaroshevich, Alexey Stepanov, Tatiana Shashkova, Sergey V. Duga, N. N. Kostin, Olga Kardymon, Yakov A. Lomakin, Yuliana A. Mokrushina, Roger D. Kornberg, Anastasia Smirnova, Ilgar Z. Mamedov, Margarita N. Baranova, Nikita V. Ivanisenko, Elena T. Aliper, Igor E. Eliseev, Nikolay Akhmetyanov, Stepan Mamontov, Hongkai Zhang, Yuhong Guo, 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
article en

Abstract

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.

Nature Communications
Scripps Research Institute (US), Nankai University (CN), ShanghaiTech University (CN), Institute of Bioorganic Chemistry (RU), Stanford Medicine (US), Bioinformatics Institute (SG), Stanford University (US)
Good health and well-being
Openalex Percentile: Top 21%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.