Integrating computational and experimental approaches to identify antigen–specific antibodies
- 1Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris
- 2Large Molecule Research
Abstract
The identification of therapeutic antibodies is critical for developing effective treatments for many diseases. We present a joint computational and experimental approach for identifying antigen–specific antibodies. We develop and test our pipeline on a probe antigen: GFRAL fused with Diphtheria Toxin Fragment A (DTA). Using humanized Trianni mice, we conducted a longitudinal study with repeated blood sampling and splenic analysis. We applied the STAR computational method that exploits similarity network properties on bulk antibody repertoire data sampled at key time points. By mapping the output from STAR to single cell data taken at the last time point, we successfully identified a pool of antibodies, of which 45% demonstrated binding capabilities. We observed convergent selection, where responding sequences with identical amino acid complementarity determining regions 3 (CDR3) were found in different mice. We provide a catalog of 70 experimentally validated antibodies against the GFRAL-DTA fusion antigen. This study underscores the utility of integrating computational methods and experimental validation for antibody discovery in therapeutic contexts by reducing time and increasing efficiency.
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BibTeX
@article{abbate2026integrating,
title = {{Integrating computational and experimental approaches to identify antigen–specific antibodies}},
author = {Maria Francesca Abbate and Paul Pereira and Pierre Toxe and Nicolas Maestrali and Marie Gagnaire and Emmanuelle Vigne and Melody A. Shahsavarian and Thierry Mora and Aleksandra M. Walczak},
journal = {Frontiers in Immunology},
year = {2026},
month = oct,
doi = {10.3389/fimmu.2026.1951538},
url = {https://www.frontiersin.org/articles/10.3389/fimmu.2026.1951538/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Integrating computational and experimental approaches to identify antigen–specific antibodies
AU - Maria Francesca Abbate
AU - Paul Pereira
AU - Pierre Toxe
AU - Nicolas Maestrali
AU - Marie Gagnaire
AU - Emmanuelle Vigne
AU - Melody A. Shahsavarian
AU - Thierry Mora
AU - Aleksandra M. Walczak
PY - 2026
DA - 2026/10/29
JO - Frontiers in Immunology
DO - 10.3389/fimmu.2026.1951538
UR - https://www.frontiersin.org/articles/10.3389/fimmu.2026.1951538/full
AB - The identification of therapeutic antibodies is critical for developing effective treatments for many diseases. We present a joint computational and experimental approach for identifying antigen–specific antibodies. We develop and test our pipeline on a probe antigen: GFRAL fused with Diphtheria Toxin Fragment A (DTA). Using humanized Trianni mice, we conducted a longitudinal study with repeated blood sampling and splenic analysis. We applied the STAR computational method that exploits similarity network properties on bulk antibody repertoire data sampled at key time points. By mapping the output from STAR to single cell data taken at the last time point, we successfully identified a pool of antibodies, of which 45% demonstrated binding capabilities. We observed convergent selection, where responding sequences with identical amino acid complementarity determining regions 3 (CDR3) were found in different mice. We provide a catalog of 70 experimentally validated antibodies against the GFRAL-DTA fusion antigen. This study underscores the utility of integrating computational methods and experimental validation for antibody discovery in therapeutic contexts by reducing time and increasing efficiency.
SN - 1664-3224
ER -