Universal paratope–epitope interaction patterns in antibody–antigen structures

The binding of antibodies (Abs) to antigens (Ags) is a fundamental mechanism by which the immune system defends the body against harmful invaders. Understanding and predicting this interaction is critical for developing effective therapeutic Abs. In this study, we performed an extensive structural analysis of the largest available non-redundant three-dimensional (3D) database of Ab-Ag complexes. By examining the 3D structures of these complexes, we identified key amino acids (AAs) and their positions within the paratope-epitope interface. We stressed the significance of examining AAs at each complementarity-determining regions (CDR) position, as their interaction frequencies at specific sites can vary greatly from their overall tendency to appear in CDRs. Importantly, we standardized all the paratope-epitope interaction patterns identified, converting them into a format that can be easily utilized by researchers outside the structural biology field, especially those working on antibody development using machine learning. Our findings provide valuable insights for optimizing Abs, particularly in therapeutic applications, where refining the CDR loops to improve Ag binding is essential for creating effective Abs. This research may also support the development of more precise and reliable Ab-Ag prediction tools.

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Publication Details

Journal
Protein Science
Published
2025-12-23
DOI
https://doi.org/10.1002/pro.70401
Primary Topic
Monoclonal and Polyclonal Antibodies Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Universal paratope–epitope interaction patterns in antibody–antigen structures

Vincent Zoete, Marta A. S. Perez
Protein Science
Monoclonal and Polyclonal Antibodies Research
article

Universal paratope–epitope interaction patterns in antibody–antigen structures

Vincent Zoete, Marta A. S. Perez
article en

Abstract

The binding of antibodies (Abs) to antigens (Ags) is a fundamental mechanism by which the immune system defends the body against harmful invaders. Understanding and predicting this interaction is critical for developing effective therapeutic Abs. In this study, we performed an extensive structural analysis of the largest available non-redundant three-dimensional (3D) database of Ab-Ag complexes. By examining the 3D structures of these complexes, we identified key amino acids (AAs) and their positions within the paratope-epitope interface. We stressed the significance of examining AAs at each complementarity-determining regions (CDR) position, as their interaction frequencies at specific sites can vary greatly from their overall tendency to appear in CDRs. Importantly, we standardized all the paratope-epitope interaction patterns identified, converting them into a format that can be easily utilized by researchers outside the structural biology field, especially those working on antibody development using machine learning. Our findings provide valuable insights for optimizing Abs, particularly in therapeutic applications, where refining the CDR loops to improve Ag binding is essential for creating effective Abs. This research may also support the development of more precise and reliable Ab-Ag prediction tools.

Protein ScienceVol. 35(1)
SIB Swiss Institute of Bioinformatics (CH), Ludwig Cancer Research (CH), University of Lausanne (CH)
Ludwig Institute for Cancer Research, Université de Lausanne
Openalex Percentile: Top 31%
Monoclonal and Polyclonal Antibodies Research
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