ArticlemAbs
Ab-Ligity: identifying sequence-dissimilar antibodies that bind to the same epitope.
Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- AI-Driven BCR Modeling for Precision Immunology.International journal of molecular sciences · 2026Review
- Contrastive learning enables epitope overlap predictions for targeted antibody discovery.Patterns (New York, N.Y.) · 2026Article
- A Pharmacophore-Based Method for Rapid and Accurate Virtual Screening of Antibody Libraries against Antigens.Molecular pharmaceutics · 2025Article
- Comparison of sequence- and structure-based antibody clustering approaches on simulated repertoire sequencing data.PLoS computational biology · 2025Article
- Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances.Molecular biotechnology · 2025Review
- Antibodies and cryptographic hash functions: quantifying the specificity paradox.Frontiers in immunology · 2025Article
- Structure-Based Epitope Profiling with the Structural Profiling of Antibodies to Cluster by Epitope 2 (SPACE2) Algorithm.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Computational detection of antigen-specific B cell receptors following immunization.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Epitope binning for multiple antibodies simultaneously using mammalian cell display and DNA sequencing.Communications biology · 2024Article
- Benchmarking antibody clustering methods using sequence, structural, and machine learning similarity measures for antibody discovery applications.Frontiers in molecular biosciences · 2024Article
- Convergent evolution and B-cell recirculation in germinal centers in a human lymph node.Life science alliance · 2023Article
- Evaluation of Molecular Simulations and Deep Learning Prediction of Antibodies' Recognition of TRBC1 and TRBC2.Antibodies (Basel, Switzerland) · 2023Article
- Recent Progress in Antibody Epitope Prediction.Antibodies (Basel, Switzerland) · 2023Review
- Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies.Nature communications · 2023Article
- Structure-free antibody paratope similarity prediction foriScience · 2023Article
- Toward real-world automated antibody design with combinatorial Bayesian optimization.Cell reports methods · 2023Article
- A comparison of the binding sites of antibodies and single-domain antibodies.Frontiers in immunology · 2023Article
- Antibodies as drugs-a Keystone Symposia report.Annals of the New York Academy of Sciences · 2023Article
- Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind to the same epitope.Frontiers in molecular biosciences · 2023Article
- Functional antibodies exhibit light chain coherence.Nature · 2022Article
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Authors and funding
9 authors.
Funding
Abstract
Solving the structure of an antibody-antigen complex gives atomic level information of the interactions between an antibody and its antigen, but such structures are expensive and hard to obtain. Alternative experimental sources include epitope mapping and binning experiments, which can be used as a surrogate to identify key interacting residues. However, their resolution is usually not sufficient to identify if two antibodies have identical interactions. Computational approaches to this problem have so far been based on the premise that antibodies with similar sequences behave similarly. Such approaches will fail to identify sequence-distant antibodies that target the same epitope. Here, we present Ab-Ligity, a structure-based similarity measure tailored to antibody-antigen interfaces. Using predicted paratopes on model antibody structures, we assessed its ability to identify those antibodies that target highly similar epitopes. Most antibodies adopting similar binding modes can be identified from sequence similarity alone, using methods such as clonotyping. In the challenging subset of antibodies whose sequences differ significantly, Ab-Ligity is still able to predict antibodies that would bind to highly similar epitopes (precision of 0.95 and recall of 0.69). We compared Ab-Ligity's performance to an existing tool for comparing general protein interfaces, InterComp, and showed improved performance on antibody cases achieved in a substantially reduced time. These results suggest that Ab-Ligity will allow the identification of diverse (sequence-dissimilar) antibodies that bind to the same epitopes from large datasets such as immune repertoires. The tool is available at http://opig.stats.ox.ac.uk/resources.
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