ArticlemAbs
Accurate determination of epitope for antibodies with unknown 3D structures.
Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- AI-enhanced profiling of phage-display-identified anti-TIM3 and anti-TIGIT novel antibodies.Frontiers in immunology · 2025Article
- Monoclonal antibodies: From magic bullet to precision weapon.Molecular biomedicine · 2024Review
- Predicting monoclonal antibody binding sequences from a sparse sampling of all possible sequences.Communications biology · 2024Article
- Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted.EBioMedicine · 2024Article
- Recent Progress in Antibody Epitope Prediction.Antibodies (Basel, Switzerland) · 2023Review
- Preclinical immunological characterization of rademikibart (CBP-201), a next-generation human monoclonal antibody targeting IL-4Rα, for the treatment of Th2 inflammatory diseases.Scientific reports · 2023Article
- A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity.International journal of molecular sciences · 2022Article
- VInternational journal of molecular sciences · 2022Review
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MAbTope is a docking-based method for the determination of epitopes. It has been used to successfully determine the epitopes of antibodies with known 3D structures. However, during the antibody discovery process, this structural information is rarely available. Although we already have evidence that homology models of antibodies could be used instead of their 3D structure, the choice of the template, the methodology for homology modeling and the resulting performance still have to be clarified. Here, we show that MAbTope has the same performance when working with homology models of the antibodies as compared to crystallographic structures. Moreover, we show that even low-quality models can be used. We applied MAbTope to determine the epitope of dupilumab, an anti- interleukin 4 receptor alpha subunit therapeutic antibody of unknown 3D structure, that we validated experimentally. Finally, we show how the MAbTope-determined epitopes for a series of antibodies targeting the same protein can be used to predict competitions, and demonstrate the accuracy with an experimentally validated example.3D: three-dimensionalRMSD: root mean square deviationCDR: complementary-determining regionCPU: central processing unitsVH: heavy chain variable regionVL: light chain variable regionscFv: single-chain variable fragmentsVHH: single-chain antibody variable regionIL4Rα: Interleukin 4 receptor alpha chainSPR: surface plasmon resonancePDB: protein data bankHEK293: Human embryonic kidney 293 cellsEDTA: Ethylenediaminetetraacetic acidFBS: Fetal bovine serumANOVA: Analysis of varianceEGFR: Epidermal growth factor receptorPE: PhycoerythrinAPC: AllophycocyaninFSC: forward scatterSSC: side scatterWT: wild typeKeywords: MAbTope, Epitope Mapping, Molecular docking, Antibody modeling, Antibody-antigen docking.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.