A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity

Autor: Astrid Musnier, Thomas Bourquard, Amandine Vallet, Laetitia Mathias, Gilles Bruneau, Mohammed Akli Ayoub, Ophélie Travert, Yannick Corde, Nathalie Gallay, Thomas Boulo, Sandra Cortes, Hervé Watier, Pascale Crépieux, Eric Reiter, Anne Poupon
Přispěvatelé: MAbSilico SAS, Physiologie de la reproduction et des comportements [Nouzilly] (PRC), Institut Français du Cheval et de l'Equitation [Saumur] (IFCE)-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Synthelis, Groupe innovation et ciblage cellulaire (GICC), EA 7501 [2018-...] (GICC EA 7501), Université de Tours (UT), Dynamiques de populations multi-échelles pour des systèmes physiologiques (MUSCA), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Physiologie de la reproduction et des comportements [Nouzilly] (PRC), Institut Français du Cheval et de l'Equitation [Saumur] (IFCE)-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Français du Cheval et de l'Equitation [Saumur] (IFCE)-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] (MaIAGE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), This publication was funded with support from the French National Research Agency under the program 'Investissements d’avenir', Grant Agreement MabImprove LabEx ANR-10-LABX-53, ANR (Contract n◦ ANR-2011–1619 01), Région Centre ARTE2, MODUPHAC (32000514), MABSILICO (32000797) grants and GPCRAb (32000593) grant from the ARD2020 Biomédicaments program., ANR-10-LABX-0053,MAbImprove,Optimization of therapeutic monoclonal antibodies development Better antibodies, better developed AND better used(2010)
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Molecular Sciences
International Journal of Molecular Sciences, 2022, 23 (17), pp.1-17. ⟨10.3390/ijms23179765⟩
International Journal of Molecular Sciences; Volume 23; Issue 17; Pages: 9765
ISSN: 1422-0067
1661-6596
DOI: 10.3390/ijms23179765
Popis: International audience; Developing a therapeutic antibody is a long, tedious, and expensive process. Many obstacles need to be overcome, such as biophysical properties (issues of solubility, stability, weak production yields, etc.), as well as cross-reactivity and subsequent toxicity, which are major issues. No in silico method exists today to solve such issues. We hypothesized that if we were able to properly measure the similarity between the CDRs of antibodies (Ab) by considering not only their evolutionary proximity (sequence identity) but also their structural features, we would be able to identify families of Ab recognizing similar epitopes. As a consequence, Ab within the family would share the property to recognize their targets, which would allow (i) to identify off-targets and forecast the cross-reactions, and (ii) to identify new Ab specific for a given target. Testing our method on 238D2, an antagonistic anti-CXCR4 nanobody, we were able to find new nanobodies against CXCR4 and to identify influenza hemagglutinin as an off-target of 238D2.
Databáze: OpenAIRE
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