Contributors: 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-.2022 (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)
نبذة مختصرة : 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.
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