Epitope Identification of an mGlu5 Receptor Nanobody Using Physics-Based Molecular Modeling and Deep Learning Techniques
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| Titel: | Epitope Identification of an mGlu5 Receptor Nanobody Using Physics-Based Molecular Modeling and Deep Learning Techniques |
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| Autoren: | Eshak, Floriane, Pion, Léo, Scholler, Pauline, Nevoltris, Damien, Chames, Patrick, Rondard, Philippe, Pin, Jean-Philippe, Acher, Francine, Goupil-Lamy, Anne |
| Weitere Verfasser: | Saints-Pères Paris Institute for Neurosciences (SPPIN - UMR 8003), Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Institut de Génomique Fonctionnelle (IGF), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes (IPC), Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Aix Marseille Université (AMU), Institut Paoli-Calmettes (IPC), Fédération nationale des Centres de lutte contre le Cancer (FNCLCC), Dassault Systèmes, This work was supported by the French National Agency for Research ANR-20-CE18-0011-01 to F.E. and P.R., ANR-22-CE11-0004-01 to J.-P.P., ANR-22-CE18-0003 to P.R. and the Fondation pour la Recherche Médicale (EQU202303016470) to P.R., ANR-20-CE18-0011,Nano4Schizo,Les nanobodies des récepteurs mGlu comme agents pharmacologiques innovants pour le traitement des symptômes de la schizophrénie(2020) |
| Quelle: | ISSN: 1549-9596. |
| Verlagsinformationen: | CCSD American Chemical Society |
| Publikationsjahr: | 2024 |
| Bestand: | Université de Montpellier: HAL |
| Schlagwörter: | Rodent models, Peptides and proteins, Conformation, Chemical structure, Antigens, MESH: Animals, MESH: Rats, MESH: Deep Learning, MESH: Epitope Mapping, MESH: Epitopes, MESH: Models, Molecular, MESH: Molecular Dynamics Simulation, MESH: Protein Conformation, MESH: Receptor, Metabotropic Glutamate 5, MESH: Single-Domain Antibodies, [SDV]Life Sciences [q-bio] |
| Beschreibung: | International audience ; The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory activity, making them promising candidates for therapeutic applications. Identifying their binding mode is essential for their development. Experimental structural techniques are effective to get such information, but they are expensive and time-consuming. Here, we propose a computational approach, aiming to identify the epitope of a nanobody that acts as an agonist and a positive allosteric modulator at the rat metabotropic glutamate receptor 5. We employed multiple structure modeling tools, including various artificial intelligence algorithms for epitope mapping. The computationally identified epitope was experimentally validated, confirming the success of our approach. Additional dynamics studies provided further insights on the modulatory activity of the nanobody. The employed methodologies and approaches initiate a discussion on the efficacy of diverse techniques for epitope mapping and later nanobody engineering. |
| Publikationsart: | article in journal/newspaper |
| Sprache: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/38423996; PUBMED: 38423996 |
| DOI: | 10.1021/acs.jcim.3c01620 |
| Verfügbarkeit: | https://hal.science/hal-04723363 https://hal.science/hal-04723363v1/document https://hal.science/hal-04723363v1/file/Epitope_identification_feshak_et_al.pdf https://doi.org/10.1021/acs.jcim.3c01620 |
| Rights: | http://hal.archives-ouvertes.fr/licences/copyright/ ; info:eu-repo/semantics/OpenAccess |
| Dokumentencode: | edsbas.C385FC70 |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | International audience ; The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory activity, making them promising candidates for therapeutic applications. Identifying their binding mode is essential for their development. Experimental structural techniques are effective to get such information, but they are expensive and time-consuming. Here, we propose a computational approach, aiming to identify the epitope of a nanobody that acts as an agonist and a positive allosteric modulator at the rat metabotropic glutamate receptor 5. We employed multiple structure modeling tools, including various artificial intelligence algorithms for epitope mapping. The computationally identified epitope was experimentally validated, confirming the success of our approach. Additional dynamics studies provided further insights on the modulatory activity of the nanobody. The employed methodologies and approaches initiate a discussion on the efficacy of diverse techniques for epitope mapping and later nanobody engineering. |
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| DOI: | 10.1021/acs.jcim.3c01620 |