A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity
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 m...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/23/17/9765 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Astrid Musnier |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T01:45:11Z |
| format | Article |
| id | doaj.art-6159e130034d4b6d8a4f4ab92cf86455 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T01:45:11Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-6159e130034d4b6d8a4f4ab92cf864552023-11-23T13:16:37ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672022-08-012317976510.3390/ijms23179765A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target ReactivityAstrid Musnier0Thomas Bourquard1Amandine Vallet2Laetitia Mathias3Gilles Bruneau4Mohammed Akli Ayoub5Ophélie Travert6Yannick Corde7Nathalie Gallay8Thomas Boulo9Sandra Cortes10Hervé Watier11Pascale Crépieux12Eric Reiter13Anne Poupon14MAbSilico, 1 Impasse du Palais, 37000 Tours, FranceMAbSilico, 1 Impasse du Palais, 37000 Tours, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FranceMAbSilico, 1 Impasse du Palais, 37000 Tours, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FranceSynthélis, BIOPOLIS, 5 Avenue du Grand Sablon, 38700 La Tronche, FranceCentre Hospitalier Régional Universitaire de Tours, Université de Tours, EA 7501, 37032 Tours, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FrancePhysiologie de la Reproduction et des Comportements, INRAE UMR-0085, CNRS UMR-7247, Université de Tours, 37380 Nouzilly, FranceDeveloping 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.https://www.mdpi.com/1422-0067/23/17/9765therapeutic antibodypoly-specificityoff-targetantibody repurposingin silico method |
| spellingShingle | 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 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 therapeutic antibody poly-specificity off-target antibody repurposing in silico method |
| title | A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity |
| title_full | A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity |
| title_fullStr | A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity |
| title_full_unstemmed | A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity |
| title_short | A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity |
| title_sort | new in silico antibody similarity measure both identifies large sets of epitope binders with distinct cdrs and accurately predicts off target reactivity |
| topic | therapeutic antibody poly-specificity off-target antibody repurposing in silico method |
| url | https://www.mdpi.com/1422-0067/23/17/9765 |
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