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| DOI | Trouver le DOI : https://doi.org/10.1038/s41598-023-42090-5 |
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| Auteur | Rechercher : Gaudreault, Francis1; Rechercher : Corbeil, Christopher R.1; Rechercher : Sulea, Traian1Identifiant ORCID : https://orcid.org/0000-0001-5301-8261 |
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| Affiliation | - Conseil national de recherches du Canada. Thérapeutique en santé humaine
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| Format | Texte, Article |
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| Résumé | Predicting the structure of antibody-antigen complexes has tremendous value in biomedical research but unfortunately suffers from a poor performance in real-life applications. AlphaFold2 (AF2) has provided renewed hope for improvements in the field of protein–protein docking but has shown limited success against antibody-antigen complexes due to the lack of co-evolutionary constraints. In this study, we used physics-based protein docking methods for building decoy sets consisting of low-energy docking solutions that were either geometrically close to the native structure (positives) or not (negatives). The docking models were then fed into AF2 to assess their confidence with a novel composite score based on normalized pLDDT and pTMscore metrics after AF2 structural refinement. We show benefits of the AF2 composite score for rescoring docking poses both in terms of (1) classification of positives/negatives and of (2) success rates with particular emphasis on early enrichment. Docking models of at least medium quality present in the decoy set, but not necessarily highly ranked by docking methods, benefitted most from AF2 rescoring by experiencing large advances towards the top of the reranked list of models. These improvements, obtained without any calibration or novel methodologies, led to a notable level of performance in antibody-antigen unbound docking that was never achieved previously. |
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| Date de publication | 2023-09-13 |
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| Maison d’édition | Nature Research |
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| Licence | |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | fd541eba-0264-4e52-a7e9-5b5f4e989200 |
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| Enregistrement créé | 2024-06-03 |
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| Enregistrement modifié | 2024-06-03 |
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