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Improved Antibody‐Specific Epitope Prediction Using AlphaFold and AbAdapt
Antibodies recognize their cognate antigens with high affinity and specificity, but the prediction of binding sites on the antigen (epitope) corresponding to a specific antibody remains a challenging problem. To address this problem, we developed AbAdapt, a pipeline that integrates antibody and anti...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543094/ https://www.ncbi.nlm.nih.gov/pubmed/35893479 http://dx.doi.org/10.1002/cbic.202200303 |
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author | Xu, Zichang Davila, Ana Wilamowski, Jan Teraguchi, Shunsuke Standley, Daron M. |
author_facet | Xu, Zichang Davila, Ana Wilamowski, Jan Teraguchi, Shunsuke Standley, Daron M. |
author_sort | Xu, Zichang |
collection | PubMed |
description | Antibodies recognize their cognate antigens with high affinity and specificity, but the prediction of binding sites on the antigen (epitope) corresponding to a specific antibody remains a challenging problem. To address this problem, we developed AbAdapt, a pipeline that integrates antibody and antigen structural modeling with rigid docking in order to derive antibody‐antigen specific features for epitope prediction. In this study, we systematically assessed the impact of integrating the state‐of‐the‐art protein modeling method AlphaFold with the AbAdapt pipeline. By incorporating more accurate antibody models, we observed improvement in docking, paratope prediction, and prediction of antibody‐specific epitopes. We further applied AbAdapt‐AF in an anti‐receptor binding domain (RBD) antibody complex benchmark and found AbAdapt‐AF outperformed three alternative docking methods. Also, AbAdapt‐AF demonstrated higher epitope prediction accuracy than other tested epitope prediction tools in the anti‐RBD antibody complex benchmark. We anticipate that AbAdapt‐AF will facilitate prediction of antigen‐antibody interactions in a wide range of applications. |
format | Online Article Text |
id | pubmed-9543094 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95430942022-10-14 Improved Antibody‐Specific Epitope Prediction Using AlphaFold and AbAdapt Xu, Zichang Davila, Ana Wilamowski, Jan Teraguchi, Shunsuke Standley, Daron M. Chembiochem Research Articles Antibodies recognize their cognate antigens with high affinity and specificity, but the prediction of binding sites on the antigen (epitope) corresponding to a specific antibody remains a challenging problem. To address this problem, we developed AbAdapt, a pipeline that integrates antibody and antigen structural modeling with rigid docking in order to derive antibody‐antigen specific features for epitope prediction. In this study, we systematically assessed the impact of integrating the state‐of‐the‐art protein modeling method AlphaFold with the AbAdapt pipeline. By incorporating more accurate antibody models, we observed improvement in docking, paratope prediction, and prediction of antibody‐specific epitopes. We further applied AbAdapt‐AF in an anti‐receptor binding domain (RBD) antibody complex benchmark and found AbAdapt‐AF outperformed three alternative docking methods. Also, AbAdapt‐AF demonstrated higher epitope prediction accuracy than other tested epitope prediction tools in the anti‐RBD antibody complex benchmark. We anticipate that AbAdapt‐AF will facilitate prediction of antigen‐antibody interactions in a wide range of applications. John Wiley and Sons Inc. 2022-08-11 2022-09-16 /pmc/articles/PMC9543094/ /pubmed/35893479 http://dx.doi.org/10.1002/cbic.202200303 Text en © 2022 The Authors. ChemBioChem published by Wiley-VCH GmbH https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Xu, Zichang Davila, Ana Wilamowski, Jan Teraguchi, Shunsuke Standley, Daron M. Improved Antibody‐Specific Epitope Prediction Using AlphaFold and AbAdapt |
title | Improved Antibody‐Specific Epitope Prediction Using AlphaFold and AbAdapt
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title_full | Improved Antibody‐Specific Epitope Prediction Using AlphaFold and AbAdapt
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title_fullStr | Improved Antibody‐Specific Epitope Prediction Using AlphaFold and AbAdapt
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title_full_unstemmed | Improved Antibody‐Specific Epitope Prediction Using AlphaFold and AbAdapt
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title_short | Improved Antibody‐Specific Epitope Prediction Using AlphaFold and AbAdapt
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title_sort | improved antibody‐specific epitope prediction using alphafold and abadapt |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543094/ https://www.ncbi.nlm.nih.gov/pubmed/35893479 http://dx.doi.org/10.1002/cbic.202200303 |
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