Improved antibody-specific epitope prediction using AlphaFold and AbAdapt
Improved antibody-specific epitope prediction using AlphaFold and AbAdapt
Abstract 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 assess the impact of integrating the state-of-the-art protein modeling method AlphaFold with the AbAdapt pipeline and demonstrate significant improvement in the prediction of antibody-specific epitope residues.
Teraguchi Shunsuke、Davila Ana、Wiamowski Jan、Xu Zichang、Standley Daron M.
Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University||Faculty of Data Science, Shiga UniversityDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka UniversityDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka UniversityDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka UniversityDepartment of Genome Informatics, Research Institute for Microbial Diseases, Osaka University
生物科学研究方法、生物科学研究技术生物科学理论、生物科学方法药学
Antibody-specific epitope predictionAntibody-Antigen dockingAlphaFoldSARS-CoV-2Receptor binding domain (RBD)
Teraguchi Shunsuke,Davila Ana,Wiamowski Jan,Xu Zichang,Standley Daron M..Improved antibody-specific epitope prediction using AlphaFold and AbAdapt[EB/OL].(2025-03-28)[2025-06-18].https://www.biorxiv.org/content/10.1101/2022.05.21.492907.点此复制
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