AbEpiTope-1.0: Improved antibody target prediction by use of AlphaFold and inverse folding.

ABSTRACT: B cell epitope prediction tools are crucial for designing vaccines and disease diagnostics. However, predicting which antigens a specific antibody binds to and their exact binding sites (epitopes) remains challenging. Here, we present AbEpiTope-1.0, a tool for antibody-specific B cell epitope prediction, using AlphaFold for structural modeling and inverse folding for machine learning models. On a dataset of 1730 antibody-antigen complexes, AbEpiTope-1.0 outperforms AlphaFold in predicting modeled antibody-antigen interface accuracy. By creating swapped antibody-antigen complex structures for each antibody-antigen complex using incorrect antibodies, we show that predicted accuracies are sensitive to antibody input. Furthermore, a model variant optimized for antibody target prediction-differ

SUBMITTER: Clifford JN 

PROVIDER: S-EPMC12165000 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature