EpiScan: accurate high-throughput mapping of antibody-specific epitopes using sequence information.

ABSTRACT: The identification of antibody-specific epitopes on virus proteins is crucial for vaccine development and drug design. Nonetheless, traditional wet-lab approaches for the identification of epitopes are both costly and labor-intensive, underscoring the need for the development of efficient and cost-effective computational tools. Here, EpiScan, an attention-based deep learning framework for predicting antibody-specific epitopes, is presented. EpiScan adopts a multi-input and single-output strategy by designing independent blocks for different parts of antibodies, including variable heavy chain (V_H), variable light chain (V_L), complementary determining regions (CDRs), and framework regions (FRs). The block predictions are weighted and integrated for the prediction of pot

SUBMITTER: Wang C 

PROVIDER: S-EPMC11383971 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature