{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T12:28:58Z","timestamp":1789043338340,"version":"build-2803163510"},"reference-count":46,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T00:00:00Z","timestamp":1771459200000},"content-version":"vor","delay-in-days":49,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shanghai Municipal Education Commission Artificial Intelligence Program"},{"name":"Scientific Research Paradigms and Empower Discipline Advancement","award":["2024AI02010"],"award-info":[{"award-number":["2024AI02010"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Shanghai Science and Technology Commission","doi-asserted-by":"crossref","award":["25JS2820100"],"award-info":[{"award-number":["25JS2820100"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Shanghai Frontiers Science Center of Molecule Intelligent Syntheses"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Epitope prediction is a key challenge in immunology and therapeutic antibody design. Existing computational methods rely on residue-level graph representations that fail to capture fine-grained atomic-level geometric information essential for antibody\u2013antigen recognition. Considering that protein structure files (e.g. Protein Data Bank (PDB) files) inherently contain 3D atomic coordinates, we model proteins as atomic-level point clouds to directly preserve high-resolution spatial features . Building on this representation, we propose Point cloud-based Epitope Prediction Network(PEPNet), a two-stage point cloud framework for epitope prediction. Inspired by the natural atom-to-residue hierarchy in proteins, PEPNet employs a residue-aware hierarchical embedding module to aggregate atomic features into residue-level embeddings. To capture sequential dependencies absent in unordered point clouds, we integrate rotary positional encoding. Additionally, PEPNet leverages a BERT-style pretraining strategy with data augmentation to mitigate data scarcity, and a cross-attention decoder to explicitly model antigen\u2013antibody interactions. Experimental results show that PEPNet achieves the best overall performance (MCC = 0.401, AUC = 0.765). Even when evaluated on AlphaFold3-predicted structures, PEPNet maintains strong robustness (MCC = 0.346), still outperforming WALLE (MCC = 0.305). These results underscore PEPNet\u2019s potential for real-world antibody\u2013antigen analysis and design.<\/jats:p>","DOI":"10.1093\/bib\/bbag067","type":"journal-article","created":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T12:39:42Z","timestamp":1769863182000},"source":"Crossref","is-referenced-by-count":1,"title":["PEPNet: a two-stage point cloud framework with hierarchical embedding and antigen\u2013antibody interaction modeling for epitope prediction"],"prefix":"10.1093","volume":"27","author":[{"given":"Jiayi","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, East China Normal University , 3663 Zhongshan North Road, Putuo District, Shanghai 200062 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guixu","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, East China Normal University , 3663 Zhongshan North Road, Putuo District, Shanghai 200062 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3063-8473","authenticated-orcid":false,"given":"Zhijian","family":"Xu","sequence":"additional","affiliation":[{"name":"Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science and Technology , 130 Meilong Road, Xuhui District, Shanghai 200237 ,","place":["China"]},{"name":"State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica and Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road, Pudong New District, Shanghai 201203 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3041-643X","authenticated-orcid":false,"given":"Qian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, East China Normal University , 3663 Zhongshan North Road, Putuo District, Shanghai 200062 ,","place":["China"]},{"name":"Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, East China Normal University , 3663 Zhongshan North Road, Putuo District, Shanghai 200062 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,2,19]]},"reference":[{"key":"2026021912533810200_ref1","doi-asserted-by":"publisher","first-page":"e2220669120","DOI":"10.1073\/pnas.2220669120","article-title":"B cell receptors and free antibodies have different antigen-binding 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