{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T05:15:05Z","timestamp":1781068505121,"version":"3.54.1"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T00:00:00Z","timestamp":1759708800000},"content-version":"vor","delay-in-days":36,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62372158"],"award-info":[{"award-number":["62372158"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62402533"],"award-info":[{"award-number":["62402533"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62572178"],"award-info":[{"award-number":["62572178"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62472165"],"award-info":[{"award-number":["62472165"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2025JJ60400"],"award-info":[{"award-number":["2025JJ60400"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Educational Commission of Hunan Province","award":["23B0237"],"award-info":[{"award-number":["23B0237"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>T-cell receptor (TCR)-epitope binding prediction is critical for immunotherapies but remains challenged by sparse interaction networks and severe class imbalance in training data. Current graph neural network (GNN) approaches for predicting TCR-epitope binding (TEB) fail to address two key limitations: over-smoothing during message propagation in sparse TCR-epitope graphs and biased predictions toward dominant epitope-TCR pairs. Here, we present GRAPE (Graph-Regularized Attentive Protein Embeddings), a framework unifying spectral graph regularization and imbalance-aware learning. GRAPE first leverages protein language models (ESM-2) to generate evolutionary-informed TCR\/epitope embeddings, constructing a topology-aware interaction graph. To mitigate over-smoothing, we introduce spectral graph regularization, explicitly constraining node feature smoothness to preserve discriminative patterns in sparse neighborhoods. Simultaneously, a dynamic edge reweighting module prioritizes unobserved TCR-epitope edges during graph propagation, coupled with a differentiable area under the ROC curve-maximization objective that directly optimizes for imbalance resilience. Extensive benchmarking on public datasets demonstrates that GRAPE significantly outperforms state-of-the-art methods in TEB prediction. This work establishes GRAPE as a robust framework for elucidating TCR-epitope interactions, with broad applications in immunology research and therapeutic design.<\/jats:p>","DOI":"10.1093\/bib\/bbaf522","type":"journal-article","created":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T17:13:02Z","timestamp":1759770782000},"source":"Crossref","is-referenced-by-count":7,"title":["GRAPE: graph-regularized protein language modeling unlocks TCR-epitope binding specificity"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6840-2573","authenticated-orcid":false,"given":"Xiangzheng","family":"Fu","sequence":"first","affiliation":[{"name":"Institute of Artificial Intelligence Application , College of Computer and Information Engineering, Central South University of Forestry and Technology, No. 498 Shaoshan South Road, Tianxin District, Changsha, Hunan 410004,","place":["China"]},{"name":"School of Chinese Medicine , Hong Kong Baptist University, 15 Baptist University Road, Kowloon Tong, Kowloon, Hong Kong SAR 999077,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5078-5091","authenticated-orcid":false,"given":"Li","family":"Peng","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering , Hunan University of Science and Technology, No. 1 Taoyuan Road, Yuhu District, Xiangtan, Hunan 411201,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4777-7525","authenticated-orcid":false,"given":"Haowen","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Science and Electronic Engineering , Hunan University, 2 Lushan South Road, Yuelu District, Changsha, Hunan 410082,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingqiang","family":"Rong","sequence":"additional","affiliation":[{"name":"The National & Local Joint Engineering Laboratory of Animal Peptide Drug Development , College of Life Sciences, Hunan Normal University, 36 Lushan Road, Yuelu District, Changsha, Hunan 410081,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence Application , College of Computer and Information Engineering, Central South University of Forestry and Technology, No. 498 Shaoshan South Road, Tianxin District, Changsha, Hunan 410004,","place":["China"]},{"name":"School of Information Engineering , Changsha Medical University, No. 1501 Leifeng Road, Wangcheng District, Changsha, 410219,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3604-3785","authenticated-orcid":false,"given":"Dongsheng","family":"Cao","sequence":"additional","affiliation":[{"name":"Xiangya School of Pharmaceutical Sciences , Central South University, No. 172 Tongzipo Road, Yuelu District, Changsha, Hunan 410003,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sisi","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics and Genomics , The University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aiping","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Chinese Medicine , Hong Kong Baptist University, 15 Baptist University Road, Kowloon Tong, Kowloon, Hong Kong SAR 999077,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,10,6]]},"reference":[{"key":"2025100613125540400_ref1","doi-asserted-by":"publisher","first-page":"100027","DOI":"10.1016\/j.immuno.2023.100027","article-title":"Interpretable deep learning to uncover the 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