{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T20:50:46Z","timestamp":1781383846341,"version":"3.54.1"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of Chin","doi-asserted-by":"crossref","award":["62272399"],"award-info":[{"award-number":["62272399"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of Chin","doi-asserted-by":"crossref","award":["U24A20742"],"award-info":[{"award-number":["U24A20742"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Noncommunicable Chronic Diseases-National Science and Technology Major Project","award":["2023ZD0501001"],"award-info":[{"award-number":["2023ZD0501001"]}]},{"name":"Major Science and Technology Project of Fujian Provincial Health Commission","award":["2021ZD01006"],"award-info":[{"award-number":["2021ZD01006"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["20720250004"],"award-info":[{"award-number":["20720250004"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,4,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Protein language models are critical for modeling antibody\u2013antigen interactions, yet sequence-based affinity prediction remains a key challenge, particularly when structural data are scarce. Existing methods often struggle to fully exploit sequence information, limiting their applicability across diverse antibody formats such as single-domain antibodies (sdAbs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We propose dual-level protein representation for affinity prediction (DLP-Affinity), a dual-level deep learning framework for accurate sequence-based affinity prediction. It leverages two complementary modules: residue-to-residue to capture local interface contacts, and global stochastic projection embedding to represent global protein properties. Utilizing a fine-tuned protein language model, our approach achieves state-of-the-art performance on the general AB-Bind dataset (reducing mean absolute error by up to 20.9%) and delivers highly competitive results on the sdAb-DB dataset. This provides a robust tool for sequence-based antibody affinity prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The source code and datasets for DLP-Affinity are freely available at https:\/\/github.com\/Zy-Wang-bit\/DLP_Affinity and archived on Zenodo at https:\/\/doi.org\/10.5281\/zenodo.18437656<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag109","type":"journal-article","created":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T12:49:22Z","timestamp":1772628562000},"source":"Crossref","is-referenced-by-count":1,"title":["Predicting antibody\u2013antigen affinity with a dual-level representation model"],"prefix":"10.1093","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1656-0638","authenticated-orcid":false,"given":"Ziyang","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Artificial Intelligence, Xiamen University, Xiamen, 361102, China"},{"name":"State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health; National Institute of Diagnostics and Vaccine Development in Infectious Diseases; National Innovation Platform for Industry-Education Integration in Vaccine Research; NMPA Key Laboratory for Research and Evaluation of Infectious Disease Diagnostic Technology, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1816-9539","authenticated-orcid":false,"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence, Xiamen University, Xiamen, 361102, China"},{"name":"State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health; National Institute of Diagnostics and Vaccine Development in Infectious Diseases; National Innovation Platform for Industry-Education Integration in Vaccine Research; NMPA Key Laboratory for Research and Evaluation of Infectious Disease Diagnostic Technology, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youli","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health; National Institute of Diagnostics and Vaccine Development in Infectious Diseases; National Innovation Platform for Industry-Education Integration in Vaccine Research; NMPA Key Laboratory for Research and Evaluation of Infectious Disease Diagnostic Technology, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8629-9229","authenticated-orcid":false,"given":"Jianwei","family":"Huang","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence, Xiamen University, Xiamen, 361102, China"},{"name":"State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health; National Institute of Diagnostics and Vaccine Development in Infectious Diseases; National Innovation Platform for Industry-Education Integration in Vaccine Research; NMPA Key Laboratory for Research and Evaluation of Infectious Disease Diagnostic Technology, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoli","family":"Lu","sequence":"additional","affiliation":[{"name":"Information and Networking Center, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoping","family":"Min","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health; National Institute of Diagnostics and Vaccine Development in Infectious Diseases; National Innovation Platform for Industry-Education Integration in Vaccine Research; NMPA Key Laboratory for Research and Evaluation of Infectious Disease Diagnostic Technology, Xiamen University, Xiamen, 361102, China"},{"name":"School of Informatics, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengxiang","family":"Ge","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health; National Institute of Diagnostics and Vaccine Development in Infectious Diseases; National Innovation Platform for Industry-Education Integration in Vaccine Research; NMPA Key Laboratory for Research and Evaluation of Infectious Disease Diagnostic Technology, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6601-9180","authenticated-orcid":false,"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health; National Institute of Diagnostics and Vaccine Development in Infectious Diseases; National Innovation Platform for Industry-Education Integration in Vaccine Research; NMPA Key Laboratory for Research and Evaluation of Infectious Disease Diagnostic Technology, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ningshao","family":"Xia","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health; National Institute of Diagnostics and Vaccine Development in Infectious Diseases; National Innovation Platform for Industry-Education Integration in Vaccine Research; NMPA Key Laboratory for Research and Evaluation of Infectious Disease Diagnostic Technology, Xiamen University, Xiamen, 361102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,3,10]]},"reference":[{"key":"2026042409464115500_btag109-B1","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1038\/s41586-024-07487-w","article-title":"Accurate structure prediction of biomolecular interactions with alphafold 3","volume":"630","author":"Abramson","year":"2024","journal-title":"Nature"},{"key":"2026042409464115500_btag109-B2","doi-asserted-by":"crossref","first-page":"2102","DOI":"10.1093\/bioinformatics\/btac020","article-title":"Proteinbert: a universal deep-learning model of protein sequence and function","volume":"38","author":"Brandes","year":"2022","journal-title":"Bioinformatics"},{"key":"2026042409464115500_btag109-B3","doi-asserted-by":"crossref","first-page":"706","DOI":"10.1016\/j.cels.2023.07.003","article-title":"Learning protein fitness landscapes with deep mutational scanning data from multiple sources","volume":"14","author":"Chen","year":"2023","journal-title":"Cell Syst"},{"key":"2026042409464115500_btag109-B4","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.1038\/nprot.2013.074","article-title":"Small-molecule ligand docking into comparative models with rosetta","volume":"8","author":"Combs","year":"2013","journal-title":"Nat Protoc"},{"key":"2026042409464115500_btag109-B5","author":"Dallago","year":"2022"},{"key":"2026042409464115500_btag109-B6","doi-asserted-by":"publisher","first-page":"1594","DOI":"10.1038\/s42256-024-00940-5","article-title":"Nanobody\u2013antigen interaction prediction with ensemble deep learning and prompt-based protein language models","volume":"6","author":"Deng","year":"2024","journal-title":"Nat Mach Intell"},{"key":"2026042409464115500_btag109-B7","doi-asserted-by":"crossref","first-page":"eads0018","DOI":"10.1126\/science.ads0018","article-title":"Simulating 500 million years of evolution with a language model","volume":"387","author":"Hayes","year":"2025","journal-title":"Science"},{"key":"2026042409464115500_btag109-B8","author":"Jamasb","year":"2024"},{"key":"2026042409464115500_btag109-B9","author":"Jiale","year":"2024"},{"key":"2026042409464115500_btag109-B10","doi-asserted-by":"crossref","first-page":"bbae304","DOI":"10.1093\/bib\/bbae304","article-title":"Attabseq: an attention-based deep learning prediction method for antigen\u2013antibody binding affinity changes based on protein sequences","volume":"25","author":"Jin","year":"2024","journal-title":"Brief Bioinform"},{"key":"2026042409464115500_btag109-B11","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1038\/s41563-020-00906-z","article-title":"Diagnostics for sars-cov-2 infections","volume":"20","author":"Kevadiya","year":"2021","journal-title":"Nat Mater"},{"key":"2026042409464115500_btag109-B12","doi-asserted-by":"crossref","first-page":"19533","DOI":"10.1038\/s41598-020-76369-8","article-title":"Predicting antibody affinity changes upon mutations by combining multiple predictors","volume":"10","author":"Kurumida","year":"2020","journal-title":"Sci Rep"},{"key":"2026042409464115500_btag109-B13","doi-asserted-by":"crossref","first-page":"100513","DOI":"10.1016\/j.patter.2022.100513","article-title":"Deciphering the language of antibodies using self-supervised learning","volume":"3","author":"Leem","year":"2022","journal-title":"Patterns"},{"key":"2026042409464115500_btag109-B14","article-title":"Mvsf-ab: accurate antibody-antigen binding affinity prediction via multi-view sequence feature learning","volume":"41","author":"Li","year":"2025","journal-title":"Bioinformatics"},{"key":"2026042409464115500_btag109-B15","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1126\/science.ade2574","article-title":"Evolutionary-scale prediction of atomic-level protein structure with a language model","volume":"379","author":"Lin","year":"2023","journal-title":"Science"},{"key":"2026042409464115500_btag109-B16","author":"Liu","year":"2024"},{"key":"2026042409464115500_btag109-B17","doi-asserted-by":"crossref","first-page":"968","DOI":"10.1016\/j.cels.2023.10.002","article-title":"Progen2: exploring the boundaries of protein language models","volume":"14","author":"Nijkamp","year":"2023","journal-title":"Cell Syst"},{"key":"2026042409464115500_btag109-B18","doi-asserted-by":"crossref","first-page":"vbac046","DOI":"10.1093\/bioadv\/vbac046","article-title":"Ablang: an antibody language model for completing antibody sequences","volume":"2","author":"Olsen","year":"2022","journal-title":"Bioinform Adv"},{"key":"2026042409464115500_btag109-B19","author":"Rao","year":"2021"},{"key":"2026042409464115500_btag109-B20","doi-asserted-by":"crossref","first-page":"e2016239118","DOI":"10.1073\/pnas.2016239118","article-title":"Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences","volume":"118","author":"Rives","year":"2021","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2026042409464115500_btag109-B21","author":"Ruffolo","year":"2021"},{"key":"2026042409464115500_btag109-B22","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1002\/pro.2829","article-title":"Ab-bind: antibody binding mutational database for computational affinity predictions","volume":"25","author":"Sirin","year":"2016","journal-title":"Protein Sci"},{"key":"2026042409464115500_btag109-B23","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/0022-2836(81)90087-5","article-title":"Identification of common molecular subsequences","volume":"147","author":"Smith","year":"1981","journal-title":"J Mol Biol"},{"key":"2026042409464115500_btag109-B24","doi-asserted-by":"crossref","first-page":"bbae403","DOI":"10.1093\/bib\/bbae403","article-title":"Antiformer: graph enhanced large language model for binding affinity prediction","volume":"25","author":"Wang","year":"2024","journal-title":"Brief Bioinform"},{"key":"2026042409464115500_btag109-B25","doi-asserted-by":"crossref","first-page":"212106","DOI":"10.1007\/s11432-024-4171-9","article-title":"Sbsm-pro: support bio-sequence machine for proteins","volume":"67","author":"Wang","year":"2024","journal-title":"Sci China Inf Sci"},{"key":"2026042409464115500_btag109-B26","author":"Wang","year":"2024"},{"key":"2026042409464115500_btag109-B27","doi-asserted-by":"crossref","first-page":"2480","DOI":"10.1021\/acssynbio.8b00407","article-title":"sdab-db: the single domain antibody database","volume":"7","author":"Wilton","year":"2018","journal-title":"ACS Synth Biol"},{"key":"2026042409464115500_btag109-B28","first-page":"31140","volume-title":"Advances in Neural Information Processing Systems","author":"Wu","year":"2023"},{"key":"2026042409464115500_btag109-B29","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1038\/s41592-019-0496-6","article-title":"Machine-learning-guided directed evolution for protein engineering","volume":"16","author":"Yang","year":"2019","journal-title":"Nat Methods"},{"key":"2026042409464115500_btag109-B30","doi-asserted-by":"crossref","first-page":"W6","DOI":"10.1093\/nar\/gkl164","article-title":"Blast: improvements for better sequence analysis","volume":"34","author":"Ye","year":"2006","journal-title":"Nucleic Acids Res"},{"key":"2026042409464115500_btag109-B31","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1038\/s43588-023-00511-5","article-title":"Efficient and accurate large library ligand docking with karmadock","volume":"3","author":"Zhang","year":"2023","journal-title":"Nat Comput Sci"},{"key":"2026042409464115500_btag109-B32","author":"Zhang","year":"2024"},{"key":"2026042409464115500_btag109-B33","author":"Zheng","year":"2024"},{"key":"2026042409464115500_btag109-B34","author":"Zheng","year":"2023"},{"key":"2026042409464115500_btag109-B35","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1038\/s41392-024-01823-2","article-title":"Tumor biomarkers for diagnosis, prognosis and targeted therapy","volume":"9","author":"Zhou","year":"2024","journal-title":"Signal Transduct Target Ther"},{"key":"2026042409464115500_btag109-B36","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1038\/s43018-023-00516-z","article-title":"Advances in antibody-based therapy in oncology","volume":"4","author":"Zinn","year":"2023","journal-title":"Nat Cancer"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btag109\/67294695\/btag109.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/42\/4\/btag109\/67294695\/btag109.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/42\/4\/btag109\/67294695\/btag109.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T13:46:52Z","timestamp":1777038412000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btag109\/8513493"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026,3,10]]},"references-count":36,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,4,7]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btag109","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,4]]},"published":{"date-parts":[[2026,3,10]]},"article-number":"btag109"}}