{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T06:34:16Z","timestamp":1776321256075,"version":"3.50.1"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100021171","name":"Guangdong Basic and Applied Basic Research Foundation","doi-asserted-by":"publisher","award":["2020A1515110840"],"award-info":[{"award-number":["2020A1515110840"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Basic Research Fund","award":["JCYJ20190807170801656"],"award-info":[{"award-number":["JCYJ20190807170801656"]}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"publisher","award":["2021YFF1200300"],"award-info":[{"award-number":["2021YFF1200300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["22250710136"],"award-info":[{"award-number":["22250710136"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["21933010"],"award-info":[{"award-number":["21933010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["22333006"],"award-info":[{"award-number":["22333006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["62106253"],"award-info":[{"award-number":["62106253"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Key Projects","award":["JCYJ20220818100804009"],"award-info":[{"award-number":["JCYJ20220818100804009"]}]},{"name":"Shenzhen Science and Technology Program","award":["KQTD20210811090115019"],"award-info":[{"award-number":["KQTD20210811090115019"]}]},{"name":"Shenzhen Medical Research Fund","award":["B2404003"],"award-info":[{"award-number":["B2404003"]}]}],"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>Enhancing antibody affinity is a critical goal in antibody design, as it improves therapeutic efficacy, specificity, and safety while reducing dosage requirements. Traditional methods, such as single-point mutations or combinatorial mutagenesis, are limited by the impracticality of exhaustively exploring the vast mutational space. To address this challenge, we developed a novel computational pipeline that integrates evolutionary constraints, antibody\u2013antigen-specific statistical potentials, molecular dynamics simulations, metadynamics, and a suite of deep learning models to identify affinity-enhancing mutations. Our deep learning framework includes MicroMutate, which predicts microenvironment-specific amino acid mutations, and graph-based models that evaluate postmutation antigen\u2013antibody-binding probabilities. Using this approach, we screened 12 single-point mutant antibodies targeting the hemagglutinin of the H7N9 avian influenza virus, starting from antibodies with initial affinities in the subnanomolar range, with one showing a 4.62-fold improvement. To demonstrate the generalizability of our method, we applied it to engineer an antibody against death receptor 5 with initial affinities in the subnanomolar range, successfully identifying a mutant with a 2.07-fold increase in affinity. Our work underscores the transformative potential of integrating deep learning and computational methods for rapidly and precisely discovering affinity-enhancing mutations while preserving immunogenicity and expression. This approach offers a powerful and universal platform for advancing antibody therapeutics.<\/jats:p>","DOI":"10.1093\/bib\/bbaf445","type":"journal-article","created":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T14:24:17Z","timestamp":1756736657000},"source":"Crossref","is-referenced-by-count":3,"title":["Significantly enhancing human antibody affinity via deep learning and computational biology-guided single-point mutations"],"prefix":"10.1093","volume":"26","author":[{"given":"Junxin","family":"Li","sequence":"first","affiliation":[{"name":"Center for Protein and Cell-based Drugs, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences , 1068 Xueyuan Avenue, Nanshan District, Shenzhen 518055 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of 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,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sai","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences , 1068 Xueyuan Avenue, Nanshan District, Shenzhen 518055 ,","place":["China"]},{"name":"Faculty of Synthetic Biology, Shenzhen University of Advanced Technology , 1 Beizhen Road, Xinhu Subdistrict, Guangming District, Shenzhen 518055 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark Akinola","family":"Ige","sequence":"additional","affiliation":[{"name":"Center for Protein and Cell-based Drugs, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences , 1068 Xueyuan Avenue, Nanshan District, Shenzhen 518055 ,","place":["China"]},{"name":"University of Chinese Academy of Sciences , No. 1\u00a0Yanqihu East Rd,\u00a0Huairou District, Beijing ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiuliyang","family":"Yu","sequence":"additional","affiliation":[{"name":"Sino-European Center of Biomedicine and Health, Institute of Biomedicine and Biotechnology Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences , Shenzhen 518055 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Faculty of Pharmaceutical Sciences, Shenzhen University of Advanced Technology , 1 Beizhen Road, Xinhu Subdistrict, Guangming District, Shenzhen 518055 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaochun","family":"Wan","sequence":"additional","affiliation":[{"name":"Center for Protein and Cell-based Drugs, Institute of Biomedicine and Biotechnology, Shenzhen Institutes of Advanced Technology, Chinese 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