{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T22:32:40Z","timestamp":1787697160782,"version":"build-2784847793"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T00:00:00Z","timestamp":1748995200000},"content-version":"vor","delay-in-days":34,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Zhejiang Key Laboratory of Intelligent Perception and Control for Complex Systems"},{"name":"General Scientific Research Projects of Zhejiang Education Department"},{"name":"the Postgraduate Teaching Reform Project of Zhejiang University of Technology"},{"name":"the Natural Science Foundation of Zhejiang"},{"name":"the \u201cPioneer\u201d and \u201cLeading Goose\u201d R&D Program of Zhejiang"},{"name":"the Zhejiang Provincial Special Support Program for High-Level Talents"},{"name":"the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang"},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Antibody\u2013antigen interactions (AAIs) are a pervasive phenomenon in the natural and are instrumental in the design of antibody-based drugs. Despite the emergence of various deep learning-based methods aimed at enhancing the accuracy of AAIs predictions, most of these approaches overlook the significance of sequence order information. In this study, we propose a new deep learning-based method RLEAAI, to improve the prediction performance of AAIs. In RLEAAI, a sequence order extraction strategy, called Composition of K-Spaced Amino Acid Pairs, is employed to generate feature representation from the feature embedding outputted by a pre-trained protein language model. In order to fully dig out the discrimination information from features, three neural network modules, i.e. convolutional neural network, bidirectional long short-term memory network and recurrent criss-cross attention mechanism, are integrated. Benchmarked results on two independent test sets demonstrate that RLEAAI is capable of achieving an average accuracy of 0.7787 and an average Matthews\u2019s correlation coefficient (MCC) value of 0.5552, representing a 5.2% and 15.8% improvement over the start-of-the-art method DeepAAI. Furthermore, the complementary determining regions-sensitivity value calculated on MCC of RLEAAI is 216.4% higher than that of the state-of-the-art method DeepAAI. The standalone package of RLEAAI is freely available at https:\/\/github.com\/zhouyu9931\/RLEAAI.git.<\/jats:p>","DOI":"10.1093\/bib\/bbaf238","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T05:13:26Z","timestamp":1749014006000},"source":"Crossref","is-referenced-by-count":5,"title":["RLEAAI: improving antibody\u2013antigen interaction prediction using protein language model and sequence order information"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9202-7515","authenticated-orcid":false,"given":"Jun","family":"Hu","sequence":"first","affiliation":[{"name":"College of Information Engineering, Zhejiang University of Technology , 288 Liuhe Road, Liuxia Street, Xihu District, Hangzhou 310023 ,","place":["China"]},{"name":"Center for AI and Computational Biology, Suzhou Institute of Systems Medicine , 100 Chongwen Road, Suzhou 215123 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Zhejiang University of Technology , 288 Liuhe Road, Liuxia Street, Xihu District, Hangzhou 310023 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen-Yi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Westlake AI Therapeutics Lab, Westlake Laboratory of Life Sciences and Biomedicine , 18 Shilongshan Road, Hangzhou, Zhejiang 310024 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6839-1923","authenticated-orcid":false,"given":"Xiao-Gen","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Zhejiang University of Technology , 288 Liuhe Road, Liuxia Street, Xihu District, Hangzhou 310023 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