{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T07:37:43Z","timestamp":1780731463843,"version":"3.54.1"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T00:00:00Z","timestamp":1759104000000},"content-version":"vor","delay-in-days":29,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62302311"],"award-info":[{"award-number":["62302311"]}],"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":["62471310"],"award-info":[{"award-number":["62471310"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFF1202104"],"award-info":[{"award-number":["2022YFF1202104"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Guangdong Basic and Applied Basic Research Foundation","doi-asserted-by":"publisher","award":["2024A1515011681"],"award-info":[{"award-number":["2024A1515011681"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Guangdong Basic and Applied Basic Research Foundation","doi-asserted-by":"publisher","award":["2025A1515010185"],"award-info":[{"award-number":["2025A1515010185"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Colleges and Universities Stable Support Program","award":["GXWD20220811170504001"],"award-info":[{"award-number":["GXWD20220811170504001"]}]},{"name":"Shenzhen Science and Technology Program","award":["JCYJ20230807094318038"],"award-info":[{"award-number":["JCYJ20230807094318038"]}]},{"name":"Shenzhen Research Initiation Program for High-Caliber Critical Talent","award":["827-000932"],"award-info":[{"award-number":["827-000932"]}]},{"name":"Internal Fund of National Engineering Laboratory for Big Data System Computing Technology","award":["SZU-BDSC-IF2024-01"],"award-info":[{"award-number":["SZU-BDSC-IF2024-01"]}]}],"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>Protein\u2013nucleic acid interactions play a crucial role in biological processes, including gene regulation and editing. Accurately identifying nucleic acid-binding domains in proteins is essential to unravel these interactions, yet traditional experimental methods like X-ray crystallography remain costly and time-intensive. Computational approaches have thus emerged as indispensable tools to complement wet-lab techniques. Here, we introduce a framework for nucleic acid-binding domain prediction by integrating cross-modal protein language models with a multiscale computational architecture. The proposed method leverages a structurally annotated benchmark dataset, which quantifies binding likelihood through hierarchical, proximity-based labels derived from experimental complexes. Evaluations demonstrate that the approach achieves state-of-the-art performance, providing a new insight into the design of multimodal learning systems in protein-nucleic acid interaction analysis and an open resource to accelerate discoveries in functional genomics and drug design.<\/jats:p>","DOI":"10.1093\/bib\/bbaf509","type":"journal-article","created":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T12:18:15Z","timestamp":1759148295000},"source":"Crossref","is-referenced-by-count":3,"title":["INAB: identify nucleic acid binding domain via cross-modal protein language models and multiscale computation"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0484-0966","authenticated-orcid":false,"given":"Jun","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Shenzhen University , Shenzhen 518060 ,","place":["China"]},{"name":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University , Shenzhen 518060 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Shenzhen University , Shenzhen 518060 ,","place":["China"]},{"name":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University , Shenzhen 518060 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0483-303X","authenticated-orcid":false,"given":"Junjie","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Harbin Institute of Technology , Shenzhen, Shenzhen 518060 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8479-6904","authenticated-orcid":false,"given":"Zexuan","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Shenzhen University , Shenzhen 518060 ,","place":["China"]},{"name":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University , Shenzhen 518060 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,9,29]]},"reference":[{"key":"2025092908181234000_ref1","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1038\/nrm3884","article-title":"The structure, function and evolution of proteins that bind DNA and RNA","volume":"15","author":"Hudson","year":"2014","journal-title":"Nat Rev Mol Cell Biol"},{"key":"2025092908181234000_ref2","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbaa397","article-title":"NCBRPred: predicting nucleic acid binding residues in proteins based on multilabel learning","volume":"22","author":"Zhang","year":"2021","journal-title":"Brief 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