{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:42:23Z","timestamp":1780360943805,"version":"3.54.1"},"reference-count":78,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:00:00Z","timestamp":1763510400000},"content-version":"vor","delay-in-days":18,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Macao Polytechnic University","award":["RP\/CAI-01\/2023"],"award-info":[{"award-number":["RP\/CAI-01\/2023"]}]},{"name":"Science and Technology Development Fund of Macau","award":["0004\/2025\/RIA1"],"award-info":[{"award-number":["0004\/2025\/RIA1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Understanding the relationship between protein sequences and structures is essential for accurate protein property prediction. We propose BridgeNet, a pre-trained deep learning framework that integrates sequence and structural information through a novel latent environment matrix, enabling seamless alignment of these two modalities. The model\u2019s modular architecture\u2014comprising sequence encoding, structural encoding, and a bridge module\u2014effectively captures complementary features without requiring explicit structural inputs during inference. Extensive evaluations on tasks such as enzyme classification, Gene Ontology annotation, coenzyme specificity prediction, and peptide toxicity prediction demonstrate its superior performance over state-of-the-art models. BridgeNet provides a scalable and robust solution, advancing protein representation learning and enabling applications in computational biology and structural bioinformatics.<\/jats:p>","DOI":"10.1093\/bib\/bbaf607","type":"journal-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T17:43:12Z","timestamp":1763574192000},"source":"Crossref","is-referenced-by-count":1,"title":["BridgeNet: a high-efficiency framework integrating sequence and structure for protein and enzyme function prediction"],"prefix":"10.1093","volume":"26","author":[{"given":"Yilin","family":"Ye","sequence":"first","affiliation":[{"name":"Faculty of Applied Sciences, Macao Polytechnic University , R. de Lu\u00eds Gonzaga Gomes, Macao, 999078 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongliang","family":"Duan","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences, Macao Polytechnic University , R. de Lu\u00eds Gonzaga Gomes, Macao, 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