{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T08:05:18Z","timestamp":1772525118777,"version":"3.50.1"},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,7,9]],"date-time":"2024-07-09T00:00:00Z","timestamp":1720483200000},"content-version":"vor","delay-in-days":47,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Open Research Fund of the National Mobile Communications Research Laboratory"},{"name":"Southeast Universtiy","award":["2023D15"],"award-info":[{"award-number":["2023D15"]}]},{"name":"Ningbo Clinical Research Center for Medical Imaging","award":["2022LYKFYB01"],"award-info":[{"award-number":["2022LYKFYB01"]}]},{"name":"National Program on Key Basic Research Project","award":["2020YFA0713600"],"award-info":[{"award-number":["2020YFA0713600"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62272214"],"award-info":[{"award-number":["62272214"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Accurate prediction of protein\u2013ligand binding affinity (PLA) is important for drug discovery. Recent advances in applying graph neural networks have shown great potential for PLA prediction. However, existing methods usually neglect the geometric information (i.e. bond angles), leading to difficulties in accurately distinguishing different molecular structures. In addition, these methods also pose limitations in representing the binding process of protein\u2013ligand complexes. To address these issues, we propose a novel geometry-enhanced mid-fusion network, named GEMF, to learn comprehensive molecular geometry and interaction patterns. Specifically, the GEMF consists of a graph embedding layer, a message passing phase, and a multi-scale fusion module. GEMF can effectively represent protein\u2013ligand complexes as graphs, with graph embeddings based on physicochemical and geometric properties. Moreover, our dual-stream message passing framework models both covalent and non-covalent interactions. In particular, the edge-update mechanism, which is based on line graphs, can fuse both distance and angle information in the covalent branch. In addition, the communication branch consisting of multiple heterogeneous interaction modules is developed to learn intricate interaction patterns. Finally, we fuse the multi-scale features from the covalent, non-covalent, and heterogeneous interaction branches. The extensive experimental results on several benchmarks demonstrate the superiority of GEMF compared with other state-of-the-art methods.<\/jats:p>","DOI":"10.1093\/bib\/bbae333","type":"journal-article","created":{"date-parts":[[2024,7,9]],"date-time":"2024-07-09T15:17:28Z","timestamp":1720538248000},"source":"Crossref","is-referenced-by-count":4,"title":["GEMF: a novel geometry-enhanced mid-fusion network for PLA prediction"],"prefix":"10.1093","volume":"25","author":[{"given":"Guoqiang","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Computer Science, Nanjing University of Posts and Telecommunications , No.9 Wenyuan Road, Jiangsu 210023 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuke","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Computer Science, Nanjing University of Posts and Telecommunications , No.9 Wenyuan Road, Jiangsu 210023 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiansen","family":"Hong","sequence":"additional","affiliation":[{"name":"School of Computer Science, Nanjing University of Posts and Telecommunications , No.9 Wenyuan Road, Jiangsu 210023 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoran","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computing and Information Technology, University of Wollongong , Northfields Avenue, NSW 2522 , Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5678-472X","authenticated-orcid":false,"given":"Huaming","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, University of Sydney , Camperdown, NSW 2050 , 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