{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T02:00:50Z","timestamp":1785376850289,"version":"3.55.0"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T00:00:00Z","timestamp":1718928000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072384"],"award-info":[{"award-number":["62072384"]}],"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":["61872309"],"award-info":[{"award-number":["61872309"]}],"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":["62072385"],"award-info":[{"award-number":["62072385"]}],"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":["61772441"],"award-info":[{"award-number":["61772441"]}],"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":["62372391"],"award-info":[{"award-number":["62372391"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Zhi jiang Lab","award":["2022RD0AB02"],"award-info":[{"award-number":["2022RD0AB02"]}]},{"name":"Fujian Provincial Major Science and Technology Project","award":["2022YZ040011"],"award-info":[{"award-number":["2022YZ040011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>In the field of drug discovery, accurately and effectively predicting the binding affinity between proteins and ligands is crucial for drug screening and optimization. However, current research primarily utilizes representations based on sequence or structure to predict protein\u2013ligand binding affinity, with relatively less study on protein surface information, which is crucial for protein\u2013ligand interactions. Moreover, when dealing with multimodal information of proteins, traditional approaches typically concatenate features from different modalities in a straightforward manner without considering the heterogeneity among them, which results in an inability to effectively exploit the complementary between modalities.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We introduce a novel multimodal feature extraction (MFE) framework that, for the first time, incorporates information from protein surfaces, 3D structures, and sequences, and uses cross-attention mechanism for feature alignment between different modalities. Experimental results show that our method achieves state-of-the-art performance in predicting protein\u2013ligand binding affinity. Furthermore, we conduct ablation studies that demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within the framework.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The source code and data are available at https:\/\/github.com\/Sultans0fSwing\/MFE.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae413","type":"journal-article","created":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T19:09:06Z","timestamp":1718996946000},"source":"Crossref","is-referenced-by-count":25,"title":["Surface-based multimodal protein\u2013ligand binding affinity prediction"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7093-0131","authenticated-orcid":false,"given":"Shiyu","family":"Xu","sequence":"first","affiliation":[{"name":"National Institute for Data Science in Health and Medicine, Xiamen University , Xiamen 361005,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lian","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Xiamen University , Xiamen 361005,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9317-6706","authenticated-orcid":false,"given":"Menglong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Xiamen University , Xiamen 361005,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changzhi","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Xiamen University , Xiamen 361005,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9618-5799","authenticated-orcid":false,"given":"Xinyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Xiamen University , Xiamen 361005,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0326-6960","authenticated-orcid":false,"given":"Yanni","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Xiamen University , Xiamen 361005,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Liu","sequence":"additional","affiliation":[{"name":"Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University , Xiamen 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