{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T14:04:38Z","timestamp":1773151478926,"version":"3.50.1"},"reference-count":73,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,4,6]],"date-time":"2024-04-06T00:00:00Z","timestamp":1712361600000},"content-version":"vor","delay-in-days":10,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"publisher","award":["2023YFA0915500"],"award-info":[{"award-number":["2023YFA0915500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2020JQ04"],"award-info":[{"award-number":["ZR2020JQ04"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Local Science and Technology Development Fund"},{"name":"Central Government of Shandong Province","award":["YDZX2022089"],"award-info":[{"award-number":["YDZX2022089"]}]},{"DOI":"10.13039\/501100001459","name":"Singapore Ministry of Education","doi-asserted-by":"crossref","award":["RG97\/22"],"award-info":[{"award-number":["RG97\/22"]}],"id":[{"id":"10.13039\/501100001459","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Key Research and Development Project of Guangdong Province","award":["2021B0101310002"],"award-info":[{"award-number":["2021B0101310002"]}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["62272449"],"award-info":[{"award-number":["62272449"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Basic Research Fund","award":["RCYX20200714114734194"],"award-info":[{"award-number":["RCYX20200714114734194"]}]},{"name":"Shenzhen Basic Research Fund","award":["KQTD20200820113106007"],"award-info":[{"award-number":["KQTD20200820113106007"]}]},{"name":"Shenzhen Basic Research Fund","award":["ZDSYS20220422103800001"],"award-info":[{"award-number":["ZDSYS20220422103800001"]}]},{"DOI":"10.13039\/501100012492","name":"Youth Innovation Promotion Association","doi-asserted-by":"publisher","award":["Y2021101"],"award-info":[{"award-number":["Y2021101"]}],"id":[{"id":"10.13039\/501100012492","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Core Facility Sharing Platform of Shandong University"},{"name":"National Demonstration Center for Experimental Physics Education"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Protein\u2013ligand interaction prediction presents a significant challenge in drug design. Numerous machine learning and deep learning (DL) models have been developed to accurately identify docking poses of ligands and active compounds against specific targets. However, current models often suffer from inadequate accuracy or lack practical physical significance in their scoring systems. In this research paper, we introduce IGModel, a novel approach that utilizes the geometric information of protein\u2013ligand complexes as input for predicting the root mean square deviation of docking poses and the binding strength (pKd, the negative value of the logarithm of binding affinity) within the same prediction framework. This ensures that the output scores carry intuitive meaning. We extensively evaluate the performance of IGModel on various docking power test sets, including the CASF-2016 benchmark, PDBbind-CrossDocked-Core and DISCO set, consistently achieving state-of-the-art accuracies. Furthermore, we assess IGModel\u2019s generalizability and robustness by evaluating it on unbiased test sets and sets containing target structures generated by AlphaFold2. The exceptional performance of IGModel on these sets demonstrates its efficacy. Additionally, we visualize the latent space of protein\u2013ligand interactions encoded by IGModel and conduct interpretability analysis, providing valuable insights. This study presents a novel framework for DL-based prediction of protein\u2013ligand interactions, contributing to the advancement of this field. The IGModel is available at GitHub repository https:\/\/github.com\/zchwang\/IGModel.<\/jats:p>","DOI":"10.1093\/bib\/bbae145","type":"journal-article","created":{"date-parts":[[2024,3,24]],"date-time":"2024-03-24T11:37:32Z","timestamp":1711280252000},"source":"Crossref","is-referenced-by-count":24,"title":["A new paradigm for applying deep learning to protein\u2013ligand interaction prediction"],"prefix":"10.1093","volume":"25","author":[{"given":"Zechen","family":"Wang","sequence":"first","affiliation":[{"name":"School of Physics, Shandong University , South Shanda Road, 250100 Shandong , China"}]},{"given":"Sheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Zelixir Biotech , Xiangke Road, 200030, Shanghai , China"}]},{"given":"Yangyang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Physics, Shandong University , South Shanda Road, 250100 Shandong , China"}]},{"given":"Jingjing","family":"Guo","sequence":"additional","affiliation":[{"name":"Centre in Artificial Intelligence Driven Drug Discovery , Faculty of Applied Sciences, , Rua de Lu\u00eds Gonzaga Gomes, Macao , China"},{"name":"Macao Polytechnic University , Faculty of Applied Sciences, , Rua de Lu\u00eds Gonzaga Gomes, Macao , China"}]},{"given":"Yanjie","family":"Wei","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences , Xueyuan Road 1068, Shenzhen, 518055 Guang Dong , China"}]},{"given":"Yuguang","family":"Mu","sequence":"additional","affiliation":[{"name":"School of Biological Sciences, Nanyang Technological University , Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1179-2106","authenticated-orcid":false,"given":"Liangzhen","family":"Zheng","sequence":"additional","affiliation":[{"name":"Shanghai Zelixir Biotech , Xiangke Road, 200030, Shanghai , China"},{"name":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences , Xueyuan Road 1068, Shenzhen, 518055 Guang Dong , China"}]},{"given":"Weifeng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Physics, Shandong University , South Shanda Road, 250100 Shandong , China"}]}],"member":"286","published-online":{"date-parts":[[2024,4,5]]},"reference":[{"issue":"9","key":"2024050313340567000_ref1","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1016\/j.chembiol.2003.09.002","article-title":"The process of structure-based drug design","volume":"10","author":"Anderson","year":"2003","journal-title":"Chem Biol"},{"issue":"18","key":"2024050313340567000_ref2","doi-asserted-by":"crossref","first-page":"4331","DOI":"10.3390\/ijms20184331","article-title":"Molecular docking: shifting paradigms in drug discovery","volume":"20","author":"Pinzi","year":"2019","journal-title":"Int J Mol 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