{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T05:48:20Z","timestamp":1773726500323,"version":"3.50.1"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:00:00Z","timestamp":1736380800000},"content-version":"vor","delay-in-days":48,"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":["62372158"],"award-info":[{"award-number":["62372158"]}],"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":["62122025"],"award-info":[{"award-number":["62122025"]}],"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":["U22A2037"],"award-info":[{"award-number":["U22A2037"]}],"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":["62250028"],"award-info":[{"award-number":["62250028"]}],"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":["62402533"],"award-info":[{"award-number":["62402533"]}],"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":["62472165"],"award-info":[{"award-number":["62472165"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2022JJ40090"],"award-info":[{"award-number":["2022JJ40090"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Educational Commission of Hunan Province","award":["23B0237"],"award-info":[{"award-number":["23B0237"]}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing","doi-asserted-by":"publisher","award":["CSTB2022NSCQ-MSX1032"],"award-info":[{"award-number":["CSTB2022NSCQ-MSX1032"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Accurately predicting the degradation capabilities of proteolysis-targeting chimeras (PROTACs) for given target proteins and E3 ligases is important for PROTAC design. The distinctive ternary structure of PROTACs presents a challenge to traditional drug\u2013target interaction prediction methods, necessitating more innovative approaches. While current state-of-the-art (SOTA) methods using graph neural networks (GNNs) can discern the molecular structure of PROTACs and proteins, thus enabling the efficient prediction of PROTACs\u2019 degradation capabilities, they rely heavily on limited crystal structure data of the POI-PROTAC-E3 ternary complex. This reliance underutilizes rich PROTAC experimental data and neglects intricate interaction relationships within ternary complexes.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this study, we propose a model based on cross-modal strategy and ternary attention technology, ET-PROTACs, to predict the targeted degradation capabilities of PROTACs. Our model capitalizes on the strengths of cross-modal methods by using equivariant GNN graph neural networks to process the graph structure and spatial coordinates of PROTAC molecules concurrently while utilizing sequence-based methods to learn the protein sequence information. This integration of cross-modal information is cohesively harnessed and channeled into a ternary attention mechanism, specially tailored for the unique structure of PROTACs, enabling the congruent modeling of both PROTAC and protein modalities. Experimental results demonstrate that the ET-PROTACs model outperforms existing SOTA methods. Moreover, visualizing attention scores illuminates crucial residues and atoms pivotal in specific POI-PROTAC-E3 interactions, thus offering invaluable insights and guidance for future pharmaceutical research.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The codes of our model are available at https:\/\/github.com\/GuanyuYue\/ET-PROTACs<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bib\/bbae654","type":"journal-article","created":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T20:26:29Z","timestamp":1733516789000},"source":"Crossref","is-referenced-by-count":9,"title":["ET-PROTACs: modeling ternary complex interactions using cross-modal learning and ternary attention for accurate PROTAC-induced degradation prediction"],"prefix":"10.1093","volume":"26","author":[{"given":"Lijun","family":"Cai","sequence":"first","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University , Changsha, Hunan 410082 ,","place":["China"]}]},{"given":"Guanyu","family":"Yue","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University , Changsha, Hunan 410082 ,","place":["China"]}]},{"given":"Yifan","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University , Changsha, Hunan 410082 ,","place":["China"]}]},{"given":"Li","family":"Wang","sequence":"additional","affiliation":[{"name":"Degree Programs in Systems and Information Engineering , Graduate School of Science and Technology Doctoral Program in Computer Science, , Tsukuba ,","place":["Japan"]},{"name":"University of Tsukuba , Graduate School of Science and Technology Doctoral Program in Computer Science, , Tsukuba ,","place":["Japan"]}]},{"given":"Xiaojun","family":"Yao","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences , Centre for Artificial Intelligence Driven Drug Discovery, , Macao 999078 ,","place":["China"]},{"name":"Macao Polytechnic University , Centre for Artificial Intelligence Driven Drug Discovery, , Macao 999078 ,","place":["China"]}]},{"given":"Quan","family":"Zou","sequence":"additional","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , Chengdu 610054 ,","place":["China"]}]},{"given":"Xiangzheng","family":"Fu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University , Changsha, Hunan 410082 ,","place":["China"]},{"name":"Research Institute of Hunan University in Chongqing, Chongqing 401120 ,","place":["China"]}]},{"given":"Dongsheng","family":"Cao","sequence":"additional","affiliation":[{"name":"Xiangya School of Pharmaceutical Sciences, Central South University , Changsha, Hunan 410003 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