{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T04:14:50Z","timestamp":1777954490023,"version":"3.51.4"},"reference-count":56,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T00:00:00Z","timestamp":1695340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["22077143"],"award-info":[{"award-number":["22077143"]}],"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":["82273856"],"award-info":[{"award-number":["82273856"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Research Project","award":["31511010402"],"award-info":[{"award-number":["31511010402"]}]},{"name":"Research Foundation","award":["XTCX2022JKA01"],"award-info":[{"award-number":["XTCX2022JKA01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>In the process of drug discovery, one of the key problems is how to improve the biological activity and ADMET properties starting from a specific structure, which is also called structural optimization. Based on a starting scaffold, the use of deep generative model to generate molecules with desired drug-like properties will provide a powerful tool to accelerate the structural optimization process. However, the existing generative models remain challenging in extracting molecular features efficiently in 3D space to generate drug-like 3D molecules. Moreover, most of the existing ADMET prediction models made predictions of different properties through a single model, which can result in reduced prediction accuracy on some datasets. To effectively generate molecules from a specific scaffold and provide basis for the structural optimization, the 3D-SMGE (3-Dimensional Scaffold-based Molecular Generation and Evaluation) work consisting of molecular generation and prediction of ADMET properties is presented. For the molecular generation, we proposed 3D-SMG, a novel deep generative model for the end-to-end design of 3D molecules. In the 3D-SMG model, we designed the cross-aggregated continuous-filter convolution (ca-cfconv), which is used to achieve efficient and low-cost 3D spatial feature extraction while ensuring the invariance of atomic space rotation. 3D-SMG was proved to generate valid, unique and novel molecules with high drug-likeness. Besides, the proposed data-adaptive multi-model ADMET prediction method outperformed or maintained the best evaluation metrics on 24 out of 27 ADMET benchmark datasets. 3D-SMGE is anticipated to emerge as a powerful tool for hit-to-lead structural optimizations and accelerate the drug discovery process.<\/jats:p>","DOI":"10.1093\/bib\/bbad327","type":"journal-article","created":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T18:47:06Z","timestamp":1695840426000},"source":"Crossref","is-referenced-by-count":8,"title":["3D-SMGE: a pipeline for scaffold-based molecular generation and evaluation"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7993-9894","authenticated-orcid":false,"given":"Chao","family":"Xu","sequence":"first","affiliation":[{"name":"Key Laboratory of Tropical Biological Resources of Ministry of Education , School of Pharmaceutical Sciences, , Haikou 570228, Hainan , P.R. China"},{"name":"Hainan University , School of Pharmaceutical Sciences, , Haikou 570228, Hainan , P.R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Runduo","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Pharmaceutical Sciences, Sun Yat-Sen University , Guangzhou, 510000, Guangdong , P.R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuheng","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Tropical Biological Resources of Ministry of Education , School of Pharmaceutical Sciences, , Haikou 570228, Hainan , P.R. China"},{"name":"Hainan University , School of Pharmaceutical Sciences, , Haikou 570228, Hainan , P.R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenchao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Pharmaceutical Sciences, Sun Yat-Sen University , Guangzhou, 510000, Guangdong , P.R. 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