{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T17:49:09Z","timestamp":1781632149533,"version":"3.54.5"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T00:00:00Z","timestamp":1684195200000},"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":["82073692"],"award-info":[{"award-number":["82073692"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"CAMS Innovation Fund for Medical Sciences","award":["2021-I2M-1-028"],"award-info":[{"award-number":["2021-I2M-1-028"]}]},{"name":"Disciplines Construction Project","award":["201920200802"],"award-info":[{"award-number":["201920200802"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The rational design of chemical entities with desired properties for a specific target is a long-standing challenge in drug design. Generative neural networks have emerged as a powerful approach to sample novel molecules with specific properties, termed as inverse drug design. However, generating molecules with biological activity against certain targets and predefined drug properties still remains challenging. Here, we propose a conditional molecular generation net (CMGN), the backbone of which is a bidirectional and autoregressive transformer. CMGN applies large-scale pretraining for molecular understanding and navigates the chemical space for specified targets by fine-tuning with corresponding datasets. Additionally, fragments and properties were trained to recover molecules to learn the structure\u2013properties relationships. Our model crisscrosses the chemical space for specific targets and properties that control fragment-growth processes. Case studies demonstrated the advantages and utility of our model in fragment-to-lead processes and multi-objective lead optimization. The results presented in this paper illustrate that CMGN has the potential to accelerate the drug discovery process.<\/jats:p>","DOI":"10.1093\/bib\/bbad185","type":"journal-article","created":{"date-parts":[[2023,5,17]],"date-time":"2023-05-17T02:54:40Z","timestamp":1684292080000},"source":"Crossref","is-referenced-by-count":21,"title":["CMGN: a conditional molecular generation net to design target-specific molecules with desired properties"],"prefix":"10.1093","volume":"24","author":[{"given":"Minjian","family":"Yang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Department of Medicinal Chemistry, Beijing Key Laboratory of Active Substances Discovery and Druggability Evaluation, Institute of Materia Medica, Peking Union Medical College and Chinese Academy of Medical Sciences , Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanyu","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Institute of Materia Medica, Peking Union Medical College and Chinese Academy of Medical Sciences , Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xue","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Institute of Materia Medica, Peking Union Medical College and Chinese Academy of Medical Sciences , Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Xue","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Institute of Materia Medica, Peking Union Medical College and Chinese Academy of Medical Sciences , Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yafeng","family":"Deng","sequence":"additional","affiliation":[{"name":"CarbonSilicon AI Technology Co., Ltd. , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojian","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Department of Medicinal Chemistry, Beijing Key Laboratory of Active Substances Discovery and Druggability Evaluation, Institute of Materia Medica, Peking Union Medical College and Chinese Academy of Medical Sciences , Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,5,16]]},"reference":[{"issue":"12","key":"2023072020023279800_ref1","doi-asserted-by":"crossref","first-page":"103366","DOI":"10.1016\/j.drudis.2022.103366","article-title":"Trends in small molecule drug properties: a developability 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