{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T08:37:53Z","timestamp":1778575073205,"version":"3.51.4"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T00:00:00Z","timestamp":1745193600000},"content-version":"vor","delay-in-days":51,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2020A1515010548"],"award-info":[{"award-number":["2020A1515010548"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2023B1515020042"],"award-info":[{"award-number":["2023B1515020042"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81973241"],"award-info":[{"award-number":["81973241"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The recent progress of deep generative models in modeling complex real-world data distributions has enabled the generation of novel compounds with potential therapeutic applications for various diseases. However, most studies fail to optimize the properties of generated molecules from the perspective of the intrinsic nature of chemical reactions. In this work, we propose a novel molecule generation model to overcome the limitation by deep reinforcement learning, in which an agent learns to optimize the properties of molecules initialized with a chemically inspired contrastive pretrained model. We finally assess the generation model by evaluating its ability to generate inhibitors against two prominent therapeutic targets in cancer treatment. Experimental results show that our model could generate 100% valid and novel structures and also exhibits superior performance in generating molecules with fewer structural alerts against several baselines. More importantly, the molecules generated by our proposed model show potent biological activities against ataxia telangiectasia and Rad3-related (ATR) and cyclin-dependent kinase 9 (CDK9) targets in wet-lab experiments.<\/jats:p>","DOI":"10.1093\/bib\/bbaf185","type":"journal-article","created":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T03:57:20Z","timestamp":1745207840000},"source":"Crossref","is-referenced-by-count":2,"title":["Self-awareness of retrosynthesis via chemically inspired contrastive learning for reinforced molecule generation"],"prefix":"10.1093","volume":"26","author":[{"given":"Yi","family":"Zhang","sequence":"first","affiliation":[{"name":"Guangdong Provincial Key Laboratory of Fermentation and Enzyme Engineering, Joint International Research Laboratory of Synthetic Biology and Medicine, Guangdong Provincial Engineering and Technology Research Center of Biopharmaceuticals, School of Biology and Biological Engineering, South China University of Technology , No. 382 Waihuan East Road, Higher Education Mega Center, Guangzhou 510006 ,","place":["China"]}]},{"given":"Jindi","family":"Huang","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Laboratory of Fermentation and Enzyme Engineering, Joint International Research Laboratory of Synthetic Biology and Medicine, Guangdong Provincial Engineering and Technology Research Center of Biopharmaceuticals, School of Biology and Biological Engineering, South China University of Technology , No. 382 Waihuan East Road, Higher Education Mega Center, Guangzhou 510006 ,","place":["China"]}]},{"given":"Xinze","family":"Li","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Laboratory of Fermentation and Enzyme Engineering, Joint International Research Laboratory of Synthetic Biology and Medicine, Guangdong Provincial Engineering and Technology Research Center of Biopharmaceuticals, School of Biology and Biological Engineering, South China University of Technology , No. 382 Waihuan East Road, Higher Education Mega Center, Guangzhou 510006 ,","place":["China"]}]},{"given":"Wenqi","family":"Sun","sequence":"additional","affiliation":[{"name":"Guizhou Provincial Engineering Technology Research Center for Chemical Drug R&D, College of Pharmacy, Guizhou Medical University , No. 6 Ankang Avenue, Guian New District, Guiyang 561113 ,","place":["China"]}]},{"given":"Nana","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guizhou Provincial Engineering Technology Research Center for Chemical Drug R&D, College of Pharmacy, Guizhou Medical University , No. 6 Ankang Avenue, Guian New District, Guiyang 561113 ,","place":["China"]}]},{"given":"Jiquan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guizhou Provincial Engineering Technology Research Center for Chemical Drug R&D, College of Pharmacy, Guizhou Medical University , No. 6 Ankang Avenue, Guian New District, Guiyang 561113 ,","place":["China"]}]},{"given":"Tiegen","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences , Zhongshan Life Science Park, No. 10 Heqing Road, Tsui Hang New District, Zhongshan 528400 ,","place":["China"]}]},{"given":"Ling","family":"Wang","sequence":"additional","affiliation":[{"name":"Guangdong Provincial Key Laboratory of Fermentation and Enzyme Engineering, Joint International Research Laboratory of Synthetic Biology and Medicine, Guangdong Provincial Engineering and Technology Research Center of Biopharmaceuticals, School of Biology and Biological Engineering, South China University of Technology , No. 382 Waihuan East Road, Higher Education Mega Center, Guangzhou 510006 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