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Bridging chemistry and artificial intelligence by a reaction description language

文献类型：期刊论文

作者Xiong, Jiacheng4,5; Zhang, Wei4,5; Wang, Yinquan3,5; Huang, Jiatao2; Shi, Yuqi4,5; Xu, Mingyan4,5; Li, Manjia5; Fu, Zunyun5; Kong, Xiangtai4,5; Wang, Yitian4,5
刊名NATURE MACHINE INTELLIGENCE
出版日期2025-05-01
卷号7期号:5页码:16
DOI10.1038/s42256-025-01032-8
英文摘要With the fast-paced development of artificial intelligence, large language models are increasingly used to tackle various scientific challenges. A critical step in this process is converting domain-specific data into a sequence of tokens for language modelling. In chemistry, molecules are often represented by molecular linear notations, and chemical reactions are depicted as sequence pairs of reactants and products. However, this approach does not capture atomic and bond changes during reactions. Here, we present ReactSeq, a reaction description language that defines molecular editing operations for step-by-step chemical transformation. Based on ReactSeq, language models for retrosynthesis prediction may consistently excel in all benchmark tests, and demonstrate promising emergent abilities in the human-in-the-loop and explainable artificial intelligence. Moreover, ReactSeq has allowed us to obtain universal and reliable representations of chemical reactions, which enable navigation of the reaction space and aid in the recommendation of experimental procedures and prediction of reaction yields. We foresee that ReactSeq can serve as a bridge to narrow the gap between chemistry and artificial intelligence.
WOS关键词TRANSFORMER ; MODEL
资助项目National Natural Science Foundation of China[T2225002] ; National Natural Science Foundation of China[82273855] ; National Key Research and Development Program of China[2022YFC3400504] ; National Key Research and Development Program of China[2023YFC2305904] ; Strategic Priority Research Program of the Chinese Academy of sciences[XDB0830200] ; Open fund of state key laboratory of Pharmaceutical Biotechnology, Nanjing University, China[KF-202301] ; Shanghai Post-doctoral Excellence Program[2024707]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001494433700004
出版者NATURE PORTFOLIO
源URL[http://119.78.100.183/handle/2S10ELR8/317959]  
专题新药研究国家重点实验室
通讯作者Zheng, Mingyue
作者单位1.ProtonUnfold Technol Co Ltd, Suzhou, Peoples R China
2.ShanghaiTech Univ, Sch Phys Sci & Technol, Shanghai, Peoples R China
3.Fudan Univ, Sch Pharm, Dept Med Chem, Shanghai, Peoples R China
4.Univ Chinese Acad Sci, Beijing, Peoples R China
5.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, State Key Lab Drug Res, Shanghai, Peoples R China
推荐引用方式
GB/T 7714		 Xiong, Jiacheng,Zhang, Wei,Wang, Yinquan,et al. Bridging chemistry and artificial intelligence by a reaction description language[J]. NATURE MACHINE INTELLIGENCE,2025,7(5):16.
APA Xiong, Jiacheng.,Zhang, Wei.,Wang, Yinquan.,Huang, Jiatao.,Shi, Yuqi.,...&Zheng, Mingyue.(2025).Bridging chemistry and artificial intelligence by a reaction description language.NATURE MACHINE INTELLIGENCE,7(5),16.
MLA Xiong, Jiacheng,et al."Bridging chemistry and artificial intelligence by a reaction description language".NATURE MACHINE INTELLIGENCE 7.5(2025):16.

入库方式： OAI收割

来源：上海药物研究所

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