https://www.cas.cn/cm/202505/t20250519_5068899.shtml

https://www.nature.com/articles/s42256-025-01032-8

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. Researchers at the CAS Shanghai Institute of Materia Medica have developed 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 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. ReactSeq might serve as a bridge to narrow the gap between chemistry and artificial intelligence.