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作 者:An Lin Jingyuan Liu Yougen Xu Haiting Wu Yating Chen Yan Zhang Lebin Su Xiaodan Zhao Kuangbiao Liao
机构地区:[1]Institute of Organic Chemistry&MOE Key Laboratory of Bioinorganic and Synthetic Chemistry,School of Chemistry,Sun Yat-sen University,Guangzhou 510006,China [2]Guangzhou National Laboratory,Guangzhou 510005,China [3]Bioland Laboratory,Guangzhou 510005,China
出 处:《Science China Chemistry》2025年第2期679-686,共8页中国科学(化学英文版)
基 金:supported by the National Natural Science Foundation of China(22372044,22393892,22002169,22071249);the Guangdong Basic and Applied Basic Research Foundation(2024A1515012583,2019A1515111111);the Major Program of Guangzhou National Laboratory(GZNL2023A02012)。
摘 要:Herein,we report a novel and highly efficient method for the synthesis ofα-phosphoryloxy carbonyl compounds via Rucatalyzed P(O)O–H insertion reactions of sulfoxonium ylides and phosphinic acids,with the assistance of high-throughput experimentation(HTE)and machine learning(ML).A variety of P(O)O−H derivatives,including diarylphosphates,alkyl phosphates,and alkoxyphosphates,are competent candidates to react with sulfoxonium ylides in this transformation,and variousα-phosphoryloxy carbonyls and propylene phosphates are directly constructed.This approach utilizes readily available sulfoxonium ylide as a carbene precursor,and features mild conditions,operational simplicity,and broad functional groups tolerance,and could be used for late-stage functionalization of structurally complex bioactive molecules.Moreover,a conducive exploration of the reaction space is also conducted(756 reactions)and a machine learning model for reaction yield prediction has been developed and applied,showcasing the practical application of this newly workflow(HTE-ML)in the field of synthetic chemistry.
关 键 词:α-phosphoryloxy ketones high-throughput experimentation machine learning P(O)O-H insertion sulfoxonium ylides
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