高通量实验和机器学习促进了ru催化亚砜基醚的P(O)O- h插入反应合成α-磷酸氧基酮

IF 9.7 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
An Lin, Jingyuan Liu, Yougen Xu, Haiting Wu, Yating Chen, Yan Zhang, Lebin Su, Xiaodan Zhao, Kuangbiao Liao
{"title":"高通量实验和机器学习促进了ru催化亚砜基醚的P(O)O- h插入反应合成α-磷酸氧基酮","authors":"An Lin,&nbsp;Jingyuan Liu,&nbsp;Yougen Xu,&nbsp;Haiting Wu,&nbsp;Yating Chen,&nbsp;Yan Zhang,&nbsp;Lebin Su,&nbsp;Xiaodan Zhao,&nbsp;Kuangbiao Liao","doi":"10.1007/s11426-024-2313-5","DOIUrl":null,"url":null,"abstract":"<div><p>Herein, we report a novel and highly efficient method for the synthesis of α-phosphoryloxy carbonyl compounds via Ru-catalyzed 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 various α-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.</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":772,"journal":{"name":"Science China Chemistry","volume":"68 2","pages":"679 - 686"},"PeriodicalIF":9.7000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-throughput experimentation and machine learning-promoted synthesis of α-phosphoryloxy ketones via Ru-catalyzed P(O)O-H insertion reactions of sulfoxonium ylides\",\"authors\":\"An Lin,&nbsp;Jingyuan Liu,&nbsp;Yougen Xu,&nbsp;Haiting Wu,&nbsp;Yating Chen,&nbsp;Yan Zhang,&nbsp;Lebin Su,&nbsp;Xiaodan Zhao,&nbsp;Kuangbiao Liao\",\"doi\":\"10.1007/s11426-024-2313-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Herein, we report a novel and highly efficient method for the synthesis of α-phosphoryloxy carbonyl compounds via Ru-catalyzed 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 various α-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.</p><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>\",\"PeriodicalId\":772,\"journal\":{\"name\":\"Science China Chemistry\",\"volume\":\"68 2\",\"pages\":\"679 - 686\"},\"PeriodicalIF\":9.7000,\"publicationDate\":\"2024-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science China Chemistry\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11426-024-2313-5\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science China Chemistry","FirstCategoryId":"1","ListUrlMain":"https://link.springer.com/article/10.1007/s11426-024-2313-5","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

在此,我们报道了一种新的、高效的方法,在高通量实验(HTE)和机器学习(ML)的帮助下,通过ru催化的亚砜酰亚砜和膦酸的P(O)O- h插入反应合成α-磷酸氧基羰基化合物。多种P(O)O- h衍生物,包括二芳基磷酸盐、烷基磷酸盐和烷氧磷酸盐,都可以在转化过程中与亚砜酰化物反应,并直接构建各种α-磷酸氧基羰基和磷酸丙烯。该方法利用易得的亚砜基吡啶作为羰基前体,具有条件温和、操作简单、官能团耐受性广等特点,可用于结构复杂的生物活性分子的后期功能化。此外,还对反应空间进行了有益的探索(756个反应),并开发和应用了用于反应产率预测的机器学习模型,展示了这种新工作流程(te - ml)在合成化学领域的实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-throughput experimentation and machine learning-promoted synthesis of α-phosphoryloxy ketones via Ru-catalyzed P(O)O-H insertion reactions of sulfoxonium ylides

Herein, we report a novel and highly efficient method for the synthesis of α-phosphoryloxy carbonyl compounds via Ru-catalyzed 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 various α-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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Science China Chemistry
Science China Chemistry CHEMISTRY, MULTIDISCIPLINARY-
CiteScore
14.40
自引率
7.30%
发文量
3787
审稿时长
2.2 months
期刊介绍: Science China Chemistry, co-sponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China and published by Science China Press, publishes high-quality original research in both basic and applied chemistry. Indexed by Science Citation Index, it is a premier academic journal in the field. Categories of articles include: Highlights. Brief summaries and scholarly comments on recent research achievements in any field of chemistry. Perspectives. Concise reports on thelatest chemistry trends of interest to scientists worldwide, including discussions of research breakthroughs and interpretations of important science and funding policies. Reviews. In-depth summaries of representative results and achievements of the past 5–10 years in selected topics based on or closely related to the research expertise of the authors, providing a thorough assessment of the significance, current status, and future research directions of the field.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书