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通过数据科学探究超分子催化氮杂芳烃的级联还原反应

Supramolecular Catalyzed Cascade Reduction of Azaarenes Interrogated via Data Science.

作者信息

Treacy Sean M, Smith Andrew L, Bergman Robert G, Raymond Kenneth N, Toste F Dean

机构信息

Department of Chemistry, University of California, Berkeley, California 94720, United States.

Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.

出版信息

J Am Chem Soc. 2024 Oct 30;146(43):29792-29800. doi: 10.1021/jacs.4c11482. Epub 2024 Oct 21.

Abstract

Catalysis of multicomponent transformations requires controlled assembly of reactants within the active site. Supramolecular scaffolds possess synthetic microenvironments that enable precise modulation over noncovalent interactions (NCIs) engaged by reactive, encapsulated species. While molecular properties that describe the behavior of single guests in host cavities have been studied extensively, multicomponent transformations remain challenging to design and deploy. Here, simple univariate regression and threshold analyses are employed to model reactivity in a cascade reduction of azaarenes catalyzed by water-soluble metal organic cages. Yield and stereoselectivity models help deduce unknown mechanisms of reactivity by the multicomponent, host-guest complexes. Furthermore, a comprehensive model is established for NCIs driving stereoselectivity in the reported host-guest adducts.

摘要

多组分转化的催化作用需要在活性位点内对反应物进行可控组装。超分子支架具有合成微环境,能够对反应性封装物种参与的非共价相互作用(NCI)进行精确调控。虽然描述单个客体在主体空腔中行为的分子性质已得到广泛研究,但多组分转化的设计和应用仍然具有挑战性。在这里,简单的单变量回归和阈值分析被用于模拟由水溶性金属有机笼催化的氮杂芳烃级联还原反应中的反应活性。产率和立体选择性模型有助于推断多组分主客体配合物未知的反应活性机制。此外,还为报道的主客体加合物中驱动立体选择性的非共价相互作用建立了一个综合模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63a0/11528432/44cd463fa455/ja4c11482_0001.jpg

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