Abstract
The atropselective iodination of 2-amino-6-arylpyridines catalyzed by chiral disulfonimides (DSIs) is described. Key to the development of this transformation was the use of a chemoinformatically guided workflow for the curation of a structurally diverse training set of DSI catalysts. Utilization of this catalyst training set in the atropselective iodination across a variety 2-aminopyridine substrates allowed for the recommendation of statistically higher-performing DSIs for this reaction. Data Fusion techniques were implemented to successfully predict the performance of catalysts when classical linear regression analysis failed to provide suitable models. This effort identified a privileged class of 3,3′-alkynyl-DSI catalysts which were effective in catalyzing the iodination of a variety of 2-amino-6-arylpyridines with high stereoselectivity and generality. Subsequent preparative-scale demonstrations highlighted the utility of this reaction by providing iodinated pyridines >90:10 er and in good chemical yield.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 22950-22964 |
| Number of pages | 15 |
| Journal | Journal of the American Chemical Society |
| Volume | 144 |
| Issue number | 50 |
| Early online date | Dec 7 2022 |
| DOIs | |
| State | Published - Dec 21 2022 |
ASJC Scopus subject areas
- General Chemistry
- Biochemistry
- Catalysis
- Colloid and Surface Chemistry
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