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Updated: Aug 18, 2025

Synthesis and Purification of Iodoaziridines Involving Quantitative Selection of the Optimal Stationary Phase for Chromatography
Published on: May 16, 2014
High-Level Data Fusion Enables the Chemoinformatically Guided Discovery of Chiral Disulfonimide Catalysts for
Brennan T Rose1, Jacob C Timmerman2, Seth A Bawel1
1Department of Chemistry, University of Illinois at Urbana-Champaign, 600 South Mathews Avenue, Urbana, IIllinois 61801, United States.
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.
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