Data Science-Enabled Palladium-Catalyzed Enantioselective Aryl-Carbonylation of Sulfonimidamides

New methods for the general asymmetric synthesis of sulfonimidamides
are of great interest due to their applications in medicinal chemistry,
agrochemical discovery, and academic research. We report a palladium-catalyzed
cross-coupling method for the enantioselective aryl-carbonylation
of sulfonimidamides. Using data science techniques, a virtual library
of calculated bisphosphine ligand descriptors was used to guide reaction
optimization by effectively sampling the catalyst chemical space.
The optimized conditions identified using this approach provided the
desired product in excellent yield and enantioselectivity. As the
next step, a data science-driven strategy was also used to explore
a diverse set of aryl and heteroaryl iodides, providing key information
about the scope and limitations of the method. Furthermore, we tested
a range of racemic sulfonimidamides for compatibility of this coupling
partner. The developed method offers a general and efficient strategy
for accessing enantioenriched sulfonimidamides, which should facilitate
their application in industrial and academic settings.