AbstractDescription of molecular stereostructure is critical for the machine learning prediction of asymmetric catalysis. Herein we report a spherical projection descriptor of molecular stereostructure (SPMS), which allows precise representation of the molecular van der Waals (vdW) surface. The key features of SPMS descriptor are presented using the examples of chiral phosphoric acid, and the machine learning application is demonstrated in Denmark’s dataset of asymmetric thiol addition to N-acylimines. In addition, SPMS descriptor also offers a color-coded diagram that provides straightforward chemical interpretation of the steric environment.
Enantiopure α-hydroxy carbonyl compounds are common scaffolds in natural products and pharmaceuticals. Although indirect approaches towards their synthesis are known, direct asymmetric methodologies are scarce. Herein, we report the first direct asymmetric α-hydroxylation of α-branched ketones through enol catalysis, enabling a facile access to valuable α-keto tertiary alcohols. The transformation, characterized by the use of nitrosobenzene as the oxidant and a new chiral phosphoric acid as the catalyst, delivers a good scope and excellent enantioselectivities.
A Molecular Stereostructure Descriptor Based On Spherical Projection
