Concise Total Synthesis of (+)-Shearilicine: A Machine Learning-Assisted Strategy for Ligand Optimization of an Enantioselective Palladium-Catalyzed α-Arylation
Abstract
Herein, we report the short enantioselective total synthesis of (+)-shearilicine, facilitated by a machine learning-empowered design of novel ligands for Pd-catalyzed α-arylation. The enantioselectivity resulting from the arylation of a highly functionalized cyclohexanone with a carbazole was predicted using a support vector regression (SVR) model. More than 120 BI-DIME-type ligands were virtually screened to identify promising candidates for experimental validation, yielding a great improvement in the enantioselectivity of this problematic arylation. Additional notable features of the synthesis include a mild silane-directed intramolecular allylative cyclization to build the final six-membered carbon framework and a singlet oxygen-mediated Achmatowicz-Ali rearrangement to construct the 6,8-dioxabicyclo[3.2.1]octane ring system.
Fields of Study & Subjects
Organoboron and organosilicon chemistry
Catalytic C–H Functionalization Methods
Machine Learning in Materials Science
Publication details
- Journal / source
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Volume
- 148
- Issue
- 23
- Pages
- 23585–23596
- Publication date
- 2 June 2026
- Language
- EN