Descriptor-Based Regression Analysis Enables the Discovery of Highly Selective Ligands for Palladium-Catalyzed Siloxycyclopropanation
- 1Department of Applied Chemistry, Graduate School of Engineering
- 2University of Osaka
- 3Computational Biotechnology, RWTH Aachen University, Worringerweg 3, Aachen, Germany, 70574
Abstract
A palladium-catalyzed siloxycyclopropanation of alkenes using acylsilanes as carbene precursors provides a distinctive catalytic approach to structurally diverse cyclopropanes through a siloxycarbene–palladium intermediate. Although the reaction scope and major mechanistic features have been established, the origin of its ligand-dependent diastereoselectivity has remained unclear, limiting the rational development of more selective catalysts. Here, we combine density functional theory (DFT) calculations, molecular parameterization, and statistical modeling to elucidate the steric and electronic factors governing the stereochemical outcome. DFT calculations of a series of NHC ligands and their corresponding siloxycarbene–palladium complexes provided a diverse set of molecular descriptors, which were used to construct a multivariate linear regression (MLR) model against experimental activation energies. The refined model identified complementary descriptors reflecting ligand steric demand, directional steric effects, and metal–ligand electronic interactions as key factors associated with the observed selectivity. MLR-guided virtual screening of 21 NHC ligands identified L24 and L30 as promising candidates for enhanced syn- and anti-selectivity, respectively, and their predicted selectivities were experimentally validated. The newly identified ligands not only improved the selectivity in their respective directions but also enabled a pronounced switch between syn- and anti-selectivity relative to the previously optimized ligand. Furthermore, L24 and L30 exhibited 2 complementary stereocontrol across a range of acylsilanes and alkenes beyond the benchmark reaction. Mechanistic analysis of the corresponding transition states revealed the roles of anisotropic steric environments and ligand-specific electronic interactions in determining the distinct stereochemical preferences of L24 and L30. These findings provide a mechanistic basis for ligand-controlled stereoselectivity in siloxycarbene–palladium cyclopropanation and establish molecular-level ligand features as useful parameters for improving and redirecting stereochemical
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BibTeX
@misc{rawat2026descriptorbased,
title = {{Descriptor-Based Regression Analysis Enables the Discovery of Highly Selective Ligands for Palladium-Catalyzed Siloxycyclopropanation}},
author = {Vishal Kumar Rawat and Ryoichi Tabata and Tetsuya Inagaki and Yuki Akita and Reiko Hirosawa and Maria Fyta and Mamoru Tobisu},
howpublished = {ChemRxiv},
year = {2026},
month = oct,
doi = {10.26434/chemrxiv.15010294/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010294/v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Descriptor-Based Regression Analysis Enables the Discovery of Highly Selective Ligands for Palladium-Catalyzed Siloxycyclopropanation
AU - Vishal Kumar Rawat
AU - Ryoichi Tabata
AU - Tetsuya Inagaki
AU - Yuki Akita
AU - Reiko Hirosawa
AU - Maria Fyta
AU - Mamoru Tobisu
PY - 2026
DA - 2026/10/12
PB - ChemRxiv
DO - 10.26434/chemrxiv.15010294/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010294/v1
AB - A palladium-catalyzed siloxycyclopropanation of alkenes using acylsilanes as carbene precursors provides a distinctive catalytic approach to structurally diverse cyclopropanes through a siloxycarbene–palladium intermediate. Although the reaction scope and major mechanistic features have been established, the origin of its ligand-dependent diastereoselectivity has remained unclear, limiting the rational development of more selective catalysts. Here, we combine density functional theory (DFT) calculations, molecular parameterization, and statistical modeling to elucidate the steric and electronic factors governing the stereochemical outcome. DFT calculations of a series of NHC ligands and their corresponding siloxycarbene–palladium complexes provided a diverse set of molecular descriptors, which were used to construct a multivariate linear regression (MLR) model against experimental activation energies. The refined model identified complementary descriptors reflecting ligand steric demand, directional steric effects, and metal–ligand electronic interactions as key factors associated with the observed selectivity. MLR-guided virtual screening of 21 NHC ligands identified L24 and L30 as promising candidates for enhanced syn- and anti-selectivity, respectively, and their predicted selectivities were experimentally validated. The newly identified ligands not only improved the selectivity in their respective directions but also enabled a pronounced switch between syn- and anti-selectivity relative to the previously optimized ligand. Furthermore, L24 and L30 exhibited 2 complementary stereocontrol across a range of acylsilanes and alkenes beyond the benchmark reaction. Mechanistic analysis of the corresponding transition states revealed the roles of anisotropic steric environments and ligand-specific electronic interactions in determining the distinct stereochemical preferences of L24 and L30. These findings provide a mechanistic basis for ligand-controlled stereoselectivity in siloxycarbene–palladium cyclopropanation and establish molecular-level ligand features as useful parameters for improving and redirecting stereochemical
ER -