Structure–Selectivity Relationship Study of IDPi Using Fragment and Remote Site Descriptors

Y Yu Zhou R Roberta Properzi (Max‐Planck‐Institut Für Kohlenforschung Mülheim an der Ruhr Germany) X Xiaozhou Wang T Ting Wang (Department of Radiation Oncology The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital Zhengzhou China) X Xingyu Wang (Eastern Institute for Advanced Study, Ningbo Key Laboratory of All-Solid-State Battery, Zhejiang Key Laboratory of All-Solid-State Battery) H Hui Zhou (Department of Chemistry and Materials) B Benjamin List G Gui‐Juan Cheng (Warshel Institute for Computational Biology School of Medicine The Chinese University of Hong Kong Shenzhen Guangdong P. R. China)

Abstract

ABSTRACT Imidodiphosphorimidate (IDPi) has emerged as a powerful chiral organocatalyst featuring a specially designed cavity constructed by aryl group‐substituted BINOL units. Despite extensive applications of IDPi in asymmetric reactions, the understanding of its structure–selectivity relationship (SSR) remains underdeveloped. In this study, we employed aryl fragment descriptors for the statistical modeling of IDPi‐catalyzed asymmetric reactions, offering a cost‐effective and efficient approach to explore the SSR of IDPi. Specifically, site parameters of remote sp 2 carbon atoms were defined to capture the features of the distal ring of the aryl substituents. The established statistical models of IDPi‐catalyzed cyanosilylation reactions align well with the mechanistic understandings of the crucial role of C‐H···π and cation‐π interactions between the distal ring of IDPi and substrate in stereo‐control. More selective catalysts for the challenging cyanosilylation reaction of 3‐hexanone were successfully identified by using these descriptors to define and screen the chemical space of IDPi catalysts. This work not only enriches our understanding of the SSR of IDPi catalysts but also highlights the potential application of aryl fragment and remote site parameters as universal descriptors for IDPi in statistical modeling.

Article Details

Volume / Issue Vol. 65, Issue 27
Published July 01, 2026
ISSN 1433-7851
Publisher Wiley

Journal Info

Angewandte Chemie International Edition

Wiley

ISSN: 1433-7851 Physical Sciences

Authors (8)

Y

Yu Zhou

R

Roberta Properzi

Max‐Planck‐Institut Für Kohlenforschung Mülheim an der Ruhr Germany

X

Xiaozhou Wang

T

Ting Wang

Department of Radiation Oncology The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital Zhengzhou China

X

Xingyu Wang

Eastern Institute for Advanced Study, Ningbo Key Laboratory of All-Solid-State Battery, Zhejiang Key Laboratory of All-Solid-State Battery

H

Hui Zhou

Department of Chemistry and Materials

B

Benjamin List

G

Gui‐Juan Cheng

Warshel Institute for Computational Biology School of Medicine The Chinese University of Hong Kong Shenzhen Guangdong P. R. China