A Conformer‐Dependent, Quantitative Quadrant Model

Abstract

This study reports the development and application of a conformer‐dependent quantitative quadrant descriptor for generating models that relate catalyst performance to catalyst structure in enantioselective transformations. The generality of these descriptors is demonstrated by using them for three different reactions: (1) copper‐catalyzed, enantioselective cyclopropanation of alkenes, (2) rhodium‐catalyzed enantioselective hydrogenation of α‐substituted N‐acyl‐enamides, and (3) enantioselective addition of thiols to N‐acyl imines. This work will provide researchers an interpretable steric descriptor that merges the heuristic value of quadrant models with a quantitative tool that can be used to create statistically meaningful correlations between the steric occupancy of catalyst quadrants and stereoselectivity. The low dimensionality of this descriptor, its ability to capture conformational effects and stereostructure, and its direct relationship to intuitive structural properties make it particularly well‐suited for creating Quantitative Structure‐Selectivity Relationships (QSSR) with smaller datasets of asymmetric reactions.

Selection of Low-Dimensional 3-D Geometric Descriptors for Accurate Enantioselectivity Prediction

“…Octant models (or quadrants of a half-sphere) have been also used recently by the Denmark group in the analysis of asymmetric cyclopropanation, hydrogenation, and thiol addition . Differently, some of us very recently showed that quadrants of the full sphere can also be used for quantitative prediction of isotactic polypropylene (iPP) enantioselectivity ( R 2 between experimental and fitted data 0.92) of rigid C 2 -symmetric indenyl-based ansa -zirconocenes ,,, , even allowing moderate extrapolation .…”

Prediction of enantioselectivity in thiol addition to imines catalyzed by chiral phosphoric acids

“…The descriptors used include conformer-dependent quantitative quadrant descriptors, [12] Sterimol parameters, [13,14] IR vibration, [13] NBO charges, [13,14] Balaban-type index, [14] average steric occupancy descriptors, [15] and conformer-dependent descriptors. [3] These models dealt with 30, [12] 38, [13] 367, [14] and 1075 [3,15] enantioselectivities ΔΔG in Minisci reactions of diazines, [13] nucleophilic addition reactions to imines, [14] and thiols addition to imines. [3,12,15] Most of the QSSR models stated above were based on small data set, and only the linear regression technique was adopted to develop models.…”

“…Recently, some researchers focused on QSSR models for enantioselectivities ΔΔG in asymmetric reactions with chiral phosphoric acids as catalysts. The descriptors used include conformer-dependent quantitative quadrant descriptors, [12] Sterimol parameters, [13,14] IR vibration, [13] NBO charges, [13,14] Balaban-type index, [14] average steric occupancy descriptors, [15] and conformer-dependent descriptors. [3] These models dealt with 30, [12] 38, [13] 367, [14] and 1075 [3,15] enantioselectivities ΔΔG in Minisci reactions of diazines, [13] nucleophilic addition reactions to imines, [14] and thiols addition to imines.…”

“…[3] These models dealt with 30, [12] 38, [13] 367, [14] and 1075 [3,15] enantioselectivities ΔΔG in Minisci reactions of diazines, [13] nucleophilic addition reactions to imines, [14] and thiols addition to imines. [3,12,15] Most of the QSSR models stated above were based on small data set, and only the linear regression technique was adopted to develop models. Although a few QSSRs mentioned have been evaluated with the internal crossvalidation or external test set, strict multiple validation metrics should be carried out to obtain more information about prediction quality of QSSR models.…”

“…[ 3 ] These models dealt with 30, [ 12 ] 38, [ 13 ] 367, [ 14 ] and 1075 [ 3,15 ] enantioselectivities ΔΔG in Minisci reactions of diazines, [ 13 ] nucleophilic addition reactions to imines, [ 14 ] and thiols addition to imines. [ 3,12,15 ]…”