Development of Ensemble Steric and Electrostatic Chirality (ESEC) descriptors for modelling chromatographic enantioseparations

In this work, chiral molecular descriptors were defined using 2 distinct approaches: (1) scalar triple products of vectorial molecular properties, and (2) descriptors that attempt to quantify the amount of twist in the overall molecular shape. Because both approaches give rise to conformation dependence, descriptor values were averaged over a conformational ensemble obtained by Molecular Dynamics. In addition, a method is introduced that attempts to quantify the asymmetry of the distribution of the descriptor values over the conformational ensemble. The totality of the resulting descriptors were named "Ensemble Steric and Electrostatic Chirality (ESEC) descriptors". A pilot validation study was performed by building Quantitative Structure-Enantioselectivity Relationships (QSER), i.e. mathematical models to predict the chromatographic separation of enantiomers, using a test set of 43 structurally diverse pharmaceuticals analyzed on a polysaccharide-based chiral stationary phase. The best linear regression model (7 descriptors) for the chiral separation (expressed as selectivity factor) featured a low leave-one-out cross validation error (0.0814), a well-predicted elution sequence of the separated enantiomers (21 out of 23 molecules) and a well-predicted αRS for 27 out of 42 molecules. To the best of our knowledge, this is the first time that acceptable linear QSER models were obtained for chiral chromatographic separations of such a chemically diverse set of pharmaceuticals.

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Publication Details

Journal
PLoS ONE
Published
2025-10-17
DOI
https://doi.org/10.1371/journal.pone.0333635
Citations
3
Primary Topic
Analytical Chemistry and Chromatography
Type
article
Field-Weighted Citation Impact
2.27
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article

Development of Ensemble Steric and Electrostatic Chirality (ESEC) descriptors for modelling chromatographic enantioseparations

Kenno Vanommeslaeghe, Debby Mangelings, Jordy Peeters, Pieter De Gauquier et al.
3 citations
PLoS ONE
Analytical Chemistry and Chromatography
2.27
article

Development of Ensemble Steric and Electrostatic Chirality (ESEC) descriptors for modelling chromatographic enantioseparations

Kenno Vanommeslaeghe, Debby Mangelings, Jordy Peeters, Pieter De Gauquier, Yvan Vander Heyden, Fardine Ameli
article en
3 citations

Abstract

In this work, chiral molecular descriptors were defined using 2 distinct approaches: (1) scalar triple products of vectorial molecular properties, and (2) descriptors that attempt to quantify the amount of twist in the overall molecular shape. Because both approaches give rise to conformation dependence, descriptor values were averaged over a conformational ensemble obtained by Molecular Dynamics. In addition, a method is introduced that attempts to quantify the asymmetry of the distribution of the descriptor values over the conformational ensemble. The totality of the resulting descriptors were named "Ensemble Steric and Electrostatic Chirality (ESEC) descriptors". A pilot validation study was performed by building Quantitative Structure-Enantioselectivity Relationships (QSER), i.e. mathematical models to predict the chromatographic separation of enantiomers, using a test set of 43 structurally diverse pharmaceuticals analyzed on a polysaccharide-based chiral stationary phase. The best linear regression model (7 descriptors) for the chiral separation (expressed as selectivity factor) featured a low leave-one-out cross validation error (0.0814), a well-predicted elution sequence of the separated enantiomers (21 out of 23 molecules) and a well-predicted αRS for 27 out of 42 molecules. To the best of our knowledge, this is the first time that acceptable linear QSER models were obtained for chiral chromatographic separations of such a chemically diverse set of pharmaceuticals.

PLoS ONEVol. 20(10)
Vrije Universiteit Brussel (BE)
Openalex Percentile: Top 11%
Analytical Chemistry and Chromatography
2.27
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Development of Ensemble Steric and Electrostatic Chirality (ESEC) descriptors for modelling chromatographic enantioseparations — Kenno Vanommeslaeghe, Debby Mangelings, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS