Samenvatting

This study aims to develop models to predict the retention, separation and elution sequence of the enantiomers of structurally diverse pharmaceuticals. More specifically, Quantitative Structure Retention Relationships (QSRR) models are built that describe the relationship between molecular descriptors and retention. Eighteen structurally diverse chiral mixtures, each consisting of a pair of enantiomers, were analyzed on two polysaccharide chiral stationary phases, Chiralcel OD-RH (cellulose tris(3,5-dimethylphenylcarbamate)) and Lux amylose-2 (amylose tris(5-chloro-2-methylphenylcarbamate)), applying either a basic or an acidic mobile phase, and their retention factor and elution sequence were determined. Both achiral and, in-house defined, chiral descriptors were used as descriptive variables to build the models. Linear regression techniques, i.e. stepwise multiple linear regression (sMLR) and partial least squares (PLS) regression, were applied to model the retention or separation as a function of the descriptors. In a first step, models were built with only achiral descriptors to model the global retention of both enantiomers of a chiral molecule. Subsequently, models were built with only chiral descriptors to predict the enantioseparation and elution sequence, and finally, models were considered with both descriptor types to predict the retention, the separation and the elution sequence of the enantiomers. The global retention was predicted well by the sMLR models with only achiral descriptors. The models with only chiral descriptors were not found suitable to predict the enantioseparation and elution sequence. Finally, the models containing both chiral and achiral descriptors allowed predicting the retention well, but their ability to predict the elution sequence and separation of the enantiomers differed widely for the chromatographic systems considered.
Originele taal-2English
Artikelnummer124497
TijdschriftTalanta
Volume259
Vroegere onlinedatum6 apr 2023
DOI's
StatusPublished - 1 jul 2023

Bibliografische nota

Funding Information:
This work was supported by the Research Foundation Flanders (FWO) [grant number 1530518 N and project number G015022 N ]. The supercomputing resources and services used in this work were provided by the VUB and the VSC (Flemish Supercomputer Center), the latter being funded by the FWO and the Flemish Government . The authors thank I. De Greef and S. Saric for technical assistance.

Publisher Copyright:
© 2023 Elsevier B.V.

Copyright:
Copyright 2023 Elsevier B.V., All rights reserved.

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