Mining Chromatographic Enantioseparation Data Using Matched Molecular Pair Analysis

Robert Sheridan (1) , Patrick Piras (2) , Edward Sherer (1) , Christian Roussel (2) , William Pirkle (3) , Christopher Welch (4)

1 Department of Structural Chemistry
2 ISM2 - Institut des Sciences Moléculaires de Marseille
3 Department of Chemistry
4 Department of Process Research & Development

We apply matched molecular pair (MMP) analysis to data from ChirBase, which contains literature reports of chromatographic enantioseparations. For the 19 chiral stationary phases we examined, we were able to identify 289 sets of pairs where there is a statistically significant and consistent difference in enantioseparation due to a small chemical change. In many cases these changes highlight enantioselectivity differences between pairs or small families of closely related molecules that have for many years been used to probe the mechanisms of chromatographic chiral recognition; for example, the comparison of N-H vs. N-Me analytes to determine the criticality of an N-H hydrogen bond in chiral molecular recognition. In other cases, statistically significant MMPs surfaced by the analysis are less familiar or somewhat puzzling, sparking a need to generate and test hypotheses to more fully understand. Consequently, mining of appropriate datasets using MMP analysis provides an important new approach for studying and understanding the process of chromatographic enantioseparation.

Domaines: Chimie

Robert Sheridan, Patrick Piras, Edward Sherer, Christian Roussel, William Pirkle, et al.. Mining Chromatographic Enantioseparation Data Using Matched Molecular Pair Analysis. Molecules, 2016, 21 (10), ⟨10.3390/molecules21101297⟩. ⟨hal-01442568⟩