As yet, the analytical process of chromatographic enantiomer separation has not been modeled using cellular automata (CA). This approach uses mathematical systems that are easily adaptable to different enantiomer analytical binding interactions. A CA model of analyte to cyclodextrin (CD) interaction accurately (R(2)=0.9960) predicts one-to-one molecular binding strengths through correlation with experimental complex stability constants while exhibiting established chromatographic behavior (i.e. retention site dependency and band broadening). The model is expanded to enantiomer HPLC retention interactions with β-CD that accurately predicts one-to-one binding strengths through the development of probabilistic rules and factors from chromatographic results. The proposed model predicts the strength of binding interactions and the degree of chromatographic separation (or lack thereof) of six enantiomer pairs that agree with published potential binding energies of enantiomer-(β-CD) complexes and published experimental HPLC separations.
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