Abstract
Developing green liquid chromatography (LC) methods is currently a cutting-edge field due to the recognized negative influence of toxic organic solvents on human health and nature. One of the available strategies for “greening” is the addition of cyclodextrin (CD) in the mobile phase. CDs are known for their ability to form inclusion complexes with various analytes, improving their solubility in the aqueous phase, thus reducing the retention times and, simultaneously, the organic solvent consumption. The presented concept could be extended to incorporate sustainability in the field of separation science, from the stage of method development to routine analysis, through the quantitative structure retention relationship (QSRR) modeling approach. This book chapter is aimed at presenting the possibilities of building and employing QSRR models in CD-modified high-performance liquid chromatography (HPLC), followed by investigating their potential utility in different areas of application. The complexity of CD-modified HPLC indicates the associated complexity of the QSRR modeling. This review provides an overview of CD structures and analytical techniques applied for characterization of the formed inclusion complexes. Special focus is placed on the practical and theoretical knowledge regarding the retention mechanisms and equilibria existing in CD-modified HPLC systems as an introduction to retention modeling. Molecular descriptors mostly applicable in modeling retention in HPLC, as well as complex association constants that can properly describe the formed inclusion complexes in CD-modified HPLC, are also presented. Further, machine learning techniques are discussed in terms of their utility and contribution in building good predictive QSRR models. Finally, the key experimental findings about the utility of the obtained QSRR models in retention prediction and evaluation of optimal conditions of the chromatographic method, and then thermodynamic parameters of complexation are presented, followed by theoretical discussion of possible benefits, drawbacks, and future perspectives of the introduced approach.
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