Exploring enantioselective molecular recognition mechanisms with chemoinformatic techniques

Abstract

A comprehensive review of chemoinformatic techniques and studies applied to the field of enantioselective molecular recognition is presented. Several approaches such as enantiophores/pharmacophore modelling, QSPRs, CoMFA and other insightful data mining procedures are discussed. The review focuses on the central role of chemoinformatic approaches on the establishment of connections between available experimental data, mainly HPLC separation data, and these algorithms that describe properties of chiral molecules. The general overview of the aforementioned calculations account for a use of these techniques as a valuable strategy to achieve reliable prediction systems, infer the mechanisms of chiral recognition, generate insight for the conception of new chiral receptors and corroborate and assist experimental techniques such as chiral LC. Moreover, it is pointed out that computer methods in this field promise a wide range of applications for both academia and industry, ranging from enantioselective reactions, drug discovery and analysis of high-throughput screenings, to analytical and semi-preparative separations or large-scale production of enantiopure compounds.