Title: Integrated Acquisition of Analytical and Biopharmaceutical Screening Data for beta-Adrenergic-Drugs Employing Diversified Macrocycle Supported Potentiometric Detection in HPLC Systems
Volume: 9
Issue: 16
Author(s): Grzegorz Bazylak and Luc J. Nagels
Affiliation:
Keywords:
integrated acquisition, biopharmaceutical screening, therapeutic intervention, pca of potentiometric data
Abstract: Potentiometric detection with poly(vinyl chloride) (PVC) based liquid membrane electrode coatings is presented for a series of eighteen beta-adrenoceptor binding drugs (five agonists and thirteen antagonists) in cation exchange-HPLC and RP-HPLC systems. Incorporation of lipophilic cation-exchanger tetrakis(pchlorophenyl) borate (TCPB) alone or in combination with trioctylated α-cyclodextrin into the polymeric liquid membrane gives very sensitive responses for racemic forms of bufuralol, propranolol, carazolol, clenbuterol, mabuterol, cimaterol, bisoprolol, oxprenolol, alprenolol, tertatolol, and bevantolol, especially in the cation-exchange HPLC system applying acetonitrile - 40 mM phosphoric acid (15: 85, v / v, pH* = 2.35) as the mobile phase. In both applied orthogonal HPLC modes we observed that use of TCPB containing electrodes (no addition of neutral macrocyclic ionophores) gives more than five fold improvement in limit of detection down to 10-7 M for mabuterol, bufuralol, alprenolol and tertatolol in comparison with UV detection. These results suggest that potentiometric detection, especially in RP-HPLC employing hybrid polymer-silica packings, can be considered as the promising alternative in the highthroughput drug abuse or doping control procedures of investigated beta-adrenergic agonists and betaadrenolytics in humans and animals. The quantitative structure - potentiometric response relationships were developed for a set of eighteen beta-adrenenergic drugs and a set of PVC based electrodes using TCPB alone or in admixture with trioctylated α-cyclodextrin, dibenzo-18-crown-6 or calix[6]arene hexaethylacetate ester. A multiple linear regression model based on computationally derived set of molecular descriptors was used to predict detection limits of beta-blocking agents and beta-adrenergic agonists from their molecular structure in the developed potentiometric detectors. Principal components analysis (PCA) of data considering determined potentiometric detection limits revealed that it can be used to establish a reliable pharmacological classification of compounds with beta-adrenoceptor activity, especially for the differentiation of cardioselective and non-cardioselective beta1-antagonists.
