Use of biopartitioning micellar chromatography and RP-HPLC for the determination of blood–brain barrier penetration of α-adrenergic/imidazoline receptor ligands,and QSPR analysis

For this study, 31 compounds, including 16 imidazoline/α-adrenergic receptor (IRs/α-ARs) ligands and 15 central nervous system (CNS) drugs, were characterized in terms of the retention factors (k) obtained using biopartitioning micellar and classical reversed phase chromatography (log k_BMC and log k_wRP, respectively). Based on the retention factor (log k_wRP) and slope of the linear curve (S) the isocratic parameter (φ₀) was calculated. Obtained retention factors were correlated with experimental log BB values for the group of examined compounds. High correlations were obtained between logarithm of biopartitioning micellar chromatography (BMC) retention factor and effective permeability (r(log k_BMC/log BB): 0.77), while for RP-HPLC system the correlations were lower (r(log k_wRP/log BB): 0.58; r(S/log BB): –0.50; r(φ₀/P_e): 0.61). Based on the log k_BMC retention data and calculated molecular parameters of the examined compounds, quantitative structure–permeability relationship (QSPR) models were developed using partial least squares, stepwise multiple linear regression, support vector machine and artificial neural network methodologies. A high degree of structural diversity of the analysed IRs/α-ARs ligands and CNS drugs provides wide applicability domain of the QSPR models for estimation of blood–brain barrier penetration of the related compounds.     

QSPR studies on the photoinduced-fluorescence behaviour of pharmaceuticals and pesticides

Fluorimetric analysis is still a growing line of research in the determination of a wide range of organic compounds, including pharmaceuticals and pesticides, which makes necessary the development of new strategies aimed at improving the performance of fluorescence determinations as well as the sensitivity and, especially, the selectivity of the newly developed analytical methods. In this paper are presented applications of a useful and growing tool suitable for fostering and improving research in the analytical field. Experimental screening, molecular connectivity and discriminant analysis are applied to organic compounds to predict their fluorescent behaviour after their photodegradation by UV irradiation in a continuous flow manifold (multicommutation flow assembly). The screening was based on online fluorimetric measurement and comprised pre-selected compounds with different molecular structures (pharmaceuticals and some pesticides with known ‘native’ fluorescent behaviour) to study their changes in fluorescent behaviour after UV irradiation. Theoretical predictions agree with the results from the experimental screening and could be used to develop selective analytical methods, as well as helping to reduce the need for expensive, time-consuming and trial-and-error screening procedures.     

Towards predicting the solubility of CO2 and N2 in different polymers using a quasi-SMILES based QSPR approach

The solubility of gases in various polymers plays an important role for the design of new polymeric materials. Quantitative structure–property relationship (QSPR) models were designed to predict the solubility of gases such as CO₂ and N₂ in polyethylene (PE), polypropylene (PP), polystyrene (PS), polyvinyl acetate (PVA) and poly (butylene succinate) (PBS) at different temperatures and pressures by using quasi-SMILES codes. The dataset of 315 systems was split randomly into training, calibration and validation sets; random split 1 led to 214 training (r² = 0.870 and RMSE = 0.019), 51 calibration (r² = 0.858 and RMSE = 0.020) and 50 validation (r² = 0.869 and RMSE = 0.017) sets. The suggested approach based on the quasi-SMILES, which are analogues of the traditional SMILES gives reasonable good predictions for solubility of CO₂ and N₂ in different polymers. The described methodology is universal for situations where the aim is to predict the response of an eclectic system upon a variety of physicochemical and/or biochemical conditions.     

Probing Substrate/Catalyst Effects Using QSPR Analysis on Friedel-Crafts Acylation Reactions over Hierarchical BEA Zeolites

Attempts to optimize heterogeneous catalysis often lack quantitative comparative analysis. The use of kinetic modelling leads to rate (k) and relative sorption equilibrium constants (K), which can be further rationalized using Quantitative Structure-Property Relationships (QSPR) based on Multiple Linear Regressions (MLR). Friedel-Crafts acylation using commercial and hierarchical BEA zeolites as heterogeneous catalysts, acetic anhydride as the acylating agent, and a set of seven substrates with different sizes and chemical functionalities were herein studied. Catalytic results were correlated with the physicochemical properties of substrates and catalysts. From this analysis, a robust set of equations was obtained allowing inferences about the dominant factors governing the processes. Not entirely surprising, the rate and sorption equilibrium constants were found to be explained in part by common factors but of opposite signs: higher and stronger adsorption forces increase reaction rates, but they also make the zeolite active sites less accessible to new reactant molecules. The most relevant parameters are related to the substrates’ molecular size, which can be associated with different reaction steps, namely accessibility to micropores, diffusion capacity, and polarizability of molecules. The relatively large set of substrates used here reinforces previous findings and brings further insights into the factors that hamper/speed up Friedel-Crafts reactions in heterogeneous media.