RESUMO
Finding a balance between a desired drug's potency and its physicochemical properties that are important for its molecule pharmacokinetic or pharmacodynamics profile is still a challenging issue in rational drug discovery. Quantitative assessment of the lipophilic characteristics of potential drug molecules is indispensable for efficient development of Absorption, Distribution, Metabolism, Excretion, Toxicity-tailored structure-activity models; therefore reliable procedures for deriving log P from molecular structure are desirable. In the current work a range of various software log P predictors for estimation of the numerical lipophilic values for a set of cholic acid derivatives were employed and subsequently cross-compared with the experimental parameters. Thus, the empirical lipophilicity (RM) was compared with the corresponding log P characteristics calculated using alternative methods for deducing the lipophilic features. The mean values of the selected molecular descriptors that were averaged over the chosen calculation methods (consensus clog P) were subsequently correlated with the RM parameter. As an additional experiment, the iterative variable elimination partial least squares (IVE-PLS) methodology for an ensemble of descriptors retrieved from Dragon 6.0 software was applied for a set of drug transporters. To investigate the variations within the ensemble of cholic acid derivatives principal component analysis (PCA) and self-organizing neural network (SOM) procedures were used to visualize the major differences in the performance of drug promoters with respect to their lipophilic profile.
Assuntos
Ácidos Cólicos/química , Ácidos Cólicos/farmacocinética , Preparações Farmacêuticas/química , Adsorção , Química Farmacêutica/métodos , Simulação por Computador , Descoberta de Drogas/métodos , Interações Hidrofóbicas e Hidrofílicas , Análise dos Mínimos Quadrados , Lipídeos/química , Estrutura Molecular , Redes Neurais de Computação , Análise de Componente Principal , Relação Quantitativa Estrutura-AtividadeRESUMO
Irisolidone, a major isoflavone found in Pueraria lobata flowers, exhibits a wide spectrum of bioactivities, while its metabolic pathway in vivo has not been investigated. In this study, an ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF MS) method was employed to investigate the in vivo metabolism of irisolidone in rats. Plasma, bile, urine, and feces were collected from rats after a single 100mg/kg oral dose of irisolidone. Protein precipitation, solid phase extraction (SPE) and ultrasonic extraction were used to prepare samples of plasma, bile/urine, and feces, respectively. A total of 46 metabolites were detected and tentatively identified based on the mass spectral fragmentation patterns, elution order or confirmed using available reference standards. The metabolic pathways of irisolidone in rats included decarbonylation, reduction, demethylation, demethoxylation, dehydroxylation, hydroxylation, sulfation, and glucuronidation. The relative content of each metabolite was also determined to help understand the major metabolic pathways of irisolidone in rats.