The aim of this article is to show the main aspects of quantitative structure activity relationship (QSAR) modeling for regulatory purposes. We try to answer the question; what makes QSAR models suitable for regulatory uses. The article focuses on directions in QSAR modeling in European Union (EU) and Russia. Difficulties in validation models have been discussed.
A new approach is described that is able to predict the most probable metabolic sites on the basis of a statistical analysis of various metabolic transformations reported in the literature. The approach is applied to the prediction of aromatic hydroxylation sites for diverse sets of substrates. Training is performed using the aromatic hydroxylation reactions from the Metabolism database (Accelrys). Validation is carried out on heterogeneous sets of aromatic compounds reported in the Metabolite database (MDL). The average accuracy of prediction of experimentally observed hydroxylation sites estimated for 1552 substrates from Metabolite is 84.5%. The proposed approach is compared with two electronic models for P450 mediated aromatic hydroxylation: the oxenoid model using the atomic oxygen and the model using the methoxy radical as a model for the heme active oxygen species. For benzene derivatives, the proposed method is inferior to the oxenoid model and as accurate as the methoxy-radical model. For hetero- and polycyclic compounds, the oxenoid model is not applicable, and the statistical method is the most accurate. Broad applicability and high speed of calculations provide the basis for using the proposed statistical approach for high-throughput metabolism prediction in the early stages of drug discovery.
ABSTRACT:The dependences of biological oxidation and toxicity of the mono-and multisubstituted benzene derivatives on the nature of substituents are studied using an oxenoid model and the quantum chemical calculations. According to this model, the P450 enzyme breaks the dioxygen molecules and generates the active atomic oxygen species (oxens); these species readily react with substrates. Using MO LCAO MNDO approach, we calculated the differences ⌬E of the total energies of aromatic compounds and corresponding arene oxides containing tetrahedrally coordinated carbon atoms. We obtained that the ⌬E values determine the positions of the enzyme mediated oxidation, rate of substrate biotransformation, and toxicity of the benzene derivatives. In addition to the "dynamic" reactivity index ⌬E related to the enzyme-mediated substrate biotransformation, we calculated many standard "static" reactivity indices, corresponding to the substrate molecules in the starting equilibrium geometry (the energies of the occupied and unoccupied MOs, the effective atomic charges, the free valence indices, and the superdelocalizabilities). The arene oxide stability ⌬E parameter is shown to be the most adequate characteristic of both the biological oxidation process and toxicity of benzenes. The ⌬E parameters were also used successfully to describe the features of di-and trichlorinated biphenyls bacterial metabolism.
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