A New Statistical Approach to Predicting Aromatic Hydroxylation Sites. Comparison with Model-Based Approaches

Abstract

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.

Prediction of Activation Energies for Aromatic Oxidation by Cytochrome P450

“…It has previously been shown that the methoxy radical can be used as a model for compound I when studying the hydroxylation of aliphatic carbon atoms , as well as in semiempirical studies of hydroxylation of aromatic carbon atoms. ,,, Therefore, we also tested how well the activation energies and the energies of the tetrahedral intermediate, calculated with the methoxy radical could reproduce the energies in Table . As is shown in part a of Figure and Table , the activation energies calculated with the methoxy radical at the B3LYP/6−31G(d) level correlate well with the final DFT energies calculated with the full compound I model.…”

“…Other correlations have also been tested. ,, For example, Bathelt et al used the bond dissociation energies (BDE) of the C−O bond in the tetrahedral intermediate using both a hydroxyl radical (BDE rad ) and a hydroxyl cation (BDE cat ) as a model of compound I. They achieved the best correlation with a combination of these two BDEs ( E ‡ ∝ BDE rad + 0.07*BDE cat , r 2 = 0.82) .…”

Radiolytic Transformations of Chlorinated Phenols and Chlorinated Phenoxyacetic Acids

“…Pentahalophenol oxidations show variation in reactivity according to the halide substituent . Many other substituent effects have been investigated to better comprehend the reactivity of the hydroxyl radical with a wide variety of aromatic compounds. − The aromatic compounds selected for this study (in addition to 2,4-D and 2,4-DCP) include 2-(2,4-dichlorophenoxy)propionic acid (2,4-DP), 2,4-D methyl ester, 2,4,6-trichlorophenol (2,4−6-TCP), and pentachlorophenol (PCP), all of which are displayed in Figure . These compounds possess varied degrees of electron density in their aromatic rings, due to the effects of the electron-withdrawing chlorine atoms, and small differences in structure and electronics from the oxygen substituents.…”

Fragment Descriptors in SAR/QSAR/QSPR Studies, Molecular Similarity Analysis and in Virtual Screening

“…Fragment descriptors derived from CGRs were used in similarity search of reactions, in reaction classification and in the development of QSPR models of the rate constant of S N 2 reactions in water. 218 To encode reaction transformations Borodina et al have developed Reacting Multilevel Neighborhood of Atom (RMNA) 219 descriptors representing an extended version of the MNA descriptors. Unlike CGRs, where reaction information is condensed, in the RMNA approach the information about modified, created or broken bonds is added to the list of the MNA descriptors generated for all products and reactants.…”