Preclinical and in vitro assessment of the potential of D0870, an antifungal agent, for producing clinical drug interactions

Classification of cytochrome P450 inhibitors with respect to binding free energy and pIC50 using common molecular descriptors

Virtual screening of chemical libraries following experimental assays of drug candidates is a common procedure in structure based drug discovery. However, the relationship between binding free energies and biological activities (pIC50) of drug candidates is still an unsolved issue that limits the efficiency and speed of drug development processes. In this study, the relationship between them is investigated based on a common molecular descriptor set for human cytochrome P450 enzymes (CYPs). CYPs play an important role in drug-drug interactions, drug metabolism, and toxicity. Therefore, in silico prediction of CYP inhibition by drug candidates is one of the major considerations in drug discovery. The combination of partial least-squares regression (PLSR) and a variety of classification algorithms were employed by considering this relationship as a classification problem. Our results indicate that PLSR with classification is a powerful tool to predict more than one output such as binding free energy and pIC50 simultaneously. PLSR with mixed-integer linear programming based hyperboxes predicts the binding free energy and pIC50 with a mean accuracy of 87.18% (min: 81.67% max: 97.05%) and 88.09% (min: 79.83% max: 92.90%), respectively, for the cytochrome p450 superfamily using the common 6 molecular descriptors with a 10-fold cross-validation.

Use of robust classification techniques for the prediction of human cytochrome P450 2D6 inhibition

A new in silico model is developed to predict cytochrome P450 2D6 inhibition from 2D chemical structure. Using a diverse training set of 100 compounds with published inhibition constants, an ensemble approach to recursive partitioning is applied to create a large number of classification trees, each of which yields a yes/no prediction about inhibition for a given compound. These binary classifications are combined to provide an overall prediction, which answers the yes/no question about inhibition and provides a measure of confidence about that prediction. Compared to single-tree models, the ensemble approach is less sensitive to noise in the experimental data as well as to changes in the training set. Internal validation tests indicated an overall classification accuracy of 75%, whereas predictions applied to an external set of 51 compounds yielded 80% accuracy, with all inhibitors correctly identified. The speed and 2D nature of this model make it appropriate for high-throughput processing of large chemical libraries, and the confidence level provides a continuous scale on which to prioritize compounds.

Summary of information on human CYP enzymes: human P450 metabolism data

This chapter is an update of the data on substrates, reactions, inducers, and inhibitors of human CYP enzymes published previously by Rendic and DiCarlo (1), now covering selection of the literature through 2001 in the reference section. The data are presented in a tabular form (Table 1) to provide a framework for predicting and interpreting the new P450 metabolic data. The data are formatted in an Excel format as most suitable for off-line searching and management of the Web-database. The data are presented as stated by the author(s) and in the case when several references are cited the data are presented according to the latest published information. The searchable database is available either as an Excel file (for information contact the author), or as a Web-searchable database (Human P450 Metabolism Database, www.gentest.com) enabling the readers easy and quick approach to the latest updates on human CYP metabolic reactions.

Use of in vitro drug metabolism data to evaluate metabolic drug-drug interactions in man: the need for quantitative databases

It has become widely accepted that metabolic drug-drug interactions can be forecast using in vitro cytochrome P450 (CYP) data. For any CYP form-inhibitor pair, the magnitude of the interaction will depend on the potency of the inhibitor (inhibition constant, Ki) the concentration of the inhibitor available for inhibition ([I]), the fraction of the substrate dose metabolized by CYP (fm), and the fraction of the CYP-dependent metabolism catalyzed by the inhibited CYP form (e.g., fm,CYP3A4). While progress is being made toward our understanding of the factors necessary for predictions of [I]/Ki in vivo, it is evident that there is a need for quantitative databases that contain in vitro (e.g., Ki, fm,CYP3A4) and in vivo pharmacokinetic/absorption-distribution-metabolism-excretion (PK/ADME) data (e.g., fm) for a large number of marketed drugs. Ultimately, such databases would allow one to integrate all of the data necessary for the prediction of drug-drug interactions and permit the rational evaluation of new drug entities.

Involvement of multiple human cytochromes P450 in the liver microsomal metabolism of astemizole and a comparison with terfenadine

AIMS

The aims of the present study were to investigate the metabolism of astemizole in human liver microsomes, to assess possible pharmacokinetic drug-interactions with astemizole and to compare its metabolism with terfenadine, a typical H1 receptor antagonist known to be metabolized predominantly by CYP3A4.

METHODS

Astemizole or terfenadine were incubated with human liver microsomes or recombinant cytochromes P450 in the absence or presence of chemical inhibitors and antibodies.

RESULTS

Troleandomycin, a CYP3A4 inhibitor, markedly reduced the oxidation of terfenadine (26% of controls) in human liver microsomes, but showed only a marginal inhibition on the oxidation of astemizole (81% of controls). Three metabolites of astemizole were detected in a liver microsomal system, i.e. desmethylastemizole (DES-AST), 6-hydroxyastemizole (6OH-AST) and norastemizole (NOR-AST) at the ratio of 7.4 : 2.8 : 1. Experiments with recombinant P450s and antibodies indicate a negligible role for CYP3A4 on the main metabolic route of astemizole, i.e. formation of DES-AST, although CYP3A4 may mediate the relatively minor metabolic routes to 6OH-AST and NOR-AST. Recombinant CYP2D6 catalysed the formation of 6OH-AST and DES-AST. Studies with human liver microsomes, however, suggest a major role for a mono P450 in DES-AST formation.

CONCLUSIONS

In contrast to terfenadine, a minor role for CYP3A4 and involvement of multiple P450 isozymes are suggested in the metabolism of astemizole. These differences in P450 isozymes involved in the metabolism of astemizole and terfenadine may associate with distinct pharmacokinetic influences observed with coadministration of drugs metabolized by CYP3A4.