Quantitative structure-activity relationship (QSAR) and three-dimensional QSAR analysis of a series of xanthates as inhibitors and inactivators of cytochrome P450 2B1

Three-dimensional quantitative structure-activity relationship analysis of inhibitors of human and rat cytochrome P4503A enzymes

Cytochrome P450 3A4 (CYP3A4) is a member of the CYP family and is an important enzyme in drug metabolism. A compound that inhibits CYP3A4 activity could also affect the pharmacokinetics of other substrates, resulting in drug-drug interactions (DDIs) that could cause side effects. Pharmacokinetic data from drug-development studies in rats often determine the dosage used in human clinical trials. It is therefore useful to understand differences in metabolism in different species at an early stage in drug development. Human and rat CYP3A enzymes show different inhibition profiles with different drugs, although the mechanisms involved are not yet clear. Here we built three-dimensional quantitative structure-activity relationship (3D-QSAR) models using structure-based comparative molecular field analysis (CoMFA), to predict the direct inhibitory activity of ligands for human CYP3A4 and rat CYP3A1, based on computer-ligand docking. The alignment of the ligand docking poses suggested that key amino acid-ligand interactions (e.g., Thr309 in CYP3A4 and Pro310 in CYP3A1) characterized the different potencies with which the ligands inhibited CYP3A4 and CYP3A1. The 3D-QSAR models for human and rat CYP3A family inhibitors predicted the potency of inhibitors and could be useful for assessing DDIs at an early stage in drug discovery.

Insights on cytochrome p450 enzymes and inhibitors obtained through QSAR studies

The cytochrome P450 (CYP) superfamily of heme enzymes play an important role in the metabolism of a large number of endogenous and exogenous compounds, including most of the drugs currently on the market. Inhibitors of CYP enzymes have important roles in the treatment of several disease conditions such as numerous cancers and fungal infections in addition to their critical role in drug-drug interactions. Structure activity relationships (SAR), and three-dimensional quantitative structure activity relationships (3D-QSAR) represent important tools in understanding the interactions of the inhibitors with the active sites of the CYP enzymes. A comprehensive account of the QSAR studies on the major human CYPs 1A1, 1A2, 1B1, 2A6, 2B6, 2C9, 2C19, 2D6, 2E1, 3A4 and a few other CYPs are detailed in this review which will provide us with an insight into the individual/common characteristics of the active sites of these enzymes and the enzyme-inhibitor interactions.

Promises and pitfalls of quantitative structure-activity relationship approaches for predicting metabolism and toxicity

The description of quantitative structure-activity relationship (QSAR) models has been a topic for scientific research for more than 40 years and a topic within the regulatory framework for more than 20 years. At present, efforts on QSAR development are increasing because of their promise for supporting reduction, refinement, and/or replacement of animal toxicity experiments. However, their acceptance in risk assessment seems to require a more standardized and scientific underpinning of QSAR technology to avoid possible pitfalls. For this reason, guidelines for QSAR model development recently proposed by the Organization for Economic Cooperation and Development (OECD) [Organization for Economic Cooperation and Development (OECD) (2007) Guidance document on the validation of (quantitative) structure-activity relationships [(Q)SAR] models. OECD Environment Health and Safety Publications: Series on Testing and Assessment No. 69, Paris] are expected to help increase the acceptability of QSAR models for regulatory purposes. The guidelines recommend that QSAR models should be associated with (i) a defined end point, (ii) an unambiguous algorithm, (iii) a defined domain of applicability, (iv) appropriate measures of goodness-of-fit, robustness, and predictivity, and (v) a mechanistic interpretation, if possible [Organization for Economic Cooperation and Development (OECD) (2007) Guidance document on the validation of (quantitative) structure-activity relationships [(Q)SAR] models. The present perspective provides an overview of these guidelines for QSAR model development and their rationale, as well as the promises and pitfalls of using QSAR approaches and these guidelines for predicting metabolism and toxicity of new and existing chemicals.