Michael Drummond, Scientific Applications Manager, Chemical Computing Group
Cytochrome P450 oxidases (CYPs) are a class of well-known heme-containing enzymes that are responsible for clearing xenobiotics, including drug molecules, through oxidative metabolism. Understanding the interactions between drug molecules and CYPs is therefore critical for evaluating drug efficacy, clearance, toxicity, and drug-drug interactions. Although dozens of crystal structures of the five predominant CYP isoforms have been solved, most modeling tools that predict drug-CYP interactions completely neglect this structural information. Understanding the shape, flexibility, and electrostatic nature of the CYP binding pockets can lead to improved modeling of CYP metabolism vis-à-vis approaches that only consider properties of the small molecules themselves. In this work, both 2D methods and 3D methods are used to predict the isoform selectivity, small molecule reactivity, and regioselectivity of CYPs. The 2D-based methods developed herein are parsimonious yet accurate, and can be used to quickly evaluate selectivity and reactivity. The 3D approach is based on a pharmacophore framework, which provides a rapid and flexible way to predict CYP isoform selectivity and regioselectivity. The modular components of the pharmacophore afford a straightforward means to tailor for a particular problem of interest. Moreover, directly incorporating 3D CYP structures into the models confers unique advantages over 2D-based approaches, such as the ability to distinguish reactivity differences among stereoisomers. Finally, predicted results can be readily visualized in a CYP pocket, and thus potential CYP liabilities are not merely flagged in a binary fashion, but can also be designed against in a structure-based design context – a clear improvement over the pass/fail filtering paradigm prevalent in CYP modeling efforts to date.