IntroductionCytochrome P450s (CYPs) are heme-containing enzymes that can be found in virtually all organisms. In humans, the CYP superfamily constitutes the most important enzymes in drug metabolism (see Chapters 4-8).Various computational approaches to study CYP metabolism have been reported over the years [1][2][3][4], and depending on the question that is being addressed, different methods may be more or less appropriate. For instance, if the actual reaction mechanism of a particular substrate is to be studied, a quantum mechanical description explicitly describing the electrons that are responsible for bonds being broken and formed is required [5]. On the other hand, a classification of a large number of compounds in terms of their likelihood to show an interaction with a CYP may rather be performed by application of cheminformatics machine learning tools [6]. In almost all cases, the versatility of the enzymes, the diversity of the substrates and inhibitors, and the malleability of the active sites pose additional challenges to the computational approach at hand. This chapter focuses on structure-based approaches to study the metabolism of substrates by CYP enzymes. Rather than addressing the actual enzymatic reactions, as in Chapters 6 and 11, we will focus here on the preferred orientations of substrates in the active site of CYP enzymes as a crucial first step in the prediction of metabolism. Using mostly examples from our own work, we will highlight some of the possibilities and challenges in structure-based predictions of sites of metabolism (SoMs).
6 Å RuleThe basic concept behind structure-based prediction of metabolism by CYP enzymes is extremely simple. The crucial cofactor of the enzymes is a heme 243 Drug Metabolism Prediction, First Edition. Edited by Johannes Kirchmair.