One of the major reasons for late-stage failure of drug candidates is due to 
problems uncovered in pharmacokinetics during clinical trials. There is now a 
general consensus for earlier consideration of these effects in the drug 
discovery process. Computer-aided design technology provides us with tools to 
develop predictive models for such pharmacokinetic properties. Among these 
tools, we focus on pharmacophore modeling techniques in this article. 
Pharmacophore models that are reported for various cytochrome P450 (CYP) enzymes 
are reviewed for the isoenzymes CYP1A2, 2B6, 2C9, 2C19, 2D6, 2E1, and 3A4. In 
addition pharmacophore models for related metabolic processes through CYP19 
(aromatase), CYP51 (14.α-lanosterol demethylase), PXR (pregnane X-receptor), and 
finally for human intrinsic clearance are also reviewed. The models reported by 
various scientists are schematically represented in the figures in order to 
visually demonstrate their similarities and differences. The models developed by 
different researchers or sometimes even by the same research group for different 
sets of ligands, provide a clear picture of the challenges in coming up with a 
single model with good predictive values. One of the main reasons for this 
challenge is related to relatively large size of the active sites and 
flexibility of the CYP isoenzymes, which results in multiple binding sites. We 
propose development of multiple- diverse pharmacophore models for each binding 
mode (as opposed to a single predictive model for each CYP isoenzyme). After 
scoring and prioritization of the models, we propose the use of a battery of 
pharmacophore models for each CYP isoenzyme binding mode to computationally 
obtain a P450 interaction profile for drug candidates early in the drug 
development cycle, when decisions on their fate can be made before incurring the 
costs of synthesis and testing.