Failures due to bad metabolic properties are one of the major reasons of problems in drug companies. Biotransformation reactions due to human CYP-enzymes must be taken into account as early as possible in the lead optimization process during the development of new therapeutic agents. To this end, it would be extremely valuable for the drug industry to have a computational predictive method to predict the isoform selectivity, the potential inhibitor effect and the site of metabolism (i.e. the place in a molecule where the metabolic reaction occurs) for xenobiotics. The experimental elucidation of these properties is usually a high resource-demanding task, which requires several experimental techniques and consumes a considerable amount of compound. The recognition of the metabolic site in silico could be of great help to design new compounds with better pharmacokinetic profile as well as to avoid the presence of toxic metabolites. Moreover, the methodology can be used either to suggest new positions that should be protected in order to avoid certain metabolic profile or to check the suitability of a pro-drug. The aim of the present paper is to report a new method, fast, easy and computationally inexpensive for predicting CYP-inhibition, substrate selectivity and site of metabolism, using human CYP X-ray structures and ad hoc developed 3D-homology models. The methodology works for the most important human cytochromes, but can be applied automatically to all the cytochromes about which the 3D-structure is known by X-ray or homology models. The methods thus appear as a valuable new tool in virtual screening and in early ADME-Tox field where potential drug-drug interaction and metabolic stability information must be evaluated to enhance drug design efforts.