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There has been much interest in the development of a predictive model of cytochrome P450 2D6 particularly because this enzyme is involved in the oxidation of at least 50 drugs. Previously we have described the combined use of homology modeling and molecular docking to correctly position a range of substrates in the CYP2D6 active site with the known sites of metabolism above the heme. Here, our approach identifies correctly the site of metabolism of the atypical (no basic nitrogen) cytochrome P450 2D6 substrate, spirosulfonamide. The same method is used to screen a small compound database for cytochrome P450 2D6 inhibition. A database containing 33 compounds from the National Cancer Institute database was docked into our cytochrome P450 2D6 homology model using the program GOLDv2.0. Experimental IC50 values for the 33 compounds were determined; comparison with the corresponding docked scores revealed a correlation with a regression coefficient of r² = 0.61 (q² = 0.59). The method was able to discriminate between tight and weak binding compounds and correctly identified several novel inhibitors. The results therefore suggest that our approach, which combines homology modeling with molecular docking, has produced a useful predictive in silico tool for cytochrome P450 2D6 inhibition, which is best used as one filter in a multifilter database screen.