  Prediction of metabolism in cytochrome P450s remains to be a crucial yet
challenging topic in discovering and designing drugs, agrochemicals and
nutritional supplements. The problem is challenging because the rate of P450
metabolism depends upon both the intrinsic chemical reactivity of the site and
the protein-ligand geometry that is energetically accessible in the active site
of a given P450 isozyme. We have addressed this problem using a two-level
screening system. The first level implements an empirical QSAR-based scoring
function employing the local chemical motifs to characterize the intrinsic
reactivity. The second level uses molecular docking and molecular mechanics to
account for the geometrical effects, including induced-fit effects in the
protein which can be very important in P450 interactions with ligands. This
approach has achieved high accuracy for both the P450 3A4 and 2D6 isoforms. In
identifying at least one metabolic site in the top two ranked positions, the
prediction rate can reach as high as 92.7% for the test set of isoform 3A4. For
the 2D6 isoform, 100% accuracy is achieved on this basic evaluation metric,
and, because this active site is considerably smaller and more selective than
3A4, very high precision is attained for full prediction of all metabolic
sites. The method also requires considerably less CPU time than our previous
efforts, which involved a large number of expensive simulations for each ligand
to be evaluated. After screening using the empirical score function, only a few
best candidates are left for each ligand, making the number of necessary
estimations in the second level very small, which significantly reduces the
computation time.
