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Vol. 59, Issue 4, 909-919, April 2001
Department of Drug Metabolism and Pharmacokinetics & Bioanalytical
Chemistry, AstraZeneca R&D, Mölndal, Sweden (L.A., I.Z., M.R.,
T.B.A., C.M.M.); and Department of Organic Pharmaceutical Chemistry,
Biomedical Center, Uppsala University, Uppsala, Sweden (L.A., A.K.)
This study describes the generation of a three-dimensional quantitative
structure activity relationship (3D-QSAR) model for 29 structurally
diverse, competitive CYP2C9 inhibitors defined experimentally from an
initial data set of 73 compounds. In parallel, a homology model for
CYP2C9 using the rabbit CYP2C5 coordinates was built. For molecules
with a known interaction mode with CYP2C9, this homology model, in
combination with the docking program GOLD, was used to select
conformers to use in the 3D-QSAR analysis. The remaining molecules were
docked, and the GRID interaction energies for all conformers proposed
by GOLD were calculated. This was followed by a principal component
analysis (PCA) of the GRID energies for all conformers of all
compounds. Based on the similarity in the PCA plot to the inhibitors
with a known interaction mode, the conformer to be used in the 3D-QSAR
analysis was selected. The compounds were randomly divided into two
groups, the training data set (n = 21) to build the
model and the external validation set (n = 8). The
PLS (partial least-squares) analysis of the interaction energies
against the Ki values generated a model with
r2 = 0.947 and a cross-validation of
q2 = 0.730. The model was able to predict the entire
external data set within 0.5 log units of the experimental
Ki values. The amino acids in the active
site showed complementary features to the grid interaction
energies in the 3D-QSAR model and were also in agreement with
mutagenesis studies.
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