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Vol. 61, Issue 5, 974-981, May 2002
Lilly Research Laboratories, Eli Lilly and Co., Lilly Corporate
Center, Indianapolis, Indiana (S.E., A.H.D., R.L.S., M.A.W., J.H.W.,
S.A.W.); Division of Clinical Pharmacology, Vanderbilt University,
Nashville, Tennessee (R.B.K., B.F.L.); Department of Pharmaceutical
Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee
(E.G.S., L.-B.L., K.Y., J.D.S.)
Using in vitro data, we previously built Catalyst 3-dimensional
quantitative structure activity relationship (3D-QSAR) models that
qualitatively rank and predict IC50 values for
P-glycoprotein (P-gp) inhibitors. These models were derived and tested
with data for inhibition of digoxin transport, calcein accumulation,
vinblastine accumulation, and vinblastine binding. In the present
study, 16 inhibitors of verapamil binding to P-gp were predicted using
these models. These inhibition results were then used to generate a new
pharmacophore that consisted of one hydrogen bond acceptor, one ring
aromatic feature, and two hydrophobes. This model predicted the rank
order of the four data sets described previously and correctly ranked
the inhibitory potency of a further four verapamil metabolites
identified in the literature. The degree of similarity in rank ordering
prediction by these inhibitor pharmacophore models generated to date
confirms a likely overlap in the sites to which the three P-gp
substrates used in these studies (verapamil, vinblastine, and digoxin)
bind. Alignment of the three substrate probes indicated that they are
likely to bind the same or overlapping sites within P-gp. Important
features on these substrates include multiple hydrophobic and hydrogen
bond acceptor features, which are widely dispersed and in agreement
among most of the five inhibitor pharmacophores we have described so
far. These 3D-QSAR models will be useful for future prediction of
likely substrates and inhibitors of P-gp.
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