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Three-dimensional quantitative structure-activity relationships of inhibitors of P-glycoprotein
Authors:Ekins Sean  Kim Richard B  Leake Brenda F  Dantzig Anne H  Schuetz Erin G  Lan Lu-Bin  Yasuda Kazuto  Shepard Robert L  Winter Mark A  Schuetz John D  Wikel James H  Wrighton Steven A
Affiliation:Lilly Research Laboratories, Eli Lilly and Co., Lilly Corporate Center, Indianapolis, Indiana, USA. ekinssean@yahoo.com
Abstract:P-glycoprotein (P-gp) is an efflux transporter involved in limiting the oral bioavailability and tissue penetration of a variety of structurally divergent molecules. A better understanding of the structural requirements of modulators of P-gp function will aid in the design of therapeutic agents. Toward this goal, three-dimensional quantitative structure-activity relationship (3D-QSAR) models were generated using in vitro data associated with inhibition of P-gp function. Several approaches were undertaken with multiple iterations, yielding Catalyst 3D-QSAR models being able to qualitatively rank-order and predict IC(50) values for P-gp inhibitors excluded from the model in question. The success of these validations suggests that a P-gp pharmacophore for 27 inhibitors of digoxin transport in Caco-2 cells consisted of four hydrophobes and one hydrogen bond acceptor. A second pharmacophore generated with 21 inhibitors of vinblastine binding to plasma membrane vesicles derived from CEM/VLB(100) cells contained three ring aromatic features and one hydrophobic feature. A third pharmacophore generated with 17 inhibitors of vinblastine accumulation in P-gp expressing LLC-PK1 cells contained four hydrophobes and one hydrogen bond acceptor. A final pharmacophore was generated for inhibition of calcein accumulation in P-gp expressing LLC-PK1 cells and found to contain two hydrophobes, a ring aromatic feature, and a hydrogen bond donor. The similarity of features for the pharmacophores of P-gp inhibitors of digoxin transport and vinblastine binding suggest some commonality in their binding sites. Utilization of such models may prove to be of value for prediction of molecules that may modulate one or more P-gp binding sites.
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