Volume 4, Issue 11 p. 1883-1896
Full Paper

Combined Pharmacophore Modeling, Docking, and 3D QSAR Studies of ABCB1 and ABCC1 Transporter Inhibitors

Ilza K. Pajeva Prof. Dr.

Ilza K. Pajeva Prof. Dr.

Pharmaceutical Institute, University of Bonn, An der Immenburg 4, 53121 Bonn (Germany), Fax: (+49) 228-737929

Center of Biomedical Engineering, Bulgarian Academy of Science, Bl. 105, Acad. George Bontchev Str., 1113 Sofia (Bulgaria)

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Christoph Globisch Dr.

Christoph Globisch Dr.

Pharmaceutical Institute, University of Bonn, An der Immenburg 4, 53121 Bonn (Germany), Fax: (+49) 228-737929

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Michael Wiese Prof. Dr.

Michael Wiese Prof. Dr.

Pharmaceutical Institute, University of Bonn, An der Immenburg 4, 53121 Bonn (Germany), Fax: (+49) 228-737929

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First published: 23 October 2009
Citations: 76

Graphical Abstract

Selective and dual inhibitors of the ABCB1 (P-gp) and ABCC1 (MRP1) transporters were studied by pharmacophore modeling, docking into the P-gp binding cavity, and 3D QSAR to describe the binding preferences of the proteins and to identify the similarities and differences in their interactions.

Abstract

Quinazolinones, indolo- and pyrrolopyrimidines with inhibitory effects toward ABCB1 (P-gp) and ABCC1 (MRP1) transporters were studied by pharmacophore modeling, docking, and 3D QSAR to describe the binding preferences of the proteins. The pharmacophore overlays between dual and/or highly selective inhibitors point to binding sites of different topology and physiochemical properties for MRP1 and P-gp. Docking of selective inhibitors into the P-gp binding cavity by the use of a structural model based on the recently resolved P-gp structure confirms the P-gp pharmacophore features identified, and reveals the interactions of some functional groups and atoms in the structures with particular protein residues. The 3D QSAR analysis of the dual-effect inhibitors allows satisfactory prediction of the selectivity index of the compounds and outlines electrostatics as most important for selectivity. The results from the combined modeling approach complement each other and could improve our understanding of the protein–ligand interactions involved, and could aid in the development of highly selective and potent inhibitors of P-gp and MRP1.