Structure and Ligand-based Design of P-glycoprotein Inhibitors: A Historical Perspective

Andreia      Palmeira; Emilia      Sousa; M.      Helena Vasconcelos; Madalena      Pinto; Miguel      X. Fernandes

doi:10.2174/138161212802430530

Abstract

Computer-assisted drug design (CADD) is a valuable approach for the discovery of new chemical entities in the field of cancer therapy. There is a pressing need to design and develop new, selective, and safe drugs for the treatment of multidrug resistance (MDR) cancer forms, specifically active against P-glycoprotein (P-gp). Recently, a crystallographic structure for mouse P-gp was obtained. However, for decades the design of new P-gp inhibitors employed mainly ligand-based approaches (SAR, QSAR, 3D-QSAR and pharmacophore studies), and structure-based studies used P-gp homology models. However, some of those results are still the pillars used as a starting point for the design of potential P-gp inhibitors. Here, pharmacophore mapping, (Q)SAR, 3D-QSAR and homology modeling, for the discovery of P-gp inhibitors are reviewed. The importance of these methods for understanding mechanisms of drug resistance at a molecular level, and design P-gp inhibitors drug candidates are discussed. The examples mentioned in the review could provide insights into the wide range of possibilities of using CADD methodologies for the discovery of efficient P-gp inhibitors.

Keywords: Computer-assisted drug design, homology modeling, P-glycoprotein inhibitors, pharmacophore, quantitative structure-activity relationships, structure-based drug design, cancer therapy, crystallographic structure, mouse P-gp, computational interpretations.