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J Med Chem ; 48(8): 2927-35, 2005 Apr 21.
Article in English | MEDLINE | ID: mdl-15828831

ABSTRACT

Trying to understand the complex interactions that substrates and inhibitors have with the efflux transporter P-glycoprotein has been the subject of various publications. In this work, we have confined our study to substrates by picking a diverse set of 129 compounds based on the efflux ratios from Caco-2 permeability measurements. These compounds were then evaluated for P-glycoprotein inhibition using a calcein-AM assay. The subsequent data was used in a 3D-QSAR analysis using GRIND pharmacophore-based and physicochemical descriptors. Pharmacophore-based descriptors produced a much more robust model than the one obtained from physicochemical-based descriptors. This supports the process proposed by Seelig and co-workers previously published whereby the substrate enters the membrane as the first step and is then recognized by P-glycoprotein in a second step. The strong correlation, highlighted by PLS statistical analysis, between pharmacophoric descriptors and inhibition values suggests that substrate interaction, with perhaps the mouth of the protein or another binding site, plays a key role in the efflux process, yielding a model in which diffusion across the membrane is less important than substrate-protein interaction. One pharmacophore emerged from the analysis of the model. We pose that the recognition elements, at least determined by the molecules used in this study, are two hydrophobic groups 16.5 A apart and two hydrogen-bond-acceptor groups 11.5 A apart and that the dimensions of the molecule also plays a role in its recognition as a substrate.


Subject(s)
ATP Binding Cassette Transporter, Subfamily B, Member 1/antagonists & inhibitors , ATP Binding Cassette Transporter, Subfamily B, Member 1/metabolism , ATP Binding Cassette Transporter, Subfamily B, Member 1/chemistry , Biological Transport , Caco-2 Cells , Fluoresceins , Fluorescent Dyes , Humans , Models, Molecular , Multivariate Analysis , Permeability , Quantitative Structure-Activity Relationship
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