Computational Models for Identifying Potential P-Glycoprotein Substrates and Inhibitors

Abstract

Multidrug resistance mediated by ATP binding cassette (ABC) transporters such as P-glycoprotein (P-gp) represents a serious problem for the development of effective anticancer drugs. In addition, P-gp has been shown to reduce oral absorption, modulate hepatic, renal, or intestinal elimination, and restrict blood-brain barrier penetration of several drugs. Consequently, there is a great interest in anticipating whether drug candidates are P-gp substrates or inhibitors. In this respect, two different computational models have been developed. A method for discriminating P-gp substrates and nonsubstrates has been set up based on calculated molecular descriptors and multivariate analysis using a training set of 53 diverse drugs. These compounds were previously classified as P-gp substrates or nonsubstrates on the basis of the efflux ratio from Caco-2 permeability measurements. The program Volsurf was used to compute the compounds' molecular descriptors. The descriptors were correlated to the experimental classes using partial least squares discriminant analysis (PLSD). The model was able to predict correctly the behavior of 72% of an external set of 272 proprietary compounds. Thirty of the 53 previously mentioned drugs were also evaluated for P-gp inhibition using a calcein-AM (CAM) assay. On the basis of these additional P-gp functional data, a PLSD analysis using GRIND-pharmacophore-based descriptors was performed to model P-gp substrates having poor or no inhibitory activity versus inhibitors having no evidence of significant transport. The model was able to discriminate between 69 substrates and 56 inhibitors taken from the literature with an average accuracy of 82%. The model allowed also the identification of some key molecular features that differentiate a substrate from an inhibitor, which should be taken into consideration in the design of new candidate drugs. These two models can be implemented in a virtual screening funnel.

Inhibition of γ-secretase induces G2/M arrest and triggers apoptosis in breast cancer cells

“…As PC-3 cells express also P-glycoprotein (Rao et al, 2005), and considering the molecular structure of GSI1, it is possible that GSI1 will be a substrate of P-glycoprotein (Crivori et al, 2006). This would make GSI1 less effective in cancers from tissues expressing P-glycoprotein such as those from colon or the adrenal gland, or in those which have acquired P-glycoprotein-mediated drug resistance (Burger et al, 2003).…”

Polarized P-glycoprotein expression by the immortalised human brain endothelial cell line, hCMEC/D3, restricts apical-to-basolateral permeability to rhodamine 123

“…them to diffuse across the lipid bilayer relatively easily (Cabrera et al, 2006;Cianchetta et al, 2005;Crivori et al, 2006;Penzotti et al, 2002;Wang et al, 2003).…”

Substrate recognition by P-glycoprotein efflux transporters: Structure-ATPase activity relationship of diverse chemicals and agrochemicals

“…In addition, from the point of view of early absorption, distribution, metabolism, and excretion (ADME) prediction of therapeutic agents, various computational prediction models have been reported for ligand interactions with P-gp. 2,[4][5][6][7][8][9][10] In general, a P-gp substrate seems to be lipophilic or amphiphilic, having a large size or molecular volume, electronegative groups and hydrogen bonding groups. 11) Although X-ray structures of the complex of mouse P-gp with enantiomeric cyclic peptide inhibitors have been reported previously by Aller et al in 2009, 12) the mechanism of P-gp substrate/inhibitor recognition is complicated and still poorly understood.…”