%0 Journal Article
%T Development of Classification Models for Identifying ¡°True¡± P-glycoprotein (P-gp) Inhibitors Through Inhibition, ATPase Activation and Monolayer Efflux Assays
%A Simona Rapposelli
%A Alessio Coi
%A Marcello Imbriani
%A Anna Maria Bianucci
%J International Journal of Molecular Sciences
%D 2012
%I MDPI AG
%R 10.3390/ijms13066924
%X P-glycoprotein (P-gp) is an efflux pump involved in the protection of tissues of several organs by influencing xenobiotic disposition. P-gp plays a key role in multidrug resistance and in the progression of many neurodegenerative diseases. The development of new and more effective therapeutics targeting P-gp thus represents an intriguing challenge in drug discovery. P-gp inhibition may be considered as a valid approach to improve drug bioavailability as well as to overcome drug resistance to many kinds of tumours characterized by the over-expression of this protein. This study aims to develop classification models from a unique dataset of 59 compounds for which there were homogeneous experimental data on P-gp inhibition, ATPase activation and monolayer efflux. For each experiment, the dataset was split into a training and a test set comprising 39 and 20 molecules, respectively. Rational splitting was accomplished using a sphere-exclusion type algorithm. After a two-step (internal/external) validation, the best-performing classification models were used in a consensus predicting task for the identification of compounds named as ¡°true¡± P-gp inhibitors, i.e., molecules able to inhibit P-gp without being effluxed by P-gp itself and simultaneously unable to activate the ATPase function.
%K P-glicoprotein
%K decision trees
%K classification model
%K consensus model
%K P-gp inhibitors
%K MDR1 ligands
%U http://www.mdpi.com/1422-0067/13/6/6924