Next Article in Journal
Reference Gene Selection in the Desert Plant Eremosparton songoricum
Previous Article in Journal
By-Passing Large Screening Experiments Using Sequencing as a Tool to Identify scFv Fragments Targeting Atherosclerotic Lesions in a Novel In Vivo Phage Display Selection
Int. J. Mol. Sci. 2012, 13(6), 6924-6943; doi:10.3390/ijms13066924
Article

Development of Classification Models for Identifying “True” P-glycoprotein (P-gp) Inhibitors Through Inhibition, ATPase Activation and Monolayer Efflux Assays

1
,
2
,
3
 and
1,4,*
1 Department of Pharmaceutical Sciences, University of Pisa, Via Bonanno 6, Pisa 56126, Italy 2 Consorzio Interuniversitario Nazionale per la Scienza e la Tecnologia dei Materiali (INSTM), Via Giusti 9, Firenze 50121, Italy 3 Fondazione S. Maugeri, Via S. Maugeri 4, Pavia 27100, Italy 4 International Centre for Studies and Research in Biomedicine (ICB) A.s.b.l., Luxembourg L-4947, Luxembourg
* Author to whom correspondence should be addressed.
Received: 22 March 2012 / Revised: 21 May 2012 / Accepted: 31 May 2012 / Published: 7 June 2012
View Full-Text   |   Download PDF [148 KB, uploaded 19 June 2014]

Abstract

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.
Keywords: P-glicoprotein; decision trees; classification model; consensus model; P-gp inhibitors; MDR1 ligands P-glicoprotein; decision trees; classification model; consensus model; P-gp inhibitors; MDR1 ligands
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Supplementary material

SciFeed

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote |
RIS
MDPI and ACS Style

Rapposelli, S.; Coi, A.; Imbriani, M.; Bianucci, A.M. Development of Classification Models for Identifying “True” P-glycoprotein (P-gp) Inhibitors Through Inhibition, ATPase Activation and Monolayer Efflux Assays. Int. J. Mol. Sci. 2012, 13, 6924-6943.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here

Comments

[Return to top]
Int. J. Mol. Sci. EISSN 1422-0067 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert