title: QSAR models for P-glycoprotein transport based on a highly consistent data set.
abstract: P-Glycoprotein (Pgp) is involved in the elimination and in the disposition of a significant portion of marketed drugs. So far, publicly available data sets used for modeling Pgp transport included compounds tested in different assays, different cell lines, and different protocols. In this work, we present a collection of 478 Efflux Ratios (ERs) in MDCK-MDR1 cell lines, and from this collection we define a data set of 187 compounds that were tested in the Borst-derived MDCK-MDR1 cell lines. Of the 23 models resulting from the use of different descriptors, classification algorithms, and variable selection techniques, the 4 most accurate in external validation (∼0.86) are based on VolSurf+ (VS+) descriptors. Two of these models are Naïve Bayes (NB) classifiers using 4 descriptors that were selected through a new technique hereby first time extensively described.
authors.affiliation: Laboratory of Chemometrics, Department of Chemistry, University of Perugia, Via Elce di Sotto 10, I-60123 Perugia, Italy. fabio@chemiome.chm.unipg.it
authors.forename: Fabio
authors.initials: F
authors.lastname: Broccatelli
mesh_terms: D018435:ATP Binding Cassette Transporter, Subfamily B / Q000378:metabolism*; D000818:Animals; D002460:Cell Line; D045744:Cell Line, Tumor; D006801:Humans; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship
chemical_list: D018435:ATP Binding Cassette Transporter, Subfamily B