title: Simultaneous Prediction of four ATP-binding Cassette Transporters' Substrates Using Multi-label QSAR.
abstract: Efflux by the ATP-binding cassette (ABC) transporters affects the pharmacokinetic profile of drugs and it has been implicated in drug-drug interactions as well as its major role in multi-drug resistance in cancer. It is therefore important for the pharmaceutical industry to be able to understand what phenomena rule ABC substrate recognition. Considering a high degree of substrate overlap between various members of ABC transporter family, it is advantageous to employ a multi-label classification approach where predictions made for one transporter can be used for modeling of the other ABC transporters. Here, we present decision tree-based QSAR classification models able to simultaneously predict substrates and non-substrates for BCRP1, P-gp/MDR1 and MRP1 and MRP2, using a dataset of 1493 compounds. To this end, two multi-label classification QSAR modelling approaches were adopted: Binary Relevance (BR) and Classifier Chain (CC). Even though both multi-label models yielded similar predictive performances in terms of overall accuracies (close to 70 %), the CC model overcame the problem of skewed performance towards identifying substrates compared with non-substrates, which is a common problem in the literature. The models were thoroughly validated by using external testing, applicability domain and activity cliffs characterization. In conclusion, a multi-label classification approach is an appropriate alternative for the prediction of ABC efflux.
authors: Medway School of Pharmacy, Universities of Kent and Greenwich, Anson Building, Central Avenue, Chatham Maritime, Chatham, Kent postCode/>ME4 4TB, UK.
authors: Natália
authors: N
authors: Aniceto
authors: School of Computing, University of Kent, Canterbury, CT2 7NF, UK.
authors: Alex A
authors: AA
authors: Freitas
authors: Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK.
authors: Andreas
authors: A
authors: Bender
authors: School of Life Sciences, JMS Building, University of Sussex, Brighton, BN1 9QG, UK. T.Ghafourian@sussex.ac.uk.
authors: Taravat
authors: T
authors: Ghafourian
mesh_terms: D018528:ATP-Binding Cassette Transporters / Q000737:chemistry* / Q000378:metabolism; D000465:Algorithms; D008024:Ligands; D008958:Models, Molecular; D015394:Molecular Structure; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship; D015203:Reproducibility of Results; D013379:Substrate Specificity
chemical_list: D018528:ATP-Binding Cassette Transporters; D008024:Ligands
keywords: BCRP1; Breast Cancer Resistance Protein; MRP1; MRP2; Multi-label Classification; Multidrug-resistance Associated Protein; P-glycoprotein; QSAR, Transporter