Predicting P-glycoprotein-mediated drug transport based on support vector machine and three-dimensional crystal structure of P-glycoprotein

Zsolt Bikadi, Istvan Hazai, David Malik, K. Jemnitz, Z. Veres, Peter Hari, Zhanglin Ni, Tip W. Loo, David M. Clarke, Eszter Hazai, Qingcheng Mao

Research output: Contribution to journalArticle

82 Citations (Scopus)

Abstract

Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates. At present, publicly available, reliable in silico models predicting P-gp substrates are scarce. In this study, a support vector machine (SVM) method was developed to predict P-gp substrates and P-gp-substrate interactions, based on a training data set of 197 known P-gp substrates and non-substrates collected from the literature. We showed that the SVM method had a prediction accuracy of approximately 80% on an independent external validation data set of 32 compounds. A homology model of human P-gp based on the X-ray structure of mouse P-gp as a template has been constructed. We showed that molecular docking to the P-gp structures successfully predicted the geometry of P-gp-ligand complexes. Our SVM prediction and the molecular docking methods have been integrated into a free web server (http://pgp.althotas.com), which allows the users to predict whether a given compound is a P-gp substrate and how it binds to and interacts with P-gp. Utilization of such a web server may prove valuable for both rational drug design and screening.

Original languageEnglish
Article numbere25815
JournalPLoS One
Volume6
Issue number10
DOIs
Publication statusPublished - Oct 4 2011

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P-Glycoprotein
crystal structure
Support vector machines
Crystal structure
drugs
Pharmaceutical Preparations
Substrates
support vector machines
P-glycoproteins
Support Vector Machine
Servers
Preclinical Drug Evaluations
Pharmacokinetics
ATP-Binding Cassette Transporters
prediction
Drug Design
Computer Simulation
pharmacokinetics
transporters
mouth

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Predicting P-glycoprotein-mediated drug transport based on support vector machine and three-dimensional crystal structure of P-glycoprotein. / Bikadi, Zsolt; Hazai, Istvan; Malik, David; Jemnitz, K.; Veres, Z.; Hari, Peter; Ni, Zhanglin; Loo, Tip W.; Clarke, David M.; Hazai, Eszter; Mao, Qingcheng.

In: PLoS One, Vol. 6, No. 10, e25815, 04.10.2011.

Research output: Contribution to journalArticle

Bikadi, Zsolt ; Hazai, Istvan ; Malik, David ; Jemnitz, K. ; Veres, Z. ; Hari, Peter ; Ni, Zhanglin ; Loo, Tip W. ; Clarke, David M. ; Hazai, Eszter ; Mao, Qingcheng. / Predicting P-glycoprotein-mediated drug transport based on support vector machine and three-dimensional crystal structure of P-glycoprotein. In: PLoS One. 2011 ; Vol. 6, No. 10.
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