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Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein

Bikádi, Zsolt and Hazai, István and Malik, Dávid and Jemnitz, Katalin and Veres, Zsuzsa and Hazai, Eszter (2011) Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein. PLOS ONE, 6 (10). e25815. ISSN 1932-6203

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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.

Item Type: Article
Subjects: Q Science / természettudomány > QD Chemistry / kémia > QD04 Organic chemistry / szerves kémia
Q Science / természettudomány > QH Natural history / természetrajz > QH301 Biology / biológia > QH3011 Biochemistry / biokémia
R Medicine / orvostudomány > RS Pharmacy and materia medica / gyógyszerészet, gyógyászati eszközök
SWORD Depositor: MTMT SWORD
Depositing User: MTMT SWORD
Date Deposited: 18 Jan 2017 16:32
Last Modified: 18 Jan 2017 16:32
URI: http://real.mtak.hu/id/eprint/45989

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