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

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 b...

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Autores principales: Bikadi, Zsolt, Hazai, Istvan, Malik, David, Jemnitz, Katalin, Veres, Zsuzsa, Hari, Peter, Ni, Zhanglin, Loo, Tip W., Clarke, David M., Hazai, Eszter, Mao, Qingcheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3186768/
https://www.ncbi.nlm.nih.gov/pubmed/21991360
http://dx.doi.org/10.1371/journal.pone.0025815
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author Bikadi, Zsolt
Hazai, Istvan
Malik, David
Jemnitz, Katalin
Veres, Zsuzsa
Hari, Peter
Ni, Zhanglin
Loo, Tip W.
Clarke, David M.
Hazai, Eszter
Mao, Qingcheng
author_facet Bikadi, Zsolt
Hazai, Istvan
Malik, David
Jemnitz, Katalin
Veres, Zsuzsa
Hari, Peter
Ni, Zhanglin
Loo, Tip W.
Clarke, David M.
Hazai, Eszter
Mao, Qingcheng
author_sort Bikadi, Zsolt
collection PubMed
description 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.
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spelling pubmed-31867682011-10-11 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, Katalin Veres, Zsuzsa Hari, Peter Ni, Zhanglin Loo, Tip W. Clarke, David M. Hazai, Eszter Mao, Qingcheng PLoS One Research Article 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. Public Library of Science 2011-10-04 /pmc/articles/PMC3186768/ /pubmed/21991360 http://dx.doi.org/10.1371/journal.pone.0025815 Text en Bikadi et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Bikadi, Zsolt
Hazai, Istvan
Malik, David
Jemnitz, Katalin
Veres, Zsuzsa
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
title Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein
title_full Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein
title_fullStr Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein
title_full_unstemmed Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein
title_short Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein
title_sort predicting p-glycoprotein-mediated drug transport based on support vector machine and three-dimensional crystal structure of p-glycoprotein
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3186768/
https://www.ncbi.nlm.nih.gov/pubmed/21991360
http://dx.doi.org/10.1371/journal.pone.0025815
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