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Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities

The hERG (human ether-a-go-go-related gene) encoded potassium ion (K(+)) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinfor...

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Autores principales: Munawar, Saba, Windley, Monique J., Tse, Edwin G., Todd, Matthew H., Hill, Adam P., Vandenberg, Jamie I., Jabeen, Ishrat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176658/
https://www.ncbi.nlm.nih.gov/pubmed/30333745
http://dx.doi.org/10.3389/fphar.2018.01035
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author Munawar, Saba
Windley, Monique J.
Tse, Edwin G.
Todd, Matthew H.
Hill, Adam P.
Vandenberg, Jamie I.
Jabeen, Ishrat
author_facet Munawar, Saba
Windley, Monique J.
Tse, Edwin G.
Todd, Matthew H.
Hill, Adam P.
Vandenberg, Jamie I.
Jabeen, Ishrat
author_sort Munawar, Saba
collection PubMed
description The hERG (human ether-a-go-go-related gene) encoded potassium ion (K(+)) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC(50)) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC(50)) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC(50)) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC(50)) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG.
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spelling pubmed-61766582018-10-17 Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities Munawar, Saba Windley, Monique J. Tse, Edwin G. Todd, Matthew H. Hill, Adam P. Vandenberg, Jamie I. Jabeen, Ishrat Front Pharmacol Pharmacology The hERG (human ether-a-go-go-related gene) encoded potassium ion (K(+)) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC(50)) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC(50)) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC(50)) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC(50)) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG. Frontiers Media S.A. 2018-09-19 /pmc/articles/PMC6176658/ /pubmed/30333745 http://dx.doi.org/10.3389/fphar.2018.01035 Text en Copyright © 2018 Munawar, Windley, Tse, Todd, Hill, Vandenberg and Jabeen. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Munawar, Saba
Windley, Monique J.
Tse, Edwin G.
Todd, Matthew H.
Hill, Adam P.
Vandenberg, Jamie I.
Jabeen, Ishrat
Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities
title Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities
title_full Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities
title_fullStr Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities
title_full_unstemmed Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities
title_short Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities
title_sort experimentally validated pharmacoinformatics approach to predict herg inhibition potential of new chemical entities
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176658/
https://www.ncbi.nlm.nih.gov/pubmed/30333745
http://dx.doi.org/10.3389/fphar.2018.01035
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