Identification of novel peroxisome proliferator-activated receptor-gamma (PPAR[gamma]) agonists using molecular modeling method

Peroxisome proliferator-activated receptor-gamma (PPAR?) plays a critical role in lipid and glucose homeostasis. It is the target of many drug discovery studies, because of its role in various disease states including diabetes and cancer. Thiazolidinediones, a synthetic class of agents that work by...

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Main Author: Kumar, Alan Prem
Format: Journal Article
Published: Kluwer Academic Publishers 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/8676
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author Kumar, Alan Prem
author_facet Kumar, Alan Prem
author_sort Kumar, Alan Prem
building Curtin Institutional Repository
collection Online Access
description Peroxisome proliferator-activated receptor-gamma (PPAR?) plays a critical role in lipid and glucose homeostasis. It is the target of many drug discovery studies, because of its role in various disease states including diabetes and cancer. Thiazolidinediones, a synthetic class of agents that work by activation of PPAR?, have been used extensively as insulin-sensitizers for the management of type 2 diabetes. In this study, a combination of QSAR and docking methods were utilised to perform virtual screening of more than 25 million compounds in the ZINC library. The QSAR model was developed using 1,517 compounds and it identified 42,378 potential PPAR? agonists from the ZINC library, and 10,000 of these were selected for docking with PPAR? based on their diversity. Several steps were used to refine the docking results, and finally 30 potentially highly active ligands were identified. Four compounds were subsequently tested for their in vitro activity, and one compound was found to have a K i values of <5 µM.
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spelling curtin-20.500.11937-86762017-09-13T14:50:55Z Identification of novel peroxisome proliferator-activated receptor-gamma (PPAR[gamma]) agonists using molecular modeling method Kumar, Alan Prem Docking QSAR PPAR? Peroxisome proliferator-activated receptor-gamma (PPAR?) plays a critical role in lipid and glucose homeostasis. It is the target of many drug discovery studies, because of its role in various disease states including diabetes and cancer. Thiazolidinediones, a synthetic class of agents that work by activation of PPAR?, have been used extensively as insulin-sensitizers for the management of type 2 diabetes. In this study, a combination of QSAR and docking methods were utilised to perform virtual screening of more than 25 million compounds in the ZINC library. The QSAR model was developed using 1,517 compounds and it identified 42,378 potential PPAR? agonists from the ZINC library, and 10,000 of these were selected for docking with PPAR? based on their diversity. Several steps were used to refine the docking results, and finally 30 potentially highly active ligands were identified. Four compounds were subsequently tested for their in vitro activity, and one compound was found to have a K i values of <5 µM. 2014 Journal Article http://hdl.handle.net/20.500.11937/8676 10.1007/s10822-014-9791-6 Kluwer Academic Publishers restricted
spellingShingle Docking
QSAR
PPAR?
Kumar, Alan Prem
Identification of novel peroxisome proliferator-activated receptor-gamma (PPAR[gamma]) agonists using molecular modeling method
title Identification of novel peroxisome proliferator-activated receptor-gamma (PPAR[gamma]) agonists using molecular modeling method
title_full Identification of novel peroxisome proliferator-activated receptor-gamma (PPAR[gamma]) agonists using molecular modeling method
title_fullStr Identification of novel peroxisome proliferator-activated receptor-gamma (PPAR[gamma]) agonists using molecular modeling method
title_full_unstemmed Identification of novel peroxisome proliferator-activated receptor-gamma (PPAR[gamma]) agonists using molecular modeling method
title_short Identification of novel peroxisome proliferator-activated receptor-gamma (PPAR[gamma]) agonists using molecular modeling method
title_sort identification of novel peroxisome proliferator-activated receptor-gamma (ppar[gamma]) agonists using molecular modeling method
topic Docking
QSAR
PPAR?
url http://hdl.handle.net/20.500.11937/8676