Discovery of new nanomolar peroxisome proliferator-activated receptor γ activators via elaborate ligand-based modeling

被引：27

作者：

Al-Najjar, Bela O. ^{[2
]}

Wahab, Habibah A. ^{[2
,3
]}

Muhammad, Tengku Sifzizul Tengku ^{[3
,4
]}

Shu-Chien, Alexander Chong ^{[3
,5
]}

Noruddin, Nur Adelina Ahmad ^{[3
]}

Taha, Mutasem O. ^{[1
]}

机构：

[1] Univ Jordan, Fac Pharm, Dept Pharmaceut Sci, Drug Discovery Unit, Amman, Jordan

[2] Univ Sains Malaysia, Sch Pharmaceut Sci, Pharmaceut Design & Simulat PhDS Lab, Minden 11800, Pulau Pinang, Malaysia

[3] SAINS USM, Minist Sci Technol & Innovat, Malaysian Inst Pharmaceut & Nutraceut, Persiaran Bukit Jambul 11900, Pulau Pinang, Malaysia

[4] Univ Malaysia Terengganu, Dept Biol Sci, Kuala Terengganu 21030, Terengganu, Malaysia

[5] Univ Sains Malaysia, Sch Biol Sci, George Town 11800, Malaysia

来源：

EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY | 2011年 / 46卷 / 06期

关键词：

Peroxisome Proliferator-activated receptor gamma; Pharmacophore modeling; Quantitative structure-activity relationship; In silico screening; Type 2 diabetes mellitus; PPAR-GAMMA; BIOLOGICAL EVALUATION; STRUCTURAL INSIGHT; DRUG DESIGN; PHARMACOPHORE; AGONISTS; POTENT; DOCKING; QSAR; INHIBITORS;

D O I：

10.1016/j.ejmech.2011.03.040

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

Peroxisome Proliferator-Activated Receptor gamma (PPAR gamma) activators have drawn great recent attention in the clinical management of type 2 diabetes mellitus, prompting several attempts to discover and optimize new PPAR gamma activators. With this in mind, we explored the pharmacophoric space of PPAR gamma using seven diverse sets of activators. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 20 physicochemical descriptors capable of accessing self-consistent and predictive quantitative structure activity relationship (QSAR) (r(71)(2) = 0.80, F = 270.3, r(LOO)(2) = 0.73, r(PRESS)(2) against 17 external test inhibitors = 0.67). Three orthogonal pharmacophores emerged in the QSAR equation and were validated by receiver operating characteristic (ROC) curves analysis. The models were then used to screen the national cancer institute (NCI) list of compounds. The highest-ranking hits were tested in vitro. The most potent hits illustrated EC50 values of 15 and 224 nM. (C) 2011 Elsevier Masson SAS. All rights reserved.

引用

页码：2513 / 2529

页数：17

共 89 条

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