Oncotarget

Research Papers:

Molecular docking, 3D-QSAR and structural optimization on imidazo-pyridine derivatives dually targeting AT1 and PPARγ

Jun Zhang, Qing-Qing Hao, Xin Liu, Zhi Jing, Wen-Qing Jia, Shu-Qing Wang, Wei-Ren Xu, Xian-Chao Cheng _ and Run-Ling Wang

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Oncotarget. 2017; 8:25612-25627. https://doi.org/10.18632/oncotarget.15778

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Abstract

Jun Zhang1, Qing-Qing Hao1, Xin Liu1, Zhi Jing1, Wen-Qing Jia1, Shu-Qing Wang1, Wei-Ren Xu2, Xian-Chao Cheng1, Run-Ling Wang1

1Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin 300070, China

2Tianjin Key Laboratory of Molecular Design and Drug Discovery, Tianjin Institute of Pharmaceutical Research, Tianjin 300193, China

Correspondence to:

Xian-Chao Cheng, email: [email protected]

Run-Ling Wang, email: [email protected]

Keywords: imidazo-\pyridines, AT1, PPARγ, molecular docking, 3D-QSAR

Received: December 20, 2016     Accepted: January 27, 2017     Published: February 28, 2017

ABSTRACT

Telmisartan, a bifunctional agent of blood pressure lowering and glycemia reduction, was previously reported to antagonize angiotensin II type 1 (AT1) receptor and partially activate peroxisome proliferator-activated receptor γ (PPARγ) simultaneously. Through the modification to telmisartan, researchers designed and obtained imidazo-\pyridine derivatives with the IC50s of 0.49~94.1 nM against AT1 and EC50s of 20~3640 nM towards PPARγ partial activation. For minutely inquiring the interaction modes with the relevant receptor and analyzing the structure-activity relationships, molecular docking and 3D-QSAR (Quantitative structure-activity relationships) analysis of these imidazo-\pyridines on dual targets were conducted in this work. Docking approaches of these derivatives with both receptors provided explicit interaction behaviors and excellent matching degree with the binding pockets. The best CoMFA (Comparative Molecular Field Analysis) models exhibited predictive results of q2=0.553, r2=0.954, SEE=0.127, r2pred=0.779 for AT1 and q2=0.503, r2=1.00, SEE=0.019, r2pred=0.604 for PPARγ, respectively. The contour maps from the optimal model showed detailed information of structural features (steric and electrostatic fields) towards the biological activity. Combining the bioisosterism with the valuable information from above studies, we designed six molecules with better predicted activities towards AT1 and PPARγ partial activation. Overall, these results could be useful for designing potential dual AT1 antagonists and partial PPARγ agonists.


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