Exploring dual agonists for PPARα/γ receptors using pharmacophore modeling, docking analysis and molecule dynamics simulation

Author:

Ding Ting-Ting1,Liu Ya-Ya1,Zhang Li-Ming1,Shi Jia-Rui1,Xu Wei-Ren2,Li Shao-Yong1,Cheng Xian-Chao1

Affiliation:

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

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

Abstract

Background: The peroxisome proliferator-activated receptors (PPARs) are ligand-activated transcription factors belonging to the nuclear receptor family. The roles of PPARα in fatty acid oxidation and PPARγ in adipocyte differentiation and lipid storage have been widely characterized. Compounds with dual PPARα/γ activity have been proposed, combining the benefits of insulin sensitization and lipid-lowering into one drug, allowing a single drug to reduce hyperglycemia and hyperlipidemia while preventing the development of cardiovascular complications. Methods: The new PPARα/γ agonists were screened through virtual screening of pharmacophores and molecular dynamics simulations. First, in the article, the constructed pharmacophore was used to screen the Ligand Expo Components-pub database to obtain the common structural characteristics of representative PPARα/γ agonist ligands. Then, the obtained ligand structure was modified and replaced to obtain 12 new compounds. Using molecular docking, ADMET and molecular dynamics simulation methods, the designed 12 ligands were screened, their docking scores were analyzed when they bound to the PPARα/γ dual targets, and also their stability and pharmacological properties were assessed when they were bound to the PPARα/γ dual targets. Results: We performed pharmacophore-based virtual screening for 22949 molecules in the Ligand Expo Components-pub database. Structural analysis and modification were performed on the compounds that were superior to the original ligand , and a series of compounds with novel structures were designed. Using precise docking, ADMET prediction and molecular dynamics methods, newly designed compounds were screened and verified, and the above compounds showed higher docking scores and lower side effects. Conclusion: 9 new PPARα/γ agonists were obtained by pharmacophore modeling, docking analysis and molecule dynamics simulation.

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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