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Combinatorial Chemistry & High Throughput Screening

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ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

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Research Article

Exploring Dual Agonists for PPARα/γ Receptors using Pharmacophore Modeling, Docking Analysis and Molecule Dynamics Simulation

Author(s): Ting-Ting Ding, Ya-Ya Liu, Li-Ming Zhang, Jia-Rui Shi, Wei-Ren Xu, Shao-Yong Li* and Xian-Chao Cheng*

Volume 25, Issue 9, 2022

Published on: 28 June, 2021

Page: [1450 - 1461] Pages: 12

DOI: 10.2174/1386207324666210628114216

Price: $65

Abstract

Background: The Peroxisome Proliferator-Activated Receptors (PPARs) are ligandactivated 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 accepted ligand structure was modified and replaced to obtain 12 new compounds. Using molecular docking, ADMET and molecular dynamics simulation methods to screen the designed 12 ligands, analyze their docking scores when they bind to the PPARα/γ dual targets, their stability and pharmacological properties when they bind to the PPARα/γ dual targets.

Results: We performed pharmacophore-based virtual screening for 22949 molecules in Ligand Expo Components-pub database. The compounds that were superior to the original ligand were performed structural analysis and modification, and a series of compounds with novel structures were designed. Using precise docking, ADMET prediction and molecular dynamics methods to screen and verify newly designed compounds, and the above compounds show higher docking scores and lower side effects.

Conclusion: 9 new PPARα/γ agonists were obtained by pharmacophore modeling, docking analysis and molecular dynamics simulation.

Keywords: PPARalpha/gamma, agonist, receptor-ligand based pharmacophore, docking, ADMET, molecular dynamics.

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