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A BW Reporter System for Studying Receptor-Ligand Interactions
Published on: January 7, 2019
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Molecular Modeling Approach to Study the PPARγ-Ligand Interactions
Merilin Al Sharif1, Ivanka Tsakovska1, Petko Alov1
1Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria.
Methods in Molecular Biology (Clifton, N.J.)
|May 2, 2019
Summary
This study integrates computational methods to predict liver toxicity from peroxisome proliferator-activated receptor gamma (PPARγ) agonists and identifies natural compounds for potential antidiabetic therapies via PPARγ partial agonism.
Area of Science:
- Computational toxicology
- Drug design
- Pharmacology
Background:
- Peroxisome proliferator-activated receptor gamma (PPARγ) is a key target for metabolic diseases and toxicity.
- Understanding ligand interactions with PPARγ is crucial for drug development and safety assessment.
Purpose of the Study:
- To develop an integrated in silico approach for predictive toxicology and computer-aided drug design.
- To predict PPARγ-mediated hepatotoxicity of full agonists.
- To identify natural antidiabetic compounds acting through PPARγ partial agonism.
Main Methods:
- Adverse outcome pathway development
- Pharmacophore modeling
- Molecular docking
- 3D Quantitative Structure-Activity Relationship (QSAR) analysis
Main Results:
- An integrated in silico approach was established to study PPARγ-ligand interactions.
- The approach successfully predicted potential PPARγ-mediated hepatotoxicity.
- Naturally derived antidiabetic triterpenoids were identified as potential PPARγ partial agonists.
Conclusions:
- The integrated in silico approach supports hazard characterization for PPARγ agonists.
- This method aids in discovering novel therapeutic agents targeting PPARγ.
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