Structure-guided identification of dipeptides modulating PPARα-associated lipid metabolism

Area of Science:

• Biochemistry
• Molecular Biology
• Metabolic Research

Background:

• The precise structural mechanisms by which dipeptides influence Peroxisome proliferator-activated receptor alpha (PPARα) activity are not well understood.
• PPARα plays a crucial role in regulating lipid metabolism and is a target for treating metabolic disorders.

Purpose of the Study:

• To investigate the structural basis of dipeptide interactions with PPARα.
• To identify specific dipeptides that can modulate PPARα activity and impact lipid metabolism.
• To evaluate the utility of computational structure-based prediction for discovering novel PPARα modulators.

Main Methods:

• Utilized AlphaFold2 for structure-based prediction of dipeptide-PPARα interactions.
• Employed HepG2 cell models to assess the functional effects of candidate dipeptides on lipid metabolism, specifically cholesterol accumulation.
• Analyzed the impact of Ile-His, Phe-Ala, and Ala-Pro dipeptides on cellular cholesterol levels.

Main Results:

• AlphaFold2 predicted Ile-His as a potential ligand interacting with a novel alternative binding site on PPARα.
• Experimental validation in HepG2 cells showed that Ile-His and Phe-Ala significantly reduced cholesterol accumulation.
• The dipeptide Ala-Pro demonstrated no significant effect on cholesterol accumulation in the tested model.

Conclusions:

• Structure-based prediction using tools like AlphaFold2 is a valuable hypothesis-generating strategy for identifying dipeptides that modulate PPARα.
• Specific dipeptides, such as Ile-His and Phe-Ala, show potential for regulating lipid metabolism by influencing PPARα activity.
• These findings open avenues for developing novel therapeutic strategies targeting PPARα for metabolic diseases.