In silico analysis of the antidiabetic terpenoid acankoreagenin binding to PPARγ.
Gérard VergotenChristian BaillyPublished in: In silico pharmacology (2021)
Acankoreagenin (ACK) is a lupane triterpene found in several Acanthopanax and Schefflera plant species. ACK, also known as acankoreanogenin or HLEDA, bears a major structural analogy with other lupane triterpenoids such as impressic acid (IA) and the largely used phytochemical betulinic acid (BA). These compounds display marked anti-inflammatory, anti-diabetes, and anti-cancer properties. BA can form stable complexes with the peroxisome proliferator-activated receptor gamma (PPARγ). The tridimensional structure of the BA-PPARγ complex was used to perform a molecular docking analysis of the binding of ACK and IA to the protein. The 3-hydroxyl epimers (R/S) of each natural product were also modeled to examine the role of the C3-OH stereochemistry that distinguishes BA [3(S)] from ACK and AI [3(R)]. Calculations indicate that ACK can form more stable complexes with PPARγ than BA, upon insertion of the drug into the same binding pocket. The inversion of the C3-OH stereochemistry is not an obstacle for binding and the additional carboxy group of ACK at C23 position seems to reinforce the protein interaction. The 3-hydroxyl group does not play a major role in the geometry of the protein-drug complex, which is preserved between BA and ACK. Additional structure-binding relationships are provided, through the evaluation of the PPARγ binding capacity of ACK derivatives. Binding of ACK to PPARγ would account for its marked antidiabetic effect, at least partially. ACK can be used as a platform to design new antidiabetic compounds.
Keyphrases
- molecular docking
- binding protein
- insulin resistance
- dna binding
- fatty acid
- molecular dynamics simulations
- type diabetes
- protein protein
- cardiovascular disease
- anti inflammatory
- amino acid
- small molecule
- artificial intelligence
- high throughput
- single cell
- machine learning
- adipose tissue
- weight loss
- drug induced
- electronic health record
- monte carlo