Correlation Between In Silico Docking/Simulation Results and In Vitro MAGL Inhibition Potency of Selected Triterpenes

Area of Science:

• Biochemistry and Molecular Pharmacology
• Computational Chemistry and Drug Discovery

Background:

• Monoacylglycerol lipase (MAGL) is a key enzyme in the endocannabinoid system, degrading 2-arachidonyl glycerol.
• Inhibitors of MAGL, including triterpenes like pristimerin, have demonstrated efficacy in alleviating neuropathic pain in preclinical models.
• Understanding the structure-activity relationship of triterpenes as MAGL inhibitors is crucial for developing novel pain therapeutics.

Purpose of the Study:

• To computationally evaluate the binding affinity and inhibitory potential of various triterpenes against monoacylglycerol lipase (MAGL).
• To correlate in silico findings with in vitro MAGL inhibition data for selected triterpenes.
• To assess the stability and binding site interactions of top-ranking triterpenes using molecular dynamic simulations.

Main Methods:

• In silico molecular docking studies were performed using SwissDock, PyRx-0.8, and CB-Dock2 to predict binding affinity and scores for triterpenes interacting with MAGL.
• Molecular dynamic simulations (MDSs) were employed to assess the stability and dynamic behavior of the triterpene-MAGL complexes.
• Linear regression analysis was used to correlate computational docking parameters with experimentally determined in vitro MAGL inhibition (IC50) values.

Main Results:

• Pristimerin demonstrated superior docking scores, free energy of binding, and affinity compared to euphol, β-amyrin, and α-amyrin in silico.
• Molecular dynamic simulations indicated that pristimerin exhibited the highest stability at the MAGL binding site.
• While pristimerin showed the highest in silico affinity, in vitro assays revealed α-amyrin and β-amyrin as more potent MAGL inhibitors (lower IC50 values).

Conclusions:

• Computational docking and molecular dynamics simulations provide valuable insights into the binding interactions of triterpenes with MAGL.
• The study highlights a significant correlation between in silico predicted binding parameters and in vitro MAGL inhibitory activity.
• These computational approaches can effectively screen triterpenes for MAGL inhibition, guiding future experimental validation and drug development for neuropathic pain.