Structural characterization of plasmodial aminopeptidase: a combined molecular docking and QSAR-based in silico approaches

Virtual identification of novel peroxisome proliferator-activated receptor (PPAR) α/δ dual antagonist by 3D-QSAR, molecule docking, and molecule dynamics simulation

The therapeutic potential of PPARs antagonists extends beyond diabetes. PPARs antagonists represent a new drug class that holds promise as a broadly applicable therapeutic approach for cancer treatment. Thus, there is a strong need to develop a rational design strategy for creating PPARs antagonists. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) models of PPARα receptor (CoMFA-1, q ² = 0.636, r ² = 0.953; CoMSIA-1, q ² = 0.779, r ² = 0.999) and PPARδ receptor (CoMFA-2, q ² = 0.624, r ² = 0.906; CoMSIA-2, q ² = 0.627, r ² = 0.959) were successfully constructed using 35 triazolone ring derivatives. Contour map analysis revealed that the electrostatic and hydrophobic fields played vital roles in the bioactivity of dual antagonists. Molecular docking studies suggested that the hydrogen bonding, electrostatic and hydrophobic interactions all influenced the binding of receptor-ligand complex. Based on the information obtained above, we designed a series of compounds. The docking results were mutually validated with 3D-QSAR results. Three-dimensional-QSAR and absorption, distribution, metabolism, excretion and toxicity (ADMET) predictions indicated that 19 newly designed compounds possessed excellent biological activity and physicochemical properties. In summary, this research could provide theoretical guidance for the structural optimization of novel PPARα and δ dual antagonists. Communicated by Ramaswamy H. Sarma.