Computational investigation reveals Picrasidine C as selective PPARα lead: binding pattern, selectivity mechanism and ADME/tox profile. Issue 18 (11th December 2020)

• Record Type: Journal Article
• Authors: Li, Fangfei; Wang, Hanxun; Wang, Ying; Feng, Shasha; Hu, Baichun; Zhang, Xiangyu; Wang, Jian; Li, Wei; Cheng, Maosheng
• Is Part Of: Journal of biomolecular structure & dynamics. Volume 38:Issue 18(2020)
• Page Start: 5401
• Page End: 5418
• Publication Date: 2020-12-11
• Subjects: Picrasidine C -- PPARα agonist -- molecular docking -- molecular dynamics simulation -- ADME/Tox prediction; Biomolecules -- Periodicals; Molecular structure -- Periodicals; Molecular Biology -- Periodicals; Biomechanics -- Periodicals; 572
• DOI: 10.1080/07391102.2019.1699861
• Languages: English
• ISSNs: 0739-1102

Abstract

Abstract: Natural products and their derivatives have been recognized as an important source of therapeutic agents for many years. Previously we isolated a dimeric β-carboline-type alkaloid Picrasidine C from the root of Picrasma quassioides as subtype-selective peroxisome proliferator-activated receptor α (PPARα) agonist. In order to modify this natural product for better affinity and druggability, we investigated a series of properties exhibited by Picrasidine C, such as its binding mode with PPARα, the selectivity mechanism over PPARγ, as well as ADME/Tox profile through computational methods including sequence alignment, molecular docking, pharmacophore modeling and molecular dynamics simulations. The detailed information of binding pattern and affinity for Picrasidine C elucidated here will be valuable for chemical modification. Besides, the steric hindrance of residue Phe363 in PPARγ pocket was speculated as the main isoform selectivity mechanism for Picrasidine C, which would be helpful for the design of selective derivatives. ADME/Tox prediction was conducted to avoid potential undesirable pharmacokinetic properties for reducing the risk of failure. Finally, novel skeletons were derived from lead compound by core hopping method, validated through molecular dynamic simulations and MM-GBSA calculation. In short, the information obtained from computational strategy would be valuable for us to find more potent, safe and selective PPARα agonists during structural optimization. Graphical Abstract: Highlights: The interactions between PPARα and Picrasidine C was thoroughly investigated by means of molecular docking, binding free energy calculation, molecular dynamics simulation. Selectivity mechanism between PPAR isoforms was analyzed with the aim to maintain or improve the selectivity of Picrasidine C depending on the difference between PPARα/γ cavities. The feasibility of Picrasidine C as a subtype-selective lead targeting PPARα was investigate to promote the further development of subtype-selective PPARα agonists. New analogs of Picrasidine C were designed through core hopping, and were validated through molecular dynamics simulations and MM-GBSA calculation. Communicated by Ramaswamy H. Sarma