Title:Comparative Computational Screening of Natural-based Partial Agonists
for PPARγ Receptor
Volume: 19
Issue: 6
Author(s): Leila Moradihaghgou*, Reinhard Schneider*, Bahram Maleki Zanjani and Taher Harkinezhad
Affiliation:
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Zanjan, Zanjan, P.O. BOX.
4537138791, Iran
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval,
House of Biomedicine II, 6 avenue du Swing, Belvaux L-4367, Luxembourg
Keywords:
Flavonoids, PPARγ, cancer, in silico drug discovery, molecular dynamics, pharmacological network.
Abstract:
Introduction: The nuclear transcription factor PPARγ, which can modulate cell growth
via proliferation and apoptosis-related mechanisms, is a promising target in cancer therapy. This
study aims to focus on PPARγ as the target and use virtual screening to find hits.
Methods: A set of 5,677 flavonoid compounds were filtered by subjecting them to descriptor-based
drug-likeness and ADMET strategies to discover drug-like compounds. The candidates' modes of
binding to PPARγ were then evaluated using docking and MD simulation. PharmMapper was used to
identify the potential targets of selected hits. The pharmacological network was constructed based on
the GO and KEGG pathway analysis.
Results: In primary screening, 3,057 compounds met various drug-likeness criteria and docked well
as partial agonists in the PPARγ-LBD. Five compounds (euchrenone b1, kaempferol-7-Orhamnoside,
vincetoxicoside B, morusin, and karanjin) were selected with the use of ADMET profiles
for further MD simulation investigation. Based on the PharmMapper findings, 52 proteins were
then submitted to GO and KEGG enrichment analysis. As expected by GO and KEGG pathway enrichment
studies, core targets were enriched in the PI3K-Akt signaling pathway (p < 0.01), indicating
that certain chemicals may be involved in cancer processes.
Conclusion: Our results suggested that the selected compounds might have sufficient drug-likeness,
pharmacokinetics, and in silico bioactivity by acting as PPARγ partial agonists. Although much work
remains to illuminate extensive cancer therapeutic/ chemopreventive efficacy of flavonoids in vivo,
in silico methodology of our cheminformatics research may be able to provide additional data regarding
the efficacy and safety of potential candidates for therapeutic targets.
