An Integrated Computational Strategy for Effective-Component Discovery of Some Flavonoids’ in Treatment of Melanoma

The majority of skin cancer-related deaths are caused by melanoma, which is one of the most aggressive and resistant to treatment tumors. This study aims to focus on computational biology to predict the potential mechanism of five Flavonoids: Morusin, Licoisoflavone A, Astrapterocarpan, 4 -Hydroxywogonin, and Pinocembrin 7-O-beta glucoside. Pharmacokinetic properties of selected flavonoids determined by subjecting to descriptor-based drug-likeness and ADMET strategies. The compounds modes of binding to PPARγ (a critical transcription factor) were then evaluated using docking and molecular dynamics (MD) simulation. Potential protein targets of selected compounds and melanoma were predicted. Core targets pharmacological network was constructed based on the GO and KEGG pathway analysis. Primary screening output displayed that compounds possessed sufficient drug-likeness and act as PPARγ partial agonists. MD results approved stability and binding mode of the compounds in complex with PPARγ. As expected by GO and KEGG pathway enrichment studies, core targets were enriched in the PI3K-Akt signaling pathway, indicating that certain chemicals may be involved in cancer processes. Although much work remains to illuminate efficacy of studied flavonoids in vivo, in silico methodology of our cheminformatics research may be able provide additional data to pave the way for subsequent experimental verification and a new researches.