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 mostaggressive and resistant to treatment tumors. this study aims to focus on computational biology to predict thepotential mechanism of five flavonoids: morusin, licoisoflavone a, astrapterocarpan, 4'-hydroxywogonin,and pinocembrin 7-o-beta glucoside. pharmacokinetic properties of selected flavonoids determined bysubjecting to descriptor-based drug-likeness and admet strategies. the compounds' modes of binding topparγ (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 targetspharmacological network was constructed based on the go and kegg pathway analysis. primary screeningoutput displayed that compounds possessed sufficient drug-likeness and act as pparγ partial agonists. mdresults approved stability and binding mode of the compounds in complex with pparγ. as expected by go andkegg pathway enrichment studies, core targets were enriched in the pi3k-akt signaling pathway, indicatingthat certain chemicals may be involved in cancer processes. although much work remains to illuminate efficacyof studied flavonoids in vivo, in silico methodology of our cheminformatics research may be able provideadditional data to pave the way for subsequent experimental verification and a new researches.