Exploring the cytotoxic potential of biflavones of Araucaria cunninghamii: Precise identification combined by LC-HRMS-metabolomics and database mining, targeted isolation, network pharmacology, in vitro cytotoxicity, and docking studies.
Bharat SahuSanheeta ChakrabartyVaishali SainiMeenakshi KandpalBharat GoelSanju KumariIjaz AhmedHem Chandra JhaShreyans K JainPublished in: Chemical biology & drug design (2024)
The leaves of Araucaria cunninghamii are known to be nonedible and toxic. Previous studies have identified biflavones in various Araucaria species. This study aimed to investigate the in vitro cytotoxicity of the isolated compounds from Araucaria cunninghamii after metabolomics and network pharmacological analysis. Methanol extract of Araucaria cunninghamii leaves was subjected to bioassay-guided fractionation. The active fraction was analyzed using LC-HRMS, through strategic database mining, by comparing the data to the Dictionary of Natural Products to identify 12 biflavones, along with abietic acid, beta-sitosterol, and phthalate. Eight compounds were screened for network pharmacology study, where in silico ADME analysis, prediction of gene targets, compound-gene-pathway network and hierarchical network analysis, protein-protein interaction, KEGG pathway, and Gene Ontology analyses were done, that showed PI3KR1, EGFR, GSK3B, and ABCB1 as the common targets for all the compounds that may act in the gastric cancer pathway. Simultaneously, four biflavones were isolated via chromatography and identified through NMR as dimeric apigenin with varying methoxy substitutions. Cytotoxicity study against the AGS cell line for gastric cancer showed that AC1 biflavone (IC 50 90.58 μM) exhibits the highest cytotoxicity and monomeric apigenin (IC 50 174.5 μM) the lowest. Besides, the biflavones were docked to the previously identified targets to analyze their binding affinities, and all the ligands were found to bind with energy ≤-7 Kcal/mol.
Keyphrases
- network analysis
- mass spectrometry
- protein protein
- genome wide
- small cell lung cancer
- small molecule
- copy number
- gene expression
- epidermal growth factor receptor
- molecular docking
- drug delivery
- deep learning
- climate change
- simultaneous determination
- transcription factor
- adverse drug
- dna methylation
- binding protein
- anti inflammatory
- case control
- data analysis
- high resolution mass spectrometry