Network pharmacology-based anti-pancreatic cancer potential of kaempferol and catechin of Trema orientalis L. through computational approach.
Shreni AgrawalRicha DasAmit Kumar SinghPradeep KumarPraveen Kumar ShuklaIndrani BhattacharyaAmit Kumar TripathiSunil Kumar MishraKavindra Nath TiwariPublished in: Medical oncology (Northwood, London, England) (2023)
In pancreatic cancer, healthy cells in the pancreas begin to malfunction and proliferate out of control. According to our conventional knowledge, many plants contain several novel bioactive compounds, having pharmaceutical applications for the treatment of disease like pancreatic cancer. The methanolic fraction of fruit extract of Trema orientalis L. (MFETO) was analysed through HRMS. In this in silico study, pharmacokinetic and physicochemical properties of the identified flavonoids from MFETO were screened out by ADMET analysis. Kaempferol and catechin followed Lipinski rules and showed no toxicity in Protox II. Targets of these compounds were taken from SwissTarget prediction and TCMSP whilst targets for pancreatic cancer were taken from GeneCards and DisGeNET databases. The protein-protein interaction (PPI) network of common genes was generated through STRING and then exported to the Cytoscape to get top 5 hub genes (AKT1, SRC, EGFR, TNF, and CASP3). The interaction between compounds and hub genes was analysed using molecular docking, and high binding affinity between them can be visualised by Biovia discovery studio visualizer. Our study shows that, five hub genes related to pancreatic cancer play an important role in tumour growth induction, invasion and migration. Kaempferol effectively check cell migration by inhibiting ERK1/2, EGFR-related SRC, and AKT pathways by scavenging ROS whilst catechin inhibited TNFα-induced activation and cell cycle arrest at G1 and G2/M phases by induction of apoptosis of malignant cells. Kaempferol and catechin containing MFETO can be used for formulation of potent drugs for pancreatic cancer treatment in future.
Keyphrases
- high throughput
- cell cycle arrest
- molecular docking
- cell death
- pi k akt
- bioinformatics analysis
- signaling pathway
- cell migration
- protein protein
- induced apoptosis
- tyrosine kinase
- cell proliferation
- genome wide
- small cell lung cancer
- oxidative stress
- epidermal growth factor receptor
- network analysis
- rheumatoid arthritis
- small molecule
- endoplasmic reticulum stress
- genome wide identification
- gene expression
- dna damage
- molecular dynamics simulations
- healthcare
- drug induced
- risk assessment
- diabetic rats
- anti inflammatory
- machine learning
- current status
- binding protein