Exploring the Mechanism of Gentiana in Treating Pancreatic Cancer Based on Network Pharmacology and Molecular Docking Techniques

Abstract

Objective: This study aims to investigate the mechanism of Gentiana in treating pancreatic cancer using network pharmacology and molecular docking techniques. Methods: Active compounds of Gentiana were screened from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. The 3D structures of the active compounds were downloaded from the PubChem database. Reverse docking was performed using the PharmMapper database to identify potential target proteins. Differential gene expression data related to colorectal cancer were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes were selected. Venn diagram analysis was employed to identify common genes between the protein targets and differentially expressed genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool. Molecular docking was performed using ChemDraw 20.0, AutoDock, and PyMOL. Results: A total of 72 common genes and 15 signaling pathways were identified from the reverse docking data of Gentiana and the pancreatic cancer dataset (GSE196009). Molecular docking results demonstrated favorable binding energies between the active compounds of Gentiana and proteins 1og5, 1pq2, 2bxr, 2bk3, 1u3w, 1wma, 1wuu, 1tdi, 1mlw, 1egc, 1s1p, 1f12, 1m51, 1kqu, 1ls6, 1ry0, 1nhx, and 1db4. Conclusion: Gentiana may exert its therapeutic effects on pancreatic cancer through a multi-component, multi-target, and multi-pathway mechanism.