Network pharmacology and molecular docking study on the treatment of polycystic ovary syndrome with angelica sinensis- radix rehmanniae drug pair

Abstract

This study aimed to investigate the angelica sinensis - radix rehmanniae (AR) role in polycystic ovary syndrome (PCOS), employing network pharmacology and molecular docking techniques for active ingredient, targets, and pathway prediction. AR active components were obtained through TCMSP platform and literature search. The related targets of AR and PCOS were obtained through the disease and Swiss Target Prediction databases. An “active ingredient-target” network map was constructed using Cytoscape software, and gene ontology and Kyoto encyclopedia of genes and genomes enrichment analysis was conducted through Hiplot. Finally, Auto Dock Tools software was used to conduct molecular docking between active ingredients and core targets. The main bioactive ingredients of AR in the treatment of PCOS are acteoside, baicalin, caffeic acid, cistanoside F, geniposide, etc. These ingredients involve 10 core targets, such as SRC, HSP90AA1, STAT3, MAPK1, and JUN. The effect of AR on anti-PCOS mainly involves the AGE-RAGE signaling pathway, Relaxin signaling pathway, TNF signaling pathway, and ErbB signaling pathway. Molecular docking results showed that the main active components and key targets of AR could be stably combined. AR can improve hyperandrogen status, regulate glucose homeostasis, and correct lipid metabolism and other physiological processes through multi-component, multi-target, and multi-pathway. Thus, it could play a significant role in PCOS treatment. The results of our study provide a scientific foundation for basic research and clinical applications of AR for the treatment of PCOS.