Exploration of the molecular mechanism of Polygonati Rhizoma in the treatment of hyperlipidemia based on network pharmacology and molecular docking

The purpose of this study was to study the potential mechanism of Polygonati Rhizoma for treating hyperlipidemia (HLP) based on network pharmacology and molecular docking. Predicted potential targets and signaling pathway networks were established between candidate active compounds and therapeutic targets of HLP. The Traditional Chinese Medicine Systems Pharmacology and Analysis Platform database is a Chinese medicine collection and analysis system, and various target genes were identified for the treatment of HLP. The treatment data on HLP in the Human Gene Card, Online Mendelian Inheritance in Man, and the Therapeutic Target Database were input into disease targets. The 4 databases in the treatment of HLP were input into Venny 2.1.0 to screen the core targets of Polygonati Rhizoma in the treatment of HLP. The "drug-ingredient-target" network model was built with Cytoscape 3.9.1 software. In order to analyze protein-protein interaction networks, the Search Tool for Retrieval of Interacting Genes/Proteins database was updated with the added key targets. To identify functional annotations and path enrichment associated with potential genes, the Metascape database was used for path enrichment analysis of data from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. A docking software program, Autodock Tools, was used to analyze and confirm chemically high-quality drug elements and key targets. In this study, 14 chemically active components were identified, along with 370 drug targets and 128 drug-HLP targets that are common to both drugs and HLPs. Protein-protein interaction network analysis with degree ordering was used to screen for key gene targets such as retinoid X receptor alpha, PIK3R1, and serine/threonine-protein kinase AKT. As an end result of enrichment analysis, these compounds modulate phosphatidylinositol 3-kinase-Akt signaling pathways, lipid and atherosclerosis, endocrine resistance, and other pathways through interventions in biological processes aimed at treating HLP. Based on the docking results, the binding energies between active components and the core targets ranged from -6.94 to -8.55 kcal·mol-1 and there were a number of high-binding targets in the regulatory network.