Exploring the Molecular Mechanism of Action of Yinchen Wuling Powder for the Treatment of Hyperlipidemia, Using Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Abstract

Background: Yinchen Wuling powder is often used to treat clinical hyperlipidemia, although its mechanism of action remains unclear. In this study, we aimed to investigate the active ingredients found in Yinchen Wuling powder and find its mechanism of action when treating hyperlipidemia, using a combination of network pharmacology, molecular docking, and molecular dynamics simulation approaches.

Methods: The TCMSP database was used to obtain the principle active ingredients found in Yinchen Wuling powder and the NCBI and DisGeNet databases were used to obtain the main target genes involved in hyperlipidemia, and the intersectional targets were obtained by EXCEL. We also used Cytoscape 3.7.2 software to construct a "Traditional Chinese Medicine-Active Ingredient-Target" network and use STRING platform to conduct "protein-protein interactional" (PPI) analyses on the intersection targets. Bioconductor software and RX 64 4.0.0 software were then used to perform GO functional enrichment analysis and KEGG pathway enrichment analysis on the targets. Molecular docking of core protein-ligand interactions was modeled using AutoDock Vina software. A simulation of molecular dynamics was conducted for the optimal core protein-ligand obtained by molecular docking using Amber18 software.

Results: A total of 63 active ingredients were found in Yinchen Wuling powder, corresponding to 175 targets, 508 hyperlipidemia targets, and 55 intersection targets in total. Cytoscape 3.7.2 showed that the key active ingredients were quercetin, isorhamnetin, taxifolin, demethoxycapillarisin, and artepillin A. The PPI network showed that the key proteins involved were AKT1, IL6, VEGFA, and PTGS2. GO enrichment analysis found that genes were enriched primarily in response to oxygen levels and nutrient levels of the vesicular lumen and were associated with membrane rafts. These were mainly enriched in AGE-RAGE (advanced glycation end products-receptor for advanced glycation end products) signaling pathway in diabetic complications, fluid shear stress, and atherosclerosis, as well as other pathways. The molecular docking results indicated key binding activity between PTGS2-quercetin, PTGS2-isorhamnetin, and PTGS2-taxifolin. Results from molecular dynamics simulations showed that PTGS2-quercetin, PTGS2-isorhamnetin, and PTGS2-taxifolin bound more stably, and their binding free energies were PTGS2-quercetin -29.5 kcal/mol, PTGS2-isorhamnetin -32 kcal/mol, and PTGS2-taxifolin -32.9 kcal/mol.

Conclusion: This study is based on network pharmacology and reveals the potential molecular mechanisms involved in the treatment of hyperlipidemia by Yinchen Wuling powder.

Figure 1

Workflow chart of YCWL for the potential treatment of hyperlipidemia based on network pharmacology.

Figure 2

Venn diagram of YCLW (blue) and hyperlipidemia genes (yellow).

Figure 3

“TCM-Active Ingredients-Target” Network. (orange rectangle represents hyperlipidemia; blue rectangle represents YCWL; red triangle represents traditional Chinese medicine; yellow rectangle represents active ingredients; cyan-blue inverted triangle represents target genes).

Figure 4

The PPI network for 55 overlapping genes (the sizes and colors of the nodes and lines are illustrated from large to small and blue to red in descending order of degree values).

Figure 5

The degree value of the top 30 genes in the PPI network.

Figure 6

Clusters of the YCLW-hyperlipidemia network (red represents clusters 1, yellow represents clusters 2, and green represents clusters 3).

Figure 7

KEGG enrichment analysis. The length represents the number of target genes, and the color represents the level of significance.

Figure 8

Pathway-target” network (the triangle represents the pathway，Rectangle represents the target.)

Figure 9

Molecular docking diagram. Molecular models of the binding of quercetin, taxifolin, and isorhamnetin with PTGS2, the results shown as 3D and 2D diagrams. (a) PTGS2-quercetin (-11.08 kcal/mol), (b) PTGS2-taxifolin (-10.5 kcal/mol), and (c) PTGS2-isorhamnetin (-10.14 kcal/mol).

Figure 10

RMSD plot during molecular dynamics simulations. (a) The RMSD of PTGS2-quercetin. (b) The RMSD of PTGS2-taxifolin. (c) The RMSD of PTGS2-isorhamnetin.

Figure 11

Rog plot during molecular dynamics simulations. (a) The Rog of PTGS2-quercetin. (b) The Rog of PTGS2-taxifolin. (c) The Rog of PTGS2-isorhamnetin.

Figure 12

RMSF plot during molecular dynamics simulations. (a) The RMSF of PTGS2-quercetin. (b) The RMSF of PTGS2-taxifolin. (c) The RMSF of PTGS2-isorhamnetin.

Figure 13

(a) 3D and 2D diagrams of PTGS2-quercetin interaction. (b) 3D and 2D diagrams of PTGS2- taxifolin interaction. (c) 3D and 2D diagrams of PTGS2-isorhamnetin interactions.