Dataset Information

Network Pharmacology-Based Dissection of the Active Ingredients and Protective Mechanism of the Salvia Miltiorrhiza and Panax Notoginseng Herb Pair against Insulin Resistance.

ABSTRACT: The Salvia miltiorrhiza and Panax notoginseng herb pair (DQ) has been widely utilized in traditional Chinese medicine for the longevity and for preventing and treating cardio-cerebrovascular diseases. Often associated with cardio-cerebrovascular diseases are comorbidities such as insulin resistance. However, the protective mechanisms of DQ against insulin resistance remain not well understood. Through network pharmacology analysis, a total of 94 candidate active compounds selected from DQ (61 from S. miltiorrhiza Bunge and 33 from P. notoginseng (Burk.) F. H. Chen) interacted with 52 corresponding insulin resistance-related targets, which mainly involved insulin resistance and the AMPK signaling pathway. Furthermore, the contribution index calculation results indicated 25 compounds as the principal components of this herb pair against insulin resistance. Among them, ginsenoside F2, protocatechuic acid, and salvianolic acid B were selected and validated to promote glucose consumption through activating AMPK phosphorylation and upregulating GLUT4 in insulin-resistant cell model (HepG2/IR) cells. These findings indicated that DQ has the potential for repositioning in the treatment of insulin resistance mainly through the AMPK signaling pathway.

SUBMITTER: Yang XY

PROVIDER: S-EPMC8280704 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundAstragalus Radix (AR)-Panax notoginseng (PN), a classical herb pair, has shown significant effects in treating diabetic nephropathy (DN). However, the intrinsic mechanism of AR-PN treating DN is still unclear. This study aims to illustrate the mechanism and molecular targets of AR-PN treating DN based on network pharmacology combined with bioinformatics.Materials and methodsThe Traditional Chinese Medicine Systems Pharmacology database was used to screen bioactive ingredients of AR-PN. Subsequently, putative targets of bioactive ingredients were predicted utilizing the DrugBank database and converted into genes on UniProtKB database. DN-related targets were retrieved via analyzing published microarray data (GSE30528) from the Gene Expression Omnibus database. Protein-protein interaction networks of AR-PN putative targets and DN-related targets were established to identify candidate targets using Cytoscape 3.8.0. GO and KEGG enrichment analyses of candidate targets were reflected using a plugin ClueGO of Cytoscape. Molecular docking was performed using AutoDock Vina software, and the results were visualized by Pymol software. The diagnostic capacity of hub genes was verified by receiver operating characteristic (ROC) curves.ResultsTwenty-two bioactive ingredients and 189 putative targets of AR-PN were obtained. Eight hundred and fifty differently expressed genes related to DN were screened. The PPI network showed that 115 candidate targets of AR-PN against DN were identified. GO and KEGG analyses revealed that candidate targets of AR-PN against DN were mainly involved in the apoptosis, oxidative stress, cell cycle, and inflammation response, regulating the PI3K-Akt signaling pathway, cell cycle, and MAPK signaling pathway. Moreover, MAPK1, AKT1, GSK3B, CDKN1A, TP53, RELA, MYC, GRB2, JUN, and EGFR were considered as the core potential therapeutic targets. Molecular docking demonstrated that these core targets had a great binding affinity with quercetin, kaempferol, isorhamnetin, and formononetin components. ROC curve analysis showed that AKT1, TP53, RELA, JUN, CDKN1A, and EGFR are effective in discriminating DN from controls.ConclusionsAR-PN against DN may exert its renoprotective effects via various bioactive chemicals and the related pharmacological pathways, involving multiple molecular targets, which may be a promising herb pair treating DN. Nevertheless, these results should be further validated by experimental evidence.

Dataset Information

Network Pharmacology-Based Dissection of the Active Ingredients and Protective Mechanism of the Salvia Miltiorrhiza and Panax Notoginseng Herb Pair against Insulin Resistance.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets