Objective To find out Shanxi genuine drug food homologous substances for type 2 diabetes complicated with hypertension, and to explore its mechanism. Methods The targets of type 2 diabetes and hypertension were obtained from TTD, Drugbank and GeneCards databases, and the intersection targets of the two were obtained. After UniProt database transformation, the protein-protein interaction network was established on the String platform. Degree values were used to screen core targets, followed by enrichment analysis. TCMSP database was used to carry out reverse screening of traditional Chinese medicine ingredients and corresponding traditional Chinese medicine. The key target-active ingredient-traditional Chinese medicine network was constructed. Chinese medicine with a certainty value≥3 was overlapped with drug food homology directory, Shanxi genuine drug directory, and drug use law directory of type 2 diabetes complicated with hypertension to obtain the best drug food homologous substances. Results After screening, 715 intersecting targets were identified, 23 key targets and 818 traditional Chinese medicine ingredients were determined, and 24 active ingredients with retention values≥4 were identified as core active ingredients. A total of 302 traditional Chinese medicines were reverse screened. There were 14 kinds of drug food homologous substances, and Radix Astragali was finally selected as the best drug food homologous substance for type 2 diabetes complicated with hypertension. Conclusion Radix Astragali may be used to prevent and treat type 2 diabetes complicated with hypertension, but the related research only involves theoretical aspects, which needs to be verified by trials in the future.
Objective To identify the therapeutic targets and molecular mechanisms of Da Chaihu Decoction in the treatment of acute pancreatitis (AP) based on network pharmacology and molecular docking. Methods From March to May 2024, the active compounds and targets of Da Chaihu Decoction were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and the targets related to AP were obtained from the GeneCards database. The intersection of these yielded the common targets of Da Chaihu Decoction for AP treatment. The STRING platform was used to construct a protein-protein interaction network, and Cytoscape 3.9.1 software was employed for network topology analysis to identify core targets and compounds. The Metascape platform was applied for gene ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, with bubble charts generated using Python 3.8 software. Molecular docking was conducted using AutoDock 1.5.6 software to predict binding affinities between core compounds and targets. Results A total of 84 common targets of Da Chaihu Decoction for AP treatment were identified. The core compounds included quercetin, β-sitosterol, kaempferol, luteolin, and baicalein. The key proteins included AKT1, B-cell leukemia/lymphoma 2 (BCL2), Jun proto-oncogene (JUN), interleukin 1 Beta (IL1B), and nuclear factor kappa B subunit 1 (NFKB1), all of which were enriched in pathways such as lipid and atherosclerosis, PI3K-Akt signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, tumor necrosis factor (TNF) signaling pathway, and apoptosis. The binding energies of some core compounds with key proteins were below –5.0 kJ/mol. Conclusion Da Chaihu Decoction may exert anti-inflammatory and anti-apoptotic effects in AP by modulating key protein targets, including AKT1, BCL2, JUN, IL1B, and NFKB1, within pathways such as lipid and atherosclerosis, PI3K-Akt signaling, MAPK signaling, TNF signaling, and apoptosis.
