ObjectiveThis study aims to analyze the efficacy and mechanism of action of the Shunaoxin pill in preventing cognitive impairment in diabetic patients using network pharmacology.MethodsThe main active compounds of the Shunaoxin pills and their action targets were identified via the TCMSP and Batman-TCM databases. The GEO database was used to identify the genes in type 2 diabetic individuals associated with cognitive impairment. Subsequently, a common target protein-protein interaction (PPI) network was constructed using the STRING database, and targets associated with diabetes and cognitive impairment were screened by performing a topological analysis of the PPI network. The AutoDock Vina software was used for molecular docking to evaluate the reliability of the bioinformatic analysis predictions and validate the interactions between the active ingredients of the Shunaoxin pill and proteins associated with diabetes and cognitive impairment.ResultsBased on the TCMSP and Batman-Tcm platform, 48 active ingredients of the Shunaoxin pill were identified, corresponding to 222 potential action targets. Further analysis revealed that 18 active components of the Shunaoxin pill might contribute to cognitive impairment in type 2 diabetic patients. Molecular docking simulations demonstrated that the active ingredients of the Shunaoxin pill (hexadecanoic acid, stigmasterol, beta-sitosterol, and angelicin) targeted four core proteins: OPRK1, GABRA5, GABRP, and SCN3B.ConclusionActive ingredients of the Shunaoxin pill may alleviate cognitive impairment in diabetic patients by targeting the proteins OPRK1, GABRA5, GABRP, and SCN3B.
ObjectiveThrough transcriptomic and metabolomic analyses, this study examined the role of high-fiber diet in obesity complicated by diabetes and neurodegenerative symptoms.MethodThe expression matrix of high-fiber-diet-related metabolites, blood methylation profile associated with pre-symptomatic dementia in elderly patients with type 2 diabetes mellitus (T2DM), and high-throughput single-cell sequencing data of hippocampal samples from patients with Alzheimer's disease (AD) were retrieved from the Gene Expression Omnibus (GEO) database and through a literature search. Data were analyzed using principal component analysis (PCA) after quality control and data filtering to identify different cell clusters and candidate markers. A protein–protein interaction network was mapped using the STRING database. To further investigate the interaction among high-fiber-diet-related metabolites, methylation-related DEGs related to T2DM, and single-cell marker genes related to AD, AutoDock was used for semi-flexible molecular docking.ResultBased on GEO database data and previous studies, 24 marker genes associated with high-fiber diet, T2DM, and AD were identified. Top 10 core genes include SYNE1, ANK2, SPEG, PDZD2, KALRN, PTPRM, PTPRK, BIN1, DOCK9, and NPNT, and their functions are primarily related to autophagy. According to molecular docking analysis, acetamidobenzoic acid, the most substantially altered metabolic marker associated with a high-fiber diet, had the strongest binding affinity for SPEG.ConclusionBy targeting the SPEG protein in the hippocampus, acetamidobenzoic acid, a metabolite associated with high-fiber diet, may improve diabetic and neurodegenerative diseases in obese people.
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