Multivariate computational strategies for mechanisms involving gut microbiome metabolite targets of Astragalus in diabetic sarcopenic obesity
Year: 2026
Type: article
Abstract: Diabetic sarcopenic obesity (SO) is a complex metabolic condition characterized by the coexistence of obesity, diabetes, and sarcopenia, leading to poor prognosis. Astragalus, is a key herb in spleen-strengthening formulas, but its pharmacological mechanisms against diabetic SO remain unclear. Drug- and disease-related genes for Astragalus, obesity, diabetes, and sarcopenia were retrieved from public databases. Overlapping genes were weighted by CytoNCA to identify core targets, which were expanded via GMFA network analysis to form core-plus genes. Gut microbiota metabolites and targets were obtained from gutMGene v2.0, with metabolite targets predicted using SEA and Swiss Target Prediction. Herb-active ingredient-target and drug–disease–gut networks were constructed via STRING and Cytoscape. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses identified key pathways, and molecular docking and molecular dynamics simulations validated binding affinity between core ingredients and hub targets. A total of 31 drug-disease genes, 8 core genes, 87 core-plus genes, 6 drug-disease-gut genes and 11 final core genes were identified. Kaempferol and jaranol, the main active ingredients of Astragalus, were predicted to interact with AKT1, ESR1, MMP9, APP, and IGF1R, with these targets being associated with insulin resistance, the AMPK signaling pathway, the HIF-1 signaling pathway, and the TNF signaling pathway. Astragalus may alleviate diabetic SO through multi-target and multi-pathway mechanisms, highlighting its promise as a therapeutic candidate.
Source: Scientific Reports
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W7222870414
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