Computational Systems Pharmacology and Molecular Docking Reveal an Anti-Apoptosis and Anti-Inflammatory Mechanism of Compound Angelica Ligusticum Wallichii Granules in the Treatment of Endometriosis
This study identified key compounds and targets of Angelica Ligusticum Wallichii Granules, revealing its anti-apoptotic and anti-inflammatory mechanisms in treating endometriosis by reducing lesion volume and inflammatory cytokines in a rat model.
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This paper describes the preparation and investigation of compound Angelica Ligusticum wallichii granules (CALG), aiming to characterize its pharmacodynamics and mechanism for treating endometriosis. The authors used UPLC-Q-TOF/MS to identify CALG ingredients, performed computational target prediction and pathway enrichment (Gene Ontology, KEGG), and applied molecular docking, then validated effects in a rat model of endometriosis. They identified 109 compositions and 104 core targets, with network analysis suggesting phenolic compounds contribute to efficacy; in vivo, CALG reduced ectopic lesion volume, promoted apoptosis, inhibited inflammatory cytokine secretion, and increased HIF-1 expression. The paper’s main limitation is that mechanism inference relies largely on computational predictions alongside animal model validation rather than direct causal confirmation of each predicted pathway component. This paper is centrally about endometriosis — it studies CALG’s anti-apoptosis and anti-inflammatory mechanisms in an endometriosis rat model.
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