ArticleFrontiers in pharmacology2026
Mechanistic prediction of angelicae pubescentis radix in preventing arrhythmia via modulation of calcium channel targets: an integrated network pharmacology and target enrichment analysis.
Article in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Abstract
Objective: This study aimed to elucidate the potential mechanisms by which Angelicae Pubescentis Radix (APR) prevents arrhythmia through the regulation of calcium channels, based on network pharmacology, molecular docking, and Methods: Active components of APR were screened from the TCMSP and PubChem databases under oral bioavailability (OB ≥ 30%) and drug-likeness (DL ≥ 0.18) criteria. Potential targets were predicted using SwissTargetPrediction and standardized using UniProt. Arrhythmia-related genes were collected from the GeneCards, OMIM, and TTD databases. Overlapping targets were identified for PPI network construction, GO/KEGG enrichment, and "component-target-pathway" network analysis. Core targets underwent molecular docking with key compounds. Furthermore, an isoproterenol (ISO)-induced arrhythmia rat model was established to evaluate the pharmacological effects of APR at different doses. Results: A total of potential 340 putative APR-related targets were identified from network pharmacology analysis. Among the APR-derived active compounds, three with the highest network connectivity (Angelol G, O-acetylcolumbianetin, and nodakenin) were selected for molecular docking. In parallel, 902 arrhythmia-related genes were retrieved, yielding 24 overlapping targets, among which five hub genes (PIK3CA, CREBBP, NR3C1, SCN10A, and KCNA5) were identified. KEGG analysis revealed significant enrichment in calcium signaling, adrenergic signaling, and PI3K-Akt/cAMP pathways. Molecular docking demonstrated strong binding affinities between Angelol G, O-acetylcolumbianetin, and nodakenin to NR3C1 and SCN10A. Conclusion: APR may exert anti-arrhythmic effects by targeting key regulatory nodes identified through network pharmacology, particularly PIK3CA, CREBBP, NR3C1, SCN10A, and KCNA5, and by exhibiting strong compound-target interactions in molecular docking. These network-predicted mechanisms were supported by
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