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Narendra Lamichhane

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Open access Aug 2026

Systems-Level Immunomodulatory Mechanisms of Swarna Bindu Prasana: An In Silico Network Pharmacology Study

Introduction: Pediatric immune dysregulation and recurrent infections are closely associated with impaired neurodevelopment through shared inflammatory and neuroimmune pathways. Conventional single-target therapies often fail to address this biological complexity. Swarna Bindu Prasana (SBP), a classical Ayurvedic formulation, is traditionally used to enhance immune resilience and cognitive development; however, its systems-level biological mechanisms remain insufficiently characterized. Methods: A computational, literature-mining-driven network pharmacology approach was applied to investigate the conserved SBP components: honey (Madhu), butter/ghee (Ghrita), and gold nanoparticles (Swarna Bhasma). The 300 most relevant immune-related PubMed abstracts per component were analyzed using biomedical named entity recognition. Identified immune targets were subjected to compound–target network construction, protein–protein interaction (PPI) analysis, Gene Ontology and KEGG pathway enrichment, transcription factor enrichment (ChEA3), and disease association analysis (MalaCards). Results: Twenty-three immune-related targets were identified, of which 21 formed a highly interconnected PPI network. IL6 emerged as the principal convergent hub across all components, followed by TLR4 and IL10. Functional enrichment analyses highlighted cytokine signaling, Toll-like receptor pathways, JAK–STAT signaling, and adaptive immune differentiation (Th1/Th2/Th17). Key upstream regulators included NF-κB, STAT family members, FOXP3, and TBX21. Disease enrichment revealed strong associations with immune deficiency, autoimmune disorders, inflammatory bowel disease, and asthma. Conclusion: These findings suggest that SBP exerts multi-target, network-based immunomodulatory effects, providing a mechanistic framework that supports its traditional use and informs future experimental and pediatric clinical validation.

Narendra Lamichhane, Lisa Dal Pozzo, Ashma Bhattarai et al. · 0 citations

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