Computational investigation of single herbal drugs for diabetes and obesity using knowledge graph and network pharmacology.

Metabolic diseases such as type 2 diabetes and obesity represent a rapidly escalating global health burden, while existing therapeutic strategies largely target isolated symptoms or single molecular pathways. To address this limitation, we developed an integrated computational pipeline leveraging a knowledge graph, pathway enrichment, and network pharmacology to elucidate multi-target mechanisms of Single Herbal Drugs (SHDs). SHDs associated with diabetes and obesity were curated from the Ayurvedic Pharmacopoeia of India, and their phytochemicals were identified using the IMPPAT database. Following drug-likeness and predicted bioavailability filtering, 11 SHDs and 188 phytochemicals were shortlisted. Molecular targets of these phytochemicals, along with disease-associated genes and therapeutic targets of FDA-approved drugs, were compiled through multi-database integration. Pathway enrichment analysis revealed significant overlap between SHD-associated and disease-associated pathways. All curated data were integrated into a Neo4j-based knowledge graph to enable SHD-disease intersection analysis, prioritizing key targets such as PTPN1, GLP1R, and DPP4. SHD-Target-Drug profiling demonstrated convergence with clinically validated drug combinations. Network pharmacology based on protein-protein interaction network analysis further identified PPARG as a central regulatory hub. We propose a quantitative framework to identify structurally dissimilar phytochemical pairs acting on complementary disease-associated targets, highlighting non-redundant network-level interactions and generating mechanistic hypotheses for potential synergy. Molecular docking of PPARG and DPP4 identified promising lead phytochemicals, including Chitraline, Isovitexin, and Pakistanine for DPP4, and Sulfurein, Sesamin, and Pterosupin for PPARG. Overall, this integrative approach provides a robust systems-level framework for mechanistically dissecting SHDs and bridging traditional herbal knowledge with modern biomedical research.