In Silico Multitarget Profiling of Betulinic Acid: ADME/Protox-II Toxicity, Network Pharmacology, and Molecular Docking for Diabetic Osteoporosis.

Diabetic osteoporosis (DO) is a chronic consequence of diabetes mellitus marked by disrupted bone metabolism and elevated fracture risk, with no effective strategies currently available. Betulinic acid (BA) is a natural pentacyclic triterpenoid demonstrating anti-diabetic, anti-inflammatory, and osteoprotective effects. This research aimed to clarify the molecular mechanisms of BA in DO using network pharmacology, molecular docking, and molecular dynamics simulations. The drug-likeness and pharmacokinetic characteristics of BA were assessed using Swiss ADME, while ProTox-II forecasted oral toxicity. Potential targets of BA and those associated with DO were identified from several databases, and overlapping targets were used to construct a protein-protein interaction (PPI) network in the STRING database, which was then analyzed in Cytoscape 3.7.2. Essential modules were found with MCODE. ShinyGO was used to conduct Gene Ontology Biological Process and Kyoto Encyclopedia of Genes and Genomes pathway enrichment studies. Molecular docking of central targets was performed with AMDock, whereas simulation studies of PPARγ were performed with the Schrödinger software suite. BA complied with Lipinski's rule of five and exhibited a mild oral toxicity profile. Network analysis revealed RXRA, RXRG, RXRB, PTGS2, PPARA, PPARG, PPARD & CYP19A1 as major targets, which were docked with BA to predict binding affinities. Enrichment analysis further revealed BA's role in lipid and glucose metabolism regulation, osteoblast differentiation & modulation of inflammatory pathways. Further, Molecular dynamics validated robust binding affinity of PPARγ in DO. The multi-target interactions of BA, especially with key signaling pathways, indicate a broad involvement in the metabolic and inflammatory processes contributing to the development of DO. BA is a secure multi-target treatment option for DO, providing molecular insights for forthcoming experimental validation.