Chemical Characterization and Mechanism Analysis of Ganjianglingzhu Decoction in the Treatment of Low Back Pain Based on UPLC-Q-TOF-MS/MS and Network Pharmacology
Abstract
Rationale
Ganjianglingzhu decoction (GJLZD), a classical traditional Chinese medicine (TCM) formula, has been widely used in the treatment of low back pain. However, its chemical composition and underlying mechanisms remain insufficiently elucidated.
Methods
The chemical profile of GJLZD was comprehensively characterized by UPLC-Q-TOF-MS/MS. Representative bioactive constituents were subsequently selected for target prediction using the PharmMapper and SwissTargetPrediction databases. Overlapping targets between compound-related targets and low back pain–related targets retrieved from the GeneCards database were subjected to protein–protein interaction (PPI) analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, as well as molecular docking and molecular dynamics (MD) simulation.
Results
Based on MS/MS fragmentation patterns and literature comparison, a total of 58 constituents were tentatively characterized from GJLZD. These mainly included flavonoids, alkaloids, phenolic acids, and terpenoids. We identified 466 overlapping targets between the active components and low back pain. PPI analysis highlighted SRC, PIK3CA, and AKT1 as the major hub targets. GO and KEGG enrichment analyses suggested that these targets were primarily involved in signal transduction, inflammatory regulation, and metabolism. The enriched pathways included VEGF, FcεRI, and AGE-RAGE signaling. Molecular docking revealed that neoglycyrol showed the strongest binding affinity to AKT1, with a binding energy of −7.93 kcal/mol. MD simulation further confirmed the stability of the neoglycyrol–AKT1 complex over 100 ns.
Conclusions
This study systematically characterized the chemical constituents of GJLZD and elucidated its potential mechanisms in treating low back pain. The results suggest a multicomponent and multi-target mode of action. The integrated strategy combining UPLC-Q-TOF-MS/MS with network pharmacology and molecular simulations proved valuable for investigating the pharmacological basis of TCM formulas. Further experimental validation is still needed to confirm these findings.