Potential mechanism of Laportea bulbifera on treating inflammation and tumor via metabolomics, network pharmacology and molecular docking.

Abstract

This study aimed to utilize metabolomics, network pharmacology, and molecular docking techniques to identify the major active components of Laportea bulbifera and investigate their anti-inflammatory and potential anti-tumor mechanisms. The metabolic constituents of L. bulbifera were examined utilizing UPLC-ESI-MS/MS. PPI networks and compound-target-pathway networks were established using resources such as TCMSP, Swiss Target Prediction, DAVID, STRING database, and Cytoscape software. Molecular docking analysis of the most important compounds and targets was conducted using Autodock4, followed by validation of the molecular docking results' stability using GROMACS. The UPLC-ESI-MS/MS analysis identified a total of 798 compounds. A network pharmacology-based analysis was conducted, revealing that eight compounds and four molecular targets-namely, TNF, IL6, PIK3CA, and HDAC1-were enriched in the network. Pathway analysis of the identified targets demonstrated enrichment in 217 KEGG pathways. Molecular docking analysis and molecular dynamics simulations demonstrated strong therapeutic potential of N-feruloyltyramine, N-feruloylagmatine, and Ellagic acid against various inflammatory and tumor diseases. This study, for the first time, employed an integrated strategy of metabolomics, network pharmacology, molecular docking, and molecular dynamics, elucidating the mechanisms underlying the anti-inflammatory and potential anti-tumor effects of L. bulbifera, laying the foundation for subsequent drug development endeavors.