Integrated analysis of liquid chromatography-mass spectrometry and network pharmacology identified active compounds of Paeoniae Radix Alba for myasthenia gravis treatment

Paeoniae Radix Alba (PRA), also known as Baishao, has been used for the clinical treatment of a variety of diseases, however, its role in myasthenia gravis (MG) remains unexplored. Active compounds of PRA were screened by Liquid chromatography-mass spectrometry (LC-MS). Their targets were predicted and intersected with MG-related targets to develop a protein-protein interaction (PPI) network, followed by performing functional enrichment analysis to uncover key biological pathways involved. Meanwhile, differentially expressed microRNAs (DEmiRNAs) in MG were filtered to select the target genes, which were then overlapped with the common genes of PRA’s active components and MG to develop “ingredient-targets-pathway” and “ingredients-targets-miRNA” networks. Molecular docking was adopted to predict the binding between the active ingredients and the key genes. Our analysis identified four active components in PRA and their corresponding MG-related targets. Intersection analysis revealed that these targets were significantly enriched in key biological pathways, including neuroactive ligand-receptor interaction, neuroactive ligand signaling, HIF-1 signaling pathway, and response to xenobiotic stimulus. Protein-protein interaction (PPI) network analysis further uncovered 23 DEmiRNAs and 4989 common genes, which were predominantly associated with MAPK signaling pathway, endocytosis, proteasome-mediated ubiquitin-dependent catabolic process, histone modification. Finally, based on the networks of “ingredient-targets-pathway” and “ingredients-targets-miRNA”, a binding between SERPINE1 and Catechin was observed. This study applied LC-MS and network pharmacology to identify active components of PRA for the treatment of MG.