Multifaceted mechanistic exploration of

Background: Asthma, a chronic inflammatory respiratory disease with significant global health burden, faces limitations in current therapies, necessitating novel therapeutic strategies. The plant Aim: To investigate the anti-asthmatic mechanisms of GWM by identifying compounds and elucidating key molecular targets involved in immune cell regulation through integrated computational and experimental approaches. Methods: We employed UPLC-QE-Orbitrap-MS to identify active compounds. Network pharmacology and machine learning analyses were conducted to identify key hub genes, followed by validation through Mendelian randomization analysis, molecular docking, and animal models. Immune infiltration and single-cell RNA sequencing analyses using publicly available Gene Expression Omnibus (GEO) datasets, combined with mediation Mendelian randomization (MR), were performed to elucidate the underlying cellular mechanisms. Results: A total of 43 compounds were identified in GWM. Network pharmacology and machine learning prioritized NOTCH2, HDAC2, and MAPK1 as hub targets, validated using MR and molecular docking. Subsequent Conclusion: This study provides novel evidence for the potential therapeutic activity of GWM in asthma. By targeting key hub genes such as NOTCH2, HDAC2, and MAPK1, GWM may modulate immune cell activity, thereby contributing to its anti-asthmatic effects.