Deciphering anti-asthmatic components in loquat leaves (Eriobotrya japonica folium) by integrating network pharmacology, Mendelian randomization, and machine learning methods

Eriobotrya japonica folium, a traditional Chinese medicine (TCM) derived from the dried loquat leaves, has been widely used for treating respiratory diseases. With the deterioration of global environment, the prevalence of asthma continues to rise worldwide. Loquat leaf acts on respiratory diseases at multiple levels, offering advantages for asthma management. However, the active constituents in loquat leaf for asthma treatment and the pharmacological mechanisms is unclear. Network pharmacology approach was applied to systematically elucidate the pharmacological mechanisms of loquat leaf active components against asthma. Based on comprehensive evaluation of structural features, number of potential targets, and network proximity Z-scores, 57 candidate anti-asthmatic compounds were screened from the extraction of loquat leaf. After that, 33 targeted genes by loquat leaf active components were identified using a dual-diffusion network algorithm, and enrichment analysis revealed their involvement in inflammatory response, immune regulation, and airway remodeling. The causal effects between critical targeted genes by loquat leaf active components and asthma were validated via Mendelian randomization. GSK3B and AKT1 elevated asthma risk, while MAPK3 and SRC conferred protection. Furthermore, the machine learning models based on targeted gene expression showed strong predictive performance for asthma classification. AKT1 and SRC exhibited high importance scores and significant differential expression between asthma patients and healthy controls. Finally, molecular docking showed 10 key components formed stable complexes with 8 asthma-related gene products. Quercetin, rutin, isorhamnetin, and EGCG in loquat leaf bound specifically to AKT1, GSK3B, MAPK3, and SRC, respectively. Totally, this study revealed the anti-asthmatic mechanisms of loquat leaf and offered a new perspective for investigating TCM complexity and synergy.