Leveraging network pharmacology in the treatment of asthma
Source: PubMed Central Open Access, NCBI / U.S. National Library of Medicine
Abstract Background and purpose Asthma, a chronic airway inflammatory disorder driven by multifaceted genetic, cellular and molecular interactions, remains inadequately managed by single-target therapies due to incomplete disease control and adverse effects; this review aimed to explore network pharmacology's role in elucidating multi-target mechanisms of phytotherapeutic agents for asthma, with a focus on integrating ADMET/DMPK profiling to predict clinical translatability and safety. Experimental approach We employed network pharmacology methodologies including target prediction (PharmMapper, PubChem), protein-protein interaction network construction (STRING, Cytoscape), pathway enrichment analysis (KEGG, Reactome), molecular docking (AutoDock) and ADMET/DMPK modelling (SwissADME, pkCSM) to dissect multi-component herbal formulations, complemented by literature-mined experimental validations. Key results Analyses identified key asthma-related targets (IL-17, TNF) and pathways (JAK-STAT, PI3K-AKT), revealing quercetin and kaempferol's multi-target efficacy in reducing airway inflammation and immune dysregulation; favourable ADMET profiles (high oral bioavailability, low toxicity) and DMPK parameters (metabolic stabilityCYP inhibition) supported their therapeutic potential in herbal combinations. Conclusion Network pharmacology, enhanced by ADMET/DMPK integration, advances a holistic understanding of herbal asthma treatments, promoting safe, multi-target drug development. Lim
Abstract
Abstract Background and purpose Asthma, a chronic airway inflammatory disorder driven by multifaceted genetic, cellular and molecular interactions, remains inadequately managed by single-target therapies due to incomplete disease control and adverse effects; this review aimed to explore network pharmacology's role in elucidating multi-target mechanisms of phytotherapeutic agents for asthma, with a focus on integrating ADMET/DMPK profiling to predict clinical translatability and safety. Experimental approach We employed network pharmacology methodologies including target prediction (PharmMapper, PubChem), protein-protein interaction network construction (STRING, Cytoscape), pathway enrichment analysis (KEGG, Reactome), molecular docking (AutoDock) and ADMET/DMPK modelling (SwissADME, pkCSM) to dissect multi-component herbal formulations, complemented by literature-mined experimental validations. Key results Analyses identified key asthma-related targets (IL-17, TNF) and pathways (JAK-STAT, PI3K-AKT), revealing quercetin and kaempferol's multi-target efficacy in reducing airway inflammation and immune dysregulation; favourable ADMET profiles (high oral bioavailability, low toxicity) and DMPK parameters (metabolic stabilityCYP inhibition) supported their therapeutic potential in herbal combinations. Conclusion Network pharmacology, enhanced by ADMET/DMPK integration, advances a holistic understanding of herbal asthma treatments, promoting safe, multi-target drug development. Limitations include data gaps in multi-omics validation and herbal standardization, with future directions leveraging AI-driven predictions for personalized pharmacotherapy.