Mechanistic investigation of Shuanghuanglian against infectious bronchitis in chickens: a network pharmacology and molecular dynamics study - You, Fuming; Zhang, Hanzhao; Meng, Linghao; Li, Chuanhong; Yang, Yuxia; Wang, Yongqiang; Zhao, Rigetu; Chao, Luomeng (Frontiers in Veterinary Science, 2025)
IntroductionInfectious bronchitis (IB) poses a major challenge to global poultry production, causing substantial economic burdens and underscoring the necessity for novel therapeutic interventions given the limitations of current vaccines and conventional antiviral agents. The purpose of this study is to comprehensively explore the active components in Shuanghuanglian and their interaction with the key pathological targets of IBV (Infectious bronchitis virus) infection. By using advanced computational methods, this study aims not only to identify the therapeutic potential of active ingredients, but also to reveal their mechanism of action against IBV.MethodsThrough integrative systems pharmacology approaches, we systematically investigated Shuanghuanglian and its phytochemical constituents against IB, employing multi-omics analysis, ensemble machine learning, and all-atom molecular dynamics (MD) simulations. Network pharmacology revealed 65 target genes associated with Shuanghuanglian’s primary bioactive components (quercetin, kaempferol, wogonin, and luteolin), exhibiting high network centrality.ResultsUsing the TCMSP database, we found 65 target genes associated with key active components, such as quercetin and kaempferol, which exhibited strong connectivity in our network analysis. The GeneCards database also identified 40 common target genes shared by Shuanghuanglian and IB. Importantly, BCL2 and IL6 were recognized as key targets in the protein–protein interaction (PPI) network analysis, highlighting their roles in apoptosis and inflammation. Furthermore, analyses using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed significant roles in regulating the cell cycle and inflammatory responses. Machine learning techniques identified BCL2 and IL6 as critical genes for therapeutic intervention, supported by molecular docking results that showed strong binding energies. Furthermore, molecular dynamics simulations confirm the stability of the complexes, underscoring the importance of these interactions for treatment efficacy.ConclusionWe used a variety of analytical methods, and finally identified the potential active ingredients of Shuanghuanglian as kaempferol, quercetin, wogonin, and luteolin. The active ingredients target BCL2 and IL6 and play a therapeutic role in avian infectious bronchitis by inhibiting apoptosis and reducing inflammatory response.