Exploring Mechanisms of Houshiheisan in Treating Ischemic Stroke with Network Pharmacology and Independent Cascade Model


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Аннотация

Background:Houshiheisan (HSHS) has been effective in the treatment of ischemic stroke (IS) for centuries. However, its mechanisms are still underexplored.

Objective:The objective of this study is to identify the active ingredients and mechanisms of HSHS in treating IS.

Methods:We searched the main active compounds in HSHS and their potential targets, and key targets related to IS. Based on the common targets of HSHS and IS, we further expanded genes by KEGG database to obtain target genes and related genes, as well as gene interactions in the form of A→B, and then constructed a directed network including traditional Chinese medicines (TCMs), active compounds and genes. Finally, based on enrichment analysis, independent cascade (IC) model, and molecular docking, we explored the mechanisms of HSHS in treating IS.

Results:A directed network with 6,348 nodes and 64,996 edges was constructed. The enrichment analysis suggested that the AGE pathway, glucose metabolic pathway, lipid metabolic pathway, and inflammation pathway played critical roles in the treatment of IS by HSHS. Furthermore, the gene ontologies (GOs) of three monarch drugs in HSHS mainly involved cellular response to chemical stress, blood coagulation, hemostasis, positive regulation of MAPK cascade, and regulation of inflammatory response. Several candidate drug molecules were identified by molecular docking.

Conclusion:This study advocated potential drug development with targets in the AGE signaling pathway, with emphasis on neuroprotective, anti-inflammatory, and anti-apoptotic functions. The molecular docking simulation indicated that the ligand-target combination selection method based on the IC model was effective and reliable.

Об авторах

Bo Cao

Department of Health Informatics and Management, School of Health Humanities, Peking University

Email: info@benthamscience.net

Jiao Jin

School of Statistics, Beijing Normal University

Email: info@benthamscience.net

Zhiyu Tang

Department of Health Informatics and Management, School of Health Humanities, Peking University

Email: info@benthamscience.net

Qiong Luo

School of Nursing, Peking University

Email: info@benthamscience.net

Jinbing An

Department of Health Informatics and Management, School of Health Humanities, Peking University

Автор, ответственный за переписку.
Email: info@benthamscience.net

Wei Pang

Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University

Автор, ответственный за переписку.
Email: info@benthamscience.net

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