Network Analysis Using the Established Database (K-herb Network) on Herbal Medicines Used in Clinical Research on Heart Failure

Subin Park, Y. Kim, Gi-Sang Bae, Cheol-hyun Kim, Inae Youn, Jungtae Leem, H. Chu
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Abstract

Objectives: Heart failure is a chronic disease with increasing prevalence rates despite advancements in medical technology. Korean medicine utilizes herbal prescriptions to treat heart failure, but little is known about the specific herbal medicines comprising the network of herbal prescriptions for heart failure. This study proposes a novel methodology that can efficiently develop prescriptions and facilitate experimental research on heart failure by utilizing existing databases.Methods: Herbal medicine prescriptions for heart failure were identified through a PubMed search and compiled into a Google Sheet database. NetMiner 4 was used for network analysis, and the individual networks were classified according to the herbal medicine classification system to identify trends. K-HERB NETWORK was utilized to derive related prescriptions.Results: Network analysis of heart failure prescriptions and herbal medicines using NetMiner 4 produced 16 individual networks. Uhwangcheongsim-won (牛黃淸心元), Gamiondam-tang (加味溫膽湯), Bangpungtongseong-san (防風通聖散), and Bunsimgi-eum (分心氣飮) were identified as prescriptions with high similarity in the entire network. A total of 16 individual networks utilized K-HERB NETWORK to present prescriptions that were most similar to existing prescriptions. The results provide 1) an indication of existing prescriptions with potential for use to treat heart failure and 2) a basis for developing new prescriptions for heart failure treatment.Conclusion: The proposed methodology presents an efficient approach to developing new heart failure prescriptions and facilitating experimental research. This study highlights the potential of network pharmacology methodology and its possible applications in other diseases. Further studies on network pharmacology methodology are recommended.
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心衰临床研究中草药数据库(K-herb Network)的网络分析
目的:心力衰竭是一种慢性疾病,尽管医疗技术不断进步,但其患病率仍在上升。韩国医学利用草药处方来治疗心力衰竭,但对构成心力衰竭草药处方网络的具体草药知之甚少。本研究提出了一种新的方法,可以有效地利用现有数据库开发处方并促进心力衰竭的实验研究。方法:通过PubMed检索确定治疗心力衰竭的草药处方,并将其编入Google Sheet数据库。使用NetMiner 4进行网络分析,并根据草药分类系统对各个网络进行分类,识别趋势。利用K-HERB NETWORK推导相关处方。结果:使用NetMiner 4对心衰处方和中草药进行网络分析,产生16个个体网络。Uhwangcheongsim-won()、gamionam -tang()、Bangpungtongseong-san()和Bunsimgi-eum()在整个网络中具有较高的相似性。共有16个个体网络利用K-HERB NETWORK提供与现有处方最相似的处方。该结果提供了1)现有处方治疗心力衰竭的潜在适应症,2)开发心力衰竭治疗新处方的基础。结论:提出的方法为开发新的心力衰竭处方和促进实验研究提供了有效的途径。本研究突出了网络药理学方法的潜力及其在其他疾病中的应用前景。建议进一步研究网络药理学方法学。
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