A system-level mechanistic investigation of traditional Chinese medicine, Yinlai Decoction, for related diseases

  • Tie-Gang Liu
  • Zi-An Zheng
  • Yu-Xiang Wan
  • Chen Bai
  • Jing-Nan Xu
  • He Yu
  • Xiao-Hong Gu
Keywords: Yinlai Decoction, Network (System) pharmacology, Inflammation, Interacting genes/proteins, Gene ocntology, Pathway enrichment analysis

Abstract

Purpose: To systemically explore the pharmacological mechanisms of traditional Chinese medicine, Yinlai Decoction (YD), used in the clinical management of pediatric diseases such as pneumonia and recurrent respiratory tract infections.

Methods: An ingredient-target-disease database of YD was constructed using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). First, the molecular targets related to lung and stomach diseases were searched and screened to avoid duplication. Second, the associations between these molecular targets were evaluated via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Gene Ontology (GO) and Pathway enrichment analysis in STRING.

Results: A total of 627 chemical ingredients and 654 protein targets in YD were obtained. After further screening, 38 molecular targets linked to respiratory diseases, inflammatory responses and various infections were identified. Finally, 576 GO terms and 75 KEGG pathway terms were obtained by analyzing gene functional annotation clusters and abundance value of these targets. Most of these terms were closely related to the inflammatory response.

Conclusion: Based on these in silico findings, the use of YD for treating respiratory diseases, inflammation and various infections, most probably via the suppression of inflammation, has been established. The approach adopted in this study can serve as a model methodology to develop an innovative TCM candidate drug at a network pharmacology level.

Keywords: Yinlai Decoction, Network (System) pharmacology, Inflammation, Interacting genes/proteins, Gene ocntology, Pathway enrichment analysis

Published
2017-09-07
Section
Articles

Journal Identifiers


eISSN: 1596-9827
print ISSN: 1596-5996