A method of mechanism analysis about a traditional chinese medicine prescription on a disease based on PageRank algorithm and network pharmacology

Abstract

Network pharmacology is a method to study the mechanism of a Traditional Chinese Medicine (TCM) prescription on a disease. However, most articles using network pharmacology to study the mechanism did not combine the weight information of herbs, the weight information of targets of disease, and the interaction information between targets together. We propose a method, network pharmacology combined with two iterations of PageRank algorithm, to make use of these information. It takes prescription-disease system as a whole, calculates PageRank score of targets in the prescription-disease system, which means an importance in the system, and the score is used to rank the analysis results of GO and KEGG pathway which help us to analyze the mechanism of a prescription on a disease. At last, we use two prescription-disease pairs which have been proved effectiveness in clinical trials: Qingfei Paidu Decoction on COVID-19, and FuFang DanShen Diwan on Coronary Heart Disease, and find that the results of our method are consistent with some results of clinical trials.

Keywords

• Network pharmacology
• Pagerank algorithm
• Mechanism research