Digging herbs and prescriptions among ancient Chinese medicine prescriptions for treatment of type 2 diabetes based on data mining and systems pharmacology

Objective To dig herbs and prescriptions with potential good medicinal value in ancient prescriptions of traditional Chinese medicine (TCM) based on data mining and network pharmacology. Method: Firstly, all published literature related to traditional Chinese ancient medicine prescriptions for treatment of T2DM were screen out form major Chinese databases from the beginning of establishment to June 2021, according to a formulated inclusion and exclusion criteria. Then the herbs and prescriptions among them used for treatment of T2DM were extracted and summarized and were ready to construct the data set. Python programming was used to perform frequency statistics of traditional Chinese medicines. Subsequently, Apriori algorithm was adopted to establish association rules to match high-frequency medicinal materials, in order to screen out high-scoring drug pairs. Next, systematic pharmacology methods was applied and the active ingredients and targets for each herb were searched out from TCMSP, ECTM and other traditional herb pharmacological databases. Moreover, type 2 diabetes-related target genes were screen out from Genecards, OMIM , PharmGkb and TTD databases, and the disease-related targets were obtained through Venn2.1; the pathway analysis on Kyoto Encyclopedia of Genes and Genomes (KEGG ) for each herb using R language and Bioconductor bioinformatics software package; A scoring formula was established based on the enrichment of drug target genes to disease-related genes and the scores about all selected herbs and prescriptions were calculated through the formula; the score was sorted and those herbs and prescriptions with higher scores were potential good clinical values. Results: 700 prescriptions were finally screened out and Astragalus was a high-frequency herb. The highest correlation of paired drug obtained from the correlation analysis was Astragalus membranaceus-Rehmannia glutinous. Through the KEGG pathway enrichment analysis and scoring, the highest score herb and prescription were Gorgon Fruit and Warming Yang got respectively. In addition, Astragalus membranaceous and Xiaoke formula, which are known to be commonly used in the treatment of T2DM, were ranked higher scored groups, and some top-ranked ones were not commonly used, such as herb Gorgon Fruit, and prescription Warming Yang. Conclusion: These results demonstrated that this research method has a certain value and significance for digging potential good clinical value of herbs and prescriptions from the available TCM database, which also provides a positive reference values for experimental research as well as clinical drug uses.