Abstract
BackgroundTraditional Chinese medicine (TCM) herbal formulae provide valuable therapeutic strategies. However, the active ingredients and mechanisms of action remain unclear for most of these formulae. Therefore, the identification of complex mechanisms is a major challenge in TCM research.MethodsThis study used a network pharmacology approach to clarify the anti-inflammatory and cough suppressing mechanisms of the Chinese medicinal preparation Eriobotrya japonica – Fritillaria usuriensis dropping pills (ChuanbeiPipa dropping pills, CBPP). The chemical constituents of CBPP were identified by high-quality ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS), and anti-inflammatory ingredients were selected and analyzed using the PharmMapper and Kyoto Encyclopedia of Genes and Genomes (KEGG) bioinformatics websites to predict the target proteins and related pathways, respectively. Then, an RNA-sequencing (RNA-Seq) analysis was carried out to investigate the different expression of genes in the lung tissue of rats with chronic bronchitis.ResultsSix main constituents affected 19 predicted pathways, including ursolic acid and oleanolic acid from Eriobotrya japonica (Thunb.) Lindl. (Eri), peiminine from Fritillaria usuriensis Maxim. (Fri), platycodigenin and polygalacic acid from Platycodon grandiflorum (Jacq.) A. DC. (Pla) and guanosine from Pinellia ternata (Thunb.) Makino. (Pin). Expression of 34 genes was significantly decreased after CBPP treatment, affecting four therapeutic functions: immunoregulation, anti-inflammation, collagen formation and muscle contraction.ConclusionThe active components acted on the mitogen activated protein kinase (MAPK) pathway, transforming growth factor (TGF)-beta pathway, focal adhesion, tight junctions and the action cytoskeleton to exert anti-inflammatory effects, resolve phlegm, and relieve cough. This novel approach of global chemomics-integrated systems biology represents an effective and accurate strategy for the study of TCM with multiple components and multiple target mechanisms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12906-015-0983-y) contains supplementary material, which is available to authorized users.
Highlights
Traditional Chinese medicine (TCM) herbal formulae provide valuable therapeutic strategies
We developed an integrated network pharmacological approach combining the virtual prediction of targets and pathways with the experimentally determined differences in gene expression to explain the synergistic mechanism of Eriobotrya japonica – Fritillaria usuriensis dropping pills (CBPP)
There were five flavone derivatives and two theaflavin derivatives in Eriobotrya japonica (Thunb.) Lindl. (Eri) [10, 11], and two peiminine derivatives were identified in Fritillaria usuriensis Maxim. (Fri) [12, 13]
Summary
Traditional Chinese medicine (TCM) herbal formulae provide valuable therapeutic strategies. A traditional Chinese medicine (TCM) preparation contains various active ingredients that exhibit synergistic effects on multiple targets to treat disease. The development of analytical theory, such as systems biology and network pharmacology, provides an opportunity to clarify the complex and holistic mechanisms by which TCM treats complex diseases [2]. The gene expression of MCF-7 cells treated with Si-Wu-Tang was evaluated by microarray, and the potential targets of each herb were identified using the TCM Integrative Database. The differentially expressed genes were identified from a myocardial infarction rat model treated with Qishen Yiqi, and their functions were analyzed based on the cardiovascular disease-related literature. Most of the above operations of TCM network pharmacology were performed virtually, and neither trace ingredients nor drug absorption were reflected at the biological level. The virtual evaluation presented a huge and complex network in which the main contact between compounds, targets and function was not clear, and it was not possible to conduct further studies on key issues
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