A Systems-Level Analysis of Mechanisms of Platycodon grandiflorum Based on A Network Pharmacological Approach

Abstract

Platycodon grandiflorum (PG) is widely used in Asia for its various beneficial effects. Although many studies were conducted to understand the molecular mechanisms of PG, it is still unclear how the combinations of multiple ingredients work together to exert its therapeutic effects. The aim of the present study was to provide a comprehensive review of the systems-level mechanisms of PG by adopting network pharmacological analysis. We constructed a compound⁻target⁻disease network for PG using experimentally validated and machine-leaning-based prediction results. Each target of the network was analyzed based on previously known pharmacological activities of PG. Gene ontology analysis revealed that the majority of targets were related to cellular and metabolic processes, responses to stimuli, and biological regulation. In pathway enrichment analyses of targets, the terms related to cancer showed the most significant enrichment and formed distinct clusters. Degree matrix analysis for target⁻disease associations of PG suggested the therapeutic potential of PG in various cancers including hepatocellular carcinoma, gastric cancer, prostate cancer, small-cell lung cancer, and renal cell carcinoma. We expect that network pharmacological approaches will provide an understanding of the systems-level mechanisms of medicinal herbs and further develop their therapeutic potentials.

Keywords: Kilkyung; Platycodon grandiflorum; network pharmacology; systems-level mechanism; traditional Asian medicine.

Figure 1

Framework of network pharmacological analysis of Platycodon grandiflorum (PG); TCMSP: Traditional Chinese Medicine Systems Pharmacology database; OB: oral bioavailability; DL: drug-likeness.

Figure 2

Chemical structures of PG compounds. (a) Four components of PG were selected from the TCMSP database with threshold values of 30 and 0.18 for OB and DL, respectively. (b) Platycodin D is a major active component of PG.

Figure 3

Compound–target–disease (CTD) network of PG. The red circles represent compounds, the purple circles represent targets, and the orange circles represent diseases. The compounds, targets, and diseases of each network are sorted in descending order from the bottom of the figure in a circular layout, on the basis of the number of degrees. The size of the target and disease nodes reflects the number of degrees. The node was removed when the number of degrees of the target and disease nodes was <3. The orange box represents the top five targets and diseases in terms of degrees.

Figure 4

Biological processes related to targets of PG. Targets were assigned to biological processes using “Panther GO-slim Biological Process”. Hits mean the number of assigned targets to the corresponding biological processes. The proportion of each biological process is color-coded in the pie chart.

Figure 5

Pathway analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) 2016 library. Analysis was performed on the “Enrichr” platform (http://amp.pharm.mssm.edu/Enrichr/). The 112 targets of PG were used to obtain the results. (a) The top 10 enriched pathway terms are displayed in a bar graph. They are ranked by a combined score calculated by p-value and z-score. The length of the bar and the brightness of its color represent the significance of the specific pathway. (b) The top 10 enriched pathway terms are displayed as a network. Each node represents a pathway, and each edge represents the gene content similarity among the pathways.

Figure 6

Clustergram of pathways. Rows and columns represent the pathways and input genes, respectively. The enriched terms in the rows of the heat map are clustered by the similarity of the gene contents. The input genes in the column are sorted in descending order of the sum of the columns from left to right. The colors of the boxes represent each cluster.

Figure 7

Degree matrices of the related diseases. Each row represents the major diseases of the CTD network, and each column represents the 10 thresholds of OB and DL. (a) The matrix shows the absolute degree of each disease. Only diseases with an average degree of 3 or higher are displayed. The color bar indicates the absolute degree of diseases. (b) The matrix represents the relative degree. Only the top 50% of diseases indicated by total herbs’ degrees are selected. The color bar represents the relative degree of diseases.