Network pharmacology suggests biochemical rationale for treating COVID-19 symptoms with a Traditional Chinese Medicine

Abstract

Chinese herbal formulas including the lung-cleaning and toxicity-excluding (LCTE) soup have played an important role in treating the ongoing COVID-19 pandemic (caused by SARS-CoV-2) in China. Applying LCTE outside of China may prove challenging due to the unfamiliar rationale behind its application in terms of Traditional Chinese Medicine. To overcome this barrier, a biochemical understanding of the clinical effects of LCTE is needed. Here, we explore the chemical compounds present in the reported LCTE ingredients and the proteins targeted by these compounds via a network pharmacology analysis. Our results indicate that LCTE contains compounds with the potential to directly inhibit SARS-CoV-2 and inflammation, and that the compound targets proteins highly related to COVID-19's main symptoms. We predict the general effect of LCTE is to affect the pathways involved in viral and other microbial infections, inflammation/cytokine response, and lung diseases. Our work provides a biochemical basis for using LCTE to treat COVID-19 and its main symptoms.

Fig. 1. The virus-inhibiting potential and anti-inflammatory property of the main chemical components in LCTE.

The circled number indicates the number of occurrences of compounds contained in multiple plants, for example, quercetin is contained in seven plants. Black lines with a blunt end indicate that the source vertex has inhibiting effects on the target vertex, while those ending in an arrow have activation effects. Green networks connect herbal ingredients to the main chemical compounds contained in the plants. PLpro and 3 CLpro stand for papain-like protease and 3C-like protease of SARS-CoV-2, respectively.

Fig. 2. Enrichment of compound-targeted proteins and proteins related to symptoms.

The enrichment is represented by the probability (P) value of hypergeometric distribution for overlap between chemically-targeted proteins and proteins related to symptoms or proteins related to viral respiratory infection. The bar colors correspond to the anatomic system affected by each symptom. The vertical dotted line indicates the threshold (P = 0.05) and the numbers in each bar are the exact adjusted P values from enrichment analysis.

Fig. 3. The network of LCTE herbal ingredients, chemical compounds, and target proteins for fever relief.

Vertex sizes are proportional to their degree. Vertices with higher degrees indicate a more important role in the network. Green, red and blue vertices represent plants, chemical compounds, and protein targets, respectively. PPSS1 stands for prostaglandin-endoperoxide synthase and PRSS1 for serine protease 1.

Fig. 4. The compounds and proteins with high degrees or high occurrences in the shortest pathways.

From the networks using LCTE to relieve each symptom or ‘viral respiratory infection’, the top five compounds and proteins (if there were any) were extracted based on both the vertex degree (red dots) and the frequencies with which the vertex appears in the shortest pathways (NSP) (blue dots). To avoid overlapping the dots, we used color transparency (alpha = 0.8) and dot position jitter (width = 0.2, height = 0). The dot sizes are based on the degree or the frequency at which the vertex appears in the shortest pathways. HADHB stands for hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta, while the full names and abbreviations of other proteins are given in the plot.

Fig. 5. Distribution of the total number of shortest pathways for random and real LCTE networks.

The brown color shows the distribution of the total number of shortest pathways from the 1,000,000 random networks. The dotted line marks the position of the 99th percentile of the distribution while the solid green line marks the value of the total number of shortest pathways from the actual LCTE network. The exact value is shown as “NSP=”.

Fig. 6. Enrichment of compound-targeted proteins in KEGG pathways.

Enrichment was performed using R package clusterprofiler with the proteins targeted by the LCTE-contained chemical compounds as input. The bar colors correspond to different pathway functions. The vertical dot line indicated the threshold (adjusted P = 0.05). The exact P values for each pathway are given in Supplementary Data 8.