Deciphering the anti‑influenza potential of Eucommiae Cortex based on bioinformatics analysis: In silico and in vitro experiments

Abstract

Influenza infections damage the airway and induce the innate immune response that contributes to hyper-inflammation. Eucommiae Cortex (EC) enhances immune function and suppresses inflammation. To determine potential compounds and targets of EC associated with influenza, bioinformatics analyses and experimental verification were employed. The active compounds of EC were retrieved from the Traditional Chinese Medicine Systems Pharmacology database. The intersecting targets of EC and influenza were determined and examined using network pharmacology to analyze the relationship between the compounds and disease targets. The network identified three main compounds (quercetin, genistein and kaempferol) and four main targets (IL6, BCL2, IL1B and TNF). The ligand-target binding affinity was calculated by molecular docking, a computational method used in drug design to predict the interaction between the compound and protein target. The docking results revealed that kaempferol and TNF showed the strongest binding affinity. In vitro experiments confirmed the therapeutic effect of EC in influenza virus-infected Madin-Darby canine kidney cells. Collectively, the present study identified the active compounds and potential targets of EC in influenza and suggested EC as a future influenza treatment.

Keywords: Eucommiae Cortex; bioinformatics; influenza; molecular docking; network pharmacology; systems biology.

Figure 1

Hub target prediction. Targets associated with EC extracts and influenza. A total of 26 hub targets were retrieved. EC, Eucommiae Cortex.

Figure 2

Compound-Disease Target network analysis. The network was constructed and analyzed using Cytoscape. A total of 37 nodes and 53 edges were identified in the network. Diamond nodes indicate compounds and rectangle nodes indicate disease targets. Quercetin showed the highest degree (degree of 18), followed by genistein (13) and kaempferol (10).

Figure 3

PPI network analysis. The PPI network shows the link between the hub targets. The degree of a node refers to the number of connections between the proteins. IL-6 had the highest degree of 14, followed by BCL2, IL1B and TNF (degree of 13). Purple nodes indicate compounds of EC and blue nodes indicate the targets. PPI, protein-protein interaction.

Figure 4

Top 10 Kyoto Encyclopedia of Genes and Genomes signaling pathways were plotted in bubble diagrams.

Figure 5

Ligand-receptor interaction of kaempferol-TNF in 3D- and 2D-simulation was constructed and analyzed using Biovia Discovery Studio.

Figure 6

Cytotoxic effect of EC ethanolic extract in Madin-Darby canine kidney cells. Cells were incubated with extract at concentrations of 1,000 µg/ml and below for 48 h at 37˚C with 5% CO₂. Cell viability was tested by spectrophotometric measurements based on the WST assay protocol. ^**P<0.01 vs. untreated control group. EC, Eucommiae Cortex.

Figure 7

Antiviral properties of the EC extract. The antiviral properties were assessed using (A) Pre-Treatment, (B) Attachment Inhibition, (C) Co-Treatment, and (D) Post-Treatment Assays. Significance: ^*P<0.05 and ^**P<0.01 compared to the virus-only control group. EC, Eucommiae Cortex; NTC, not-treated/not-infected group; V(+), infected/not-treated group.

Figure 8

Time-of-addition assay. Madin-Darby canine kidney cells were pre-infected for 1 h with the influenza virus. After the virus removal, EC extract treatments started after 2, 4, 8 or 12 h and cell viability was detected after 48 h. ^**P<0.01 compared with virus-only control. EC, Eucommiae Cortex; NTC, not-infected/not-treated control group; V(+), infected and not-treated group.