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Table of Contents
ORIGINAL ARTICLE
Year : 2020  |  Volume : 6  |  Issue : 2  |  Page : 180-187

A network pharmacology study of reduning injection for the treatment of coronavirus disease-19


1 Clinical College of Traditional Chinese Medicine, Hubei University of Chinese Medicine, Wuhan, China
2 Department of Nephrology, Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan, China

Date of Submission22-Mar-2020
Date of Acceptance26-Mar-2020
Date of Web Publication30-May-2020

Correspondence Address:
Prof. Jun Yuan
Department of Nephrology, Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan 430065
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/wjtcm.wjtcm_19_20

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  Abstract 


Objective: The 2019 novel coronavirus (2019-nCoV) outbreak has escalated into a global pandemic. According to Chinese guidance for coronavirus disease-19 (COVID-19): Prevention, control, diagnosis, and management, Reduning injection can effectively treat, the disease caused by the virus. To identify the active ingredients of Reduning injection and COVID-19 disease-related pathways, we conducted a network pharmacology study. Methods: The Traditional Chinese Medicine Systems Pharmacology database was used to screen the chemical constituents and potential targets of Reduning injection. The gene names were converted to the corresponding protein names using UniProt. GeneCards and OMIM databases were used to select targets related to 2019-nCoV. Using Cytoscape 3.7.2 software platform and STRING database, we constructed drug-common target and target protein protein-protein interaction network diagrams. Rx64 3.6.2 software and Bioconductor biological information software package were used for Gene Ontology (GO) functional enrichment and KEGG pathway analyses. Results: In Reduning injection, a total of 33 effective chemical components were obtained that were involved in 151 signaling pathways, of which 44 targets were considered therapeutically relevant. Conclusion: Reduning injection can be potentially applied for the treatment of COVID-19 based on the results of our network pharmacology study.

Keywords: 2019-novel coronavirus, network pharmacology, reduning injection, signaling pathway, target


How to cite this article:
Wu J, Ruan DD, Fu TF, Yuan J. A network pharmacology study of reduning injection for the treatment of coronavirus disease-19. World J Tradit Chin Med 2020;6:180-7

How to cite this URL:
Wu J, Ruan DD, Fu TF, Yuan J. A network pharmacology study of reduning injection for the treatment of coronavirus disease-19. World J Tradit Chin Med [serial online] 2020 [cited 2020 Jul 5];6:180-7. Available from: http://www.wjtcm.net/text.asp?2020/6/2/180/285412




  Introduction Top


Since December 2019, coronavirus disease-19 (COVID-19) has been outbreak in many places around the world, which is highly infectious and highly epidemic.[1] The World Health Organization officially named the virus severe acute respiratory syndrome (SARS) coronavirus 2.[2] The 2019-novel coronavirus (2019-nCoV) is transmitted mainly through respiratory droplets and person-to-person or contaminated surface contact. The main symptoms of COVID-19 are fever, dry cough, and fatigue. The patients with severe and critical illness present with dyspnea and acute respiratory distress syndrome.[3] Currently, there is no effective antiviral treatment for the nCoV. At present, a symptomatic supportive treatment with Western medicines and traditional Chinese medicine is primarily implemented in the clinical setting.

Previously, Reduning injection, a traditional Chinese medicine injection, has shown efficacy for the treatment of respiratory viral infections in China. Chinese guidance for COVID-19: Prevention, control, diagnosis, and management (7th edition) has recommended Reduning injection to treat COVID-19.[4] Although Reduning injection has been used clinically to treat respiratory viral infections for a long time, its mechanism of action is unclear because of the complex composition. Reduning injection contains three herbs: Honeysuckle, Artemisia apiacea, and Gardenia. It is necessary to elucidate the mode of action of multi-target compounds by figuring out the key components and their functional pathways. The network pharmacology approach integrates the complex networks of drugs, multiple targets, and associated diseases through a biomolecular network model, which can clarify the complicated mechanisms of multi-target compounds of traditional Chinese medicine. In this study, the main active ingredients and targets of Reduning injection were explored by applying the network pharmacology method, and the targets for the treatment of new coronavirus pneumonia were identified. Moreover, GO functional enrichment and KEGG pathway analysis were performed for Reduning injection. The network pharmacology-based treatment of new coronavirus pneumonia by Reduning injection provides a basis for further scientific and clinical research.


  Methods Top


Screening of active ingredients in reduning injection

Based on the absorption, distribution, metabolism, and excretion parameters of the drug, oral bioavailability (OB) ≥30% and compound drug-likeness (DL) ≥0.18 were selected as the screening criteria. The three components of the traditional Chinese medicine such as Honeysuckle, A. apiacea, and Gardenia, were deposited into The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) (http://lsp.nwu.edu.cn/tcmsp.php) to retrieve and screen qualified compounds.

Screening of compound targets of Reduning injection, gene name conversion, and screening of target genes for diseases.

Based on the function of related targets in the TCMSP database, the eligible compounds were screened and matched to predict their potential targets. The potential drug targets were standardized using the UniProt database (http://www.uniprot.org), and the gene names of the drug targets were screened. Key words “novel coronavirus pneumonia” were entered into the GeneCards database (http://www.genecards.org/) to screen the disease targets (saved in Excel). Key words “Gene Map” were also used for screening and disease keywords were entered into the OMIM database (http://www. omim. org/) search to screen the disease targets (saved in Excel)., Construction of druginteraction target map and proteinprotein interaction (PPI) Network Diagram.

A “Venn Diagram” package was installed into the Rx64 3.6.2 software Developed by Ross Ihaka and Robert Gentleman, University of Auckland, New Zealand). Next, a Venn diagram of the drug common target-disease was constructed by plugging the screened drug gene name and disease target into the software, and Cytoscape 3.7.2 software (https://cytoscape.org/, USA) was used to construct the drug-target diagram. With the terms “multiple proteinse and “ndte sapienss in the STRING (http://string-db.org/) database, the target of drug-disease interaction was introduced to construct a core PPI network diagram.

GO functional enrichment and KEGG pathway analysis

GO functional enrichment and KEGG pathway analysis were performed on the intersecting proteins using the Rx64 3.6.2 software and “clusterProfiler,” “DOSE,” and “pathview” packages (http://www. bioconductor. org/). P ≤ 0.05 was considered statistically significant).


  Results Top


Screening of active components

With OB ≥30% and compound DL ≥0.18 as the screening parameters, 60 compounds were screened from TCMSP: 23 compounds from Honeysuckle, 22 from A. apiacea, and 15 from Gardenia. The components were quercetin, kaempferol, luteolin, stigmasterol, and β-sitosterol.

Drug target, target gene name, and disease target

From the TCMSP database, 1322 compound-related targets were screened: 449 from Honeysuckle, 510 from A. apiacea, and 363 from Gardenia. The gene names of the selected targets, related to the compounds, were converted using the UniProt database. A total of 1173 target genes were obtained of which 402 belonged to Honeysuckle, 453 to A. apiacea, and 315 to Gardenia. Finally, 208 target genes were selected to eliminate duplicate targets using Excel. A total of 253 disease genes were screened with GeneCards, and 2 disease genes were screened using the OMIM database. All disease gene data were exported and saved as Excel files.

Construction of Reduning Injection Common Target-Disease Network Diagram

Cytoscape 3.7.2 software platform (version Rx64 3.6.2) and a corresponding installation package were used to build the Reduning injection common target-disease network diagram [Figure 1], [Figure 2] and [Table 1]. As shown in [Figure 2], the blue triangles represent the common drug target and disease genes; the identity information of the drug ingredient or a numeric code (MOL ID) that represents the drug ingredient is unique and the small green ovals represent the ID of the active ingredients of the drug Honeysuckle; the small red ovals represent the ID of the active ingredients shared by multiple drugs and the small yellow ovals represent ID of the active ingredients of A. apiacea; and the small pink ellipses represent the ID of the active ingredients of Gardenia. Interactions between the nodes are represented by wires. The higher the number of node connections, the more important is the role of the target or compound in the network.
Figure 1: Drug-disease Venn diagram

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Figure 2: Drug-interaction target map

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Table 1: 33 effective active ingredients of Reduning injection in treating coronavirus disease

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There are a total of 44 Reduning injection active ingredient targets interacting with 2019-nCoV targets, among which 33 active ingredients, such as quercetin, luteolin, stigmasterol, beta-sitosterol, and kaempferol, exert a regulatory effect on 2019-nCoV [Figure 1], [Figure 2] and [Table 1]. These results suggest that the Reduning injection active ingredients play a key role in the treatment of COVID-19.

Construction of a protein-protein interaction network diagram

Forty-four potential targets of the active components interacting with 2019-nCoV were imported into the STRING database for analysis after the term “Homo sapiens” was used as the screening parameter, and a PPI network diagram was generated [Figure 3]. Based on the database analysis, there are 44 node points and 494 edges with an average node degree of 22.5 (the nodes represent proteins and the edges represent the interactions between proteins). Similarly, the 44 interacting genes were input into the Rx64 3.6.2 software for screening, and 20 proteins with the first node number were selected to obtain a 20-core-protein histogram [Figure 4]. These core proteins are mainly involved in inflammatory response, mitogen-activated protein kinase signaling, and cell apoptosis.
Figure 3: Reduning injection protein-protein interaction network diagram

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Figure 4: Histogram of top 20 core proteins of Reduning injection

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The target analysis results

Eighty-seven GO terms were enriched, 20 items with the lowest P value were selected, and a histogram and a bubble chart were generated [Figure 5] and [Figure 6]. The enriched targets were mainly related to cytokine receptor binding, cytokine activity, receptor ligand activity, and phosphatase binding.
Figure 5: Histogram of GO function enrichment of Reduning injection

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Figure 6: Bubble chart of enrichment of GO function by Reduning injection

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A total of 151 signaling pathways were selected based on KEGG pathway enrichment analysis, and 20 signal pathways with the lowest P value were chosen to draw a histogram and a bubble diagram [Figure 7], [Figure 8] and [Table 2]. The signaling pathways were related to viral infections, inflammation, and immune response. The enriched targets were mainly associated with six signaling pathways: Advanced glycosylation end products-receptor of AGEs AGE-RAGE signaling associated with diabetic complications, Kaposi sarcoma-associated herpesvirus infection-related signaling, human cytomegalovirus infection-related signaling, tumor necrosis factor (TNF) signaling, interleukin-17 (IL-17) signaling, and influenza A infection-related signaling.
Figure 7: Histogram analysis of KEGG pathway of Reduning injection for coronavirus disease-19

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Figure 8: KEGG pathway analysis bubble chart of Reduning injection for coronavirus disease-19

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Table 2: The lowest P value of 20 results of KEGG pathway analysis of Reduning injection for coronavirus disease

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  Discussion Top


COVID-19 is an acute respiratory infection caused by the 2019-nCoV virus belonging to genus β.[5] Currently, there is still no effective approved treatment for this infection. COVID-19 spreads quickly and it is highly contagious. According to traditional Chinese medicine (TCM) philosophy, the disease is caused by pathogenic factors. The etiological factors, such as damp evil, heat evil, blood stasis, toxins, and other evils, cause weakness of the body. Therefore, TCM defines COVID-19 as an “epidemic disease”.[4]A. apiacea The pharmaceutical composition of Reduning injection has good effects of expelling wind, relieving the exterior, clearing heat, and detoxifying. Previous research indicates that Reduning injection exerts anti-inflammatory and antipyretic effects not only by inhibiting the activity of neuraminidase but also by reducing the production and release of bacterial lipopolysaccharide inflammatory mediators.[6] TCM involves multiple targets and pathways. To better understand the mode of action of Reduning injection, we built an integrated analytical platform based on network pharmacology. The network pharmacology approach, through biomolecular network models, can clarify the complex treatment modality of TCM for respiratory viral infections.

A total of 33 active ingredients with potential therapeutic effects against COVID-19 were identified in Reduning injection. Among them, quercetin, luteolin, and kaempferol acted on a large number of downstream targets. Quercetin and kaempferol are components of Honeysuckle, Fructus Gardeniae, and A. apiacea, while luteolin is a component of Honeysuckle and A. apiacea. It has been demonstrated that quercetin not only exerts anti-inflammatory and immunomodulatory effects by blocking the TNFα-mediated inflammatory response [7],[8] but also inhibits MERS-CoV3C protease activity.[9] Kaempferol exerts anti-inflammatory, anti-oxidant, and immunomodulatory [10] effects and inhibits coronavirus 3a channel protein to inhibit virus release.[11] Luteolin can downregulate the expression of P65, IL-1B, and IL-6 at low concentrations, thus reducing the release of inflammatory factors and exerting an anti-inflammatory effect.[12] As mentioned above, the active ingredients of Reduning injection have specific antiviral, anti-inflammatory, anti-oxidant, and immunomodulatory activities, revealing its potential ability to fight the nCoV.

The core target proteins of Reduning injection were identified by constructing the PPI network diagram, and the top 20 core target proteins mainly belonged to three groups: (1) interleukins, including IL-6, IL-1B, IL-4, and IL-2; (2) silk MAPK family of mitogen-activated protein kinases, including MAPK8, MAPK1, and MAPK14; and (3) proteins that regulate cell apoptosis, including CASP3 and CASP8. The main characteristic of nCoV pneumonia is the inflammatory response, which is similar to that of SARS.[13] Interleukins are implicated in the development of nCoV pneumonia.[13] IL-1B, an endogenous pyrogen and proinflammatory cytokine, is involved in immunomodulatory and inflammatory responses. IL-2 is mainly produced by CD4 and CD8 cells. It can stimulate the synthesis of antibodies and promote the proliferation and differentiation of NK cells, subsequently increasing their cytolytic effect; IL-4 is a multi-effect cytokine that prolongs the lifespan of T- and B-cells and mediates tissue adhesion and inflammation;[14] IL-6 is produced by endothelial cells, fibroblasts, and macrophages during inflammation. IL-6 can promote the proliferation of T-cells and differentiation of B-cells and participate in immune and inflammatory responses.[15] MAPK8, MAPK1, and MAPK14, members of the MAPK family, can be rapidly activated in response to DNA damage, viral infection (including SARS coronavirus and human coronavirus), and oxidative stress.[16] The MAPK pathways are the c-JUN amino terminal kinase (SAPK/JNK) pathway, the extracellular regulatory protein kinase (ERK1/2, p44/42) pathway, and the p38 MAPK pathway. They are involved in regulating the inflammatory response and basic cellular physiological activity.[17],[18] CASP3 and CASP8 play a key role in cell apoptosis.

Eighty-seven enriched GO terms were identified, and the top 20 terms were selected. Three of these terms contained more than nine genes involved in cytokine receptor binding, cytokine activity, and receptor ligand activity. These biological processes play a key role in the treatment of COVID-19 with Reduning injection. KEGG pathway enrichment analysis identified 151 signaling pathways, and the top 20 pathways relating to the virus infection, inflammation, and immune reaction were selected. The five signaling pathways with 15 or more enrichment targets were AGE-RAGE diabetic complication signaling, Kaposi sarcoma-related herpes virus infection-related signaling, human cytomegalovirus infection-related signaling, tumor cytokine signaling, and influenza A infection-related signaling. The AGE-RAGE signaling pathway not only disrupts the glucose and lipid metabolism and enhances oxidative stress but also induces the activation of MAPK and PI3K-Akt signaling pathways, thus promoting the inflammatory response.[19]

Based on the results of our network pharmacology study, there are 33 effective Reduning injection chemical components, with quercetin, luteolin, and kaempferol being the major three. The components possibly affect 151 signaling pathways, including AGE-RAGE, TNF, and IL-17, and participate in the regulation 44 disease targets, such as PTGS2, CALM1, DPP4, and BCL2, related to the nCoV pneumonia.


  Conlusion Top


In summary, our network pharmacological analysis revealed the active components of Reduning injection can be potentially applied for the treatment of COVID-19 and also predicted the possible mechanisms. The above results must be verified by subsequent pharmacological experiments and clinical trials.

Acknowledgments

The authors would like to thank the Natural Science Foundation of Hubei Province (No. 2019CFB619) for their support.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]
 
 
    Tables

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