Network Pharmacology Integrated Molecular Docking Analysis of Potential Common Mechanisms of Shu-Feng-Jie-Du Capsule in the Treatment of SARS,MERS,and COVID-19

Abstract

Shu-Feng-Jie-Du Capsules (SFJDCs) have been clinically proven to have a good therapeutic effect on COVID-19 in China. This study aimed to analyze the common mechanisms of SFJDC in the treatment of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19 via network pharmacology and molecular docking. We further explored the potential application value of SFJDC in the treatment of coronavirus infection. All components of SFJDC were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The viral associated targets of the active components were forecast using the Pharmmapper database and GeneCards. The Database for Annotation, Visualization, and Integrated Discovery and KOBAS 3.0 system were used for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of SFJDC’s core targets. Further, the protein–protein interaction network was built using STRING database. The herb–component network and component–target–pathway network were constructed using Cytoscape 3.7.2. The core active components of SFJDC were docked with core targets and COVID-19 coronavirus 3 Cl hydrolase and angiotensin-converting enzyme 2 (ACE2) via Discovery Studio 2016 software. A total of 110 active components were filtered from SFJDC, with 47 core targets, including epidermal growth factor receptor, mitogen-activated protein kinase 1, mitogen-activated protein kinase 3, and interleukin 6. There were 416 GO items in the GO enrichment analysis (P < .05) and 57 signaling pathways (P < .05) in KEGG, mainly including pathways in cancer, pancreatic cancer, colorectal cancer, apoptosis, and neurotrophin signaling pathway, among others. The results of molecular docking showed that luteolin and rhein had a higher docking score with 3 Cl, ACE2, and core targets of SFJDC for antiviral effect. SFJDC is characterized by multicomponent, multitarget, and multisignaling pathways for the treatment of coronavirus infection. The mechanism of action of SFJDC in the treatment of MERS, SARS, and COVID-19 may be associated with the regulation of genes coexpressed with ACE2 and immune- related signaling pathways.

Keywords

coronavirus network pharmacology Shu-Feng-Jie-Du Capsule COVID-19 SARS MERS flavonoids

Coronavirus (CoV) belongs to the family Coronaviridae, which is named based on its crown-like appearance under an electron microscope. So far, approximately 15 different strains of CoV have been discovered, which can infect a variety of mammals and birds; some can cause illnesses in humans.¹ In the past 20 years, there have been 3 severe CoV outbreaks worldwide; these are severe acute respiratory syndrome (SARS) in 2002, Middle East respiratory syndrome (MERS) in 2012, and a new CoV disease at the end of 2019 (COVID-19). On comparing the 3, COVID-19 has to date caused the worst impact. According to statistics, as of August 12th, 2020, a total of 20 548 562 individuals have been infected with SARS-CoV-2 worldwide, of which 746 327 have died. The key epidemic areas are shown in Figure 1. Thus, CoV infection has become a major threat to global public health. In terms of epidemiology and biological characteristics, SARS, MERS, and COVID-19 have high similarities, with the clinical manifestations of all 3 including fever and respiratory infections. During the SARS virus outbreak in 2002, Chinese medicine played a critical role in fighting against the virus. Further, during the first outbreak of COVID-19, China vigorously used traditional Chinese medicine (TCM) for antiviral treatment. The results showed that the effective rate of TCM has reached more than 90%. Chinese medicine has thus shown its unique advantages.²

Figure 1

Statistics on the cumulative number of confirmed cases and cumulative death toll in key epidemic areas.

In Chinese medicine, Shu-Feng-Jie-Du Capsule (SFJDC) is often used for treating acute upper respiratory tract infections, sore throat, headache, fever, and cough.³ SFJDC was included in the treatment of CoV-induced pneumonia on January 27th, 2020 by China’s National Health Commission and the State Administration of Traditional Chinese Medicine, and has achieved results.⁴ In fact, SFJDC has been previously included in the diagnosis and treatment plan for viral pneumonia several times in China. SFJDC consists of Isatidis Radix (Banlangen), Polygonum cuspidatum (Huzhang), Forsythiae Fructus (Lianqiao), Bupleuri Radix (Chaihu), Glycyrrhiza uralensis (Gancao), Herba Patriniae (Baijiangcao), Verbenae Herb (Mabiancao), and Phragmitis Rhizoma (Lugen). According to TCM theory, the pathogenesis of CoV-induced pneumonia mainly indicates damp pathogens caused by cold and dampness outside the lungs and spleen, leading to Qi disorder and heat stagnation. Isatidis Radix, Polygonum cuspidatum, and Forsythiae Fructus in SFJDC have the functions of clearing heat, detoxifying dampness, and relieving asthma, respectively.^5
-7 In the clinical treatment of COVID-19 in China, SFJDC has also been used for treating critically ill patients, and the results show that it could have an anti-CoV effect and enhance immunity. However, the mechanism of SFJDC treatment for COVID-19 is unclear. Further, the efficacy of the main compound of each drug is not known.

Network pharmacology is a research discipline that uses multiple components and multiple targets as the starting point, to study the mechanism of action of TCM in the treatment of diseases under the guidance of systems biology theory.⁸ Unlike the previous single-target and single-pathway mechanism research, network pharmacology conforms to the systemic and holistic thinking mode of Chinese medicine. The high-throughput molecular docking technique can simulate interactions between receptors and drug molecules.⁹ It is usually used to study the active sites of drugs and plays an important role in the study of natural products. In this study, we predicted the core components and core targets of SFJDC and the signaling pathways for treatment of SARS, MERS, and COVID-19 through network pharmacology and molecular docking, and the common effects and mechanisms of SFJDC in the treatment of these 3 kinds of CoV infection are discussed.

Materials and Methods

Collection of Active Ingredients

Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, http://tcmspw.com/index.php), which provides pharmacokinetic properties of natural compounds such as oral bioavailability (OB) and drug-likeness (DL) for new drug discovery, was used to collect all the chemical components of SFJDC.¹⁰ PubChem database (http://pubchem.ncbi.nlm.nih.gov/) was used to establish a chemical composition database of the SFJDC.

Screening of Active Ingredients and Target Proteins

OB and DL are the most significant pharmacokinetic parameters. In the drug absorption, distribution, metabolism, and excretion system, OB indicates the speed and degree at which the active components or active groups of an oral drug are absorbed into systemic circulation.¹¹ DL refers to the similarity of a compound with a known drug, and the potential of this class of compounds to become drugs.¹² Here, the active compounds in SFJDC were selected according to the criterion of OB ≥30% and DL ≥0.18.^13,14 The protein targets associated with active compounds were retrieved from the TCMSP database. The targets, including the gene names and gene ID, were further extracted using UniProtKB (http://www.uniprot.org).

Predicting the Targets of SARS, MERS and COVID-19

GeneCards (https://www.genecards.org/) is a comprehensive database of functions involving proteomics, genomics, and transcriptomics. Accordingly, target information concerning SARS, MERS, and COVID-19 was gathered using GeneCards. At the same time, the common targets of the 3 diseases were obtained by mapping the target genes of the 3 diseases through the Venny2.1.0 database, an interactive tool for comparing lists with Venn’s diagrams. The common targets of SFJDC and the 3 diseases were then gathered as the core targets of SFJDC for treating the 3 CoVs through the Venny2.1.0 database.

GO and KEGG Pathway Enrichment Analysis

The Database for Annotation, Visualization, and Integrated Discovery (DAVID, https://david. ncifcrf.gov/) was used to process data and visualize the enrichment results of gene ontology (GO) enrichment analysis. GO enrichment analysis included biological processes (BPs), molecular functions (MFs), and cellular components (CCs).¹⁵ Further, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the KOBAS3.0 system (http://kobas.cbi.pku.edu.cn/anno_iden.php), which provides comprehensive biofunctional annotations for a large number of genes. Subsequently, we selected the identifier as “GENE OFFICIAL SYMBOL” and species as “Homo sapiens” for GO enrichment and KEGG pathway annotations. All results were screened with P < .05. The top 20 relevant results from the KEGG pathway and GO enrichment analysis were plotted using the Omicshare tool (http://www.omicshare.com) as bubble plots.

Construction of Protein–Protein Interactions Network

The core targets of SFJDC for treating the 3 CoVs were put into STRING (https://string-db.org/cgi/input.pl) to build a protein–protein interactions (PPI) network. Angiotensin-converting enzyme 2 (ACE2) was confirmed to be closely related to SARS-CoV-2 in human cells. Simultaneously, the top 10 core targets interacting with ACE2 were found through the STRING database.¹⁶

Network Construction

A visual herb–component network was established based on the aforementioned data sets through Cytoscape 3.7.2 (http://www.cyto-scape.org/) to reflect the complex relationships between herbs and their active compounds. The component–target–pathway network was also constructed in the same way. Different nodes were used to represent the active components, targets, and pathways. Edges were used to indicate the correlation between the 2 nodes.

Molecular Docking

The core components selected from the active ingredients of SFJDC were molecularly docked with COVID-19 CoV 3 Cl hydrolase and ACE2, and some core targets of SFJDC for the treatment of the 3 CoVs using Discovery Studio 2016 software. For comparison, we chose Remdesivir as a positive control for molecular docking.¹⁷ The structures of the related proteins were downloaded from the RSCB PDB database (https://www.rcsb.org/) and compound structures were downloaded from the Pubchem database (https://pubchem.ncbi.nlm.nih.gov/). LiDockscore ≥90 is generally believed to have a strong binding ability when docking with the processed protein.

Results

Active Compounds of SFJDC

A total of 110 chemical components were selected with OB ≥30% and DL ≥0.18 from the TCMSP database, of which 15 were from Isatidis Radix; 4 from Polygonum cuspidatum; 6 from Forsythiae Fructus; 7 from Bupleuri Radix; 66 from Glycyrrhiza uralensis; 6 from Herba Patriniae; 5 from Verbenae Herb, and 1 from Phragmitis Rhizoma. The basic information of some compounds in SFJDC is shown in Table 1. All collected compound information is shown in Supplemental Table S1.

Table 1

Basic Information on Some Components in Shu-Feng-Jie-Du Capsule.

Herb	Chemical component	Pubchem CID	MW	OB (%)	DL
Isatidis Radix	Ineketone	188456	318.50	37.14	0.3
	Dinatin	5281628	300.28	30.97	0.27
	Neohesperidin	42607889	302.30	71.17	0.27
	Sinensetin	145659	372.40	50.56	0.45
	Qingdainone	3035728	363.39	45.28	0.89
Polygonum cuspidatum	Physovenine	442113	262.37	106.21	0.19
	Physciondiglucoside	442762	608.6	41.65	0.63
	Rhein	10168	284.23	47.07	0.28
Forsythiae Fructus	Wogonin	5281703	284.28	30.68	0.23
	Mairin	64971	456.78	55.38	0.78
	Hyperforin	441298	536.87	44.03	0.60
	Dimethylmatairesinol	384877	386.48	52.30	0.48
	Isolariciresinol	160521	316.28	66.51	0.39
Bupleuri Radix	Baicalin	64982	446.39	40.12	0.75
	Isorhamnetin	5281654	316.28	49.60	0.31
	Areapillin	158311	360.34	48.96	0.41
	Cubebin	117443	356.4	57.13	0.64
	Sainfuran	185034	426.5	79.91	0.23
Glycyrrhiza uralensis	Glyasperin C	480859	356.45	45.56	0.40
	Glycyrol	5320083	366.39	90.78	0.67
	Licochalcone B	5318999	286.3	76.76	0.19
	Glyzaglabrin	5317777	298.26	61.07	0.35
	Phaseol	44257530	336.36	78.77	0.58
Herba Patriniae	Acacetin	5280442	284.28	34.97	0.24
	Linarin	5317025	592.6	39.84	0.71
	Luteolin	5280445	286.25	36.16	0.25
	Kaempferol	5280863	286.25	41.88	0.24
	Quercetin	5280343	330.31	46.43	0.28
Verbenae Herb	Epi-oleanolic Acid	11869658	456.78	32.03	0.76
	Diosmetin	5281612	300.28	31.14	0.27
	Artemetin	5320351	388.4	49.55	0.48
	Cornudentanone	46191017	378.56	39.66	0.33
Phragmitis Rhizoma	Stigmasterol	5280794	412.77	43.83	0.76

Abbreviations: DL, drug-likeness; MW, molecular weight; OB, oral bioavailability.

The Core Targets of SFJDC for Treatment of the 3 Coronaviruses

A total of 133 common targets were found for treatment of the 3 CoVs using Venny2.1.0. Among the 133 shared disease targets, there were 47 intersections with compound targets, and these were considered to be core targets of SFJDC for the 3 types of CoVs, as shown in Figure 2. Specific information of these 47 core targets is shown in Supplemental Table S2.

Figure 2

Wayne diagram for coincidence targets. (A) Common targets of 3 diseases: SARS, MERS and COVID-19; (B) Wayne for compound predicted target and common targets of 3 diseases illustration. COVID-19, coronavirus disease 19; MERS, Middle East respiratory syndrome; SARS, severe acute respiratory syndrome.

Target Biological Function Analysis

GO functional enrichment analysis in DAVID yielded 416 GO entries, including 366 (88.0%) BP entries, 21 (5.0%) CC entries, and 29 (7.0%) MF entries. The top 20 BPs, CCs, and MFs are shown in Figure 3(A-C), respectively.

Figure 3

Bubble chart of the results of the identified target proteins by Database for Annotation, Visualization, and Integrated Discovery. (A) The top 20 significantly enriched terms in biological process; (B) The top 20 significantly enriched terms in cellular component; (C) The top 20 significantly enriched terms in MF; (D): The top 20 KEGG pathways enrichment analysis. BP, biological process; CC, cellular component; GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular function.

KEGG pathway enrichment was conducted to cluster the major effects associated with SFJDC. In all, 57 signaling pathways were enriched, and the top 20 pathways are shown in Figure 3(D). The main pathway included pathways in cancer, pancreatic cancer, colorectal cancer, apoptosis, and so on. Among them, pathways in cancer involved 24 genes including epidermal growth factor receptor (EGFR), interleukin (IL)6, caspase (CASP)3, mitogen-activated protein kinase (MAPK)1, MAPK3, and phosphatidylinositol-4,5-bisphosphate-kinase catalytic subunit gamma. The apoptosis pathway involved 11 genes, including PI3KCG, CASP6, CASP3, tumor necrosis factor (TNF), B-cell lymphoma 2, and Nuclear Factor Kappa B Subunit 1 (NFKB)1. We predicted that some compound of SFJDC could act on EGFR, MAPK1, MAPK3, IL6, TNF, NFKB1, and other genes to regulate apoptosis, small-cell lung cancer, the inflammation pathway, and other signaling pathways, to achieve an anti-CoV effect. Specific information of gene degree is shown in Supplemental Table S2.

PPI Network

The core potential targets were analyzed using the STRING database; the PPI network is shown in Figure 4(A). We further found that IL6 and MAPK3 were the links between ACE2 and other targets, as shown in Figure 4(B). Moreover, we found that these 2targets were widely present in the top 20 compounds. This suggested that the mechanism of action of SFJDC in the treatment of the 3 CoV diseases may be related to the regulation of genes coexpressed with ACE2.

Figure 4

Protein–protein interaction network. (A) Interaction of core potential targets of SFJDC for the treatment of 3 coronaviruses; (B) Network between top 10 genes and ACE2. ACE2, angiotensin-converting enzyme 2; CASP3, caspase 3; EGFR, epidermal growth factor receptor; IL6, interleukin 6; MAPK3, mitogen-activated protein kinase 3; SFJDC, Shu-Feng-Jie-Du Capsule.

Topology Analysis Network

The herb–component network (shown in Figure 5(A)) included 118 nodes (8 herb nodes, 110 component nodes) and 110 edges. Further, the constructed network of component–target–pathway included 177 nodes (110 component nodes, 47 target nodes, 20 pathway nodes) and 779 edges, as shown in Figure 5(B). The green color represents the pathway, purple the target, and blue the active components. According to the degree analysis, the top 6 compounds were MOL001689 (acacetin), MOL001774 (ineketone), MOL000422 (kaempferol), MOL000006 (luteolin), MOL004961 (quercetin), and MOL002268 (rhein). We found a phenomenon wherein different compounds interacted with the same target, reflecting the mechanism of interaction between multiple components and multiple targets in TCM. This was mutually corroborated with the multitarget therapeutic mechanism of TCM.

Figure 5

Network constructed by Cytoscape. (A): Herb–component network. The network formed with 118 nodes and 110 edges; (B): Herb–target–pathway network. The blue circle was the active compounds of SFJDC, and the purple regular hexagon was the core target proteins of SFJDC for treatment of the 3 coronaviruses, the green square was the pathway signaling. SFJDC, Shu-Feng-Jie-Du Capsule.

Molecular Docking Display

The 6 core components (acacetin, ineketone, kaempferol, luteolin, quercetin, and rhein) mentioned in Topology Analysis Network were docked with the top 3 core targets (EGFR, MAPK1, and MAPK3) mentioned in Supplemental Table S2. Further, the 6 components were also docked with SARS-CoV-2 3 Cl protein and ACE2 protein. The result showed that all core components had strong affinity for EGFR, MAPK3, ACE2 protein, and SARS-CoV-2 3 Cl protein. Compared with other targets, the docking score of MAPK1 with the core compounds was not too high. In addition, via molecular docking, luteolin and rhein showed strong affinity toward the 5 targets, which suggested that these 2 compounds are important components of SFJDC for treatment against the 3 CoVs. The docking scores of Remdesivir with the 5 targets are all around 150, which implied that our molecular docking data were accurate and true. The details are shown in Figures 6 and 7, and Table 2. The molecular docking diagram of components with EGFR, MAPK1, and MAPK3 is shown in Supplemental Figures S1-S3. The molecular docking diagram of Remdesivir with 5 targets is shown in Supplemental Figure S4. From this, we found that conventional hydrogen bonds and carbon hydrogen bonds were the most important chemical bonds in the docking of the compounds with the targets. Specific information of the amino acid residue and chemical bond is shown in Supplemental Table S3.

Figure 6

Results of molecular docking of each compound with COVID-19 3 Cl hydrolase. (A) Acactein; (B) ineketone; (C) kaempferol; (D) luteolin; (E) quercetin; (F) rhein.

Figure 7

Results of molecular docking for each compound with angiotensin-converting enzyme 2. (A) Acacetin; (B) ineketone; (C) kaempferol; (D) luteolin; (E) quercetin; (F) rhein.

Table 2

Results of Molecular Docking.

Gene	PDB (ID)	Compound	LiDockScore	Amino acid residue	Chemical bond
3 Cl	6M2N	acactein	97.8431	ARGA298	Conventional hydrogen bond
		ineketone	90.703	ASPA153	Conventional hydrogen bond
		kaempferol	91.5518	PHEA294	Pi–pi stacked
		luteolin	109.2459	PHEA294	Van Der Waals
		quercetin	93.1217	TYRA154	Carbon hydrogen bond
		rhein	101.6748	TYRA154	Pi–donor hydrogen bond
		remdesivir	169.391	PHEA3	Conventional hydrogen bond
ACE2	3D0G	acactein	99.633	ASPA206	Pi–anion
		ineketone	92.9445	ARGA514	Conventional hydrogen bond
		kaempferol	94.7515	ASNA397	Conventional hydrogen bond
		luteolin	102.8176	HISA401	Conventional hydrogen bond
		quercetin	90.4925	ASNA397	Conventional hydrogen bond
		rhein	100.9256	ARGA514	Conventional hydrogen bond
		remdesivir	150.556	ALAA348	Conventional hydrogen bond
EGFR	6DUK	acactein	107.217	ASNB996	Carbon hydrogen bond
		ineketone	98.5733	GLUA1005	Conventional hydrogen bond
		kaempferol	108.425	ASNB771	Conventional hydrogen bond
		luteolin	112.777	ARGA776	Conventional hydrogen bond
		quercetin	103.025	LYSE852	Conventional hydrogen bond
		rhein	104.157	ARGA776	Conventional hydrogen bond
		remdesivir	158.207	ASPB770	Carbon hydrogen bond
MAPK1	6G54	acactein	86.3101	META108	Conventional hydrogen bond
		ineketone	82.7762	LYSA54	Alkyl
		kaempferol	86.5627	LYSA114	Conventional hydrogen bond
		luteolin	92.7048	ASPA167	Conventional hydrogen bond
		quercetin	83.7626	ILEA31	Conventional hydrogen bond
		rhein	90.3351	GLNA105	Conventional hydrogen bond
		remdesivir	148.265	SERA153	Carbon hydrogen bond
MAPK3	4QTB	acactein	113.582	SERA74	Carbon hydrogen bond
		ineketone	97.4927	THRA85	Conventional hydrogen bond
		kaempferol	101.801	ASPA184	Conventional hydrogen bond
		luteolin	119.281	ASPA184	Conventional hydrogen bond
		quercetin	107.63	ALAA52	Carbon hydrogen bond
		rhein	121.139	TYRA81	Pi–pi stacked
		remdesivir	165.759	TYRA53	Conventional hydrogen bond

Abbreviations: ACE2, angiotensin-converting enzyme 2; EGFR, epidermal growth factor receptor; MAPK, mitogen-activated protein kinase.

Discussion

In this study, the mechanism underlying the treatment of CoV infection with SFJDC was studied by network pharmacology, and 110 effective compounds, 47 effective targets, and 57 signal pathways were screened out. Acacetin, ineketone, kaempferol, luteolin, quercetin, and rhein were found to be the main active ingredients against CoV infection. These 6 compounds were molecularly docked with 3 Cl and ACE2, which were identified as the basic receptors for SARS-CoV, and luteolin and rhein showed strong affinity.¹⁸ This indicates that luteolin and rhein might play an important role in the treatment of CoV infection. Luteolin is a flavonoid, which is a constituent of various plants and has antibacterial, anti-inflammatory, and antitumor activities, in addition to other pharmacological properties.¹⁹ At present, controlling the expression of inflammatory factors to improve the body’s immunity is considered to be an important method for treatment against viral pneumonia.²⁰ As previously reported, luteolin inhibits the expression of inflammatory factors by reducing the activity of NF-κB by reducing the phosphorylation of IκBα and p65.²¹ Chen et al have reported that luteolin produces anti-inflammatory effects by decreasing the expression level of high mobility group protein 1 (HMGB1) and inhibiting the effects of c-Jun and AKT.²² In addition, luteolin has a direct antiviral pharmacological effect; it has a strong affinity to the S2 subunit of S protein, which is a SARS-CoV transmembrane protein. Luteolin may block the virus from entering the cell by blocking the S2 subunit-mediated fusion of the virus with the host cell, thereby achieving an anti-SARS effect.²³ Rhein is a lipophilic anthraquinone, which is widely present in Chinese herbal medicines such as rhubarb, cassia seed, and fleece-flower roots.²⁴ Rhein has anti-inflammatory, hypoglycemic, antitumor, and antiviral pharmacological effects. Rhein can significantly reverse the activation of transcription factor 6 during inflammation, and inhibit the increase in matrix MMP-2 and pAKT/Akt ratio, thereby reducing the inflammatory response.²⁵ Rhein has also been found to significantly inhibit the proliferation of mouse influenza A virus, and a high -dose (150 mg·kg⁻¹·day⁻¹) of rhein can also significantly reduce the viral load in mouse lungs through TLR4, Akt, MAPK, and NF-κB signal pathways.²⁶ Therefore, luteolin and rhein may be effective against CoV infection-induced pneumonia through their anti-inflammatory or antiviral pharmacological effects.

KEGG enrichment analysis showed that the key targets were mainly concentrated in pathways such as the TNF signaling pathway, apoptosis pathway, and MAPK signaling pathway. The main genes involved in these pathways include EGFR, MAPK1, MAPK3, TNF, IL-6, NFKB1, and CASP3, among others. Based on the results of molecular docking, we speculate that SFJDC can be used to treat SARS, MERS, and COVID-19 through the activation of EGFR, MAPK, and TNF in the following ways. EGFR is a member of the type I tyrosine kinase receptor gene family, which is mainly involved in cell signal transduction.²⁷ Once activated, it leads to cell differentiation, proliferation, infiltration, and angiogenesis; inhibits the high-expression CASP3 protein in virus-infected cells; antagonizes virus-induced apoptosis; and achieves an antiviral effect. MAPK is involved in mediating various physiological and pathological processes such as cell growth, development, division, and differentiation. Many anti-inflammatory drugs work through the MAPK signaling pathway.²⁸ Luteolin was found to inhibit airway inflammation through its effect on p38MAPK and peroxisome proliferator-activated receptor γ signaling pathways.²⁹ Further, rhein was found to suppress neuroinflammation via multiple signaling pathways (PI3K/Akt, p38, ERK1/2, and TLR4/NF-kappa B) in lipopolysaccharide-stimulated BV2 microglia cells.³⁰ These may also be an important pathway for SFJDC to fight against CoV infection. TNF causes tumor cell necrosis and apoptosis, and plays a key role in various immune and inflammatory processes, including cell activation, survival, proliferation, necrosis and apoptosis.³¹ TNF induces the production of IL-6 and other cytokines participating in the process of inflammation. Previous studies have reported that luteolin significantly reduced serum TNF-α levels in patients with chronic obstructive pulmonary disease, and significantly improved dyspnea and pulmonary ventilation.³²

However, there are still some limitations in network pharmacology and molecular docking technology. In-depth experimental research should be performed in the future from the viewpoint of material science, pharmacokinetics, and pharmacodynamics, to provide a more specific pharmacological basis for the treatment of CoV-infected pneumonia using SFJDC.

Conclusion

In summary, we screened the active ingredients, core targets, and potential signaling pathways of SFJDCs for the treatment of CoV-induced pneumonia by network pharmacology and molecule docking techniques, and found that SFJDC regulates multiple signaling pathways and plays a role in treating CoV-induced pneumonia as observed in SARS, MERS, and COVID-19.

Supplemental Material

Supplementary Material 1 - Supplemental material for Network Pharmacology Integrated Molecular Docking Analysis of Potential Common Mechanisms of Shu-Feng-Jie-Du Capsule in the Treatment of SARS, MERS, and COVID-19

Supplemental material, Supplementary Material 1, for Network Pharmacology Integrated Molecular Docking Analysis of Potential Common Mechanisms of Shu-Feng-Jie-Du Capsule in the Treatment of SARS, MERS, and COVID-19 by Ying Zhang, Yi Xie, Bing Yu, Chong Yuan, Zixin Yuan, Zongchao Hong, Hezhen Wu and Yanfang Yang in Natural Product Communications

Footnotes

Acknowledgments

The authors would like to thank all the colleagues and students who contributed to this study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the National Natural Science Foundation of China [No. 31570343]; Hubei University of Chinese Medicine Funding Project on COVID-19 Emergency Science and Technology Research.

ORCID iDs

Ying Zhang

Bing Yu

Zongchao Hong

Supplemental Material

Supplemental material for this article is available online.

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