Efficacy of Xuebijing injection for the treatment of coronavirus disease 2019 via network pharmacology

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doi: 10.12032/TMR20200507178
Submit a manuscript: https://www.tmrjournals.com/tmr
Traditional Chinese Medicine
Efficacy of Xuebijing injection for the treatment of coronavirus
disease 2019 via network pharmacology
Yu-Liang Zhang1
, Qian Cui1
, Dou Zhang1
, Xin Ma1
, Guo-Wei Zhang1*
1
College of Traditional Chinese Medicine, Hebei University, Baoding 071000, China.
*Corresponding to: Guo-Wei Zhang. No.342, Yuhua Dong Road, College of Traditional Chinese Medicine, Hebei University,
Baoding 071000, China. E-mail: xxzgw@126.com.
Highlights
The Chinese drug formula Xuebijing (XBJ) injection ameliorated the inflammatory reaction, respiratory
distress, and hypoxia caused by coronavirus disease 2019 infection. Its underlying mechanism is via
affecting the angiotensin-converting enzyme 2 and signaling pathways of hypoxia inducible factor-1,
PI3K-Akt, and NF-κB by regulating the expression of protein kinase 1, VEGF-A, B-cell lymphoma-2, TNF,
and other targets.
Traditionality
The prescription of XBJ injection was first introduced in the Xuefu Zhuyu decoction in the medical book
Yilin Gaicuo (Correction of Errors in Medical Classics), written by Wang Qingren, a famous Chinese
physician in the 1830s of the Qing Dynasty of China. The decoction is composed of such main ingredients
as Honghua (Carthami Flos), Chishao (Radix Paeoniae Rubra), Chuanxiong (Chuanxiong Rhizome),
Danshen (Radix Salvia) and Danggui (Angelicae Sinensis Radix) with glucose as an auxiliary material that
can clear away heat and toxic material (equivalent to an anti-inflammatory effect in Western medicine). XBJ
injection has obtained the production approval of the State Food and Drug Administration of China and a
new drug certificate for the drug of second class (approval number: Z20040033) in 2004. It has been
employed for the clinical treatment of pneumonia for more than ten years, primarily as a treatment for
severe pneumonia and severe pneumonia with sepsis, respiratory distress, respiratory failure, and fever with
profound effects. It was designated as a severe drug in the Diagnosis and Treatment Protocol for the Novel
Coronavirus Pneumonia (trial version 7) and obtained an approval letter of supplementary application by
the State Food and Drug Administration of China for use as an additional drug application for new
indications including severe pneumonia, critical systemic inflammatory response syndrome, or multiple
organ failure from the novel coronavirus.

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Abstract
Background: To evaluate the mechanism of Chinese patent drug Xuebijing (XBJ) injection in the treatment of a
new coronavirus disease 2019 (COVID-19) based on network pharmacology and molecular docking technology.
Methods: The TCMSP database was employed to collect and screen the active ingredients of the Chinese herb
contained in the XBJ injection. The GeneCards database and STRING database were applied to collect and expand
the targets of COVID-19 and compare and screen the related targets of COVID-19 by XBJ injection. Cytoscape
was employed to build a network connecting Chinese medicine, compounds, targets, disease, and topology analysis
was performed via the Network Analyzer to screen the key ingredients and targets. The software of Schrödinger
molecular docking was used to verify the binding activity of the key ingredients of XBJ injection and the key
targets of COVID-19. Metascape platform and DAVID database were utilized to conduct Gene Ontology analysis
and Kyoto Encyclopedia of Genes and Genomes analysis on the key targets of COVID-19 treated by XBJ injection.
Results: Eight key compounds and 15 key targets were screened and verified by molecular docking; these key
compounds included luteolin, quercetin, baicalein, and kaempferol. The key targets included DPP4, AR, ESR1,
CALM1, and protein kinase 1. Gene Ontology analysis involved an apoptosis and hypoxia reaction and the changes
in blood vessel morphology. Kyoto Encyclopedia of Genes and Genomes analysis involved signaling pathways of
hypoxia inducible factor-1, VEGF, and PI3K/AKT/NF-κB. Conclusion: The mechanism of XBJ injection when
used to treat COVID-19 should be further investigated as the key compounds in XBJ regulated the expression of
key targets such as protein kinase 1, VEGF-A, B-cell lymphoma-2, and TNF, which affected the COVID-19
receptors such as angiotensin-converting enzyme 2 and signaling pathways like hypoxia inducible factor-1,
PI3K-Akt, and NF-κB, which alleviated the inflammation, respiratory distress, and hypoxia caused by COVID-19
infection.
Keywords: Network pharmacology, Molecular docking, COVID-19, Xuebijing injection, Luteolin, Quercetin
Author contributions:
Yu-Liang Zhang analyzed most of the data from database, and wrote the initial draft of the paper; Guo-Wei
Zhang developed the idea for the study; Qian Cui and Dou Zhang conducted the enrichment analyses; all authors
analyzed the data and discussed the results and revised the manuscript.
Acknowledgments:
This study was supported by the Foundation of Health Commission of Hebei Province (20190123) and the
Natural Science Foundation of Hebei Province of China (H2018201179).
Abbreviations:
XBJ, Xuebijing; COVID-19, coronavirus disease 2019; TCM, traditional Chinese medcine; KEGG, Kyoto
Encyclopedia of Genes and Genomes; GO, Gene Ontology; I-T-G-K, ingredients-targets-GO-KEGG; BC,
betweenness centrality; CC, closeness centrality; IL, interleukin; AKT1, protein kinase 1; HIF-1, hypoxia
inducible factor-1; BCL2, B-cell lymphoma-2; ACE2, angiotensin-converting enzyme 2; DPP4, dipeptidyl
peptidase-4; PDB, Protein Data Bank.
Competing interests:
The authors declare no conflicts of interest.
Citation:
Yu-Liang Zhang, Qian Cui, Dou Zhang, et al. Efficacy of Xuebijing injection for the treatment of coronavirus
disease 2019 via network pharmacology. Traditional Medicine Research 2020, 5 (4): 201–215.
Executive editor: Rui-Wang Zhao.
Submitted: 06 April 2020, Accepted: 20 April 2020, Online: 18 May 2020.

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Background
A new coronavirus disease 2019 (COVID-19) occurred
in Wuhan, Hubei Province, China, in December of
2019, which quickly spread to other countries. The fast
sprawl of this epidemic and the potentially deadly
respiratory symptoms of this disease have created a
global public health hazard of pandemic proportions [1,
2]. Coronaviruses are species of virus in the family
Coronaviridae, which are associated with common
colds and significantly more serious diseases such as
Middle East Respiratory Syndrome and Severe Acute
Respiratory Syndrome [3]. The new coronavirus
belongs to a new strain that has never been found in
the human body before. No targeted, effective drug,
primarily aimed at the symptomatic treatment of
COVID-19, is currently available. Thus, the
formulation of a plan for the rapid and effective
treatment of this disease is an overarching problem
[4].
Traditional Chinese medicine (TCM) has proved to
be useful for viral pneumonia treatment and has shown
favorable efficacy in the treatment of the Severe Acute
Respiratory Syndrome outbreak in 2003. The treatment
of COVID-19 with TCM is one of the vital treatment
protocols in the Diagnosis and Treatment Protocol for
the Novel Coronavirus Pneumonia issued and
continuously updated by the National Health
Commission of China. The prescription of Xuebijing
(XBJ) injection came from the Xuefu Zhuyu decoction
in the medical book Yilin Gaicuo (Correction of Errors
in Medical Classics), written by Wang Qingren, a
famous Chinese physician in the 1830s of the Qing
Dynasty of China. The decoction is composed of
Honghua (Carthami Flos), Chishao (Radix Paeoniae
Rubra), Chuanxiong (Chuanxiong Rhizome), Danshen
(Radix Salvia) and Danggui (Angelicae Sinensis Radix)
with glucose as an auxiliary material and is associated
with clearing away heat and toxic material (equivalent
to an anti-inflammatory effect in Western medicine).
XBJ injection has obtained production approval from
the State Food and Drug Administration of China and a
new drug certificate as a drug of second class
(approval number: Z20040033) in 2004. It has been
employed for the clinical treatment of pneumonia for
more than ten years, primarily for severe pneumonia,
severe pneumonia with sepsis, respiratory distress,
respiratory failure, and fever with profound effects [5].
It was designated as a severe drug in the Diagnosis and
Treatment Protocol for the Novel Coronavirus
Pneumonia (trial version 7) and has obtained an
approval letter for the supplementary application by
the State Food and Drug Administration of China for
an additional drug application for newer indications
such as severe pneumonia, critical systemic
inflammatory response syndrome, or multiple organ
failure caused by the novel coronavirus [6].
Analysis of the multiple ingredients and targets can
be conducted via network pharmacology, a holistic
approach used to explore the potential effects of the
drugs on diseases [7]. Furthermore, this research
method coincided with the overall concept of the TCM
treatment of diseases, placing a bedrock for research
into the mechanism of action of TCM. Molecular
docking is a method of designing drug molecules
through computer-aided means. By simulating the
geometric structure of the molecules and the
intermolecular forces, it can be used to predict the
interaction between drugs and targets and can screen
the effects of the active ingredients of TCM quickly
and accurately, which has played a paramount role in
the study of the mechanism of the effects of drugs [8].
This study analyzed the potential mechanism of
XBJ’s treatment in COVID-19 through multiple targets,
channels, and pathways by network pharmacology and
molecular docking. The research flow chart is shown
in Figure 1.
Figure 1 Flow chart of this study

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Material and methods
Screening of effective compound ingredients and
the targets of XBJ injection
Candidate active compounds and targets were
ultimately acquired via screening conditions by using
TCMSP (http://tcmspw.com/tcmsp.php) [9] database to
search the XBJ related active ingredients with oral
bioavailability ≥ 30% according to the parameters of
the human body absorption distribution metabolism
and drug-likeness ≥ 0.18.
Prediction of the potential therapeutic targets of
COVID-19
Based on the GeneCards [10] database with
“coronavirus disease 2019” as a keyword, the related
disease targets were collected and screened with a
relevance score > 20 and then the target proteins
related to COVID-19 were expanded by the STRING
(https://string-db.org/) database [11]. The
protein-protein interactions included in the STRING
database could adequately reflect which proteins
conducted the interaction. With the medium
confidence set to 0.400 and the limitation of species as
“Homo sapiens”, the targets expanded thereafter were
the ones that interacted with the known target of
COVID-19, which was capable of being used as a
potential therapeutic target of COVID-19.
Screening of the related targets for XBJ injection in
the treatment of COVID-19
The collected targets of XBJ were compared with the
potential therapeutic targets of COVID-19 through the
graphics option in TB tools to find the intersection of
tow targets as the potential target, and then the Venn
diagram of the collection of the injection targets of
XBJ and the COVID-19-related targets were drawn to
collect the intersection of the target genes, which were
the targets in the XBJ treatment of COVID-19. Finally,
the gene symbols of the related targets were mapped to
UniProt ID through the UniProt
(https://www.uniprot.org/) database.
Screening of the key targets and key compounds
involved in XBJ treatment of COVID-19
In order to further screen the key compounds and key
targets, the related targets of COVID-19 were treated
with XBJ injection and were mapped to the
corresponding chemical ingredients, and Cytoscape
3.7.2 [12] was applied to construct a
herb-compound-targets-disease network to visualize
this relationship. Subsequently, the key ingredients and
key targets were screened via a topology analysis of
the network performed by Network Analyzer.
Verification of the binding activity of the key
ingredients of XBJ injection and the key targets of
COVID-19 by molecular docking
The 3D structure of the compound in the mol2 format
was obtained in the Pubchem
(https://pubchem.ncbi.nlm.nih.gov/). Then, searched
and screened for the target protein in the Protein Data
Bank (PDB) database (https://www.rcsb.org/). The
Ligand Docking module of Schrödinger was used for
molecular docking. The PDB database stores structural
data such as molecular crystallography, nuclear
paramagnetic resonance spectroscopy, and 3D electron
microscopy [13]. Screening conditions of this protein
were as follows: (1) the analysis method was
single-crystal X-ray diffraction; (2) resolution < 2A; (3)
time of discovery was as late as possible; (4)
preference was given to those containing small
molecule ligands, of which angiotensin-converting
enzyme 2 (ACE2) was currently selected due to the
smaller database structure, and the conditions did not
include resolution. Then, pretreatment of the
compounds and proteins before docking involved the
following the small molecule ligand was docked based
on the active site of the small molecule ligand, and
those without were docked with the active site
calculated by using the binding site detect function of
the Schrödinger software. The docking precision was
set to standard precision, and the reference was the
original ligand and ACE2, a known target of
COVID-19. The results of the molecular docking and
scoring were drawn as a heat map, and the binding
mode was analyzed to verify the degree of binding of
the key ingredients of XBJ injection to the key targets
of COVID-19.
Gene Ontology (GO) annotation and Kyoto
Encyclopedia of Genes and Genomes (KEGG)
pathway analysis of key targets
The GO annotated gene targets the following three
aspects: cellular components, molecular function, and
biological processes. KEGG pathway analysis was
used to comprehend the advanced functions and
applications of the biological systems from the
perspective of the molecular level. In order to explore
the mechanism of XBJ treatment of COVID-19, GO
annotation analysis was carried out via Metascape
(https://metascape.org/) [14] platform using the
UniProt ID of the key target. The threshold was P <
0.01 and minimum count3, enrichment factor > 1.5;
KEGG pathway analysis was created by the UniProt
ID of key targets in the DAVID
(https://david.ncifcrf.gov/) [15] database. Cytoscape
3.7.2 was used to construct the
ingredients-targets-GO-KEGG (I-T-G-K) diagram for
the results of the analysis.
Results
Active ingredients and targets of XBJ injection
The TCMSP database was applied, removing the sterol

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vitamins and sugars shared in the plants and vitamins,
115 effective compounds of XBJ were obtained,
including 19 of Honghua (Carthami Flos), 25 of
Chishao (Radix Paeoniae Rubra), 6 of Chuanxiong
(Chuanxiong Rhizome), 65 of Danshen (Radix Salvia)
and none of Danggui (Angelicae Sinensis Radix).
Among them, there are 411 predicted targets of
Honghua (Carthami Flos), 275 of Chishao (Radix
Paeoniae Rubra), 72 of Chuanxiong (Chuanxiong
Rhizome), 197 of Danshen (Radix Salvia). Five
hundred thirty predicted targets of XBJ were obtained
after removing the duplicates.
Prediction of the potential therapeutic targets of
COVID-19
The COVID-19-related disease targets collected using
the GeneCards database are shown in Figure 2 after the
STRING database is expanded. The red nodes in the
central area collected 24 targets for the GeneCards
database, and the purple nodes in the outer circle
expanded the STRING database. A total of 218 related
disease targets were collected following expansion.
Screening of the related targets during XBJ
treatment of COVID-19
The Venn diagram is a comparison between the
COVID-19 potential therapeutic targets expanded, and
the XBJ target and is depicted in Figure 3. A total of 44
intersection targets were visible, which are shown in
Table 1. It has been suggested that these targets might
be related to the targets for XBJ treatment of
COVID-19. The intersection targets of the drug and the
target of the disease do not include the currently found
targets related to coronavirus infection, such as ACE2,
which indicates that XBJ injection may not directly act
on the ACE2 protein, and maybe an indirect
relationship exists between them.
Figure 2 Network of expanding targets. The red nodes collect 24 targets for the GeneCards database, and the
purple nodes expand the STRING database.

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Figure 3 Venn diagram of coincidence targets
Table 1 Targets of COVID-19
Gene symbol UniProt ID Gene symbol UniProt ID Gene symbol UniProt ID
AKT1 P31749 CRP P02741 MDM2 Q00987
ALB P02768 CXCL8 P10145 NKX3-1 Q99801
AR P10275 DPP4 P27487 NOS3 P29474
BAX Q07812 ERG P11308 PARP1 P09874
BCL2 P10415 ESR1 P03372 PCNA P12004
BCL2L1 Q07817 FOS P01100 SERPINE1 P05121
CALM1 P0DP23 IKBKB O14920 SOD1 P00441
CASP3 P42574 IL10 P22301 STAT1 P42224
CASP8 Q14790 IL1B P01584 STAT3 P40763
CAT P04040 IL4 P05112 TGFB1 P01137
CAV1 Q03135 IL6 P05231 TNF P01375
CCL2 P13500 JUN P05412 TP53 P04637
CDKN1A P38936 KDR P35968 VEGF-A P15692
CDKN2A P42771 MAPK14 Q16539 XIAP P98170
CHEK2 O96017 MCL1 Q07820
Key targets and compounds of the XBJ treatment
for COVID-19
The related targets of XBJ injection treatment of
COVID-19 were mapped to the corresponding
chemical ingredients, and Cytoscape was applied to
construct a network diagram of the
herb-compound-target-disease, as depicted in Figure 4.
In order to further screen the key compounds and
targets, Network Analyzer was employed to perform a
topological analysis on the network in Figure 4 to
obtain three network topology parameters such as
degree centrality, betweenness centrality (BC), and
closeness centrality (CC). The screening was based on
parameters twice than the median [16], and eight key
compounds were selected, as shown in Table 2. 15 key
targets were selected, and the related characteristics are
shown in Table 3. It has been suggested that XBJ
treatment of COVID-19 might involve such
compounds as luteolin, quercetin, baicalein,
kaempferol, and others acting on the key target
proteins like dipeptidyl peptidase-4 (DPP4), AR, ESR1,
CALM1, protein kinase 1 (AKT1), of which DPP4,

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TP53, TNF, CASP3, and NOS3 were the targets
without expanding protein-protein interactions, which
played a significant role in the treatment.
The verification of the binding activity of the XBJ
key compounds and the COVID-19 key targets via
molecular docking
Molecular docking using Schrödinger software
verified whether the strong binding activity is between
the smaller molecular compounds and the target.
Protein Data Bank-identification (ID), Ligand-ID and
resolution can all be seen in Table 4. A
component-target docking score of less than 0
indicated a successful docking, the higher the absolute
value of the score, the tighter the binding [17]. The fact
that the score of the docking compound is close to the
original ligand proves that the compound plays a
significant role in determining the targets during
treatment. The heat map of the molecular docking
results is depicted in Figure 5. The depth of the color
represents the docking score. The comparison of the
scores of the key targets and the positive control ACE2
to the original ligand demonstrated that each key
compound exhibited effective binding activity with at
least 8 COVID-19 key targets. This result proved that
the XBJ key compound performed binding activity to
the COVID-19 key targets.
Through a detailed analysis of the image of the
molecular docking result, the small molecule could be
tightly bound to the active site of the target protein. In
order to show a link between the target protein and the
small molecules through a variety of chemical bonds,
this is the typical binding model involved in the
relevant chemical bond in the selection. In this paper,
the combination mode of ellagic acid (MOL001002)
docking ACE2, quercetin (MOL000098) docking
DPP4, luteolin (MOL000006) docking ATK1, and
baicalein (MOL002714) docking B-cell lymphoma-2
(BCL2) are depicted in Figure 6. From the overall
diagram on the left, the small molecule compounds
could bind tightly to the active sites of the receptor
proteins. Small molecules were interlocked through
their hydrogen bonds, salt bridge, and pi-pi
interactions (Figure 6). The salt bridge exhibited by the
purple dotted line is the most common force between
the proteins, and the effect of binding on the two
atomic groups together is due to a strong electrostatic
interaction between the positive and negative charges.
This force is weaker than the hydrogen bonds; however,
it has a significant influence on the overall stability of
the combination as it is found in large amounts [18].
The pi-pi stacking showed by the red dotted line tends
to occur in the weak interactions between the
electron-rich aromatic ring and the electron-deficient
aromatic ring. To a large extent, it affects the reliability
of the combination [19]. The hydrogen bond of the
yellow dotted line is a kind of intermolecular force
between the permanent dipoles. Hydrogen bonds
occurred between a hydrogen atom bound to other
atoms by covalent bonds, which result in another atom
afforded a more substantial binding capacity second
only to the covalent bond. Hydrogen bonds are the
primary determinant as to whether the small molecules
could bind to the target protein or not [20].
Figure 4 Herb-compounds-targets-disease network. The blue bold text is the target before expansion.

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Table 2 Related characteristics of the key compounds
MOL ID Molecule Name Degree BC CC
Oral
bioavailability
(%)
Drug-likeness Structure
MOL000006 Luteolin 36 0.0777 0.4667 36.16 0.19
MOL000098 Quercetin 33 0.1370 0.5158 46.43 0.05
MOL002714 Baicalein 29 0.0312 0.4298 33.52 0.63
MOL000422 Kaempferol 13 0.0284 0.4375 41.88 0.26
MOL007154 Tanshinone iia 8 0.0145 0.4153 49.89 1.05
MOL002135 Myricanone 7 0.0308 0.4083 40.60 0.67
MOL007093 Dan-shexinkum d 6 0.0078 0.4153 38.88 0.67
MOL001002 Ellagic acid 6 0.0099 0.3684 43.06 −0.44
BC, betweenness centrality; CC, closeness centrality.
Table 3 Related characteristics of key targets
Target UniProt ID Degree BC CC Target UniProt ID Degree BC CC
DPP4 P27487 31 0.2076 0.5185 TP53 P04637 8 0.0030 0.4100
AR P10275 27 0.1196 0.4975 BCL2 P10415 8 0.0055 0.4135
ESR1 P03372 24 0.1084 0.4925 TNF P01375 7 0.0155 0.4135
CALM1 P0DP23 12 0.0388 0.4317 JUN P05412 7 0.0052 0.4100
AKT1 P31749 10 0.0051 0.4135 CDKN1A P38936 6 0.0045 0.4100
CASP3 P42574 10 0.0070 0.4170 FOS P01100 6 0.0022 0.4066
NOS3 P29474 9 0.0182 0.4170 BAX Q07812 6 0.0017 0.4033
VEGF-A P15692 8 0.0071 0.4135
ID, identification; BC, betweenness centrality; CC, closeness centrality.

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Table 4 Information on 15 proteins involved in molecular docking
Target PDB-ID Ligand-ID Resolution Target PDB-ID Ligand-ID Resolution
ACE2 6M18 NAG 2.90 Å VEGF-A 4QAF OMA 1.80Å
DPP4 6B1E LF7 1.77 Å TP53 6GGB EXQ 1.32Å
AR 6UO3 QCP 1.09 Å BCL2 6UDV Q51 1.35 Å
ESR1 6SBO L5B 1.48 Å TNF 5UUI MTN 1.40 Å
CALM1 6M7H KN9 1.60 Å JUN 6I0J GZE 1.35 Å
AKT1 4EKL ORF 2.00Å CDKN1A 5WDQ GNP 1.25 Å
CASP3 5IBP PRD 1.38 Å FOS 1FXL – 1.80 Å
NOS3 6CIE 7R2 1.95 Å BAX 6HPH ANP 1.13 Å
PDB, Protein Data Bank; ID, identification; –, not mentioned.
Figure 5 Heat map for docking score. The depth of color represents the docking score; a docking score of less
than 0 indicates a successful docking, the higher the absolute value of the score, the tighter the binding.
Analysis of the GO biological process and the
KEGG pathway for the key targets
GO biological process analysis. GO biological
process analysis obtained a total of 172 enrichment
pathways, including 33 pathways related to COVID-19.
It selected the 20 GO terms with the smallest P-value
to display in a graphical table (Figure 7). In Figure 7,
the ordinate is a GO term, and the abscissa is the
percentage of the target gene count of the GO term to
the total count of the target genes, the darker the color,
the smaller the P-value. The value of the column was
the count of the genes in a GO term.

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A. ACE2 and MOL001002 B. DPP4 and MOL000098
C. ATK1 and MOL000006 D. BCL2 and MOL002714
Figure 6 Binding modes of targets and compounds. The purple dotted line is the salt bridge, the red dotted line is
pi-pi stacking, and the yellow dotted line is the hydrogen bond. ACE2, angiotensin-converting enzyme 2; DPP4,
dipeptidyl peptidase-4; AKT1, protein kinase 1; BCL2, B-cell lymphoma-2.
Figure 7 Enrichment analysis of the GO biological process. The ordinate is a GO term and the abscissa is the
percentage of the target gene count of the GO term to the count of all of the target genes. The color represents the
P-value, the darker the color, the smaller the P-value. The value of the column is the count of genes in a GO term.

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The biological processes indicated that the treatment
of COVID-19 by XBJ involved apoptosis, response to
hypoxia, blood vessel morphogenesis, regulation of
macroautophagy, and response to TNF. This result
shows that XBJ can affect these biological processes in
the treatment of diseases.
KEGG pathway analysis. KEGG pathway
enrichment obtained a total of 57 enriched pathways,
of which 27 pathways were related to COVID-19. The
20 KEGG pathways with the smallest P-value are
depicted in the graphical display (Figure 8). The Y-axis
represents the pathway name, the X-axis represents the
enrichment degree, and the air bubble size indicates
the number of targets contained in the pathway, the
color of the significance of the pathway, is correlated
to the data of the P-value.
The KEGG pathway analysis results showed that the
XBJ treatment of COVID-19 involved the signaling
pathways of hypoxia inducible factor-1 (HIF-1), TNF,
NF-κB, VEGF, PI3K-Akt, and p53. It illustrated that
the active ingredients of XBJ might be able to treat
diseases via influencing these signaling pathways.
The construction of the
ingredients-targets-diseases-pathway relationship.
In order to organize the I-T-G-K relationship,
Cytoscape 3.7.2 was used to construct the I-T-G-K
relationship diagram. The nodes with different colors
and shapes represent the corresponding diseases,
ingredients, and targets (Figure 9). The 15 key targets
of XBJ were distributed in distinct metabolic pathways
and biological processes which jointly regulated the
organismal level. The targets reflected the mechanism
of action involved in this multi-component TCM,
which suggested potential as a multi-targeted therapy
to treat COVID-19.
Figure 8 Enrichment analysis of the KEGG pathway. The Y-axis represents the pathway name, and the X-axis
represents the enrichment degree; the air bubble size indicates the number of targets contained in the pathway and
the color shows the data of the P-value of the pathway.

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Figure 9 I-T-G-K network. I-T-G-K, ingredients-targets-GO-KEGG; KEGG, Kyoto Encyclopedia of Genes and
Genomes.
Discussion
XBJ has been used as a specific, clinical, and
evidence-based treatment of pneumonia for more than
a decade. It is mostly used in severe pneumonia and
severe pneumonia complicated with sepsis, respiratory
distress, and respiratory failure, and fever [21].
Therefore, it has become a Chinese patent medicine as
a joint recommendation for use as a therapy for both
Chinese medicine and Western medicine and has been
proven to be effective in improving
community-acquired pneumonia outcomes [22].
Severe COVID-19 patients will experience symptoms
such as acute respiratory distress syndrome, fibrosis of
the lungs, septic shock, metabolic acidosis, and blood
coagulation dysfunction. Therefore, the optimal
treatment for severe patients should improve
pulmonary function and hypoxia, reduce acute lung
injury, pulmonary fibrosis, and enhance the antiviral
immune response to reduce inflammation and other
aspects [23, 24]. Therefore, the current study was
based on research to determine a multi-component and
multi-targeted therapy for COVID-19. Through
network pharmacology technology and molecular
docking technology, this study explored the potential
targets of XBJ treatment for COVID-19 and stated the
mechanism of action found to provide a scientific basis
for clinical application. Our specific findings are as
follows.

ARTICLE
TMR | July 2020 | vol. 5 | no. 4 | 213
doi: 10.12032/TMR20200507178
The analysis results of the XBJ treatment for the
COVID-19 key targets and key compounds showed
that eight key compounds regulated 15 key targets.
Among the key compounds found in XBJ, the
flavonoids accounted for the majority including
luteolin (MOL000006), quercetin (MOL000098),
baicalein (MOL002714), tanshinone iia (MOL007154),
myricanone (MOL002135); then the phenols such as
ellagic acid (MOL001002), kaempferol (MOL000422);
and the quinone dan-shexinkum d (MOL007093).
Flavonoids such as baicalein inhibit the inflammatory
factors such as TNF and interleukin (IL) by interfering
with the NF-κB pathway, which exert antipyretic and
anti-inflammatory effects, inhibit inflammation and
apoptosis, and reduce acute lung injury [25]. Quercetin
reduces the production of NF-κB and ICAM-1 by
inhibiting the NF-κB signaling pathway and achieves
anti-inflammatory effects [26]; reportedly, it could
improve lung fibrosis in murine models by inhibiting
the SphK1/S1P signal transduction [27]. Phenolic
compounds such as ellagic acid has anti-inflammatory,
anti-allergic, antiviral, and anti-cancer properties. It is
reported that ellagic acid inhibits the Akt, ERK, p38,
MAPK, and PI3K/Akt pathways, and the NF-κB
anti-inflammatory signaling pathways to trigger
anti-inflammatory effects [28].
Key targets included DPP4, AR, ESR1, CALM1,
AKT1, CASP3, NOS3, VEGF-A, TP53, BCL2, TNF,
JUN, CDKN1A, FOS and BAX. The results of
molecular docking suggest that the above targets and
ACE2 could effectively bind to the compound. AKT1
is a direct target downstream of the PI3K pathway and
regulated many processes, including proliferation,
apoptosis, inflammation, and angiogenesis [29]. The
literature shows that AKT1 could regulate apoptotic
resistance and pulmonary fibrosis by mediating the
mitochondria [30]. BCL2 is a protein with inhibitory
effects on apoptosis, through the interaction between
proteins, and regulats the permeability of the outer
mitochondrial membrane, thereby it controlls
mitochondrial autophagy and affects apoptosis [31].
Other literature reports that in fibroid lungs and
activated fibroblasts, regulating the expression of
BCL2 and autophagy activity could be adjusted to
reduce autophagy, which plays a role in inhibiting
pulmonary fibrosis [32]. TP53 is a transcription factor,
and transcriptional activation functioned to maintain
the stability of the genome and plays multiple roles in
apoptosis, including differentiation, aging, DNA repair,
metabolism, and the immune response [33]. Another
study has demonstrated that promoting the expression
of TP53 could induce the secretion of the WNT ligands,
stimulate tumor-associated macrophages to produce
IL-1β, and inhibit the subsequent neutrophil
inflammation [34]. Therefore, it might play a similar
role in the pathogenesis of COVID-19. VEGF-A, a
vascular regulator, plays a vital role in promoting
angiogenesis, endothelial cell migration, and
proliferation [35, 36]. Furthermore, ACE2 reportedly
antagonized the increase in pulmonary vascular
permeability mediated by VEGF-A and thereby
improved pulmonary function following an acute lung
injury [39]. Since ACE2 is considered as a viral
receptor of COVID-19 [38–40], XBJ might affect the
expression of the ACE2 receptors by influencing the
VEGF-A enough to treat this disease.
Based on the analysis of the Go biological process,
this article found that the relevant biological processes
involved in XBJ as a potential treatment of COVID-19
primarily included apoptosis, response to hypoxia,
blood vessel morphogenesis, regulation of
macroautophagy, and the response to TNF. These
processes might have regulated the mechanism of
generation and development of COVID-19. The
generation process of COVID-19 includes pulmonary
injury and lung fibrosis, inflammation, and hypoxia.
XBJ restored the impaired blood vessels and
ameliorated hypoxia by interfering with
macroautophagy and relieving inflammation. The
analysis of the I-T-G-K network suggested that XBJ
could treat COVID-19 by acting on multiple pathways.
The HIF-1 signaling pathway is crucial for an
organism during a low oxygen concentration and
hypoxia response [41]. HIF-1 regulates hundreds of
gene transcriptions in the expression of cell-specific,
including VEGF-A, IL6, AKT1, and NF-κB [42].
Under hypoxia, the HIF-1 signaling pathway activates
the VEGF signaling pathway, which could be
protective by up-regulating the reverse transcription of
VEGF, and inflammation could be relieved by
regulating IL6, TNK, AKT1, and NF-κB [43]. Thus,
XBJ might improve pulmonary injury, restore impaired
vessels, and hypoxia by affecting HIF-1 and VEGF.
NF-κB signaling pathway is found to be crucial to
the inflammation and immune response of cells [44].
NF-κB pathway reportedly inhibits replication of the
influenza a virus and exacerbates viral pneumonia [45,
46]. TNF, AKT1, and NF-κB are closely related to the
PI3K-Akt signaling pathway and NF-kappaB signaling
pathway. PI3K-Akt activates NF-κB to regulate many
aspects, such as anti-inflammation-related to multiple
cellular gene expressions [46]. In the development of
cancer, NF-κB plays a vital role in regulation.
Reportedly, lower transcription activity by NF-κB
decreases expression of the inflammatory cytokines
such as IL-1β, TNF-α, and IL-6; thus, reducing
inflammation and apoptosis as well as alleviating
pulmonary injury [47]. In vitro, TNF-α-induced acute
lung injury could be attenuated via inhibiting NF-κB
and activating Nrf2 [48]. Moreover, in vivo animal
experiments found the release of proinflammatory
cytokines-was mediated by PI3K/AKT/GSK3β and
NF-κB [49]. Therefore, XBJ might have an
anti-inflammatory effect by affecting the activation of
PI3K/AKT/NF-κB, which could reduce inflammation
caused by COVID-19.

ARTICLE
TMR | July 2020 | vol. 5 | no. 4 | 214
doi: 10.12032/TMR20200507178
Conclusion
Currently, no golden standard exists for the treatment
of COVID-19. TCM plays a significant role in treating
new diseases because it features multiple ingredients,
targets, and approaches. These features were used to
explore the complicated mechanism of XBJ in the
treatment of COVID-19 via network pharmacology
and molecular docking. The mechanism of action
showed potential for the key compounds in XBJ, as
they regulated the expression of key targets such as
AKT1, VEGF-A, BCL2, and TNF, which affected the
COVID-19 viral receptors such as ACE2 and the
signaling pathways like HIF-1, PI3K-Akt, and NF-κB.
Thus, XBJ might take effect by (1) affecting the key
targets, and flavonoids in XBJ that attenuated acute
lung injury by alleviating the inflammation and
apoptosis; (2) affecting VEGF-A and then the
expression of the ACE2 receptor; (3) activating VEGF
by affecting HIF-1, which improved pulmonary injury,
restored the impaired vessels, and hypoxia; (4)
alleviating the inflammation caused by COVID-19 by
activating PI3K/AKT/NF-κB.
At present, the pathogenesis of COVID-19 has not
yet been elucidated. Thus, the mechanism of XBJ
involved in the treatment of COVID-19 requires
further research. The current study reflects the holistic
and systematic characteristics of TCM treatment by
studying the interactions between these therapeutic
targets and pathways. This article has provided a basis
for exploring the mechanism of XBJ in the treatment
of COVID-19 and offers insight into the potential of
XBJ for future researchers.
References
1. Hui DS, Azhar EI, Madani TA, et al. The
continuing 2019-nCoV epidemic threat of novel
coronaviruses to global health-the latest 2019
novel coronavirus outbreak in Wuhan, China. Int
J Infect Dis 2020, 91: 264–266.
2. Heymann DL, Shindo N. COVID-19: what is next
for public health? Lancet 2020, 395: 542–545.
3. Henry BM. COVID-19, ECMO, and lymphopenia:
a word of caution. Lancet Respir Med 2020.
4. Li G, De Clercq E. Therapeutic options for the
2019 novel coronavirus (2019-nCoV). Nat Rev
Drug Discov, 2020, 19: 149–150.
5. Liu S, Yao C, Zhang J, et al. Efficacy of
Xuebijing injection for sepsis (EXIT-SEP):
protocol for a randomised controlled trial. BMJ
Open 2019, 9: e28664.
6. Scheme for diagnosis and treatment of 2019 novel
coronavirus pneumonia (The 7th Trial Edition).
Jiangsu Journal of Traditional Chinese Medicine
2020, 52: 1–6. (Chinese)
7. Boezio B, Audouze K, Ducrot P, et al.
Network-based approaches in pharmacology. Mol
Inform 2017, 36.
8. Saikia S, Bordoloi M. Molecular docking:
challenges, advances and its use in drug discovery
perspective. Curr Drug Targets 2019, 20:
501–521.
9. Ru J, Li P, Wang J, et al. TCMSP: a database of
systems pharmacology for drug discovery from
herbal medicines. J Cheminform 2014, 6: 13.
10. Stelzer G, Rosen N, Plaschkes I, et al. The
GeneCards Suite: from gene data mining to
disease genome sequence analyses. Curr Protoc
Bioinformatics 2016, 54: 1–30.
11. Szklarczyk D, Gable AL, Lyon D, et al. STRING
v11: protein-protein association networks with
increased coverage, supporting functional
discovery in genome-wide experimental datasets.
Nucleic Acids Res 2019, 47(D1): D607–D613.
12. Shannon P, Markiel A, Ozier O, et al. Cytoscape:
a software environment for integrated models of
biomolecular interaction networks. Genome Res
2003, 13: 2498–2504.
13. Burley SK, Berman HM, Bhikadiya C, et al.
RCSB Protein Data Bank: biological
macromolecular structures enabling research and
education in fundamental biology, biomedicine,
biotechnology and energy. Nucleic Acids Res
2019, 47(D1): D464–D474.
14. Zhou Y, Zhou B, Pache L, et al. Metascape
provides a biologist-oriented resource for the
analysis of systems-level datasets. Nat Commun
2019, 10: 1523.
15. Huang DW, Sherman BT, Lempicki RA.
Bioinformatics enrichment tools: paths toward the
comprehensive functional analysis of large gene
lists. Nucleic Acids Res 2009, 37: 1–13.
16. Cui Q, Zhang YL, Ma YH, et al. A network
pharmacology approach to investigate the
mechanism of Shuxuening injection in the
treatment of ischemic stroke. J Ethnopharmacol
2020: 112891.
17. Etti I, Abdullah R, Hashim NM, et al. Artonin E
and structural analogs from Artocarpus species
abrogate estrogen receptor signaling in breast
cancer. Molecules 2016, 21.
18. Zhang N, Wang Y, An L, et al. Entropy drives the
formation of salt bridges in the protein GB3.
Angew Chem Int Ed Engl 2017, 56: 7601–7604.
19. Zhuang W, Wang Y, Cui P, et al. Applications of
pi-pi stacking interactions in the design of
drug-deliverysystems. J Control Release 2019,
294: 311–326.
20. Arunan E, Mani D. Dynamics of the chemical
bond: inter- and intra-molecular hydrogen bond.
Faraday Discuss 2015, 177: 51–64.
21. Li C, Wang P, Zhang L, et al. Efficacy and safety
of Xuebijing injection (a Chinese patent) for
sepsis: a meta-analysis of randomized controlled

ARTICLE
TMR | July 2020 | vol. 5 | no. 4 | 215
doi: 10.12032/TMR20200507178
trials. J Ethnopharmacol 2018, 224: 512–521.
22. Song Y, Yao C, Yao Y, et al. Xuebijing injection
versus placebo for critically ill patients with
severe community-acquired pneumonia: a
randomized controlled trial. Crit Care Med 2019,
47: e735–e743.
23. Guan WJ, Zhong NS. Clinical characteristics of
COVID-19 in China. N Engl J Med 2020, 382.
24. Jiang F, Deng L, Zhang L, et al. Review of the
clinical characteristics of coronavirus disease
2019 (COVID-19). J Gen Intern Med 2020.
25. Chu L, Zhu F, Zhou W, et al. Baicalein attenuates
acute lung injury induced by intestinal
ischemia/reperfusion via inhibition of nuclear
factor-kappaB pathway in mice. Chin Crit Care
Med 2017, 29: 228–232. (Chinese)
26. Liu Y, Yu C, Ji K, et al. Quercetin reduces
TNF-alpha-induced mesangial cell proliferation
and inhibits PTX3 production: involvement of
NF-kappaB signaling pathway. Phytother Res
2019, 33: 2401–2408.
27. Zhang X, Cai Y, Zhang W, et al. Quercetin
ameliorates pulmonary fibrosis by inhibiting
SphK1/S1P signaling. Biochem Cell Biol 2018,
96: 742–751.
28. Kowshik J, Giri H, Kishore TKK, et al. Ellagic
acid inhibits VEGF/VEGFR2, PI3K/Akt and
MAPK signaling cascades in the hamster cheek
pouch carcinogenesis model. Anticancer Agents
Med Chem 2014, 14: 1249–1260.
29. Rafalski VA, Brunet A. Energy metabolism in
adult neural stem cell fate. Prog Neurobiol 2011,
93: 182–203.
30. Larson-Casey JL, Deshane JS, Ryan AJ, et al.
Macrophage Akt1 kinase-mediated mitophagy
modulates apoptosis resistance and pulmonary
fibrosis. Immunity 2016, 44: 582–596.
31. Dai H, Meng W, Kaufmann S. BCL2 family,
mitochondrial apoptosis, and beyond. Cancer
Transl Med 2016, 2: 7.
32. Han R, Ji X, Rong R, et al. MiR-449a regulates
autophagy to inhibit silica-induced pulmonary
fibrosis through targeting Bcl2. J Mol Med 2016,
94: 1267–1279.
33. Kung C, Basu S, Murphy ME. A link between
TP53 polymorphisms and metabolism. Mol Cell
Oncol 2016, 3: e1173769.
34. Delbridge ARD, Kueh AJ, Ke F, et al. Loss of
p53 causes stochastic aberrant X-chromosome
inactivation and female-specific neural tube
defects. Cell Rep 2019, 27: 442–454.
35. Li T, Jiang Y, Hu Y, et al.
Interleukin-17-producing neutrophils link
inflammatory stimuli to disease progression by
promoting angiogenesis in gastric cancer. Clin
Cancer Res 2017, 23: 1575–1585.
36. Asensio-Sanchez VM. VEGF-A and VEGF-Ax:
bad protein and good protein. Arch Soc Esp
Oftalmol 2015: 90, 149–150.
37. Yu X, Lin Q, Qin X, et al. ACE2 antagonizes
VEGF-A to reduce vascular permeability during
acute lung injury. Cell Physiol Biochem 2016, 38:
1055–1062.
38. Yang JM, Meng X, Xue F, et al. ACE2 in the
context of 2019-nCoV infection: friend or foe?
Zhonghua Xin Xue Guan Bing Za Zhi 2020, 48:
E12. (Chinese)
39. Batlle D, Wysocki J, Satchell K. Soluble
angiotensin-converting enzyme 2: a potential
approach for coronavirus infection therapy? Clin
Sci 2020, 134: 543–545.
40. Diaz JH. Hypothesis: angiotensin-converting
enzyme inhibitors and angiotensin receptor
blockers may increase the risk of severe
COVID-19. J Travel Med 2020.
41. Lu Y, Wang B, Shi Q, et al. Brusatol inhibits
HIF-1 signaling pathway and suppresses glucose
uptake under hypoxic conditions in HCT116 cells.
Sci Rep 2016, 6: 39123.
42. Wilkins SE, Abboud MI, Hancock RL, et al.
Targeting protein-protein interactions in the HIF
system. ChemMedChem 2016, 11: 773–786.
43. Pugh CW, Ratcliffe PJ. Regulation of
angiogenesis by hypoxia: role of the HIF system.
Nat Med 2003, 9: 677–684.
44. Harikrishnan H, Jantan I, Haque MA, et al.
Anti-inflammatory effects of Phyllanthus amarus
Schum. & Thonn. through inhibition of
NF-kappaB, MAPK, and PI3K-Akt signaling
pathways in LPS-induced human macrophages.
BMC Complement Med Ther 2018, 18: 224.
45. Dai J, Gu L, Su Y, et al. Inhibition of curcumin
on influenza a virus infection and influenzal
pneumonia via oxidative stress, TLR2/4, p38/JNK
MAPK and NF-kappaB pathways. Int
Immunopharmacol 2018, 54: 177–187.
46. Xu Y, Liu L. Curcumin alleviates macrophage
activation and lung inflammation induced by
influenza virus infection through inhibiting the
NF-kappaB signaling pathway. Influenza Other
Respir Viruses 2017, 11: 457–463.
47. Ju M, Liu B, He H, et al. MicroRNA-27a
alleviates LPS-induced acute lung injury in mice
via inhibiting inflammation and apoptosis through
modulating TLR4/MyD88/NF-kappaB pathway.
Cell Cycle 2018, 17: 2001–2018.
48. Yang H, Zhuo J, Sun C, et al. Pogostone
attenuates TNF-alpha-induced injury in A549
cells via inhibiting NF-kappaB and activating
Nrf2 pathways. Int Immunopharmacol 2018, 62:
15–22.
49. Jiang K, Guo S, Yang C, et al. Barbaloin protects
against lipopolysaccharide (LPS)-induced acute
lung injury by inhibiting the ROS-mediated
PI3K/AKT/NF-kappaB pathway. Int
Immunopharmacol, 2018, 64: 140–150.

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