Molecular mechanism prediction analysis of compound Kushen injection in the treatment of COVID-19 based on network pharmacology and molecular docking

ARTICLE
TMR | September 2020 | vol. 5 | no. 5 | 413
Submit a manuscript: https://www.tmrjournals.com/tmr
doi: 10.12032/TMR20200518180
Traditional Chinese Medicine
Molecular mechanism prediction analysis of compound Kushen
injection in the treatment of COVID-19 based on network
pharmacology and molecular docking
Wan-Ying Zhang1
, Ying Chen1
, Miao-Miao Zhang1
, Guo-Wei Zhang1*
1
College of Chinese Medicine, Hebei University, Baoding 071000, China.
*Corresponding to: Guo-Wei Zhang. College of Chinese Medicine, Hebei University, No.342 Yuhua Road, Baoding 071000,
China. E-mail: xxzgw@126.com.
Highlights
The alkaloids in compound Kushen injection (CKI) can blocking viral replication and its binding to severe
acute respiratory syndrome coronavirus 2 3CL hydrolase and angiotensin-converting enzyme 2 receptors.
They regulate the interleukin-6-mediated signaling pathway, tumor necrosis factor signaling pathway, and
steroid hormone biosynthesis, thereby initiating therapeutic responses against coronavirus disease 2019.
Traditionality
The traditional Chinese medicine CKI was launched in China in 1995 with the approval number of State
Food and Drug Administration of China Z14021230, which is composed of Kushen (Sophorae Flavescentis
Radix) and Baituling (Rhizoma Heterosmilacis Japonicae). It can effectively clear damp heat, and cool and
detoxify blood, which is similar to the anti-inflammatory effects of Western medicine. Kushen (Sophorae
Flavescentis Radix) was first recorded in the ancient Chinese medicine record Shen Nong Ben Cao Jing
(Shennong’s Classic of Materia Medica, unknown author, written in the Han Dynasty), and Baituling
(Rhizoma Heterosmilacis Japonicae) was recorded in Ben Cao Gang Mu (Compendium of Materia Medica)
by the famous medical scientist Li Shizhen (written in 1552–1578 C.E.). CKI, one of the eight effective
Chinese medicines for treating atypical pneumonia, played an important role in combating severe acute
respiratory syndrome coronavirus-induced pneumonia in China in 2003. The study found that CKI has the
effect of inhibiting inflammation, and its main chemical ingredients, namely matrine and oxymatrine,
promotes Th cells to recognize and eliminate viruses. CKI is now used in the clinical treatment of
coronavirus disease 2019, but its molecular mechanism remains unclear and warrants further investigation.

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doi: 10.12032/TMR20200518180
Abstract
Background: As one of the eight effective traditional Chinese medicines for the treatment of atypical pneumonia,
compound Kushen injection (CKI) played an important role in combating pneumonia caused by severe acute
respiratory syndrome coronavirus 2 virus in China in 2003. CKI is known to inhibit inflammation, and its main
chemical components, namely matrine and oxymatrine, can promote Th cells to recognize and eliminate viruses. In
this study, network pharmacology and molecular docking were used to explore the mechanisms of CKI for treating
coronavirus disease 2019. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and
Analysis Platform and other related literature were used to screen CKI’s active ingredients in the blood. Traditional
Chinese Medicine Systems Pharmacology Database and Analysis Platform, Swiss Target Prediction and STITCH
were used to search for potential targets of the active ingredients. The “ingredient-target” network was constructed
using the Cytoscape software. The STRING online database was used to construct a target protein-protein
interaction network that can be visualized and analyzed using the Cytoscape software to obtain key targets. Results:
Sophocarpine, sophoridine, matrine, (+)-allomatrine, AIDS211310, and sophranol were the six active ingredients.
After docking the active ingredients with severe acute respiratory syndrome coronavirus 2 3CL hydrolase and
angiotensin-converting enzyme 2 (ACE2), they displayed suitable affinity, which could block viral replication and
its binding to ACE2. The key targets mainly involved inflammatory factors, such as interleukin-6 (IL-6) and tumor
necrosis factor (TNF). Gene Ontology enrichment analysis mainly indicated the IL-6 cytokine-mediated signaling
pathway and cytokine-mediated signaling pathway. The Kyoto Encyclopedia of Genes and Genome pathway
enrichment analysis mainly indicated steroid hormone biosynthesis and the TNF signaling pathway. Conclusion:
The alkaloids in CKI can block viral replication and its binding to severe acute respiratory syndrome coronavirus 2
and ACE2 receptors. They regulate the IL-6-mediated signaling pathway, TNF signaling pathway, and steroid
hormone biosynthesis, thereby initiating therapeutic responses against coronavirus disease 2019.
Keywords: Compound Kushen injection, Novel coronavirus, Molecular docking, Mechanism of action, Severe
acute respiratory syndrome coronavirus 2 3CL hydrolase, Angiotensin-converting enzyme 2
Author contributions:
Guo-Wei Zhang and Miao-Miao Zhang coordinated and directed the project. Wan-Ying Zhang analyzed most of
the data from database, and drafted the paper. Ying Chen assisted in the analysis of data. All authors read and
approved the final manuscript.
Competing interests:
The authors declare no conflicts of interest.
Acknowledgments:
This study was supported by Natural Science Foundation of Hebei Province (H2018201179), Youth Fund of
Education Department of Hebei Province (QN2019146), and Scientific Research Fund of Health Department of
Hebei Province (NO: 20190948). Thanks to Beijing Zhendong Guangming Pharmaceutical Research Institute for
providing relevant data of Baituling (Rhizoma Heterosmilacis Japonicae) ingredients.
Abbreviations:
CKI, compound Kushen injection; ACE2, angiotensin-converting enzyme 2; IL-1, interleukin-1; IL-6,
interleukin-6; TNF, tumor necrosis factor; COVID-19, coronavirus disease 2019; SARS-CoV-2, severe acute
respiratory syndrome coronavirus 2; TNF-α, tumor necrosis factor alpha; TCMSP, Traditional Chinese Medicine
Systems Pharmacology Database and Analysis Platform; PPI, protein-protein interaction; GO, Gene Ontology;
KEGG, Kyoto Encyclopedia of Genes and Genome; OB, oral bioavailability; DL, drug-likeness; CASP3,
caspase 3.
Citation:
Wan-Ying Zhang, Ying Chen, Miao-Miao Zhang, et al. Molecular mechanism prediction analysis of compound
Kushen injection in the treatment of COVID-19 based on network pharmacology and molecular docking.
Traditional Medicine Research 2020, 5 (5): 413–424.
Executive editor: Rui-Wang Zhao.
Submitted: 26 March 2020, Accepted: 14 May 2020, Online: 29 May 2020.

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doi: 10.12032/TMR20200518180
Background
In December 2019, multiple cases of unexplained
pneumonia were diagnosed in Wuhan, Hubei, China,
and its pathogen was subsequently confirmed as a
novel coronavirus. On January 20, 2020, academician
Zhong Nanshan affirmed the human-to-human
coronavirus disease 2019 (COVID-19) transmission,
by which time 217 cases of COVID-19 have been
diagnosed in China. As the epidemic worsened, all
provinces across the country launched a level-1
emergency response to prevent and control the
COVID-19 epidemic. At the press conference of the
Joint Defense and Control Mechanism of the State
Council last February 8, 2020, pneumonia from novel
coronavirus infection was collectively referred to as
the “novel coronavirus pneumonia” [1]. On February
11, 2020, the World Health Organization named this
disease as coronavirus disease “COVID-19”, and the
International Committee on Taxonomy of Viruses
officially named the corresponding virus “severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2)”.
Related studies [2] have reported that both
SARS-CoV-2 and SARS-CoV bind to the
angiotensin-converting enzyme 2 (ACE2) receptor in
the human body through spiked protein, resulting in
viral invasion. SARS-CoV-2 3CL hydrolase is a key
protein involved in viral translation and replication in
human cells. After binding to the ACE2 receptor,
SARS-CoV-2 can activate the classical
renin-angiotensin regulatory pathways to act on the
lungs and other target organs, eventually leading to
multiple organ damage [3]. Therefore, SARS-CoV-2
3CL hydrolase and ACE2 were selected for molecular
docking in this study.
The combination of traditional Chinese and Western
medicine has been shown to be effective in COVID-19
treatment. The traditional Chinese medicine compound
Kushen injection (CKI) was launched in China in 1995
with the approval number of State Food and Drug
Administration of China Z14021230, which is
composed of Kushen (Sophorae Flavescentis Radix)
and Baituling (Rhizoma Heterosmilacis Japonicae). It
can effectively clear damp heat, and cool and detoxify
blood, and these are similar to the anti-inflammatory
effects of Western medicine. CKI, one of the eight
effective Chinese medicines for atypical pneumonia
treatment, played an important role in combating
SARS-CoV-related pneumonia in China in 2003.
Relevant research has indicated that CKI can
effectively protect SARS-infected patients from
multiple organ damage, such as injury to the heart,
liver, kidneys, and other organs, and enhance immune
functions in humans [4]. Sun et al. [5] have shown that
CKI’s anti-inflammatory effect is mediated by
inhibiting the excessive activation of nuclear factor
kappa-B in macrophages. The clinical trial conducted
by Yu et al. [6] demonstrated that CKI inhibited
inflammatory pathways by reducing tumor necrosis
factor alpha (TNF-α) expression, transforming growth
factor beta synthesis, and cytokine production to
prevent and treat radiation pneumonitis. Matrine and
oxymatrine can regulate immune functions and
enhance Th lymphocyte activity, which contribute to
the ability of immune cells to recognize and neutralize
viruses [7–8]. CKI is now used in COVID-19 clinical
treatment, but its molecular mechanism remains
unclear and warrants further investigation.
This study explores CKI’s mechanism in COVID-19
treatment using network pharmacology and molecular
docking to provide a scientific basis for clinical
applications.
Materials and Methods
Screening of active ingredients
CKI’s active ingredients were screened in the
Traditional Chinese Medicine Systems Pharmacology
Database and Analysis Platform (TCMSP) database
(http://lsp.nwu.edu.cn/tcmsp.php) using the search
terms “Sophorae Flavescentis Radix” and “Rhizoma
Heterosmilacis Japonicae”. According to
pharmacokinetic absorption, distribution, metabolism,
and excretion parameters, oral bioavailability (OB ≥
30%) and drug-likeness (DL ≥ 0.18) were set as the
screening conditions for the active ingredients.
Relevant literature was cross-referenced to further
determine the active ingredients in the blood infused
with CKI.
Screening of active ingredient targets
The TCMSP, Swiss Target Prediction
(http://www.swisstargetprediction.ch/), and STITCH
(http://stitch.embl.de/) databases were used to search
for the targets of CKI’s active ingredients. In the
TCMSP database, the names of the active ingredients
were used as the search terms to select the
corresponding targets. The Canonical SMILES format
of the active ingredients obtained from the PubChem
database (https://pubchem.ncbi.nlm.nih.gov/) were
searched in the Swiss Target Prediction database with
the species set to “Homo sapiens”, and the top ten
targets were selected from the prediction results. In
addition, the active ingredients in the canonical
SMILES format that were not queried were input into
the database as predictive 2-D structures under the
same filtering conditions. Similarly, the names of the
active ingredients were searched in the STITCH
database, and the top ten targets were selected from the
prediction results. The target gene names and the
UniProt IDs of the active ingredients were obtained
from the UniProt (https://www.uniprot.org/) database
with the species set to “Homo sapiens” for subsequent
analyses.

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doi: 10.12032/TMR20200518180
Construction of ingredient-target network
CKI’s active ingredients and targets that were obtained
from the aforementioned databases were input into the
Cytoscape 3.7.2 software to visualize and construct the
ingredient-target network.
Construction of protein-protein interaction (PPI)
network
Several known or predicted PPIs were collected from
the STRING database (https://string-db.org/) [9]. The
aforementioned genes that were obtained were input
into the STRING database with the species setting as
“Homo sapiens”. The obtained PPI network was saved
as a .tsv file and visualized. Network topology analysis
was performed by importing the .tsv file into the
Cytoscape 3.7.2 software.
Gene Ontology (GO) functional enrichment
analysis and Kyoto Encyclopedia of Genes and
Genome (KEGG) pathway enrichment analysis
DAVID (http://www.david.niaid.nih.gov) is an online
tool for enriching large-scale genetic biological
processes and pathways [10]. In this study, DAVID
was used to perform CKI-based GO and KEGG
pathway enrichment analyses. The obtained target
UniProt IDs were input into DAVID with the species
set to “Homo sapiens”, the GOTERM_BP function in
GO was used to enrich target biological processes.
KEGG pathway enrichment analysis was used for
channel enrichment, and the key CKI signal pathways
with P values less than 0.05 were selected.
Molecular docking
The ChemBioDraw plug-in in ChemOffice was used to
draw the 2-D structures of the active ingredients,
which were imported into the ChemBioDraw3D
program to obtain the 3-D structures that were saved as
a.mol2 file to reduce its size. The 3-D crystal structures
of ACE2 (PDB ID: 1R42) and SARS-CoV-2 3CL
hydrolase (PDB ID: 6LU7) were downloaded from the
PDB database (https://www.rcsb.org/) and saved in the
pdb format. The PyMOL software was used to separate
the protein from the primary ligand, which was
dehydrated and hydrogenated. The protein and primary
ligand were saved in the pdb format. Using
AutoDockTools 1.5.6, the active ingredients and
proteins in the pdb format were converted to the pdbqt
format. The active pocket parameters were set, and
Vina was administered for docking. When the affinity
was equal to or less than −5.0 kJ/mol [11], the active
ingredient was considered to have good target-binding
activity.
Results
Active ingredients
From the TCMSP database, 113 active ingredients
were obtained for Kushen (Sophorae Flavescentis
Radix), whereas there was no active ingredient related
to Baituling (Rhizoma Heterosmilacis Japonicae). A
total of 66 chemical ingredients in Baituling (Rhizoma
Heterosmilacis Japonicae) were selected after
cross-referencing with related literature [12–16]. The
ingredients of Baituling (Rhizoma Heterosmilacis
Japonicae) were derived from the internal data of the
Beijing Zhendong Guangming Pharmaceutical
Research Institute; however, several data have not been
published. The obtained ingredients were screened
with OB ≥ 30% and DL ≥ 0.18, and compared with the
CKI ingredients reported by Gao et al. [17]. As a result,
six active ingredients were selected for Kushen
(Sophorae Flavescentis Radix), and no active
ingredient was found for Baituling (Rhizoma
Heterosmilacis Japonicae), resulting in a total of six
active ingredients in the CKI-infused blood (Table 1).
Targets of active ingredients
The aforementioned CKI active ingredients were input
into TCMSP, Swiss Target Prediction, and STITCH
databases. A total of 12, 60, and 10 targets were
obtained from the TCMSP, Swiss Target Prediction,
and STITCH databases. After deduplication, a total of
44 targets of the active ingredients were obtained
(Table 2).
Active ingredient-target network
The ingredient-target network included 50 nodes (six
ingredient nodes and 44 target nodes) and 82 edges, as
shown in Figure 1. In this network, each ingredient
interacted with an average of 13.67 targets, and the top
two, matrine and sophoridine, interacted with 30 and
12 targets, respectively. In addition, CHRNA7 and
CHRNB2 interacted with five ingredients. Therefore,
CKI displays the phenomenon in which the same
active ingredient acts on multiple targets, and the same
target acts on multiple active ingredients, reflecting the
characteristic multi-ingredient and -target interactions
of traditional Chinese medicine.
PPI network topology
The target gene name of CKI were input into the
STRING program to get the PPI relationships of the
target, and the Cytoscape 3.7.2 software was used for
visualization (Figure 2). Topological parameters, such
as degree, betweenness centrality, and closeness
centrality, were obtained using the topology analysis
function of the Network Analyzer tool in the
Cytoscape 3.7.2 software. Moreover, 23 key targets
were obtained using the average of degree as the
condition for screening core targets, mainly involving
interleukin-6 (IL-6), caspase 3 (CASP3), tumor
necrosis factor (TNF), acetylcholinesterase, and
androgen receptor.
GO and KEGG enrichment analyses
Seventy-seven biological processes (P < 0.05) were

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doi: 10.12032/TMR20200518180
obtained from the GO enrichment analysis and sorted
according to P values in an ascending order. Moreover,
15 processes related to immunity and inflammation are
shown in Table 3. The biological processes related to
immunity mainly involved B cell activation and
response to glucocorticoids. The biological processes
related to the inflammatory responses mainly involved
cellular responses to interleukin-1 (IL-1), the
IL-6-mediated signaling pathway, positive regulation
of chemokine production, and the cytokine-mediated
signaling pathway. CKI’s therapeutic effect is therefore
suggestively mediated by regulating biological
processes, such as B-cell activation, IL-6, and other
cytokine-mediated signaling pathways, to regulate
immunity and suppress inflammation.
The KEGG pathway enrichment and screening
resulted in 19 signal pathways (P < 0.05) (Figure 3).
The COVID-19-associated pathways were mainly
enriched in the TNF signaling pathway, steroid
hormone biosynthesis, and natural killer cell-mediated
cytotoxicity, where the TNF signaling pathway is the
inflammatory factor in the TNF-mediated pathway
related to inflammation, steroid hormone biosynthesis,
and natural killer cell-mediated cytotoxicity, which are
closely related to the body's immune responses
[18–19]. These findings suggest that CKI exerts its
therapeutic effect by regulating body immunity and
inhibiting inflammatory responses.
Table 1 The active ingredients of CKI
MOL ID Molecule name OB (%) DL Molecular weight Structure
MOL003627 Sophocarpine 64.26 0.25 246.39
MOL003680 Sophoridine 60.07 0.25 248.41
MOL005944 Matrine 63.77 0.25 248.41
MOL006564 (+)-Allomatrine 58.87 0.25 248.41
MOL006565 AIDS211310 68.68 0.25 248.41
MOL006649 Sophranol 55.42 0.28 264.41
CKI, compound Kushen injection; OB, oral bioavailability; DL, drug-likeness.

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Table 2 Target genes of active ingredients of CKI
Active ingredient Target
Sophocarpine SRD5A2 SRD5A1 CYP2C9 AR KCNH2 CHRM4 CHRM5 CHRM3 ACHE DRD3
Sophoridine
TNF IL-6ST CHRNA4 CHRNB2 CHRNA7 CHRNA3 CHRNB4 DNM1 BCHE
EPHX1 SRD5A2 HSD17B7
Matrine
SNRPD3 SART1 PRPF4 LSM7 SNRPA1 TXNL4A PRPF3 PRPF38A SF3B1
SCHRNA4 CHRNB2 CHRNA7 CHRNA3 CHRNB4 DNM1 BCHE EPHX1
SRD5A2 HSD17B7 SF3A3 RELA MMP2 TNF IL-6 CASP3 MYC ICAM1 HPSE
IER3IP1 CD44
(+)-Allomatrine
CHRNA4 CHRNB2 CHRNA7 CHRNA3 CHRNB4 DNM1 EPHX1 BCHE
SRD5A2 HSD17B7
Sophranol
CHRNA4 CHRNB2 CHRNA7 PRKCA FUCA1 CHRNA3 CHRNB4 HSD11B1
BCHE REN
AIDS211310
CHRNA4 CHRNB2 CHRNA3 CHRNB4 CHRNA7 DNM1 BCHE EPHX1
HSD17B7 SRD5A2
Table 3 Enrichment analysis of GO biological processes of CKI
Term Count P value
Positive regulation of NF-kappaB transcription factor activity 5 3.65 × 10−4
Regulation of dopamine secretion 3 4.91 × 10−4
Response to glucocorticoid 4 6.12 × 10−4
Hypothalamus development 3 6.58 × 10−4
Cellular response to IL-1 4 7.92 × 10−4
Response to hypoxia 5 9.61 × 10−4
Positive regulation of ERK1 and ERK2 cascade 5 1.02 × 10−3
B cell activation 3 2.49 × 10−3
Positive regulation of nitric oxide biosynthetic process 3 5.41 × 10−3
IL-6-mediated signaling pathway 2 2.28 × 10−2
Positive regulation of acute inflammatory response 2 2.53 × 10−2
Signal transduction 8 2.68 × 10−2
Regulation of smooth muscle contraction 2 4.02 × 10−2
Positive regulation of chemokine production 2 4.27 × 10−2
Cytokine-mediated signaling pathway 3 4.43 × 10−2
CKI, compound Kushen injection; IL-1, interleukin-1; IL-6, interleukin-6.

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doi: 10.12032/TMR20200518180
Figure 1 Active ingredient-target network of CKI. Rose red bubbles, active ingredients; light blue bubbles,
targets; lines, interactions among the ingredients and targets.
Figure 2 PPI networks. The size and darkness of the node correspond to the size of the degree value (degree).

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doi: 10.12032/TMR20200518180
Figure 3 KEGG enrichment pathway analysis for CKI. The number in each cyan bar indicates the number of
genes, which also corresponds to the length of the bar. The number in each purple bar indicates the negative
logarithm (−l g) of the P value with base 10, whereas the length of the bar corresponds to the −l g P value and the
level of significance of the enrichment.
Molecular docking
Molecular docking of the active ingredients of CKI
with SARS-CoV-2 3CL hydrolase and ACE2 was
performed. Chloroquine, remdesivir, ribavirin,
ritonavir, and other COVID-19 medications were used
as positive controls. The molecular docking fraction
was negatively correlated with the affinity of the
docking between receptor and ligand. The results
indicated that all of the docking fractions were less
than −5.0 kJ/mol (Table 4), whereas the affinity of
(+)-allomatrine and AIDS211310 with SARS-CoV-2
and ACE2 was stronger than that of Western
medications, such as ribavirin and favipiravir. When
the docking mode with the lowest binding energy to
SARS-CoV-2 3CL hydrolase and ACE2 (Figure 4 and
Figure 5) was selected, AIDS211310 formed a
hydrogen bond with the amino acid residue AGR-393,
whereas (+)-allomatrine did not interact with
SARS-CoV-2 3CL hydrolase to form hydrogen bonds.
The results of the molecular docking showed that the
active ingredients of CKI had high affinity for ACE2
and SARS-CoV-2 proteins. Therefore, CKI’s
therapeutic effect may involve blocking viral
translation and replication, as well as its binding to the
ACE2 receptor through alkaloids, such as sophoridine
and matrine.
Discussion
In this study, six active ingredients, including
sophoridine, sophocarpine, matrine, (+)-allomatrine,
AIDS211310, and sophranol, in CKI-infused blood
were screened based on OB, DL, and related literature.
Among these, sophocarpine [20, 21], matrine [22, 23],
and sophoridine[24] have demonstrated efficacy in
regulating immunity and inhibiting inflammation.
AIDS211310, (+)-allomatrine, and other active
ingredients showed good docking activity with
SARS-CoV-2 and ACE2 proteins. These results
indicate that these ingredients may directly act on
SARS-CoV-2 3CL hydrolase to inhibit viral replication
and proliferation. They may also act on ACE2
receptors of human cells to block viral invasion.
During viral infection, an inflammatory response is
induced to engulf and isolate the virus. However, the
excessive immune responses may release high levels
of cytokines and inflammatory chemokines, such as
TNF-α, IL-1, IL-6, and IL-8, causing uncontrollable
inflammatory reactions and triggering a cytokine storm,
which result in serious tissue and organ damage
[25–27]. Therefore, cytokine storms play an important
role in disease progression in COVID-19 patients [28].
Glucocorticoids have been currently used to treat
refractory cytokine storms in which IL-6 receptor
antagonists are ineffective [29]. However,
corticosteroids not only suppress inflammation in the
lungs, but also suppress immune responses and viral
clearance by the immune system, resulting in their
controversial clinical applications [30]. The results
from the KEGG pathway analysis suggest that CKI
may inhibit excessive immune responses through
steroid hormone biosynthesis regulation, thereby
inhibiting cytokine storm occurrences.
Suppressing the outbreak of inflammatory factors

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doi: 10.12032/TMR20200518180
is of great significance COVID-19 prevention and
treatment, as well as alleviating multiple organ
damage COVID-19 patients [28]. Based on the
results of the PPI network topology, the key targets of
CKI in COVID-19 treatment were IL-6, TNF, and
CASP3. IL-6 plays an important role in the
inflammatory process and B cell maturation, and is
mainly produced at inflammation site. Wu et al. [31]
reported that serum levels of inflammatory factors,
such as IL-6, were negatively correlated with lung
function indicators, such as forced lung capacity in the
first-second vital capacity, peak expiratory flow, and
respiratory velocity of lung capacity, in patients with
mycoplasma pneumonia. Research by Jiang et al. has
shown that the serum IL-6 levels in patients with
asthma-COPD overlap syndrome, COPD, or asthma
are higher than those of the control group, indicating
that IL-6 is involved in airway inflammation and lung
injury [32]. The serum IL-6 and TNF-α levels in
patients with cervical cancer receiving conventional
radiotherapy and chemotherapy alone with external
radiotherapy and chemotherapy than those in patients
who were simultaneously supplemented with CKI,
suggesting that CKI may therapeutically inhibit
inflammatory responses [33]. TNF is considered as the
core of cytokine storms [34]. TNF overproduction in
the body can cause respiratory failure, septic shock,
and even death in severe cases. The mortality rate is
positively correlated with TNF level. Zhou et al. [35]
stimulated angiotensin II in rats, observed contractions
of the aortic ring, and concluded that TNF-α could
affect blood pressure stability in early-stage septic
shock by activating the inositol 1, 4, 5-trisphophate
receptor pathway. CASP3 is the main apoptotic protein
[36], which promotes the apoptosis of lymphocytes to
downregulate or terminate inflammatory responses.
The results from this study suggest that CKI’s
anti-inflammatory effect may be mediated by
downregulating IL-6 and TNF while simultaneously
upregulating CASP3 expression.
During the clinical application of CKI, symptoms,
such as nausea, vomiting, fever, chills, abdominal
distension, and stomach discomfort, are occasionally
observed. Occasional allergic reactions manifested by
flushing, sweating, itching, and rashes on the skin of
the head and neck may be related to the patient's
specific constitution [37–38]. Furthermore, local use is
mildly irritating but well-absorbed.
Table 4 The binding energy values of the active ingredients and ACE2.
Compound Molecular formula CAS
Binding energy values
(SARS-CoV-2 3CL
hydrolase) (kcal/mol)
Binding energy
values (ACE2)
(kcal/mol)
Sophocarpine C15H22N2O 6483-15-4 −6.4 −6.4
Sophoridine C15H24N2O 6882-68-4 −6.7 −7.0
Matrine C15H24N2O 519-02-8 −6.4 −6.6
(+)-Allomatrine C15H24N2O 641-39-4 −6.9 −7.0
AIDS211310 C15H24N2O 17801-36-4 −6.4 −7.3
Sophranol C15H24N2O2 3411-37-8 −6.2 −7.0
Chloroquine C18H26ClN3 54-05-7 −6.8 −5.8
Remdesivir C27H35N6O8P 1809249-37-3 −7.3 −5.9
Ribavirin C8H12N4O5 36791-04-5 −6.4 −6.2
Ritonavir C37H48N6O5S2 155213-67-5 −9.2 −6.4
Nitazoxamide C12H9N3O5S 55981-09-4 −7.4 −6.8
Lopinavir C37H48N4O5 192725-17-0 −9.1 −6.5
Favipiravir C5H4FN3O2 259793-96-9 −5.5 −5.8
ACE2, angiotensin-converting enzyme 2; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

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Figure 4 Molecular docking pattern of (+)-allomatrine and SARS-CoV-2 3CL hydrolase. The dotted frame in
the figure is an enlarged view of the location of the active pocket where the target protein and its receptor bind.
SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.
Figure 5 Molecular docking pattern of AIDS211310 with ACE2. The dotted frame in the figure is an enlarged
view of the location of the active pocket where the target protein and its receptor bind. The yellow dotted line is the
hydrogen bond, and around the receptor molecule is the amino acid residue within 4A of the binding site. ACE2,
angiotensin-converting enzyme 2.
Conclusion
In this study, the mechanism of CKI in COVID-19
treatment has been preliminarily explored in terms of
its active ingredients, targets, and pathways using
network pharmacology and molecular docking
technology. Alkaloids in CKI, such as sophocarpine,
sophoridine, and matrine, have been reported to block
viral replication and its binding to SARS-CoV-2 3CL
hydrolase and the ACE2 receptor, thereby regulating
the IL-6-mediated signaling pathway, TNF signaling
pathway, and steroid hormone biosynthesis, which
inhibit IL-6- and TNF-mediated inflammatory
responses to therapeutically protect the body against
COVID-19. However, this study is based only on
network pharmacology method for prediction, which
has certain limitations and requires further
experimental verification.
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