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. 2024 May 30;11(1):102–115. doi: 10.1002/wjo2.185

Pharmacological mechanism of action of Lianhua Qingwen in the treatment of COVID‐19 and facial neuritis

Guang‐Jin Li 1,2,3, Zhi‐Hong Hao 2,3,4, Han‐Jing Wang 2,3,4, Chen Wang 2,3,4, Da‐Wei Liu 2,3, Liang Chen 2,3, Yan Sun 2,3,✉
PMCID: PMC11891286  PMID: 40070503

Abstract

Objective

Coronavirus disease‐2019 (COVID‐19) can cause not only respiratory symptoms but also facial paralysis. Lianhua Qingwen (LHQW) has been reported to have therapeutic effects on COVID‐19 and facial neuritis (FN). We explored the potential mechanism of LHQW in the treatment of COVID‐19 and FN through a network‐pharmacology approach.

Methods

Active compounds and relevant targets of LHQW were obtained from the databases of Traditional Chinese Medicine Systems Pharmacology Database, HERB, UniProt Knowledge Base, SwissADME, and Swiss Target Prediction. Disease targets of COVID‐19 and FN were acquired from Gene Cards. Database For Annotation, Visualization And Integrated Discovery and Metascape were used to search the biological functions of intersecting targets. After identifying the core targets and their corresponding ingredients, KEGG Mapper analyzes the localization of core targets in key pathways. AutoDock were employed to conduct molecular docking of the core targets and their corresponding ingredients.

Results

We obtained four core genes: interleukin (IL)‐8, IL‐1B, IL‐6, and tumor necrosis factor (TNF)‐α. Database searching revealed the anti‐inflammatory and antiviral effects of LHQW may be related to the action of aleo‐emodin, hyperforin, kaempferol, luteolin, and quercetin on these four genes by regulating the pathways of IL‐17 and NOD‐like receptor. The molecular‐docking results of the four core targets and their corresponding active ingredients showed good binding activity between receptors and ligands.

Conclusions

We uncovered the active ingredients, potential targets, and biological pathways of LHQW for COVID‐19 and FN coinfection. Our data provide a theoretical basis for further exploration of the mechanism of action of LHQW in treatment of COVID‐19 and FN.

Keywords: COVID‐19, facial neuritis, LHQW, molecular docking, pharmacological mechanisms

Key points

  • The active ingredients of Lianhua Qingwen (LHQW) which contain aleo‐emodin, hyperforin, kaempferol, luteolin, and quercetin may play an important role in the treatment of COVID‐19 and facial neuritis (FN).

  • This study indicated through a network pharmacology approach that the active ingredients of LHQW may modulate the IL‐17 signaling pathway and the NOD‐like receptor pathway by regulating IL‐8, IL‐1B, IL‐6, and TNF‐a to reduce excessive inflammatory responses.

Abbreviations

BP

biological process

CC

cellular component

COVID‐19

Corona Virus Disease 2019

DAVID

Database for Annotation, Visualization, and Integrated Discovery

DL

drug likeness

FN

facial neuritis

GO

Gene ontology

hACE2

human angiotensin converting‐enzyme 2

IL

interleukin (IL)

KEGG

Kyoto Encyclopedia of Genes and Genomes

LHQW

Lianhua Qingwen

MF

molecular function

NF‐κB

nuclear factor‐kappa B

NLRP3

NOD‐like receptor thermal protein domain associated protein 3

OB

oral bioavailability

PPI

protein‐protein interaction

TCM

traditional Chinese medicine

TCMSP

Pharmacology Database and Analysis Platform

TNF

tumor necrosis factor

UniProtKB

UniProt knowledge base

INTRODUCTION

Since the outbreak of coronavirus disease 2019 (COVID‐19) in December 2019, it has spread globally and wrought havoc on health and economic systems worldwide. 1 The virus that causes COVID‐19, severe acute respiratory syndrome‐coronavirus‐2 (SARS‐CoV‐2), continues to mutate, 2 so COVID‐19 has not been eradicated. Also, specific drugs to treat COVID‐19 have not been developed. Therefore, the prevention and treatment of COVID‐19 is a rational strategy.

Facial neuritis (FN) is a type of nonspecific neurological inflammation characterized by motor dysfunction of the facial muscles devoted to expression. Its common causative factors are viral infection and its typical clinical presentation is peripheral facial palsy. Facial palsy seriously affects the quality of life of FN patients. A higher incidence of facial palsy was reported during the COVID‐19 outbreak compared with the same period in previous years, and 21% of patients with facial palsy had symptoms consistent with active infection with SARS‐CoV‐2. 3 Some studies have suggested that people may develop the symptoms of facial palsy if they have COVID‐19. 4 , 5 Patients with COVID‐19 and FN concurrently elicit an inflammatory response in vivo, so there may be common pathogenic targets between these two diseases. Thus, the study of patients with facial palsy caused by SARS‐CoV‐2 infection is of great importance.

Lianhua Qingwen (LHQW) is a traditional Chinese medicine (TCM) formulation used in antiviral therapy. Numerous studies have shown that a combination of LHQW and agents used in Western medicine for COVID‐19 treatment help to reduce the inflammatory response and have clinical efficacy. 6 , 7 One clinical study showed that acupuncture combined with LHQW had a treatment effect on acute facial paralysis.

In view of the multicomponent, multitarget, and complex mechanism of action (MoA) of TCM formulations, we undertook a network pharmacology‐based study to investigate the MoA of LHQW in the treatment of COVID‐19 and facial neuritis (Figure 1).

Figure 1.

Figure 1

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The flow chart of study.

METHODS

Determination of the active ingredients of LHQW

To ascertain the active ingredients of a drug, the essential parameters of compounds of LHQW should be set, such as oral bioavailability (OB) ≥ 30% and “drug‐likeness” (DL) ≥ 0.18 in The Traditional Chinese Medicine Systems Pharmacology Database (TCMSP; http://lsp.nwsuaf.edu.cn/tcmsp.php/). 8 Information on the active ingredients and protein targets of drugs were acquired apart from Rhodiola rosea. Next, information on R. rosea‐related components was obtained from HERB (http://herb.ac.cn/). After inputting information on active compounds selected from HERB into SwissADME (www.swissadme.ch), we obtained the result of DL based on the Lipinski, Ghose, Veber, Egan, Muegge rules and OB criteria. If more than two of these six items in DL were positive, then the ingredient was considered to be an “active compound.”

Acquisition of drug targets and disease targets

We matched the protein targets of LHQW with gene targets through UniProt Knowledge Base (UniProtKB; www.uniprot.org/). Then, the reviewed human genes were selected. After screening the active ingredients through SwissADME, the active ingredients of R. rosea were imported into Swiss Target Prediction (STP; www.swisstargetprediction.ch/) to predict gene targets. After removing unmatched targets, the final gene targets were obtained.

In addition, we obtained the genes associated with COVID‐19 and FN from Gene Cards (www.genecards.org/). To acquire meaningful targets, we set the parameter for the target of FN to select 800–1000 gene targets. COVID‐19 is a previously unrecognized disease, so we kept all targets related to COVID‐19 in the gene database.

Acquisition of intersection targets

Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/) can be operated readily, which aids acquisition of intersection targets. Intersection gene targets were obtained through mapping the Venn diagram.

Protein‐protein interaction (PPI) networks

To further explore the associations of genes, the intersection‐target genes were submitted to STRING (https://string-db.org/) to construct PPI networks. STRING is a platform for collecting, scoring, and integrating all publicly available protein–protein interactions, and complementing relevant information with computational information.

Enrichment analysis

Database for Annotation, Visualization and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/) and Metascape (https://metascape.org/) are used to analyzed the genes associated with biological information and signaling pathways to understand the MoA of LHQW. Analysis of functional enrichment using the Gene Ontology (GO) database (http://geneontology.org/) provides information on biological process (BP), cell components (CC), and molecular function (MF). The signaling pathways of gene targets can be determined using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (www.genome.jp/).

Searching for core targets and identifying the location of core targets in critical pathways

The most valuable gene targets were selected through synthesizing the results of searching STRING, Metascape, and Cytoscape 3.2.7 (https://cytoscape.org/). Then, we could indetify the gene‐corresponding components. We also determined the part played by core targets and the signaling pathways through which key genes exerted their functions by analyzing the analytical results of STRING and Cytoscape. KEGG Mapper (https://www.kegg.jp/) identified the localization of core targets in key pathways.

Molecular docking

Molecular docking is used to study the characteristics of receptors and the interactions between receptors and drug molecules, and predicts their binding patterns and affinities. The Protein Data Bank (PDB; www.pdb.org/) can be used to obtain the PDB format file of proteins. Then AutoDock 1.5.6 (https://autodock.scripps.edu/), and Autodock Vina 1.1.2 (https://vina.scripps.edu/) were used to process the molecular structure of receptors and ligands. We carried out molecular docking by AutoDock Vina based on Python and visualized docking results via PyMOL 2.3.4 (https://pymol.org/).

RESULTS

Active ingredients of LHQW

After filtering data using TCMSP, we identified the active compounds of 10 components in LHQW: isatidis radix (33 active compounds), radix rhei et rhizome (7), licorice (87), fortunes bossfern rhizome (5), Pogostemon cablin benth (10), lonicerae Japonicae flos (17), amygdalus communis vas (16), forsythiae fructus (19), ephedra herba (22), and houttuyniae herba (7). The active compounds of R. rosea (10) were obtained by searching in HERB, predicting with SwissADME and combining the data with related studies.

Drug targets of LHQW

Through regulation and matching in UniProtKB, all corresponding drug targets were screened from this database: isatidis radix (293 drug targets), radix rhei et rhizome (65), licorice (1565), fortunes bossfern rhizome (100), Pogostemon cablin benth (228), lonicerae Japonicae flos (422), amygdalus communis vas (189), forsythiae fructus (421), ephedra herba (422), and houttuyniae herba (165). The number of targets of active compounds in R. rosea was 321. Finally, 350 target genes of active ingredients in LHQW were obtained after deleting duplicate values.

Targets of COVID‐19 and FN

We obtained 4585 genes of COVID‐19 by searching GeneCards. Besides, 852 targets of FN were selected after inputting the key words “facial neuritis” in GeneCards.

Intersection targets of LHQW, COVID‐19, and FN

Venny 2.1 was employed to identify the intersection targets between LHQW, COVID‐19, and FN: 44 intersection gene targets were acquired (Figure 2).

Figure 2.

Figure 2

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The venny diagram of intersection genes among COVID‐19, facial neuritis and active ingredients related targets.

PPI networks

Inputting the common targets into STRING, setting the minimum required interaction score to the highest confidence (0.900) and hiding disconnected nodes in the network, we end up with a PPI‐network diagram (Figure 3). After setting the binding parameter to >0.995, eligible genes were selected from the PPI network. The final analytical results of PPI networks indicated that interleukin (IL)‐8, IL‐1B, IL‐10, IL‐6, and tumor necrosis factor (TNF)‐α genes, as core genes, played a key part in the treatment of COVID‐19 and FN by LHQW.

Figure 3.

Figure 3

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Protein–protein interaction (PPI) networks of hub genes and visualized by String. Different colored nodes represent different genes and the number of line segments represents the closeness of the linkage between genes.

Enrichment analysis using the GO database

Forty‐four core protein targets were analyzed and visualized by DAVID and Metascape. The enrichment‐analysis results using DAVID are shown in Figure 4. For BP, the relevant proteins participated mainly in “cytokine‐mediated signaling pathway,” “inflammatory response,” and “immune response.” For CC, the core genes exerted functions on “extracellular space,” “extracellular exosome,” and “macromolecular complex.” For MF, gene targets had significant roles in “protein binding,” “cytokine activity,” “enzyme binding,” “receptor binding,” and “chemokine activity.”

Figure 4.

Figure 4

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Gene ontology (GO) enrichment analysis based on DAVID database. In the bar graph, the length of the columns represents the number of genes involved. BP, biological process; CC, cellular component; MF, molecular function.

The enrichment‐analysis results on 44 genes using Metascape revealed genes to be enriched in “cytokine receptor binding,” “positive regulation of leukocyte migration,” “response to reactive oxygen species,” “regulation of ion transport,” and “response to wounding.”

Comprehensive data analysis

We mapped the obtained components, targets, and pathways in a network and visualized the results using Cytoscape (Figures 5 and 6). After setting the screening criteria to degree >2 in Cytoscape and binding score >0.995 in STRING, we obtained four core genes: IL‐8, IL‐1B, IL‐6, and TNF‐α. Then, the active ingredients (aloe‐emodin, hyperforin, irisolidone, isovitexin, kaempferol, luteolin, quercetin, and wogonin) and target pathways corresponding to these four core genes were visualized by STRING and Cytoscape (Figure 7).

Figure 5.

Figure 5

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Topology diagram between 44 intersecting genes and their corresponding active ingredients. The size of graphics represents the degree of association between genes and compounds.

Figure 6.

Figure 6

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The network of gene targets and signaling pathway. The size of graphics represents the degree of relation between targets and pathways.

Figure 7.

Figure 7

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The relationship diagram among effective, core genes, and signal pathway. Yellow nodes represent the pathway, the red nodes show effective ingredients, and the green nodes indicated core targets. BLG26, DH5, GHX5, H, I, LQ11, LQ14, and U represents isovitexin, aloe‐emodin, irisolidone, quercetin, kaempferol, hyperforin, wogonin, and luteolin, respectively.

Enrichment analysis of the KEGG

The signaling pathways in which genes were involved were determined by exploring DAVID (Figure 8) and Metascape (Figure 9). We selected the top‐20 signaling pathways of DAVID, which included “cytokine‐cytokine receptor interaction,” “influenza A,” “IL‐17 signaling pathway,” “coronavirus disease—COVID‐19,” “pathways of neurodegeneration—multiple diseases,” “viral protein interaction with cytokine and cytokine receptor,” and “NOD‐like receptor signaling pathway.” After analyzing the results by Metascape and reviewing the relevant literature, the most valuable signaling pathways in Metascape were “pathways of neurodegeneration—multiple diseases.” Among the pathways involved in the core targets, the most significant ones are IL‐17 signaling pathway “IL‐17 signaling pathway” and “NOD‐like receptor signaling pathway” after reviewing relevant studies. We entered the screened core targets and signaling pathways into the KEGG database and demonstrated the specific form of action of their core targets involved in the signaling pathways (Figure 10).

Figure 8.

Figure 8

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Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the basis of DAVID. In the bubble diagram, the size of the dots represents the number of genes and the color shows the different p value.

Figure 9.

Figure 9

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Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis in accordance with Metascape. The length of the bars represents the number of genes involved.

Figure 10.

Figure 10

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IL‐1B, IL‐6, IL‐8, and TNF‐α are involved in two pathways: IL‐17 signaling pathway (A), and NOD‐like receptor signaling pathway (B). The green marked node represents the core genes.

Molecular docking

The results of molecular docking of processed genes and active ingredients by AutoDock and visualization by PyMol are shown in Figure 11. A molecular‐docking diagram shows the best way to bind the active ingredient to a gene by docking in terms of the least amount of energy required for such binding. Studies have shown if the binding energy of a receptor and a ligand is −5.0 kcal/mol, then there is good binding activity between them. 9 If the binding energy is −7.0 kcal/mol, then a strong binding force between receptor and ligand is present. In the present study, the binding energy of all ligands and receptors was greater than −5.0 kcal/mol, which suggested that these ingredients had a key role in the action of LHQW.

Figure 11.

Figure 11

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The results of molecular docking as follows: CXCL8 linked with hyperforin (A), quercetin (B) and wogonin (C) individually which the binding energies of the receptors and ligands were −5.3, −6.2 and −6.1 kcal/mol; IL‐1B combined with aloe‐emodin (D), irisolidone (E), and quercetin (F) separately which the binding energies between the receptors and ligands were −6.2, −6.5 and −7.3 kcal/mol; IL‐6 couple with luteolin (G), quercetin (H), and wogonin (I) differently which the binding energies are −7.1, −7.2, and −6.4 kcal/mol; TNF docked with aloe‐emodin (J), irisolidone (K), isovitexin (L), kaempferol (M), luteolin (N), quercetin (O), and wogonin (P), respectively, which binding energies between ingredients and targets are −6.1, −6.6, −6.5, −6.0, −6.9, −6.7 and −7.9 kcal/mol. The text in the diagram represents the binding site of the receptors and the ligands.

DISCUSSION

COVID‐19 is characterized by fever, dry cough, and malaise, and some patients have upper‐respiratory and gastrointestinal symptoms such as nasal congestion, runny nose, and diarrhea. 10 , 11 Patients with severe COVID‐19 can develop acute respiratory distress syndrome, electrolyte disturbances, multiorgan failure syndrome, or die. 12 , 13 , 14 In addition, COVID‐19 causes damage to several systems, including the nervous system, and causes different clinical manifestations. 15 , 16 , 17 Scientists have found that coronaviruses have a tendency to be neuroinvasive and that patients infected with COVID‐19 have a certain chance of developing acute facial paralysis. 18 , 19 , 20 , 21 Further studies found that inflammation and demyelination of the facial nerve caused by the virus were closely related to the nerve damage caused by the replication and dissemination of the virus. 20 Based on previous studies, we believe that inflammation plays an important role in COVID‐19 and the facial neuritis it causes, and that there is a common pathogenic mechanism between them. Studies have shown that a combination of LHQW and agents used in Western medicine has an important role in reducing symptoms and improving the prognosis during the treatment of COVID‐19. 6 , 7 It has been found that LHQW has antiviral and anti‐inflammatory effects by exploring the mechanism of Lotus purgative for COVID‐19. 7 , 22 Therefore, we investigated the MoA of LHQW in the treatment of COVID‐19 and FN by means of network pharmacology. In this way, we hoped to provide a reference for the future development of treatment protocols.

We found the corresponding active ingredients based on the core targets of LHQW to be aloe‐emodin, hyperforin, irisolidone, isovitexin, kaempferol, luteolin, quercetin, and wogonin. Hyperforin has been found to have an effect on the neurological inflammation caused by COVID‐19, 23 so we think that it may be helpful against FN caused by SARS‐CoV‐2 infection. Isovitexin has potential to resist COVID‐19 through the optimal binding affinity and stability of e human angiotensin converting‐enzyme 2 (hACE2) complexes. 24 According to one study, kaempferol has been shown to reduce the “cytokine storm” and to inhibit the replication and transcription of viruses. 25 In addition, kaempferol relieves the inflammation and acute lung injury caused by infection by the H9N2 influenza virus, and also can inhibit replication of the pseudorabies virus in mice. 26 Luteolin has been shown to protect neurons from the damage wrought by COVID‐19 through inhibiting the consequent release of neurotoxic proinflammatory mediators. 27 , 28 Some studies have shown that quercetin can relieve nerve pain by reducing the production of TNF‐α and IL‐1B, and can also exert anti‐inflammation actions by inhibiting activation of the nuclear factor‐kappa B (NF‐κB) signaling pathway. 29 , 30 It is helpful for the treatment of COVID‐19 patients because quercetin can act on the NOD‐like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome to reduce the inflammatory response. 31 Unfortunately, studies to show the specific effects of irisolidone, isovitexin, or wogonin on COVID‐19 and FN have not been done.

Subjecting 44 intersecting targets to further analysis revealed IL‐8, IL‐1B, IL‐6, and TNF‐α genes to be associated with the inflammatory response. Transcriptomic analysis of bronchoalveolar lavage fluid from patients with mild–severe COVID‐19 has revealed increased expression of IL‐1B, IL‐6, and TNF‐α (Shaath et al., 2020). Increased expression of IL‐1B, IL‐6, IL‐8, and TNF‐α has been found upon serum analysis of patients with mild and severe COVID‐19, but to be higher in severely ill patients with COVID‐19. 32 , 33 A high serum level of IL‐6, IL‐8, or TNF‐α is a strong and independent predictor of survival of patients with severe COVID‐19. 34 SARS‐CoV‐2 can be recognized by Toll‐like receptor seven located on endosomes and activate the myeloid differentiation primary response 88‐dependent mitogen‐activated protein kinase‐NF‐κB pathway, leading to the release of TNF‐α, IL6, and IL‐8. 35 In addition, NF‐κB can act as a ligand for the NOD‐like receptor family (mainly NLRP3) to activate and upregulate expression of NLRP3, caspase‐1, pro‐IL‐1B, and pro‐IL‐18, which are converted to mature IL‐1B and IL‐18 to mediate extracellular inflammation. 36 COVID‐19 has been reported to cause inflammation in the lung by binding to toll‐like receptors and releasing pro‐IL1B subsequently, which causes an inflammatory response by being cleaved by caspase‐1 to the mature form of IL‐1B. 36 , 37 , 38 Moreover, an increased level of interferon‐stimulated gene protein is a characteristic of mild‐to‐moderate disease, whereas severe COVID‐19 is related to an increase in IL‐8‐induced protein pathways. 39 Roshanravan and colleagues showed that the viral load in serum correlated with cytokine storms and was related directly to the serum IL‐6 level. 40 TNF‐α and interferon‐γ can cause lethal cytokine shock in mice, which reflects the tissue damage and inflammation caused by COVID‐19. 41 In addition, “inflammatory storms” induced by IL‐8, IL‐1B, IL‐6, and TNF‐α genes can have effects on multiple systems (immune, pulmonary, nervous) in COVID‐19 patients. 42 Pathologic changes in facial nerves as a result of various factors can lead to edema and inflammation of facial nerves. 43 Serum levels of IL‐6, IL‐8, and TNF‐α have been shown to be increased in patients with Bell's facial palsy, and these cytokines may be causative factors for facial palsy. 44 , 45 Therefore, the genes of IL‐8, IL‐1B, IL‐6, and TNF‐α may be common pathogenic targets in COVID‐19 and FN.

Enrichment analysis of core genes using the GO database indicated these hub genes to be involved in “cytokine‐mediated signaling pathway,” “inflammatory response,” and “immune response.” Hub targets play a key part in stabilizing cell membranes, combining with receptors, proteins and enzymes, as well as regulating the activity of cytokines. These biological functions have important roles in the treatment of COVID‐19 and FN using LHQW. Analysis of signaling‐pathway enrichment on intersecting genes using the KEGG database revealed the signaling pathways related to COVID‐19 and FN to be “Cytokine‐cytokine receptor interaction,” “IL‐17 signaling pathway,” “Coronavirus disease—COVID‐19, pathways of neurodegeneration—multiple diseases,” “viral protein interaction with cytokine and cytokine receptor,” and “NOD‐like receptor signaling pathway.” The most important pathways were the IL‐17 signaling pathway and NOD‐like receptor signaling pathway. The IL‐17 signaling pathway plays an important part in promoting the activation and release of proinflammatory factors and regulating the inflammatory response. Activation of IL‐17 (which activates the IL‐17 signaling pathway) can lead to the production of multiple cytokines (e.g., IL‐6, IL‐1β, TNF‐α, TGF‐β) and chemokines (e.g., IL8) and mediation of the inflammatory response by regulation of multiple signaling pathways. 46 , 47 NOD‐like receptors (which are intracellular pattern‐recognition receptors) can activate the transcription factor NF‐κB to mediate expression of proinflammatory mediators by influencing the NOD‐like receptor signaling pathway. 36

In this study, we focused on analyzing the relationship of some components, targets, and pathways, and in the future, we also intend to verify our study through further experiments. In addition, we did not conduct further studies on the components, targets, and pathways with lower relevance, which does not mean that other components, targets, and pathways are completely irrelevant to the therapeutic effects of LHQW. We believe that with the progress of the study, the related mechanism of action of LHQW can be better elucidated.

CONCLUSIONS

This article is the first to apply a network pharmacology study to the mechanism of action of LHQW in the treatment of COVID‐19 and FN through a network pharmacology approach. The therapeutic MoA of LHQW may be related to the action of aleo‐emodin, hyperforin, kaempferol, luteolin, and quercetin on IL‐8, IL‐1B, IL‐6, and TNF‐α genes through the IL‐17 signaling pathway and NOD‐like receptor signaling pathway. We hope that this study will be useful for further exploration of therapeutic strategies for COVID‐19‐induced FN. However, relevant experiments could not be performed for validation in this study, and only a possible pathogenesis could be explored in conjunction with previous studies and provide a reference for subsequent studies.

AUTHOR CONTRIBUTIONS

Da‐Wei Liu, Liang Chen, and Yan Sun: Conceptualization and methodology. Guang‐Jin Li: Software, data curation. Guang‐Jin Li, Zhi‐Hong Hao, Han‐Jing Wang and Chen Wang: Writing‐original draft preparation. Yan Sun: Investigation, supervision. Da‐Wei Liu, Liang Chen and Yan Sun: Visualization, writing‐reviewing and editing.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

ETHICS STATEMENT

No relevant experiments were conducted in this study, so there were no ethical implications.

ACKNOWLEDGMENTS

This study is funded by Natural Science Foundation of Shandong Province (ZR2021MH378) and Natural Science Foundation of Shandong Province (ZR2022QH073).

Li G‐J, Hao Z‐H, Wang H‐J, et al. Pharmacological mechanism of action of Lianhua Qingwen in the treatment of COVID‐19 and facial neuritis. World J Otorhinolaryngol Head Neck Surg. 2025;11:102‐115. 10.1002/wjo2.185

Guang‐Jin Li, Zhi‐Hong Hao and Han‐Jing Wang have contributed equally to this work.

DATA AVAILABILITY STATEMENT

The data used in this study were obtained from open public databases, and addresses of relevant websites where data acquisition has been annotated with databases. The data that support the figures of this study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data used in this study were obtained from open public databases, and addresses of relevant websites where data acquisition has been annotated with databases. The data that support the figures of this study are available from the corresponding author upon reasonable request.

Articles from World Journal of Otorhinolaryngology - Head and Neck Surgery are provided here courtesy of Chinese Medical Association

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