Similarity and Specificity of Lianhua Qingwen and Damp-Heat Plague Formula for the Management of Mild COVID-19

Abstract

Lianhua Qingwen (LHQW) and damp-heat plague formula (DHPF) have positive therapeutic outcomes on coronavirus disease 2019 (COVID-19). This study aimed to clarify the mechanisms of LHQW and DHPF in COVID-19 treatment, and examined the differences between the 2 formulas in the treatment process. This study is based on systems biology and network pharmacology; the Traditional Chinese Medicine Systems Pharmacology database and Encyclopedia of Traditional Chinese Medicine were used to compare information on LHQW and DHPF; the STRING database was used to construct the “protein–protein interaction (PPI)” and protein module networks. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment were used to analyze the intersecting targets of LHQW and DHPF. Ingenuity Pathway Analysis was used to analyze the specific targets of the 2 formulas. Molecular docking and molecular dynamic simulation were used to validate the interactions of candidate active compounds and targets. The results show that both LHQW and DHPF alleviate mild COVID-19 by relieving inflammation, increasing immunity, apoptosis, and reducing oxidative stress. Furthermore, Machiline and Estrone in Armeniacae Semen Amarum (Kuxingren) in LHQW can target neurological disease-related genes (ADRA2B, ADRA2C, and DRD2). In contrast, Ellagic acid in Paeoniae Radix Rubra (Chi Shao) in DHPF can target immunity- and inflammation-related genes (GSTA1 and GSTA2). These findings suggest that when translated into clinical applications, LHQW would likely be more potent in treating patients with nervous disorders who experienced mild COVID-19, whereas DHPF would effectively perform antioxidant and anti-inflammatory activities.

Keywords

traditional Chinese medicine systems biology COVID-19 psychological disorder disease inflammation molecular dynamics simulations

Introduction

Coronavirus disease 2019 (COVID-19) is a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected patients typically exhibit symptoms such as fever, cough, dizziness, headache, anosmia, anxiety, and depression.^1–3 Severe cases exhibit complications of acute respiratory distress syndrome caused by cytokine storms.⁴ For patients experiencing mild cases of COVID-19, the use of traditional Chinese medicine (TCM) for intervention in the early stage of disease development is an important strategy to alleviate these symptoms and delay further development.^5,6

TCM has for a long time played an indispensable role in preventing and treating several epidemic diseases.^7–9 TCM played a significant role in treating patients during the SARS epidemic in 2003.^7,10 The early use of TCM in clinical applications is one of the main reasons for the control of the COVID-19 epidemic in China.¹¹ Consequently, TCM was recommended for the treatment of COVID-19 in trial version 7 of the “Diagnosis and Treatment Protocol for COVID-19”.¹² Further, a retrospective study at the Wuhan University Tongren Hospital demonstrated that the risk of death was reduced in patients who were administered TCM. Moreover, faster turnaround times for pharyngeal swabs and fecal nucleic acid were attributed to earlier intervention with TCM.¹³ TCM efficacy is a result of viral inhibition and has been postulated to block the development of infection, regulate immune responses, inhibit the progression of cytokine storms, and restore bodily functions.^11,14 Following positive therapeutic outcomes from TCM use, China has shared some of its treatment strategies, including “Three Chinese Patent Medicines and Three Herbal Formulas,” with Japan, Brazil, Sweden, the United States, Cuba, Singapore, and various other countries and has received feedback regarding similar positive therapeutic outcomes.¹⁵

Lianhua Qingwen (LHQW) was extended from 2 TCM prescriptions: “Yinqiao San” in Wen Bing Tiao Bian (Treatise on Differentiation and Treatment of Seasonal Warm Diseases) and “Maxing Shigan Tang” in Shang Han Lun (Treatise on Febrile and Miscellaneous Diseases) and has subsequently been used successfully during several respiratory infectious disease epidemics, such as that of influenza A in 2009.^10,16 After the outbreak of COVID-19, LHQW was recommended for treating the mild and common types of the disease in the multi-version “Diagnosis and Treatment Protocol for COVID-19” of China. During the same period, damp-heat plague formula (DHPF) was also recommended for treating mild cases of COVID-19.¹⁷ Although both formulas are recommended for treating mild COVID-19, their components are different. Therefore, the similarity and specificity in the biological mechanisms of the 2 formulas underlying treatment of mild COVID-19 require further investigation.

LHQW has exhibited various therapeutic properties in pharmacological studies, including immuno-regulatory, anti-inflammatory, antiviral, and antioxidant activities as well as activity against lung injury.^17–19 However, the molecular mechanisms of DHPF in treating patients with mild COVID-19 are yet to be explored.¹⁸ This study selected LHQW and DHPF as representatives of TCM for treating mild COVID-19. Based on systems biology and integrated network pharmacology, the similarity and specificity of biological mechanisms and pharmacological functions of these formulas for rational clinical applications in treating mild COVID-19 were analyzed. Consequently, this study sought to pave the way for precise medical treatment and rational clinical applications in treating patients with mild COVID-19.

Results

Comparison of LHQW and DHPF Composition

LHQW and DHPF can both be used to treat mild cases of COVID-19. To determine the similarity and specificity of the biological mechanisms of the 2 formulas during COVID-19 therapeutics, the similarity, and specificity of herbs in the 2 TCM formulas were first investigated (Supplemental Table S1). LHQW and DHPF share 2 herbs, viz. Glycyrrhizae Radix et Rhizoma (Gancao) and Forsythiae Fructus (Lianqiao). Menthae Haplocalycis Herba (Bohe), Lonicerae Japonicae Flos (Jinyinhua), Cyrtomium fortunei J. Sm. (Guanzhong), Pogostemonis Herba (Guanghuoxiang), Isatidis Radix (Banlangen), Rhei Radix et Rhizoma (Dahuang), Armeniacae Semen Amarum (Kuxingren), Houttuyniae Herba (Yuxingcao), Ephedrae Herba (Mahuang), and Rhodiolae Crenulatae Radix et Rhizoma (Hongjingtian) are herbs specific to LHQW. In contrast, Bupleuri Radix (Chaihu), Magnoliae Officinalis Cortex (Houpu), Artemisiae Annuae Herba (Qinghao), Atractylodis Rhizoma (Cangzhu), Paeoniae Radix Rubra (Chishao), Anemarrhenae Rhizoma (Zhimu), Arecae Semen (Binglang), Tsaoko Fructus (Caoguo), Isatidis Folium (Daqingye), and Scutellariae Radix (Huangqin) are specific to DHPF.

Each component has different properties (such as whether it is served warm, cold, or mild), flavor, and channel tropism, which represent the property of the component. In LHQW and DHPF, the property of most herbs is cold, so the 2 formulas are regarded as cold medicine based on the TCM principle, with both formulas having heat-clearing effects (Figure 1A and B). TCM also considers the connection between drug action and human meridians, ie, channel tropism. Therefore, channel tropism can be used to elucidate the selectivity of drug action to a specific part of the human body. As a result, the channel tropism of the 2 formulas was analyzed. Based on the Encyclopedia of Traditional Chinese Medicine (ETCM) database, in LHQW, 10 herbs target the lungs, and 7 target the stomach; thus, the formula belongs to the lung and stomach meridian (Figure 1C). For DHPF, 7 herbs target the stomach, and 6 target the lungs; thus, the formula belongs to the stomach, lung, and spleen meridian (Figure 1D). These findings demonstrate that LHQW and DHPF exert a heat-clearing effect mainly through the lungs and stomach.

Figure 1.

Channel tropism, property, and flavor of LHQW and DHPF based on TCM theory. (A) The property of LHQW and DHPF. (B) The flavor of LHQW and DHPF. (C, D) The channel tropism of LHQW and DHPF. Abbreviations: LHQW, Lianhua Qingwen; DHPF, damp-heat plague formula; TCM, traditional chinese medicine.

Comparison of Chemical Ingredients and Putative Targets of LHQW and DHPF

In total, 224 chemical ingredients from 13 herbs of LHQW and 232 chemical ingredients of DHPF were collected from public databases (Traditional Chinese Medicine Systems Pharmacology [TCMSP] and Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine [TCMIP]) after ADME screening (oral bioavailability ≥ 30%, drug-likeness evaluation ≥ 0.18). One hundred and twenty-nine chemical ingredients were found to be common between LHQW and DHPF, whereas 95 and 103 were found to be unique to LHQW and DHPF, respectively (Supplemental Figure S1A). The TCMSP database was used to analyze the putative targets of the 2 formulas; LHQW had 245 targets, whereas DHPF had 259. In addition, 232 intersecting targets were identified between them, with 13 and 27 unique targets belonging to LHQW and DHPF, respectively (Supplemental Figure S1B). These results revealed that the 2 formulas share similar targets but also contain unique targets. Therefore, we hypothesized that the mechanisms of LHQW and DHPF in treating mild COVID-19 might occur through similar pathways. In contrast, the unique genes may reflect the essence of TCM personalized treatment. Thus, the use of the different formulas depends on the symptoms exhibited by each patient.

Target Analysis of TCM Formulas

After determining chemical ingredients and targets, the 232 intersecting targets were selected as potential targets and imported into the STRING database to explore the potential common and unique mechanisms between LHQW and DHPF in treating symptoms of COVID-19. The protein–protein interaction (PPI) network was predicted (degree > 0.7). The top 7 targets (MAPK1, IL6, STAT3, AKT1, JUN, RELA, and MAPK3) were located in the center of the PPI network (Figure 2A). In addition, 2 significant modules (modules 1 and 2) with scores ≥ 6 were screened out via molecular complex detection (MCODE). MAPK1, RELA, JUN, FOS, NR3C1, IL2, MAPK6, NFKBIA, and STAT3 were the hub nodes with higher node degrees in module 1 (score = 6.3) (Figure 2B); and IL6, CXCL8, IL1B, CCL2, IL4, and IL10 were hub nodes in module 2 (score = 6.0) (Figure 2C).

Figure 2.

PPI network construction. (A) The PPI network was constructed using LHQW and DHPF intersecting targets. (B, C) The significant module identified from the PPI network using the MCODE method with a score ≥ 6.0; the red and yellow nodes represent hub targets, the light yellow color represents lower degree, and red represents higher degree. Abbreviations: LHQW, Lianhua Qingwen; DHPF, damp-heat plague formula; PPI, protein–protein interaction; MCODE, molecular complex detection.

Gene Ontology and Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment Analyses of Potential LHQW and DHPF Intersecting Targets

To elucidate the processes and pathways common to LHQW and DHPF in treating mild COVID-19, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments were used to analyze the intersecting targets of the 2 formulas. Gene Ontology results indicated that these intersecting targets played an essential role in treatment, such as in the response to steroids, nutrient levels, and oxidative stress (Figure 3A). The top 15 pathways of KEGG enrichment analysis (p. adjust <0.05) indicated that the 2 formulas, when used to treat mild COVID-19, are associated with pathways such as the advanced glycation end product (AGE)-receptor for AGE signaling pathway in diabetic complications, IL-17 signaling pathway, C-type lectin receptor signaling pathway, and Th17 cell differentiation (Figure 3B). This indicated that LHQW and DHPF might treat mild COVID-19 via similar pathways, including relieving inflammation, increasing immunity, viral apoptosis, and reducing oxidative stress.

Figure 3.

Go and KEGG enrichment analyses of overlapping targets between LHQW and DHPF in treating mild COVID-19. (A) GO analysis of the genes and the top ten GO terms are depicted; X-axis represents the categories of GO terms, and the Y-axis represents the enrichment score. (B) KEGG analysis of the genes and the top 15 pathways. The color and the size of the dot represent different p. adjust and the number of targets enriched in the pathway, respectively. Abbreviations: LHQW, Lianhua Qingwen; DHPF, damp-heat plague formula; COVID-19, coronavirus disease 2019; GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Specificity of LHQW and DHPF in Treating Mild COVID-19

LHQW and DHPF are efficient in treating mild COVID-19, and their specific targets may reflect the personalized treatment effects of TCM and their precise clinical applications. To understand better their use in clinical applications, we analyzed the specific targets of the 2 formulas and compared their biological functions and diseases with which they are associated for treatment. We determined the canonical pathways and diseases related to LHQW-specific targets (ALB, CTNNB1, MMP10, CACNA2D1, DGAT2, OPRK1, DRD2, ADRA2C, ADRA2B, DRD5, DRD3, RHO, and PRKCE) and DHPF-specific targets (KLF7, PLA2G4A, ABCC2, MTOR, FOSL1, CYCS, ALOX12, NFATC1, TDRD7, EGLN1, NOX5, APOD, CYP2C9, PDE10A, GSTA1, GSTA2, CD14, LBP, TDP1, SOD2, ABCB1, CYP2B6, VEGFC, PRDX4, CCL5, NQO2, and CDKN3) using Ingenuity Pathway Analysis (IPA). The 13 and 27 unique genes were imported into IPA software for canonical pathway analysis, and the results indicated that the specific targets of LHQW were enriched in cAMP response element-binding protein signaling in the nervous pathway, G-Protein coupled receptor signaling pathway, dopamine-darpp32 feedback in the cAMP signaling pathway, opioid signaling pathway, estrogen receptor signaling pathway, and IL-12 signaling and production in macrophages pathway (Figure 4A). In contrast, the DHPF-specific targets were enriched in IL-6 signaling, LPS/IL-1-mediated inhibition of RXR function, NRF2-mediated oxidative stress response, aryl hydrocarbon receptor signaling, and phagosome formation (Figure 4B). Disease prediction indicated that the LHQW-specific targets were enriched in psychological disorders, such as acute mania, generalized anxiety disorder, bipolar II disorder, single major depressive episode, refractory schizophrenia, and suicidal ideation (Figure 4C). In contrast, the DHPF-specific targets of DHPF were enriched in xenobiotic metabolism, organ inflammation, lung cell line proliferation, and lipid oxidation (Figure 4D). In a previous study, adrenergic and dopamine receptors were found to play a crucial role in psychological disorders, whereas down-regulation of glutathione transferase A (GSTA1 and GSTA2) expression protected cells against inflammation.^20–23 Further, a recent study indicated that adrenergic receptors could be considered a putative candidate target in schizophrenia. Dopamine receptors are the main targets of antipsychotics, and the systemic dysfunction of dopamine receptors is linked to the pathophysiology of depression.²⁴ The results of this study indicate that LHQW was strongly associated with psychological disorders by targeting adrenergic receptors (ADRA2C and ADRA2B) and a dopamine receptor (DRD5), whereas DHPF was strongly associated with inflammation by targeting GSTA1 and GSTA2.

Figure 4.

Pathways and diseases of the specific targets targeted by LHQW and DHPF in treating mild COVID-19. (A) Top pathways and networks associated with specific targets targeted by LHQW. (B) Top pathways and networks associated with specific targets targeted by DHPF. (C, D) The diseases associated with specific targets targeted by LHQW and DHPF. Abbreviations: LHQW, Lianhua Qingwen; DHPF, damp-heat plague formula; COVID-19, coronavirus disease 2019.

Validation of Specific Target-Chemical Ingredient Interactions by Molecular Docking

The “component–active ingredient–specific target” network clearly describes the relationship between the targets and the ingredients. Therefore, we defined the ingredients (Machiline, l-SPD, 11-hydroxynumantenine, and Estrone) of LHQW significant targets (ADRA2B, ADRA2C, and DRD2) (Figure 5A) and the ingredients (Ellagic acid and Artemisinin) of DHPF significant targets (GSTA1 and GSTA2) (Figure 5B). To validate further whether LHQW and DHPF can be used for treating mild COVID-19, where patients are experiencing symptoms of depression or inflammation, by targeting specific targets (ADRA2B, ADRA2C, and DRD2 or GSTA1 and GSTA2), GOLD 5.2 and Autodock 1.1.2 were used to analyze the binding capacity between specific targets and the chemical ingredients obtained from the “component–active ingredient–specific target” network. The GOLD 5.2 docking results were shown using PyMOL 1.8 and Molecular Operating Environment (MOE) v2019.0102. The docking results indicate that the ingredients could enter the active pocket of the proteins (Figure 6A to E). Machiline exhibited better binding activity than the positive controls (Clonixin and ORM-10921) when docking with ADRA2B and ADRA2C (Supplemental Table S2) and mainly formed hydrogen bonds with the ASP-92, SER-180, PHE-412, and TYR-391 residues in ADRA2B (Figure 6F, K). In contrast, Machiline formed hydrogen bonds with the ASP-131 and TYR-427 residues in ADRA2C (Figure 6G, L). Estrone formed a hydrogen bond with the CYS-118 and VAL-190 residues in DRD2 (Figure 6H, M). Ellagic acid formed hydrogen bonds with the TYR-9 and VAL-55 residues in GSTA1 (Figure 6I, N), whereas it also formed hydrogen bonds with the ARG-45, VAL-55, and PHE-220 residues in GSTA2 (Figure 6J, O). These results collectively suggest that LHQW might benefit patients with mild COVID-19 and psychological disorders by targeting neurological disease-related targets (ADRA2B, ADRA2C, and DRD2) through Machiline and Estrone in Armeniacae Semen Amarum (Kuxingren). In contrast, DHPF is strongly associated with inflammation and acts on immunity- and inflammation-related targets (GSTA1 and GSTA2) through Ellagic acid in Paeoniae Radix Rubra (Chi Shao).

Figure 5.

“ Component–active ingredient–specific target” network of LHQW and DHPF. (A) “ Component–active ingredient–specific target” network of LHQW; (B) “ Component–active ingredient–specific target” network of DHPF. Abbreviations: Lianhua Qingwen; DHPF, damp-heat plague formula; COVID-19, coronavirus disease 2019

Figure 6.

Molecular models of active ingredients with specific key targets targeted by LHQW and DHPF. (A–E) The candidate ingredients could enter the active pocket of the proteins. (F–G) Hydrogen bonds of active ingredients with specific key targets targeted calculated by PyMOL 1.8. (K–O) Hydrogen bonds of active ingredients with specific key targets targeted calculated by MOE v2019.0102. (A, F, and K). The molecular model of Machiline binding to ADRA2B. (B, G, and L) The molecular model of Machiline binding to ADRA2C. (C, H, and M) The molecular model of Estrone binding to DRD2. (D, I, and N) The molecular model of Ellagic acid binding to GSTA1. (E, J, and O) The molecular model of Ellagic acid binding to GSTA2. The yellow dashed lines indicate H-bonds; the thick pink-colored and green-colored sticks represent the active ingredients and residues in the protein binding site, respectively. The blue and green dashed lines indicate H-bonds between the active ingredients and the residue backbones and residue sidechains, respectively. The dashed lines denote the acceptor. Abbreviations: LHQW, Lianhua Qingwen; DHPF, damp-heat plague formula; MOE, Molecular Operating Environment.

Validation of Specific Target-Chemical Ingredient Interactions by Molecular Dynamics Simulations

To explore the binding between the targets and chemical ingredients, Amber18 was used to determine the binding capacity between specific targets (ADRA2B, ADRA2C, DRD2, GSTA1, and GSTA2) and the chemical ingredients (Machiline, Estrone, and Ellagic acid). Root-mean-square deviation (RMSD) can be used to characterize the stability of the chemical ingredients that bind to the targets. The RMSD was seen to fluctuate in the early period, whereas that of ADRA2B-Machiline stabilized at approximately 0.45 Å, with an average RMSD value of 0.46 Å (Figure 7A). ADRA2C-Machiline stabilized after 10 ns; the RMSD value was stable at approximately 0.4 Å, and the average RMSD value was 0.39 Å (Figure 7A). The RMSD value of DRD2-Estrone was stable at approximately 0.40 Å, and the average RMSD value was 0.39 Å (Figure 7E). GSTA1-Ellagic acid and GSTA2-Ellagic acid stabilized after 5 ns; the RMSD value of GSTA1-Ellagic acid was stable at approximately 0.25 Å, with an average RMSD value 0.23 Å, and the RMSD value of GSTA2-Ellagic acid was stable at approximately 0.20 Å, with an average RMSD value 0.21 Å (Figure 7H).

Figure 7.

Molecular dynamics simulations of ADRA2B and machiline. (A, E, and H) The RMSD of Machiline binding to ADRA2B and ADRA2C, Estrone binding to DRD2, and Ellagic acid binding to GSTA1 and GSTA2. (B, C, F, I, and J).The energy decomposition of ADRA2B-Machiline, ADRA2C-Machiline, DRD2-Estrone, GSTA1-Ellagic acid, and GSTA2-Ellagic acid. (D, G, and K) The SASA of Machiline binding to ADRA2B and ADRA2C, Estrone binding to DRD2, and Ellagic acid binding to GSTA1 and GSTA2. Abbreviation: RMSD, root-mean-square deviation; SASA, solvent-accessible surface area

The energy decomposition determined the contribution of chemical ingredients to the binding free energy of amino acid residues in the range of 6 Å, and a binding free energy less than −1 kcal/moL was defined as key amino acids. The key amino acids of ADRA2B-Machiline were VAL:61, ILE:65, SER:69, and TYR:88 (Figure 7B); of ADRA2C-Machiline were VAL:132, PHE:399, and PHE:398 (Figure 7C); of DRD2-Estrone were PHE:389, TRP:386, CYS:118, VAL:115, PHE:390, PHE:198, and ILE:184 (Figure 7F); of GSTA1-Ellagic acid were PHE:220, VAL:111, and VAL:216 (Figure 7I); and of GSTA2-Ellagic acid were PHE:111, LEU:108, PHE:220, and PHE:222 (Figure 7J). The solvent-accessible surface area (SASA) is characterized by the area of the protein exposed to the solvent, and the SASA value is inversely proportional to its stability. The SASA values of ADRA2B-Machiline and ADRA2C-Machiline were stable at approximately 155 nm² (Figure 7D); of DRD2-Estrone was stable at approximately 150 nm² (Figure 7G); and of GSTA1-Ellagic acid and GSTA2-Ellagic acid were stable at approximately 120 nm² (Figure 7K). The binding energy of ADRA2B-Machiline was −28.65 kJ/moL, ADRA2C-Machiline was −24.07 kJ/moL, DRD2-Estrone was −38.22 kJ/moL, GSTA1-Ellagic acid was −20.46 kJ/moL, and GSTA2-Ellagic acid was −24.43 kJ/moL (Table 1). According to the RMSD, energy decomposition, SASA, and binding energy results, Machiline could combine with ADRA2B and ADRA2C stably and Estrone could combine with DRD2 stably. Ellagic acid could combine with GSTA1 and GSTA2, and are thus potential target ingredients.

Table 1.

Gibbs Free Energy of Active Ingredients With Target Proteins.

Target protein	Research Collaboratory for Structural Bioinformatics Protein Data Bank ID (PDBID)	Active ingredient	Gibbs free energy (kJ/mol)
ADRA2B	6K41	Machiline	−28.65
ADRA2C	6KUW	Machiline	−24.07
DRD2	7DFP	Estrone	−38.22
GSTA1	6YAW	Ellagic acid	−20.46
GSTA2	2WJU	Ellagic acid	−24.43

Discussion

Therapeutic strategies to eradicate the virus remain limited, and we lack the knowledge of drugs to specifically treat COVID-19.²⁵ Fortunately, TCM has benefited the Chinese people since ancient times and continues to play a vital role in preventing and treating several epidemic diseases. TCM, represented by LHQW and DHPF, is an effective strategy for treating COVID-19. In this study, Machiline and Estrone in Armeniacae Semen Amarum (Kuxingren) were confirmed to target neurological disease-related targets (ADRA2B, ADRA2C, and DRD2), and recent research indicated that Machiline has been validated as one of the top 10 components related to targets of LHQW.²⁶ Estrone in Armeniacae Semen Amarum (Kuxingren) is a potentially active compound for use in treating of COVID-19.²⁷

GSTA1 and GSTA2 are vital members of the glutathione S-transferase family and can scavenge free radicals and reduce oxidative stress in cells. Therefore, they possess potent antioxidant and anti-inflammatory functions. Further, Ellagic acid in Paeoniae Radix Rubra (Chishao) was found to target the immunity- and inflammation-related targets (GSTA1 and GSTA2). Studies have shown that Ellagic acid is one of the chemical components of Paeoniae Radix Rubra (Chishao), which was analyzed using UPLC-Q-TOF-MS and HPLC methods.²⁸ In vitro studies show that Ellagic acid binds to several components of the SARS-CoV-2 virus with different affinities, supporting host defense during virus infection and disease recovery, thereby achieving antiviral effects.²⁹

These results collectively indicate that in a clinical setup, LHQW is likely to be more potent in treating COVID-19 patients with neurological disorders. In contrast, DHPF would exhibit better antioxidant and anti-inflammatory properties. These findings provide insight into the association between different TCM formulas and mild COVID-19 therapeutics.

LHQW, as a representative of Chinese Traditional Patent Medicine for respiratory public health events, once played a therapeutic role equivalent to oseltamivir in treating influenza A (H1N1). In addition, it inhibits infections by SARS-CoV and MERS-CoV.³⁰ Furthermore, LHQW significantly improves the symptoms of patients with confirmed mild and moderate COVID-19 and is, therefore, listed as a drug for treatment in these cases. In the seventh edition of the “Diagnosis and Treatment Protocol for COVID-19”,¹² DHPF was prescribed for treating mild cases that presented with the TCM syndrome: “Dampness and heat-accumulation lung syndrome.” In clinical practice, pharmacological studies of TCM suggest that the ingredients often have an inhibitory effect on the virus. The antiviral activity of TCM can be divided into 2 stages: (i) Eliminating pathogens by directly killing the virus or preventing its replication and (ii) indirectly enhancing the body's ability to resist the virus by promoting specific and nonspecific host immunity. Therefore, highly efficacious TCMs exhibit antiviral, anti-inflammatory, and immunity-boosting functions.¹⁶ Glycyrrhizin and glycyrrhetinic acid in Glycyrrhizae Radix et Rhizoma (Gancao), a herb in LHQW and DHPF, inhibit inflammatory pathways and viral penetration through shedding or releasing virus particles.³¹ Different ingredients derived from the extracts of Isatidis Radix (Bailangen) can directly inactivate influenza A 1 virus³²; anthraquinones derived from Rhei Radix et Rhizoma (Dahuang) can inhibit SARS-CoV infection by blocking S protein and ACE-2 interaction.³³ Astragalus polysaccharides from Scutellariae Radix (Huangqin) increase the weight of the spleen and thymus, restore the structure of the damaged thymus and spleen tissue, and induce interferon production. Further, they inhibit viral protein synthesis and improve immune dysfunction in patients.³⁴ These reports suggest that TCM has vital applications in treating mild COVID-19.

Previous studies have indicated that LHQW and DHPF can treat mild COVID-19 cases.^12,35 As this study suggests, the 2 formulas can treat mild COVID-19 through anti-inflammation, immune regulation, and reducing oxidative stress. In patients with COVID-19, the excessive release of cytokines and chemokines could result in a cytokine storm, leading to diffuse lung injury and respiratory distress syndrome. Thus, TCM intervention in the early stage of the disease is critical for preventing inflammation.^36,37 Previous studies have shown that LHQW can dose-dependently inhibit SARS-CoV-2 replication and reduce the release of cytokines in host cells in vitro,³⁷ suggesting that the integrated network pharmacology results of this study are reliable. Although different constituents are present in LHQW and DHPF, the targets of the 2 formulas were relatively similar and generated a similar target pattern in treating mild COVID-19.

A high similarity was observed in the targets of LHQW and DHPF; however, specific targets are acted on by the individual formulas, indicating that the therapeutic mechanisms underlying each formula may differ. Based on the target enrichment analysis, LHQW exhibited robust associations with psychological disorders, whereas DHPF appeared to have a strong influence on inflammation and immunization. Focus was placed on the specific targets of both formulas. The determined targets, ADRA2B and ADRA2C, are subtypes of alpha (2B) adrenoceptors and are associated with neurotransmitter release from adrenergic neurons. Therefore, either deletion or mutation of ADRA2B or ADRA2C would evoke the memory of negative emotions.^38,39 DRD2 is one of the most studied dopamine receptors. It can regulate dopamine release in the midbrain and the development of dopaminergic neurons,⁴⁰ influencing various mental disorders, such as depression, anxiety, and cognitive impairment. DRD2 has also been a target of many antipsychotics and drugs used to treat Parkinson's disease, such as risperidone and bromocriptine.^41,42

This study lays the foundation for research into further applications of LHQW and DHPF in other neurological and respiratory disorders and can benefit both researchers and clinicians alike. The ability of the compounds (Machiline, Estrone, and Ellagic acid) in these 2 formulas to treat mild COVID-19 with other diseases will be further explored through in vivo and in vitro experiments in subsequent studies.⁴³

Conclusions

This study focuses on the similarities and differences in the mechanisms of LHQW and DHPF for treating mild COVID-19. These results collectively indicate that LHQW and DHPF can alleviate symptoms in patients with mild COVID-19 by relieving inflammation, improving immunity, and reducing oxidative stress. Machiline and Estrone in LHQW can target neurological disease-related genes (ADRA2B, ADRA2C, and DRD2), therefore benefiting COVID-19 patients with mental disorders, and Ellagic acid in DHPF can target immunity- and inflammation-related genes (GSTA1 and GSTA2), benefiting patients with COVID-19 experiencing inflammation.

Materials and Methods

Screening of Active Ingredients in LHQW and DHPF

The TCMSP database (http://tcmspw.com/tcmsp.php)⁴⁴ was used to ascertain the active ingredients of the 2 formulas. To ensure that the obtained results were valid, we used 2 screening parameters, viz. drug-likeness evaluation and oral bioavailability, set at limits of ≥0.18% and 30%, respectively, to identify the potential effective ingredients in both formulas.

Procuring Ingredients and Targets of LHQW and DHPF

The active ingredients and targets of the 2 formulas were obtained from the TCMSP database, and the UniProt database (https://www.uniprot.org/) was used to standardize the gene symbol names corresponding to the protein target names.

The channel tropism, property, and flavor of the plant were found in the ETCM (http://www.tcmip.cn/ETCM/)⁴⁵ database. The obtained targets were then captured from the STRING (https://string-db.org/)⁴⁶ database to build the PPI network. The MCODE algorithm in Cytoscape was used to obtain the clustered PPI network, and the degree value of the PPI network and protein module targets were calculated. The degree value represents the correlation between targets, and its value is proportional to the correlation.

GO and KEGG Pathway Enrichment

GO and KEGG pathway enrichment analyses were performed using the “Cluster Profiler” package in R software to extract the canonical bioprocesses and pathways. Smaller p adjusted values indicated higher enrichment, and the top 15 enriched GO and KEGG pathways were obtained. Finally, the similarities between enriched pathways of LHQW and DHPF were analyzed and compared.

PPI Network Construction and Analysis

To reveal the association between the intersecting targets of the 2 formulas, a network was built using Cytoscape (version 3.4.0). The targets and interactions between targets were described by nodes and lines in the network, respectively.

Prediction of Pathways and Diseases Affected by the Specific Targets of LHQW and DHPF in Treating Mild COVID-19

To explore the mechanisms of LHQW and DHPF in treating mild COVID-19, their specific targets were uploaded into IPA software for pathways and associated disease prediction analysis based on known interactions between genes and proteins. Subsequently, the top associated pathways and diseases were generated and displayed in the network.

Construction of the “Component–Active Ingredient–Specific Target” Network and Molecular Docking

According to the IPA network and literature review, the significant targets of the specific genes of LHQW and DHPF were identified, and the structures of proteins coded by the genes were obtained from the RCSB PDB database (https://www.rcsb.org/). The “component–active ingredient–specific target” networks of LHQW and DHPF were constructed using Cytoscape software, and the ingredients of the significant targets were defined from this network. The three-dimensional structures of the active ingredients were obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). GOLD 5.2 and Autodock 1.1.2 software were used for virtual docking, and Chemscore, ChemPLP, and binding energy values were used simultaneously to evaluate the docking results. Subsequently, the GOLD 5.2 docking results were visualized using PyMOL 1.8 and MOE v2019.0102.

Molecular Dynamic Simulation

Molecular dynamic simulation of the targets and chemical ingredients after molecular docking were performed using Amber18 software. The simulations were performed for 50 ns using Amber99sb force parameters. The time step was 2 ps, and trajectory data were saved every 10 ps. Subsequently, the data were presented in terms of binding energy, RMSD, energy decomposition, and SASA.

Supplemental Material

sj-xlsx-1-npx-10.1177_1934578X231194164 - Supplemental material for Similarity and Specificity of Lianhua Qingwen and Damp-Heat Plague Formula for the Management of Mild COVID-19

Supplemental material, sj-xlsx-1-npx-10.1177_1934578X231194164 for Similarity and Specificity of Lianhua Qingwen and Damp-Heat Plague Formula for the Management of Mild COVID-19 by Xiao Guo, Liyuan Li, Xiaoying Wang, Yikun Li, Congning Liu, Qiuhang Song and Aiying Li in Natural Product Communications

Supplemental Material

sj-xlsx-2-npx-10.1177_1934578X231194164 - Supplemental material for Similarity and Specificity of Lianhua Qingwen and Damp-Heat Plague Formula for the Management of Mild COVID-19

Supplemental material, sj-xlsx-2-npx-10.1177_1934578X231194164 for Similarity and Specificity of Lianhua Qingwen and Damp-Heat Plague Formula for the Management of Mild COVID-19 by Xiao Guo, Liyuan Li, Xiaoying Wang, Yikun Li, Congning Liu, Qiuhang Song and Aiying Li in Natural Product Communications

Supplemental Material

sj-docx-3-npx-10.1177_1934578X231194164 - Supplemental material for Similarity and Specificity of Lianhua Qingwen and Damp-Heat Plague Formula for the Management of Mild COVID-19

Supplemental material, sj-docx-3-npx-10.1177_1934578X231194164 for Similarity and Specificity of Lianhua Qingwen and Damp-Heat Plague Formula for the Management of Mild COVID-19 by Xiao Guo, Liyuan Li, Xiaoying Wang, Yikun Li, Congning Liu, Qiuhang Song and Aiying Li in Natural Product Communications

Footnotes

Data Availability

The data used and analyzed during this study are available from the corresponding author upon reasonable request.

Declaration of Conflicting Interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Projects of Medical Science Research of Hebei Province, Science and Technology Project of Hebei Provincial Education Department, Projects of Medical Science Research of Hebei Province, Doctoral Research Funding Project of Hebei University of Chinese Medicine (grant numbers 20210258, QN2021106, 20221482, BSZ2020011).

ORCID iD

Qiuhang Song

Supplemental Information

Supplemental information is available online.

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