Exploring the mechanism of Radix pseudostellariae in the treatment of chronic gastritis based on network pharmacology and molecular docking techniques

doi:10.21203/rs.3.rs-3958812/v1

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Exploring the mechanism of Radix pseudostellariae in the treatment of chronic gastritis based on network pharmacology and molecular docking techniques

https://doi.org/10.21203/rs.3.rs-3958812/v1

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Radix pseudostellariae (RP) has been used for the treatment of various diseases, including gastric disorders such as Chronic gastritis (CG), However, the multi-targeting mechanism of RP on CG still needs to be clarified. Drug targets were established through TCMSP, PubChem and Swiss Target Prediction online database. GeneCards database was used to search for chronic gastritis related targets. Cytoscape was utilized to construct the "drug-active ingredient-target" network relationship diagram. Venny plots of drug targets and disease targets were obtained from online software to get the intersecting genes, and the coincidence targets were imported into STRING database to construct a PPI network. The intersecting targets were subjected to pathway enrichment analysis KEGG and GO functional enrichment analysis with the help of the DAVID database. Molecular docking was performed by Autodocktools software and then visualized by PYMOL. 8 active ingredients and 117 action targets were obtained for Radix Pseudostellariae, 758 action targets for chronic gastritis disease, 31 intersecting targets for Radix Pseudostellariae in chronic gastritis were obtained. PPI network analysis showed that the core targets of the drug affecting chronic gastritis were TNF, MMP9, AKT1, etc. The molecular docking validation results showed good binding of core components and core targets.

Chronic gastritis (CG) is a chronic inflammatory lesion of the gastric mucosa caused by various factors, such as Helicobacter pylori infection, autoimmunity, and duodenal fluid reflux ¹. Typical symptoms of CG include nonspecific dyspepsia, such as epigastric pain, abdominal distension, postprandial fullness, and early satiety. Other symptoms may include loss of appetite, belching, acid reflux, and nausea. Concomitant symptoms of marked erosions and prolonged small amounts of bleeding may include pallor, dizziness, and weakness, which could be due to iron deficiency anaemia. Patients with autoimmune gastritis may present with pernicious anaemia and neurological symptoms, such as glossitis, mild jaundice, numbness of the limbs, and weakness ². In recent years, the prevalence of CG has been increasing steadily. At least 80% of the population experiences gastric upset, making CG the most common disease. In China, the prevalence of CG is as high as 30%, and it is associated with Helicobacter pylori infection, which increases with age. In fact, the prevalence of CG can be as high as 60–70% in people aged 70–80 years. Additionally, the prevalence of CG is also increasing among young and middle-aged groups ^3,4.

In clinical treatment, drugs are primarily used to treat CG by inhibiting gastric acid secretion, protecting the gastric mucosa, and providing antimicrobial effects. Drugs that inhibit gastric acid are classified into two main categories: proton pump inhibitors and H2 receptor antagonists. However, long-term use of proton pump inhibitors may lead to a series of serious side effects: (1) Patients with allergic reactions after long-term use of these drugs may further suffer from severe diseases such as acute interstitial nephritis and chronic kidney disease ^5,6. (2) It may also lead to hypomagnesemia caused by reduced absorption of magnesium in the small intestine ^7,8. (3) In the elderly, prolonged use probably also increases the risk of dementia ^9,10. (4) It may also lead to changes in the intestinal microbiome and small intestinal bacterial overgrowth ¹¹. The main side effects of H2 receptor antagonists are nausea, vomiting, dizziness, dry mouth, constipation, and increased heart rate ¹². Almagate Suspension as a Gastric Mucosal Protectant is facing non-negligible side effects, including liver inflammation, nephritis, decreased acidity, impotence, osteoporotic fractures, and hyperglycaemia ¹³. Commonly used antimicrobial drugs include amoxicillin and clarithromycin. However, it is important to note that these drugs have the potential to trigger Mycobacterium vaginalis infections, which requires attention ¹⁴. In conclusion, there are potential risks associated with the clinical treatment of CG that must be considered. Traditional Chinese medicine (TCM) is a reliable treatment option for CG due to its clinical efficacy, low toxicity, and minimal side effects.

Radix pseudostellariae (RP) is a tuberous root from the genus Staphylococcus and is commonly used in TCM ¹⁵. Clinically, RP is often combined with Chinese medicines such as Rhizoma Dioscoreae and Poria cocos to treat CG and loss of appetite ^16,17. In the market, the proprietary Chinese medicine's of RP include Jianwei Xiaoshi Tablets and Compound Taizishen Granules, which are widely used in the treatment of CG ^18,19. Modern studies have shown that RP contains a variety of chemical components with various pharmacological effects, such as anti-inflammatory and antibacterial properties ²⁰. RP can effectively inhibit the propagation of H. pylori, thereby inhibiting the occurrence of CG ²¹. RP polysaccharide can promote the proliferation of T cells and effectively remove Helicobacter pylori, thus inhibiting CG ²².

In summary, numerous clinical and basic studies have demonstrated the exact efficacy of RP in treating CG. However, the mechanism of action and active substance basis of RP for CG have not been clarified. Therefore, the current study utilised network pharmacology approach to examine the potential interactions between the active ingredients of RP and the potential targets of CG. Additionally, the affinity of the active compounds in RP with potential targets was further explored by molecular docking techniques. (Fig. 1) illustrates our workflow. These studies aim to provide theoretical support for the development of more effective drugs by gaining a clearer understanding of the mechanism of RP in the treatment of CG.

2.1. Collection of active ingredients of RP

The TCMSP database is a reliable herbal medicine database that establishes links between drugs, targets, and diseases. Chemical compounds of PG were obtained from the TCMSP using 'PG' as the keyword (http://tcmspw.com/tcmsp.php). Oral bioavailability (OB) pertains to the fraction of an oral medicine that enters the systemic circulation and demonstrates how well it is assimilated and employed by the body. Drug similarity (DL) indicates the structural similarity between the compound and drug molecule. Hence, compounds with a high DL value have a greater likelihood of demonstrating appropriate pharmacodynamic and pharmacokinetic properties. Consequently, OB and DL provide vital references for the screening of active compounds, and as per the TCMSP database, OB ≥ 30% and DL ≥ 0.18 were utilized as the screening criteria for selection of the active compounds of RP.

The PubChem database (https://pubchem.ncbi.nlm.nih.gov/) is a comprehensive and freely accessible resource, providing valuable information for drug discovery and chemical biology research. To retrieve the chemical formula, we utilized the keyword "RP active ingredient" in the search box.

SwissTargetPrediction (http://www.swisstargetprediction.ch/) was employed to obtain potential targets of RP active ingredients.

2.2. Acquisition of potential targets for CG and PPI network construction

2.2.1. Target acquisition for CG

GeneCards (https://www.genecards.org) is a database that aims to elucidate the connection between genes, drugs, and diseases. It offers crucial insights into the correlation between genes, gene interactions, disease, and chemical phenotype. The information provided by the database is chosen from peer-reviewed scientific literature. As a result, we utilized this database to forecast the prospective target genes for CG. Only those genes with an interaction value of ≥ 1 have been shortlisted as candidate target genes.

2.2.2. PPI network construction

The RP-associated target genes and CG-associated genes that were screened were inputted into the Venny graph platform (https://bioinfogp.cnb.csic.es/tools/venny/) to generate a relationship venny graph, and overlapping genes were subsequently filtered out. The resulting data was then imported into the STRING platform (https://cn.string-db.org/) with the human condition set and a confidence level of 0.4 to establish the PPI network graph. The PPI network obtained was imported into Cytoscape software, and further processed using the STRING app within this software. Subsequently, the "RP-active ingredient-target" diagram was pl.

2.3. Gene Function and Pathway Enrichment Analysis

DAVID (https://david.ncifcrf.gov/) is a well-known software option for analyzing functional and pathway enrichment. The GO is a comprehensive reference for gene and gene product functions, which includes molecular functions, biological pathways, and cellular components. Furthermore, KEGG databases provide functional interpretations of genes and genomes at both molecular and higher levels. Therefore, the potential target genes are fed into the DAVID server, and both GO and KEGG databases are employed to perform enrichment analysis. The top 10 GO and KEGG outcomes were entered into the graphing tool at "http://bioinformatics.com.cn/login/.

2.4. Compound-Target Molecular Docking

The first step involved downloading the chemical structure formula of the RP active ingredient from the TCMP database. The formula was saved in mol2 format. Next, 3D structures of the top three proteins with the highest degree values in the PPI network were downloaded from the PDB data (https://www.rcsb.org/) and saved in PDB format. The solvent molecules and ligands were then removed with the aid of PyMOL software. Finally, AutoDock software was utilised to carry out additional operations including hydrogenation, electron addition, and root addition. The compounds and target protein formats were converted to pdbqt format. Molecular docking was completed using a rigid macromolecule protein structure and the Genetic Algorithm Parameters algorithm. PyMOL was employed to generate 3D images and heat maps for the protein group with the lowest binding energy in the results.

3.1. Collection of active ingredients of RP

Eight active compounds were screened from the TCMSP database (Table 1) and their chemical structures were obtained through the PubChem database. The target genes of 118 RP were obtained from the SwissTargetPrediction database.

Table 1

Basic information of the active ingredients of RP.
numbering	Molecule names	OB/%	DL/%
MOL001506	Supraene	33.55	0.42
MOL001689	Acacetin	34.97	0.24
MOL001790	Linarin	39.84	0.71
MOL000358	beta-Sitosterol	36.91	0.75
MOL000006	Luteolin	36.16	0.25
MOL006554	Taraxerol	38.4	0.77
MOL006756	Schottenol	37.42	0.75
MOL002464	1-Monolinolein	37.18	0.3

3.2. Acquisition of potential targets for CG and PPI network construction

3.2.1. Target acquisition for CG

Using "chronic gastritis" as the search term, 758 related genes were retrieved from the Genecards database.

3.2.2. PPI network construction

The drug active ingredient targets were intersected with disease targets, resulting in the identification of 31 drug active ingredient targets that were related to CG for further analysis (Fig. 2). The RP targets were color-coded in purple and CG targets were colored in yellow. These intersecting targets were then analyzed using the STRING online software to generate a PPI network (Fig. 3), which contained a total of 278 target-to-target relationships. Finally, the "RP-active ingredient-target" diagram was plotted (Fig. 4).

3.3. Gene Function and Pathway Enrichment Analysis

The 31 coincident genes were analyzed to obtain the relationship diagram of GO functional enrichment analysis (Fig. 5). BP: response to xenobiotic stimulus, negative regulation of apoptotic process, positive regulation of transcription from RNA polymerase II promoter, negative regulation of gene expression, signal transduction, positive regulation of apoptotic process, positive regulation of gene expression, positive regulation of transcription, DNA-templated, negative regulation of transcription from RNA polymerase II promoter, negative regulation of extrinsic apoptotic signaling pathway in absence of ligand.

CC: plasma membrane, cytoplasm, nucleus, integral component of membrane, extracellular space, extracellular region, membrane, Integral component of plasma membrane, cell surface, macromolecular complex.

MF: identical protein binding, ATP binding, protein homodimerization activity, zinc ion binding, enzyme binding, protein serine/ Threonine/tyrosine kinase activity, endopeptidase activity, iron ion binding, protein kinase activity, protein serine.

Kyoto Encyclopedia of KEGG (Fig. 6). Pathways in cancer, PI3K-Akt signaling pathway, Gastric cancer, Diabetic cardiomyopathy, Proteoglycans in cancer, Rap1 signaling Pathway, Fc epsilon RI signaling pathway, Central carbon metabolism in cancer, C-type lectin receptor signaling pathway, T cell receptor signaling pathway.

3.4. Compound-Target Molecular Docking

The combinations with the least free energy were derived by autodocktools software (Table 2), and then plotted on the heatmap ( Fig. 7). The lowest binding energy was obtained for the result TNF-Linarin, TNF-Luteolin, AKT1-Linarin, AKT1-Taraxerol, MMP9-Linarin, MMP9-Luteolin were obtained and then visualised by PYMOL software (Fig. 8).

Table 2

Magnitude diagram of molecular docking free energy.
numbering	Compound	Afnity score (kcal·mol-1).
numbering	Compound	TNF	AKT1	MMP9
MOL001506	Supraene	-5.1	-7.6	-7.6
MOL001689	Acacetin	-7	-9	-10.3
MOL001790	Linarin	-7.6	-10.7	-10.8
MOL000358	beta-Sitosterol	-6.7	-8.3	-8.3
MOL000006	Luteolin	-7.6	-9.1	-10.5
MOL006554	Taraxerol	-7.7	-10	-9
MOL006756	Schottenol	-6.5	-9.4	-8.5
MOL002464	1-Monolinolein	-4.9	-6.3	-6.9

CG is an inflammatory condition of the stomach wall that can be caused by various factors. In China, the prevalence of gastrointestinal diseases is high, affecting up to 120 million people, with CG being particularly prevalent, affecting up to 30% of the population. In regions such as Yunnan, Guizhou and Sichuan, the probability of developing CG is higher than in other regions due to the long-term consumption of excessively spicy food ²³. If CG patients are neglected for a long time or not treated in time, their condition may gradually deteriorate and eventually evolve into stomach cancer ²⁴.

The study identified TNF, MMP9, and AKT1 as core targets of gastritis and potential key genes for CG treatment by RP. TNF-α is a pro-inflammatory cytokine with multiple biological functions, which is involved in several processes such as inflammation, immunity, cell differentiation, and cell survival and death. TNF-α is secreted mainly by activated T-lymphocytes and mononuclear macrophages. In addition, TNF-α induces the release of pro-inflammatory factors in the stomach ^25,26. These pro-inflammatory factors play an important role in the inflammatory response, which can be exacerbated by further promoting the aggregation and activation of inflammatory cells. TNF-α may modulate the intrinsic Vago-Vagal reflex pathway during the disease by functioning as a hormone, which leads to persistent gastric stasis, resulting in the development of CG ²⁷. MMP9 is a metallo-matrix protease that degrades extracellular matrix and vascular basement membrane. Increased MMP9 activity can lead to the destruction of gastric mucosal structure, as seen in gastric mucosal injury ²⁵. Studies have shown a positive correlation between H. pylori infection and MMP9 expression levels. H. pylori can stimulate the gastric mucosa to produce an inflammatory response, which is a significant factor in the increased expression of MMP9. Therefore, detecting the expression level of MMP9 can indirectly indicate whether a patient has CG or not ²⁸. AKT is able to influence the transcription of a variety of genes and can reduce MMP9 expression by regulating p65 ²⁵. It is also a downstream factor of the PI3K signalling pathway, and activation of the PI3K signalling pathway can cause a variety of inflammatory responses, which can affect AKT1 expression ²⁹. In the case of CG, H. pylori infection can activate the PI3K signalling pathway, leading to an increase in AKT1 expression. This may lead to damage to the gastric mucosa and an increased inflammatory response, thus causing CG pathogenesis. Therefore, AKT1 plays a crucial role in the inflammatory response and the development of CG. In summary, TNF, MMP9, and AKT1 are the main factors that affect CG. RP can play a role in treating CG by regulating the aforementioned proteins.

The present study obtained eight active ingredients from RP, including Supraene, Acacetin, Linarin, beta-sitosterol, Luteolin, Taraxerol, Schottenol, and 1-Monolinolein. Beta-sitosterol is a beneficial phytosterol with anti-inflammatory and antibacterial effects. Various studies have shown that beta-sitosterol can inhibit the expression of several pro-inflammatory factors, thus exerting anti-inflammatory effects. In experiments on rat foot swelling and pleurisy, Paniagua-Pérez R et al. discovered that beta-sitosterol has a potent anti-inflammatory effect ³⁰. Furthermore, Liz et al. and Choi et al. demonstrated that beta-sitosterol can promote cellular calcium uptake, inhibit the activities of myeloperoxidase and adenosine deaminase, and reduce the levels of IL-1β and TNF-α, respectively, thereby exerting anti-inflammatory effects ³¹. Choi et al. found that beta-sitosterol inhibits macrophage IL-6 activity, reduces the secretion of inflammatory factors such as TNF-α and IL-1β, and exerts anti-inflammatory effects ³². Luteolin is a flavonoid with multiple pharmacological activities, has anti-tumour, anti-inflammatory and antibacterial effects. Its anti-inflammatory effects are mainly exerted by regulating Src and signal transduction in the nuclear transcription factor NF-κB pathway, thus regulating the release of inflammatory mediators ³³. Li B et al. Experimental evidence that Luteolin modulates the gut microbiota for the treatment of gastroenteritis ³⁴. Liu Z et al. also showed that Luteolin can attenuate LPS-induced inflammatory injury and reduce inflammatory factor expression in H9C2 cells, thereby inhibiting inflammation. This further confirms the role of Luteolin in anti-inflammation ³⁵. Taraxerol has significant anti-inflammatory effects and suppresses the production of PGE2, TNF-α, IL-6 and IL-1β ³⁶. Aodah AH et al. found that Taraxerol inhibits the expression of pro-inflammatory mediators in macrophages by inhibiting the activation of TAK1 and AKT proteins, which inhibits NF-κB activation and its downstream expression of inflammatory factors ³⁷. Linarin effectively inhibits inflammation caused by gastrointestinal problems ³⁸. Kim B conducted a study which showed that Linarin can reduce inflammation by decreasing the secretion of NO, IL-1, and IL-6 in a dose-dependent manner ³⁹.Linarin also inhibits cellular NF-κB and MAPKS, as well as TXNIN/NLRP3 activity, thereby attenuating the inflammatory response ^40,41. In short, the many active ingredients in RP are effective in suppressing inflammation in the gut.

In summary, this study has been validated by network pharmacology and molecular docking technology. The results show that RP regulates CG through multiple components, multiple targets and multiple pathways. This finding is consistent with the therapeutic characteristics of Chinese medicine theory and provides a theoretical basis for the clinical application of RP. However, network pharmacology does not involve coordination between active ingredients and metabolic changes in the body. Therefore, this study is only a theoretical prediction, and further experiments are necessary to verify the pharmacodynamic mechanism of the drug.

CG, Chronic gastritis; RP, Radix pseudostellariae; TCM, traditional Chinese medicine theory; OB, Oral bioavailability; DL, Drug similarity; PPI, Protein-Protein Interaction; GO, Gene Ontology; CC, Cellular Component; MF, Molecular Function; BP, Biological Process; KEGG, Kyoto Encyclopedia of Genes and Genomes

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors thank Lailai Li, for developmental editing of the manuscript.

Authors’ Contributions

Y L and L-L L conceived and designed the study. S-H C, D-Y Z, Y , X-K T performed the data analysis. Y L wrote the paper. All authors have read and approved the final manuscript.

Data availability

All data generated or analysed during this study are included in this published article and itsSupplementary information fles.

Funding

This study was Supported by National Natural Science Foundation of China (82060913); Project of Science and Technology department of Guizhou Province (ZK [2021]-546); Project of Science and Technology department of Guizhou Province ([2019]1401); Guizhou Provincial Health Commission(gzwkj2021-464).

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No competing interests reported.

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Exploring the mechanism of Radix pseudostellariae in the treatment of chronic gastritis based on network pharmacology and molecular docking techniques

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Abstract

Figures

1. Introduction

2. Materials and Methods

2.1. Collection of active ingredients of RP

2.2. Acquisition of potential targets for CG and PPI network construction

2.2.1. Target acquisition for CG

2.2.2. PPI network construction

2.3. Gene Function and Pathway Enrichment Analysis

2.4. Compound-Target Molecular Docking

3. Results

3.1. Collection of active ingredients of RP

3.2. Acquisition of potential targets for CG and PPI network construction

3.2.1. Target acquisition for CG

3.2.2. PPI network construction

3.3. Gene Function and Pathway Enrichment Analysis

3.4. Compound-Target Molecular Docking

4. Discussion

5. Conclusion

Abbreviations

Declarations

References

Additional Declarations

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