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Method Article

The Efficacy and Underlying Pathway Mechanisms of ShiDuGao Treatment for Anus Eczema Based on GEO Datasets and Network Pharmacology

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DOI:

10.3791/66453

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January 12th, 2024

 ,  ,  ,  , 
1Department of General Surgery, Tianjin Medical University General Hospital, 2Tianjin General Surgery Institute, 3Department of General Surgery, Zibo Municipal Hospital

* These authors contributed equally

In This Article

Summary

This investigative effort sought to elucidate the mechanism of topical drug administration using a synergistic integration of network pharmacology and gene expression omnibus (GEO) datasets. This article evaluated the feasibility, target, and mechanism of ShiDuGao (SDG) in treating anus eczema.

Abstract

Anus eczema is a chronic and recurrent inflammatory skin disease affecting the area around the anus. While the lesions primarily occur in the anal and perianal skin, they can also extend to the perineum or genitalia. ShiDuGao (SDG) has been found to possess significant reparative properties against anal pruritus, exudation control, moisture reduction, and skin repair. However, the genetic targets and pharmacological mechanisms of SDG on anal eczema have yet to be comprehensively elucidated and discussed. Consequently, this study employed a network pharmacological approach and utilized gene expression omnibus (GEO) datasets to investigate gene targets. Additionally, a protein-protein interaction network (PPI) was established, resulting in the identification of 149 targets, of which 59 were deemed hub genes, within the "drug-target-disease" interaction network.

The gene function of SDG in the treatment of perianal eczema was assessed through the utilization of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. Subsequently, the anti-perianal eczema function and potential pathway of SDG, as identified in network pharmacological analysis, were validated using molecular docking methodology. The biological processes associated with SDG-targeted genes and proteins in the treatment of anus eczema primarily encompass cytokine-mediated responses, inflammatory responses, and responses to lipopolysaccharide, among others. The results of the pathway enrichment and functional annotation analyses suggest that SDG plays a crucial role in preventing and managing anal eczema by regulating the Shigellosis and herpes simplex virus 1 infection pathways. Network pharmacology and GEO database analysis confirms the multi-target nature of SDG in treating anal eczema, specifically by modulating TNF, MAPK14, and CASP3, which are crucial hub targets in the TNF and MAPK signaling pathways. These findings provide a clear direction for further investigation into SDG's therapeutic mechanism for anal eczema while highlighting its potential as an effective treatment approach for this debilitating condition.

Introduction

Anal eczema is an allergic skin condition that affects the perianal region and mucosa, exhibiting various clinical manifestations1. The characteristic symptoms include anal erythema, papules, blisters, erosion, exudates, and crusting. These symptoms mostly arise due to scratching, thickening, and roughness of the affected area2.

Anal eczema, characterized by a prolonged duration of the disease, recurrent attacks, and challenging treatment, can have adverse effects on patients' physical and mental health3. The pathogenesis of anal eczema is not yet clear, and modern medicine suggests that it may be related to local anal lesions, diet, environment, genetics, and other factors4. In addition to avoiding contact with irritants and potential allergens, the treatment of anal eczema mainly focuses on methods such as inhibiting inflammation, anti-allergy, and relieving itching5.

SDG has been extensively utilized for the treatment of anal eczema and other anal conditions. SDG regulates anal skin exudation, reduces moisture, repairs anal skin, and effectively addresses pruritus6,7,8. Furthermore, SDG has the potential to regulate perianus microbiota, thereby improving anus eczema9,10.

Network pharmacology, a novel and interdisciplinary, cutting-edge bioinformatic approach in the realm of artificial intelligence and big data, provides an in-depth exploration of traditional Chinese medicine. This discipline emphasizes the systemic expounding of molecular correlation rules between drugs and diseases from an ecological network perspective. It has been extensively adopted for various aspects, including identifying key active ingredients in herb extracts, deciphering their global mechanisms of action, formulating drug combinations, and studying prescription compatibility. Traditional Chinese prescriptions exhibit the attributes of multi-component and multi-target, signifying their substantial adaptability to the realm of network pharmacology. Driven by this methodology, fresh perspectives have emerged in the examination of complex traditional Chinese medicine systems, furnishing robust technical support for clinical application rationalization and drug innovation11,12,13,14.

This study aims to explore the mechanism of effectiveness of SDG in the treatment of anal eczema. This investigative effort sought to elucidate the mechanism of topical drug administration using a synergistic integration of network pharmacology and GEO datasets. The findings provide valuable insights into the efficacy and underlying mechanisms of SDG in the management of anus eczema, indicating its potential as an effective therapeutic approach for this condition.The detailed workflow diagram of the study is presented in Figure 1.

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Protocol

This study does not refer to ethical approval and consent to participate. The data used in this study was obtained from gene databases.

1. Prediction of disease targets

  1. Access the GeneCards database (https://www.genecards.org) and online Mendelian inheritance in man database (OMIM, https://www.omim.org), utilizing "anus eczema" as the search term for disease targets.
  2. Download the spreadsheets of the disease targets. Delete the repeated targets to obtain the anus eczema targets.

2. Selection of active components

  1. Search the keyword "indigo naturalis, golden cypress, calcined gypsum, calamine, and Chinese Gall" on the Traditional Chinese Medicine system's pharmacology database (TCMSP; http://tcmspw.com/tcmsp.php) to obtain the list of the candidate active ingredients and targets of SDG.
  2. Entrust the component onto the Swiss ADME database (http://www.swissadme.ch/index.php), extracting details of those exhibiting "high" GI absorption, coupled with at least two "Yes" DL values as active elements.
    NOTE: Normally, only ingredients with drug-like (DL) values ≥0.18 in the database are included as active ingredients.

3. Construction of the PPI network and screening of the core proteins

  1. In Venny2.1( https://bioinfogp.cnb.csic.es/tools/venny/index.html), enter the targets of SDG and anus eczema into LIST1 and LIST2, respectively. A visual representation of the intersection is generated instantly. Click on the shared area to reveal the common targets in the Results section.
  2. Access the STRING database (https://string-db.org/). Enter the targets in the List of Names field. Then Select Homo sapiens as the Organism and proceed with Search > Continue.
  3. When the results are available, open Advanced Settings and select the hide disconnected nodes in the network. In the Minimum Required Interaction Score, set the highest confidence (0.900) and then click on Update.
  4. Click on Exports to download the text of the protein-protein interaction (PPI) network in .png and .tsv format.

4. Construction of a drug-component-disease-target network

  1. Open Cytoscape 3.9.1 and import the .tsv file mentioned in step 3.4. Click on the Style bar in the control panel to optimize the color, font, and side of the network nodes.
  2. For network topology analysis, employ the Analyze Network function. To obtain hub genes, use CytoHubba in Cytoscape software. Establish the drug-component-disease-target network.

5. GO and KEGG enrichment analysis

  1. Access the Metascape website (https://metascape.org/). Select a file or paste a gene list into the dialog box and click the Submit button. Then select H. sapiens in both Input as Species and Analysis as Species; after that, enable the Custom Analysis function.
  2. In the enrichment option, select GO Molecular Functions, GO Biological Processes, GO Cellular Components, and the KEGG Pathway database. Check Pick Selective GO Clusters, then click on the Enrichment Analysis button. Upon completion of the progress bar, initiate an Analysis Report Page click to retrieve the enrichment results.

6. GEO gene chip dataset analysis

  1. Search and analyze the GEO gene chip dataset (GDS3806) using the GEO2R tool (https://ncbi.nlm.nih.gov/geo/geo2r/) to investigate the expression of central genes in different data groups (control group-non-atopic dermatitis; experimental group-atopic dermatitis).
  2. Enter the GEO database website (https://www.ncbi.nlm.nih.gov/geo/). Input keyword or GEO Accession, and click on the Search button. Select the best matching result. Find the Reference Series (GSE26952).
  3. Enter the GEO2R tool website (https://ncbi.nlm.nih.gov/geo/geo2r/), enter the reference series in the GEO Accession box, and click the Set button. Select Atopic Dermatitis as the experimental group, select Nonatopic Control as the control group, and click the Analyze button. After the calculation is completed, the result will appear.

7. Molecular docking

  1. Open the TCMSP database and download the 3D structure of the selected ingredients. Use the Chemical Name search box and search the selected ingredient names to download the corresponding 3D structure files in mol2 format.
  2. Open the RCSB protein database (http://www.pdb.org/) and download the crystal structures of the key targets. In the search box, search the target names and download the corresponding crystal structure files in pdb format.
  3. Import ingredients and target structure files into the analysis software. Delete water molecules by clicking on Edit > Delete Water. Add hydrogens by clicking on Edit > Hydrogens > Add. Set the ingredients as the ligand, select whole targets as the receptor, and perform blind docking.
  4. Determine the range of molecular docking.
    1. Select the receptor and ligand in sequence. Click on Grid > Grid Box to adjust the grid box to include the entire model. Click on File > Close saving current to save the grid box status. Save files in gpf format.
    2. Click on Run > Run Autogrid4 > Parameter Filename > Browse, select the gpf file, then click the Launch button.
  5. Use AutoDock 4 to perform molecular docking.
    1. Click on Docking > Macromolecule > Set Rigid Filename to select the receptor. Click on Docking > Ligand > Open/ Choose to select the ligand.
    2. Click on Docking > Search Parameters to set operation algorithms and Docking > Docking Parameters to set docking parameters. Select the dpf file, then click the Launch button. Save files in the dpf format.
    3. Click on Analyze > Docking > Open, select the dlg file, click on Analyze > Macromolecule to open the receptor, click on Analyze > Conformations > Play, Ranked by Energy to analyze the results. Click Set Play > Write Complex to save the results in pdbqt format.
  6. Import the docking files into PyMOL software to construct further visualization.
    1. Select the ligand, and click on Action > Find > Polar Contacts > To Other Atoms in Object to display hydrogen bonds between ligands and the external environment. Click on c to change color.
    2. Click on Action > Extract Object. Click on Show > Sticks to show the stick structure of the receptor. Identify the residues connected to ligands and show the stick structure.
    3. Click on Hide > Sticks to hide the stick structure of the receptor. Click on Wizard > Measurement and click on two atoms in sequence. Click on Label > Residue to show the label of the residues. Adjust the background color and transparency if necessary. Click on File > Export Image as to save the picture.

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Results

Anus eczema-related genes, SDG target genes, and common targets
A total of 958 potential gene candidates were screened in Genecards and 634 in OMIM databases, while duplicates were excluded. To gain a comprehensive understanding of anal eczema-related genes, the findings from multiple databases were amalgamated, yielding a total of 958 distinct genes. Consequently, a protein-protein interaction network (PPI) specific to anal eczema was meticulously formulated. SDG is composed of five traditional Chin...

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Discussion

Atopic dermatitis is a specific form of eczema that shares underlying mechanisms with eczema. Hub genes believed to be related to this condition are TNF, MAPK14, and CASP3. The therapeutic effects of SDG on anal eczema are mainly attributed to its action on the TNF and MAPK signaling pathways via these three hub genes17.

SDG includes five distinct drugs: indigo naturalis, golden cypress, calcined gypsum, calamine, and Chinese Gall. In traditional Chinese medicine, calci...

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Disclosures

The authors have nothing to disclose.

Materials

List of materials used in this article
NameCompanyCatalog NumberComments
AutoDockToolsAutoDockhttps://autodocksuite.scripps.edu/adt/
Cytoscape 3.9.1 Cytoscapehttps://cytoscape.org/
GeneCards database GeneCardshttps://www.genecards.org
GEO databaseNational Center for Biotechnology Informationhttps://www.ncbi.nlm.nih.gov/geo/
GEO2R tool National Center for Biotechnology Informationhttps://ncbi.nlm.nih.gov/geo/geo2r/
MetascapeMetascapehttps://metascape.org/
Online Mendelian inheritance in man databaseOMIMhttps://www.omim.org
RCSB protein database RCSB Protein Data Bank (RCSB PDB)http://www.pdb.org/
STRING database STRINGhttps://string-db.org/
Swiss ADME database Swiss Institute of Bioinformaticshttp://www.swissadme.ch/index.php
Traditional Chinese Medicine system's pharmacology database (TCMSP)Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platformhttp://tcmspw.com/tcmsp.php
Venny2.1BioinfoGPhttps://bioinfogp.cnb.csic.es/tools/venny/index.html

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The Efficacy and Underlying Pathway Mechanisms of ShiDuGao Treatment for Anus Eczema Based on GEO Datasets and Network Pharmacology
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