Pharmacology and molecular docking-based core target spot screening method for stomach disease anti-inflammation of licorice compound
The screening of core targets related to gastritis by network pharmacology and molecular docking technology of licorice compounds has solved the problem of difficulty in effective screening in the existing technology, and the key targets and mechanisms of licorice compounds in the treatment of gastritis were discovered, which has improved the efficacy and research depth of licorice in the treatment of gastritis.
Patent Information
- Application Number
- CN202411643122.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-18
- Publication Date
- 2025-04-08
AI Technical Summary
The prior art is difficult to effectively screen the core targets of licorice compounds for gastric disease, which affects the research on the efficacy and mechanism of licorice in the treatment of gastritis.
Using a method based on network pharmacology and molecular docking technology, the core targets related to licorice compounds and gastritis are screened, and the potential role between the target and the compound is predicted and verified by building a ‘drug-component-target’ network.
The key targets and main mechanisms of licorice compounds in the treatment of gastritis were successfully discovered, and the binding activity of the compound uralenin and AKT1 was verified, providing new ideas and clinical applications based on the anti-inflammatory mechanism of licorice.
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Abstract
Description
Technical Field
[0001] The invention relates to a method for docking and screening traditional Chinese medicine molecules, and in particular to a method for screening core targets of liquorice compounds for gastric disease anti-inflammatory effects based on pharmacology and molecular docking. Background Art
[0002] Gastritis refers to inflammatory lesions of the gastric mucosa. It is one of the most common diseases of the digestive system and can be divided into acute gastritis, chronic gastritis and special types of gastritis. The occurrence of gastritis is often closely related to stress, infection, drugs, immunity, physical and chemical factors. And the causes of different types are different. Acute gastritis is often caused by stress, drugs, alcohol and trauma; chronic gastritis may be related to Helicobacter pylori infection, autoimmunity, duodenal-gastric reflux and other factors; different special types of gastritis may be caused by different causes, and some causes are unknown. Due to social competition and changes and influences in dietary structure, the incidence of gastric disease in today's society is as high as 80%. Acute and chronic gastritis are the most common types of gastric diseases, among which the incidence of chronic gastritis (about 50%) ranks first among various gastric diseases. Traditional Chinese medicine has the advantages of obvious improvement of clinical symptoms and excellent efficacy in the treatment of stomach medicine.
[0003] Licorice is a perennial herbaceous plant of the Leguminosae family, known as Guolao, sweet grass, and Ural licorice. Licorice is sweet and flat in nature, and has the functions of replenishing qi and deficiency, relieving cough and expectoration, clearing away heat and detoxifying, moistening dryness and relieving pain, and harmonizing various medicines. Domestic and foreign scholars have conducted a lot of research on the components of licorice. Its main active ingredients are flavonoids, terpenes, polysaccharides, amino acids, alkaloids, lignins and coumarins. Qizhi Weitong Granules have a definite effect on the treatment of gastric diseases, and are widely used in the clinical treatment of chronic gastritis, gastric ulcers, and promoting gastric motility. Modern research shows that Qizhi Weitong Granules may mainly alleviate the pathological symptoms of chronic gastritis and gastric ulcers by inhibiting secondary inflammatory reactions and inhibiting the conduction of peripheral nerve endings. Among them, licorice is the main drug in this prescription, which plays the role of relieving pain, clearing away heat and detoxifying, and harmonizing various medicines. Among them, the important components of licorice that play an anti-inflammatory role include flavonoid compounds, coumarin compounds, triterpenoid saponins and triterpenoid aglycone compounds.
[0004] Network pharmacology combines multiple disciplines such as computer analysis, bioinformatics, and pharmacology. It constructs an interaction network to analyze the relationship between various compounds and core targets in the network to show the mechanism of drug treatment of diseases.
[0005] Molecular docking is a method of drug design based on the characteristics of receptors and the interaction between receptors and drug molecules. It is a theoretical simulation method that mainly studies the interaction between molecules (such as ligands and receptors) and predicts their binding mode and affinity. The two major topics of molecular docking are spatial recognition and energy recognition between molecules. Spatial matching is the basis for the interaction between molecules, and energy matching is the basis for the stable binding between molecules. Summary of the invention
[0006] The purpose of the present invention is to provide a method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking. The present invention screens the key compounds and core targets of licorice based on network pharmacology, and predicts and verifies the potential interaction between the target and the compound through molecular docking technology. The online database is comprehensively used to collect licorice targets for treating gastritis, and a "drug-ingredient-target" PPI network for licorice to treat gastritis is constructed. Using multiple data analysis software, the potential therapeutic targets of licorice for treating gastritis are explored from the molecular level, providing a reference basis and new ideas for the further clinical application of the anti-inflammatory mechanism of licorice.
[0007] The objective of the present invention is achieved through the following technical solutions: The present invention provides a method for screening key compounds and core targets of licorice based on network pharmacology and molecular docking, and predicting and verifying the potential interaction between the target and the compound by molecular docking technology to study its anti-inflammatory mechanism, comprising the following steps: (1) Use the database to search and screen the chemical components and targets of licorice.
[0008] (2) Search and screen disease targets using the keyword “gastritis”.
[0009] (3) Intersecting the compound targets described in step (1) and the disease targets described in step (2) to obtain potential targets of licorice compounds for treating gastritis.
[0010] (4) Import the intersection targets of the two into the String database, create a PPI network of interactions between potential targets, and obtain core targets.
[0011] (5) Construct a “drug-ingredient-target” network diagram visualization to obtain key compounds.
[0012] (6) Obtain the three-dimensional structures of the core targets in the core targets and the key compounds in the licorice compounds for molecular docking, determine the binding sites and optimal binding energy, and predict the main compounds in the licorice compounds for treating gastritis.
[0013] Preferably, the liquorice compound is obtained from TCMSP, Swiss ADME database Preferably, the licorice target acquisition method is the Swiss Target Prediction platform Preferably, the gastritis targets are obtained from GeneCards database, DrugBank database, and TTD database.
[0014] Preferably, the potential targets are obtained by drawing a Venn diagram and taking the intersection.
[0015] Preferably, GO enrichment analysis and KEGG enrichment analysis are performed on the potential targets described in step (3) to obtain the molecular mechanism of licorice in treating gastritis.
[0016] Preferably, the analysis software used in step (4) and step (5) is Cytoscape 3.7.1 Preferably, the software used for molecular docking in step (6) is Autodock Vina, Pymol, or DiscoveryStudio.
[0017] The advantages and effects of the present invention are: The present invention provides a method for screening key compounds and core targets of licorice based on network pharmacology, and predicting and verifying the potential effects between targets and compounds through molecular docking technology. The present invention utilizes the cross-integration of network pharmacology and molecular docking technology, and uses computer-assisted preliminary research on the anti-inflammatory mechanism of licorice in the research process. By constructing a complex biological network model, the key action targets and main action mechanisms of licorice in treating gastritis are visually revealed, and it is found that licorice acts on core targets such as AKT1, TNF, MMP9, STAT3, EGFR, NFKB1, BCL2, PTGS2, PPARG, TLR4, etc. Molecular docking technology verifies that the binding energy of uralenin, a licorice compound, and the core target of AKT1 is low, and has good binding activity. The present invention focuses on the mechanism of action of a main component in licorice compounds for treating gastritis, based on the cross-integration of multiple disciplines such as network pharmacology, traditional Chinese medicine, and computer-assisted drug design, and uses computer-assisted research in the research process. The use method of the present invention is conducive to studying the relationship between drug action targets and action mechanisms, and provides an innovative research idea for studying Chinese medicine compound prescriptions. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] Figure 1 A Venn diagram of potential targets of the liquorice compound in Example 1 for treating gastritis; Figure 2 is a PPI network diagram of the interaction between potential target proteins in Example 1; Figure 3This is a potential target map of the licorice compound in Example 1 for treating gastritis; Figure 4 is the network diagram of “drug-ingredient-target” in Example 1; Figure 5 It is a bar graph of the GO enrichment analysis results in Example 1; Figure 6 It is a bubble chart of the KEGG enrichment analysis results in Example 1; Figure 7 This is a visualization analysis diagram of the molecular docking results of the core target AKT1 in Example 1 and the top ten key compounds. DETAILED DESCRIPTION
[0019] The present invention provides a method for screening key anti-inflammatory compounds and core targets of licorice, the main drug of Qizhi Weitong granules, based on network pharmacology and molecular docking technology, comprising the following steps: Search and collect active ingredients in licorice to establish a compound library The targets and disease targets of licorice compounds were obtained using an online database. The intersection of the two was taken after screening and deduplication. The obtained intersection targets were the potential targets of licorice compounds in the treatment of gastritis.
[0020] The above potential targets were imported into the String database to obtain the PPI network diagram. The analysis results were exported and the network topology analysis was performed using Cytoscape software to obtain the core targets.
[0021] Construct a PPI network diagram of "drug-ingredient-target" and perform visual analysis to obtain key compounds.
[0022] GO enrichment analysis and KEGG enrichment analysis were performed on the potential targets described in step (2) to obtain the molecular mechanism of licorice compounds in treating gastritis.
[0023] The protein structure of the core target in the core target is obtained, and molecular docking is performed with the three-dimensional structure of the key compound described in step (4) to determine its binding site and optimal binding energy, so as to verify the network pharmacology prediction of the main active ingredients in licorice compounds for the treatment of gastritis.
[0024] The present invention first obtains the compounds in licorice and the target of action of the licorice compounds In the present invention, the licorice compound is preferably obtained through the TCMSP database and the Swiss ADME platform.
[0025] In the present invention, the target of the licorice compound is preferably obtained through the Swiss Target Prediction platform.
[0026] In the present invention, the target sites of the licorice compound are preferably screened, integrated and duplicates are removed.
[0027] In the present invention, the gastritis target is preferably obtained through GeneCards database, Drugbank database, and TTD database.
[0028] In the present invention, the gastritis targets are preferably screened, integrated and duplicates are removed.
[0029] The present invention obtains the potential target of the licorice compound for treating gastritis by drawing a Venn diagram to obtain the intersection of the target of the licorice compound and the target of gastritis.
[0030] The present invention imports the potential targets into the String database to obtain a PPI network diagram, exports the analysis results and performs network topology analysis on them to obtain core targets.
[0031] After the potential targets obtained in the present invention are imported into the String database, Homosapiens is selected for Organisms, and the rest are set as default parameters to obtain a PPI network diagram of target protein interactions and perform network topology analysis.
[0032] The present invention uses the licorice compound, potential action targets and licorice to establish a type file for network topology analysis, visualizes the network diagram of the drug-ingredient-target, and obtains the key compound.
[0033] The present invention preferably performs GO enrichment analysis and KEGG enrichment analysis on the potential action targets to obtain the molecular mechanism of licorice compounds in treating gastritis.
[0034] The network topology analysis software used in the present invention is preferably Cytoscape 3.7.1 The GO enrichment analysis and KEGG enrichment analysis described in the present invention are preferably performed using the DAVID database.
[0035] The software for molecular docking and its visualization analysis used in the present invention is preferably Autoduck vina, Pymol, Discovery Studio.
[0036] The specific process of molecular docking described in the present invention is preferably to use the PDB database to search for the 3D structure of the core target and import it into Pymol for processing; then use the 3D structure of the above key compound, and finally import the two into Autodock Tools for molecular docking, and use Discovery Studio to visualize and analyze the docking results.
[0037] The technical solutions provided by the present invention will be described in detail below in conjunction with the embodiments, but they should not be understood as limiting the protection scope of the present invention. Example 1
[0038] This example provides a method for screening the key anti-inflammatory compounds and core targets of the main drug of Qizhi Weitong Granule, Licorice, based on network pharmacology and molecular docking technology. The specific process is as follows: (1) The chemical components of licorice were searched based on the TCMSP database and screened based on the principles of oral availability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18. A total of 92 licorice chemical components were obtained. The chemical components were further screened using the Linpinski five principles in the Swiss ADME platform, and 72 compounds were finally obtained.
[0039] (2) The smile numbers of the above 72 compounds were searched in PubChem, and they were imported into the Swiss TargetPrediction platform for target prediction. The threshold P≧0.1 was set. After screening, integration and deduplication, 511 targets of licorice compounds were finally obtained.
[0040] (3) Using “gastritis” as the keyword, we searched the GeneCards database, DrugBank database, and TTD database, and after screening and removing duplicates, we obtained 477 disease targets related to gastritis.
[0041] (4) Import compound targets and disease targets into the Venny platform to draw a Venn diagram, such as Figure 1 As shown, a total of 77 intersection targets were obtained, and the intersection targets are the potential targets of licorice compounds in treating gastritis.
[0042] (5) The 77 potential targets were imported into the String database, Homosapiens was selected for Organisms, and the rest were set to default parameters to obtain the PPI network diagram of the potential target interactions, as shown in the figure: Figure 2 As shown in the figure, the network has 77 nodes, 766 edges, and an average degree of 8.2. The more edges a node is connected to, the higher the degree, and the more important its role in the network. Except for F13A1, CCR4, ACVR1, and CCKBR, other proteins have good interactions.
[0043] (6) The analysis results were exported to TSV format and the network topology analysis was performed using Cytoscape software. The results are as follows: Figure 3As shown in the figure, the size and color of the nodes in the figure represent the target degree. The larger the node, the darker the color, and the larger the degree. According to the degree value, the targets with higher degree values are likely to be core targets. The top ten targets are predicted as core targets, and the target with the first degree value is predicted as a core target, as shown in Table 1.
[0044] Table 1 Core targets of licorice compounds in treating gastritis Gene Degree AKT1 55 TNF 54 EGFR 48 MMP9 48 STAT3 48 NFKB1 46 BCL2 45 PTGS2 43 PPARG 40 TLR4 38 (7) 72 licorice compounds, 77 potential targets and licorice were used to create a type file, which was imported into Cytoscape software for topological analysis to visualize the drug-ingredient-target network diagram, such as Figure 4 As shown in Figure 2, the graph has 15 nodes and 61 connection paths, where brown-red triangles represent drugs, diamond nodes represent targets, and circular nodes represent compounds. The larger the node, the darker the color, and the greater its degree value. The compounds are sorted according to the degree value. The higher the degree value, the more important the role of the compound in the network. The top ten compounds with the highest degree value are selected as key compounds, as shown in Table 2.
[0045] Table 2 Key compounds in licorice for treating gastritis Serial number Key compounds Degree GC68 uralenin 21 GC3 3-hydroxyglabrol 20 GC15 genistein 19 GC17 glabridin 19 GC37 kumatakenin A 19 GC38 kumatakenin B 19 GC4 3-methylkaempferol 18 GC42 licoflavone A 18 GC61 Neouralenol 18 GC66 Topazolin 18 (8) The DAVID database was used to perform GO enrichment analysis on the intersection targets, and a total of 542 results were obtained, including 426 biological processes (BP), 44 cellular components (CC), and 72 molecular functions (MF). The results were sorted from small to large according to the P value, and the top ten results of each item were selected and imported into the microbial information platform to draw a bar chart, as shown in Figure 2. Figure 5Among them, the biological processes are mainly enriched in negative regulation of apoptotic process, phosphorylation, inflammatory response, positive regulation of cell migration, positive regulation of smooth muscle cell proliferation, muscle cell proliferation, protein phosphorylation, response to xenobiotic stimulation, positive regulation of cell population proliferation, positive regulation of peptidyl-serine phosphorylation and other processes. Among the cellular components, the greatest correlation was with the extracellular region, receptor complex, plasma membrane, cell surface, extracellular space, collagen-containing extracellular matrix, extracellular matrix, cytoplasm, perinuclear region of cytoplasm, and mitochondria.In terms of molecular function, it is related to protein tyrosine kinase activity, identical protein binding, protein homodimerization activity, enzyme binding, ATP binding, protein kinase activity, heme binding, endopeptidase activity, protein phosphatase binding, and oxidoreductase activity.
[0046] (9) According to the results of KEGG enrichment analysis, the intersection targets were involved in 84 signal pathways. The top 20 signal pathways were selected and imported into the microbial information platform to draw a bubble chart, as shown in Figure 1. Figure 6 The size of the bubble point is related to the number of core targets in the pathway. The larger the point, the more core targets are enriched in the pathway. The color of the bubble represents the size of the p value. (10) The redder the color, the smaller the p-value, and the greener the color, the larger the p-value. The top 20 signaling pathways involve multiple related pathways such as inflammation, metabolism, and tumors. Among them, the main pathways involved in inflammation are EGFR tyrosine kinase inhibitor resistance, PI3K-Akt signaling pathway, HIF-1 signaling pathway, gastric cancer, lipid and atherosclerosis, and microRNAs in cancer.
[0047] (11) In order to verify the prediction that the compounds in licorice can effectively treat gastritis, the present invention will use molecular docking technology. The core target AKT1 in Table 1 is selected as the receptor protein, and the three-dimensional structure of the receptor protein is obtained using the PDB database and saved in pdb. format. The 2D structures of the key compounds in Table 2 are obtained in the pubchem database, and they are converted into 3D structures using Chem3D software and saved in mol2. format. The 3D structure of the target protein AKT1 and the 3D structures of the 10 key compounds are successively imported into Autodock Tools for molecular docking, and the docking results are visualized and analyzed using Discovery Studio software. The analysis results are shown in FIG. Figure 7 The binding energy and the number of hydrogen bonds between the target and the compound are calculated to determine which compound binds most tightly to the core target. The calculation results are shown in Table 3.
[0048] (12) The smaller the binding energy between the ligand and the receptor, the tighter the binding, and the greater the possibility of interaction between the two. Molecular docking results show that the licorice compound ulralenin can bind tightly to the amino acid residues LYS-158 and ALA-230 of the core target AKT1 through hydrogen bonds. The binding energy between the compound ulralenin and the target protein AKT1 is the smallest, indicating that the two are most tightly bound. Therefore, it can be inferred that the compound ulralenin is more likely to play a major role in the treatment of gastritis with licorice.
[0049] Table 3 Molecular docking results of key compounds and core target AKT1 (PDB ID: 4GV1) Serial number Compound Name Optimal binding energy / (Kcal / mol) Number of hydrogen bonds Binding site amino acid residue 1 uralenin -9.5 2 LYS-158 ,ALA-230 2 Glabridin -9.0 1 PHE-236 3 licoflavone A -8.6 1 LYS-179 4 genistein -8.5 3 GLU-228 ,ALA-230 ,LYS-158 5 3_hydroxyglabrol -8.3 2 ASN-279, LYS-276 6 kumatakenin A -8.1 3 GLU-198 ,GLY-311 ,GLY-294 7 kumatakenin B -7.7 3 GLY-162, LYS-179, PHE-161 8 3_methylkaempferol -7.7 4 GLY-162,PHE-161,LYS-179,ASP-274 9 Topazolin -7.7 1 GLU-278 10 Neouralenol -7.6 5 GLY-311, PHE-161, GLY-162, LYS-179, LYS-276 The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.
Claims
1. A method for screening the core target of licorice compounds for gastric anti-inflammatory effects based on pharmacology and molecular docking, characterized in that: The method comprises the following steps: (1) Obtaining the target sites of licorice compounds; (2) Obtain disease targets for gastritis; (3) Intersecting the action targets described in step (1) and the disease targets described in step (2) to obtain potential action targets of licorice for treating gastritis; (4) Import the obtained intersection targets into the String database, select Homo sapiens for Organisms, and set the rest to default parameters to obtain the PPI network diagram. Export the analysis results to TSV format and use Cytoscape software to perform network topology analysis to obtain the core targets; (5) Establish a compound library of licorice. Use the compound library, intersection targets and licorice to create a type file, import it into Cytoscape software for topological analysis, visualize the drug-ingredient-target network diagram, and obtain key compounds; (6) performing GO enrichment analysis and KEGG enrichment analysis on the potential targets and key compounds described in step (3); Through GO analysis, we can obtain the biological processes, cell components, and molecular functions of the core targets. Through KEGG analysis, we can obtain the signal pathways related to inflammation involved in the core targets, so as to obtain the molecular mechanism of licorice in treating gastritis. (7) Obtain the three-dimensional structures of the core targets in the core targets and the key compounds in the licorice compounds for molecular docking, determine the binding sites and optimal binding energy, and verify the network pharmacology prediction of the main compounds in the licorice compounds for treating gastritis by molecular docking technology.
2. The method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking according to claim 1, characterized in that: The licorice compound in step (1) is obtained from TCMSP and Swiss ADME databases.
3. The method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking according to claim 1, characterized in that: The target of licorice described in step (1) is obtained by using the Swiss Target Prediction platform.
4. The method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking according to claim 1, characterized in that: The disease targets of gastritis described in step (2) are obtained from GeneCards database, DrugBank database, and TTD database.
5. The method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking according to claim 1, wherein the method in step (3) is characterized in that: The intersection target point is obtained by drawing a Venn diagram and taking the intersection.
6. The method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking according to claim 1, characterized in that: The Cytoscape software described in step (4) performs network topology analysis.
7. The method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking according to claim 1, characterized in that: Topological analysis was performed in the Cytoscape software described in step (5).
8. The method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking according to claim 1, characterized in that: The String database described in step (6) was used for GO enrichment analysis and KEGG enrichment analysis.
9. The method for screening the core target of licorice compounds for gastric disease anti-inflammatory based on pharmacology and molecular docking according to claim 1, characterized in that: The Autodock vina described in step (7) performs molecular docking.