CN112201365A - Method for analyzing action mechanism of pachyman against glandular cystitis based on network pharmacology - Google Patents
Method for analyzing action mechanism of pachyman against glandular cystitis based on network pharmacology Download PDFInfo
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Abstract
The invention belongs to the field of biomedicine, discloses a method for analyzing an action mechanism of pachyman for resisting glandular cystitis based on network pharmacology, and reports a detailed target point and a specific pharmacology mechanism of pachyman for preventing and treating glandular cystitis for the first time. The method comprises the following steps: analyzing online databases such as TCMSP and DisGeNET to obtain pachyman pharmacological target and glandular cystitis pathogen target; intersecting the pachyman and the glandular cystitis target to obtain a drug-disease intersection target gene target and constructing a related protein interaction network to screen a core target; further utilizing an R language related packet to perform gene ontology GO biological process and KEGG channel enrichment analysis on the core target; and finally, constructing a medicine-target point-gene ontology function-pathway-disease visual map for deep analysis of a treatment mechanism. The method provides a new idea for explaining the research mechanism of the pachyman for resisting the glandular cystitis, and simultaneously provides an early research basis for the clinical application of the pachyman for the glandular cystitis.
Description
Technical Field
The invention relates to the field of biomedicine, in particular to a method for analyzing an action mechanism of pachyman against glandular cystitis based on network pharmacology.
Background
Glandular Cystitis (GC) usually refers to the pathological changes and inflammatory reactions of the bladder and its glands [1 ]. In clinical observation, patients can have pathological features such as hematuria, calculus, urethral pain and the like [2 ]. The pathogenesis of glandular cystitis is currently unknown, and infectious bladder injury and secondary inflammation caused thereby are the major causes of further exacerbation of the disease [3 ]. Clinical diagnosis of patients with early glandular cystitis remains deficient, while accurate screening for the disease in terms of biochemical diagnosis remains inadequate [4 ]. In addition, the treatment of glandular cystitis has limited protocols, and bladder perfusion therapy is commonly performed with anti-infective, anti-inflammatory, etc. [5], but is often accompanied by some adverse reactions such as anaphylaxis, gastrointestinal reactions and drug resistance [6 ]. Therefore, there is an urgent need to develop a novel bioactive composition against glandular cystitis for future clinical treatment.
Poria, a common fungus, has been used as a medicinal food since ancient times in China [7 ]. Notably, this medicinal fungus has potential antibacterial, immune activating effects [8 ]. Pachyman (Pachyman), also known as Pachyman, is a main active ingredient of poria cocos, and has certain pharmacological activity in the adjuvant treatment of cancer, so it is considered that Pachyman can enhance the immunity of the organism [9 ]. Related studies have shown that pachyman can also exert a powerful pharmacological effect by inhibiting inflammatory stress responses of the liver, thereby alleviating drug-induced liver injury in mice [10-11 ].
Network pharmacology is an application tool developed in recent years that can be used to screen candidate genes or targets to study related disease functions and drug treatment mechanisms [12-13 ]. The network pharmacology has the advantages of breaking through the bottleneck of the traditional single-drug and single-target-point drug research and development mode, providing a brand-new multi-drug and multi-target-point interaction drug development new mode and a new idea, improving the current drug research strategy and accelerating the drug discovery process. At present, no report is found about the mechanism of pachyman for resisting glandular cystitis.
In conclusion, the invention researches and develops natural active ingredients by referring to a network pharmacological method, determines related genes of an action mechanism of pachyman for treating the glandular cystitis, so as to research the function and the pharmacological action mechanism of pachyman for resisting the glandular cystitis based on the target spot, and provides important guidance and basis for the development of medicines for resisting the glandular cystitis.
Disclosure of Invention
The invention aims to provide a method for analyzing an action mechanism of pachyman against glandular cystitis based on network pharmacology. Through combining a plurality of network pharmacology databases and carrying out big data analysis, the pachyman target point with potential treatment function is comprehensively screened in the background of the glandular cystitis, ten target points of ALB, VEGFA, TNF, EGF, HRAS, ACE, MMP9, STAT3, ABCB1 and LGALS3 which are not researched in the glandular cystitis before are found, and the regulation potential of the pachyman in the occurrence and development of the glandular cystitis is predicted.
The technical scheme of the invention is as follows:
a method for analyzing an action mechanism of pachyman against glandular cystitis based on network pharmacology comprises the following steps:
s1 screening of active ingredient action targets
Screening criteria were set according to the study objectives. Screening pachyman action Target point with online database (TCMSP, Swiss Target Prediction, BATMAN and HITPICK).
S2 disease candidate target recognition
In the disease target database (DisGeNET, Genecard and Malarard), search for glandular Cystitis candidate targets using "Cystis glandularis" as a keyword. And then carrying out intersection mapping with the component action target obtained in S1 to obtain a component-disease intersection target gene, namely the action target of the pachyman for resisting glandular cystitis.
S3, constructing component target-disease target network and screening core target
And analyzing the intersection target of the S2 by using a STRING database to obtain a target protein interaction network relation graph (PPI network) and tsv data. And (3) analyzing the topological structure characteristic parameters of the network nodes by using cytoscape3.7.1 software, determining the core target screening conditions and carrying out subsequent screening analysis.
S4, enrichment analysis of core target to discuss action mechanism of medicine component
Performing GO biological process and KEGG channel annotation enrichment analysis on a core target by utilizing an R language related packet, outputting a corresponding chart, and analyzing an action mechanism of pachyman for resisting glandular cystitis in a contrast manner.
S5, construction and visualization of 'component-target-pathway-disease' network
Constructing a drug-target-pathway-disease visual graph by using Cytoscape according to the result of S4; the method specifically applies a Pathview package in the R language to map the related target points of the KEGG enrichment channel to a channel map, so as to facilitate subsequent analysis.
In the method, the screening range of the BATMAN database in S1 is score cutoff >20, and P is less than 0.05.
According to the method, the upper limit of the screening range of the core target spot in S3 is the maximum Degree value in the topological data, and the lower limit is the Degree median.
The invention has the beneficial effects that:
(1) a network pharmacological technology is utilized to construct a network diagram of the pachyman for resisting glandular cystitis, namely 'medicinal component-target spot-disease' for the first time, and the network diagram discloses how the active component pachyman can play the medicinal effect of the pachyman through 'multi-target spot, multi-channel and multi-path' combined regulation and control. As a result: the pachyman regulates and controls related inflammatory molecular signal channels to play a role in resisting glandular cystitis through 10 related disease targets such as ALB, VEGFA, TNF and the like. The method provides a new idea for explaining a research mechanism of the pachyman for playing the role of resisting the glandular cystitis, and the biological information of the systems is verified in future research, thereby further providing an early research basis for the prevention and treatment of the glandular cystitis by the pachyman.
(2) The invention networks and systematizes the research method of the drug action diseases, and compared with the traditional research method, the invention reduces the research and development range and realizes the accurate research and development purpose, thereby saving the research and development cost of the drugs. Meanwhile, the efficiency of drug screening and prediction is greatly improved, a new reference is provided for the research and development of other natural active ingredients such as pachyman, and the like, and the method has breakthrough significance for the development and industrialization of rich Chinese medicine resources.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a Venn diagram of the intersection target of pachyman-glandular cystitis
FIG. 2 is a PPI graph of pachyman anti-glandular cystitis target protein. Wherein: circles represent target proteins, with the sides in an interaction relationship.
FIG. 3 is a core-point diagram of pachyman-glandular cystitis
FIG. 4 is a pachyman anti-glandular cystitis GO biological process bubble diagram
FIG. 5 is a bar graph of pachyman anti-glandular cystitis GO biological process
FIG. 6 is a pachyman anti-glandular cystitis KEGG pathway enriched bubble diagram
FIG. 7 is a pachyman anti-glandular cystitis KEGG pathway enrichment histogram
FIG. 8 is a pachyman-target-GO-KEGG-glandular cystitis network relation diagram
FIG. 9 is a flow chart of the steps of the pachyman anti-glandular cystitis study
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further illustrated and described with reference to the accompanying drawings by specific embodiments.
1. Method for analyzing action mechanism of pachyman against glandular cystitis based on network pharmacology
1.1 Pachymaran action target screening
And searching in a TCMSP database by taking the pachyman as a keyword to obtain a pachyman structural formula. The Swiss Target Prediction, the HITPICK database and the BATMAN database input SMILE codes and IMCHI codes corresponding to structural formulas respectively to search for pachyman action targets. Wherein SMILE codes and IMCHI codes are obtained by conversion of ChemDraw software, and the target screening range of the BATMAN database is score cutoff >20 and P < 0.05. A total of 4 databases (TCMSP, Swiss Target Prediction, BATMAN, HITPICK databases) are applied to comprehensively screen the action targets of pachyman. After the repeated target spot is removed, the final pachyman target spot meeting the conditions is obtained through the Uniprot verification of a protein database.
1.2 glandular cystitis candidate target recognition
The method is characterized in that the method takes Cystiis glandularis as a keyword, and uses a DisGeNET database, a Genecard database and a Malarard database to search related disease targets, wherein the Genecard database is screened under the conditions as follows: relevance score > 1. Then, the disease target and the pachyman target obtained in 1.1 are subjected to Venn map mapping intersection treatment by using an online biological tool (http:// bioinformatics. psb. element. be/webtools/Venn /), so as to obtain the pachyman-glandular cystitis intersection target gene.
1.3 construction of pachyman target-glandular cystitis target network and screening of core target
Uploading the 1.2 intersection target genes to a STRING database, searching for Organism, namely Homo sapiens, under the Multiple Proteins item, and setting a minimum required interaction score, namely 0.400, in an analysis page to obtain a target protein interaction network and tsv data. And simultaneously analyzing topological parameters of all nodes in the interaction network by using a network analyzer module in the Cytoscape software, selecting the node connectivity (Degree) and the median of the Degree of freedom as the screening conditions of the core target spot, wherein the upper limit of the screening range is the maximum Degree value in the topological data, the lower limit is the median of the Degree, and the core target spot meeting the conditions is subjected to next analysis.
1.4 enrichment analysis of core target to investigate the mechanism of action of pharmaceutical ingredients
Performing gene body GO biological process and KEGG channel enrichment annotation analysis on the 1.3 core target by using related R packets such as 'ClusterProfiler', 'ReactomePA', 'AnnotationHub' of R language, outputting corresponding bubble diagram and histogram, predicting the function distribution of the target, analyzing the core channel enrichment degree according to enrichment factors, and obtaining key channel information participating in the key core target, thereby analyzing the action mechanism of the pachyman against the glandular cystitis.
1.5 constructing network relationship visualization graph
In order to more visually reflect the relationship among the drugs, the target points, the channels and the diseases, the Cytoscape software is used for connecting the interaction relationship among the drugs, the target points, the diseases and the target points, the core target points and the key enrichment channels, a 'drug-target point-gene body function-channel-disease' relationship network is established, and a network diagram is visually displayed.
2. Results and discussion
2.1 Pachymaran action target screening
The pachyman action Target points are searched by databases such as TCMSP (tcMSP) and Swiss Target Prediction, and 166 pachyman Target points are obtained by repeated screening and correction. See table 1 for details.
TABLE 1 pachyman partial action target information
Tab.1 Part of targets information for pachyman
2.2 glandular cystitis candidate target recognition
A total of 303 glandular cystitis-related genes were collected by the DisGeNET, Genecar and Malarad databases, and 20 component-disease intersection targets were obtained by the mapping process of the letter on-line tool, see FIG. 1.
2.3 construction of pachyman target-glandular cystitis target network and screening of core target
The interaction network of pachyman for treating glandular cystitis target and the function related protein thereof is constructed by using the STRING database, and the result is shown in figure 2. The Cytoscape software introduces an intersection target point, calculates the pachyman-glandular cystitis target point and the topological parameters of a function-related protein interaction network, and obtains a target point Degreee median of 8.4 and a maximum Degreee of 18, so that the core target point screening condition range is set to be 9-18, and finally 10 core target points are obtained, namely ALB, VEGFA, TNF, EGF, HRAS, ACE, MMP9, STAT3, ABCB1 and LGALS 3. Table 2 and figure 3.
TABLE 2 Pachymaran-glandular cystitis core target information
Tab.2 The hub biotargets of information for pachyman against Cystitis glandularis
2.4 enrichment analysis of core targets to investigate the mechanism of action of pharmaceutical ingredients
2.4.1 GO bioprocess analysis
In order to further clarify the biological process of the core targets, 10 core targets are subjected to gene ontology GO enrichment analysis through an R language-related package, the first 10 enrichment channels are listed according to a P-Value and are shown in a table 3, and the specific detailed biological process enrichment results are shown in a table 4 and a table 5.
TABLE 3 GO bioprocess enrichment analysis results for key targets
Table3 GO biological process of hub targets enrichment analyses
As shown in Table 3, pachyman anti-glandular cystitis is involved in many related biological processes, including regulation of peptidyl-tyrosine phosphorylation, positive regulation of peptidyl-tyrosine phosphorylation, myeloid differentiation, negative regulation of hydrolytic activity, positive regulation of MAP kinase activity, and the like.
2.4.2KEGG pathway enrichment analysis
The KEGG channel enrichment analysis indicates that 66 related information channels are related to the pachyman anti-glandular cystitis core target, and according to the P-Value, 10 channels are known to have higher correlation, which is shown in Table 4, and more detailed channels are shown in figures 6 and 7.
TABLE 4 KEGG pathway enrichment analysis results for key targets
Table4 KEGG pathway of hub targets enrichment analyses
As shown in Table 4, other disease pathways involved in core targets include Bladder cancer (Bladder cancer), EGFR tyrosine kinase inhibitor resistance, Proteglycans in cancer, AGE-RAGE signaling pathway in diabetic compositions (AGE-RAGE signaling pathway changes in diabetic complications), MicroRNAs in cancer (microRNA changes in cancer), Hepatitis C (Hepatitis C), Hepatitis B (Hepatitis B), Non-small cell cancer, Pancreatic cancer, Human cytomegalovirus infection, and the like.
2.5 constructing network relationship visualization graphs
Analysis of experimental data was followed by "pachyman-target-GO-KEGG-glandular cystitis" network visualization, with results as shown in fig. 8, which consists of 52 "nodes" (1 active ingredient pachyman, 1 glandular cystitis disease, 10 core targets, 20 GO bioprocesses and 20 KEGG-related pathways) and multiple "edges": pachyman is Pachyman, Cystis glanduris is glandular Cystitis, a triangle of a middle ring is a core target spot, 20 rectangles on the left side are used for a GO biological process, 20 rectangles on the right side are used for KEGG related channels, and the sides represent the interaction relation between a drug-target spot-gene body function-channel-disease. The pachyman and the glandular cystitis respectively correspond to 10 target points, each target point is connected with a plurality of biological processes and passages, the mechanism that the pachyman plays a role in resisting the glandular cystitis through multiple target points is embodied, and simultaneously, each independent biological process and passage are connected into a network through a common target point, so that the pachyman is further explained to play a role in resisting the glandular cystitis by depending on multiple passages.
3. Discussion of the related Art
The invention utilizes the network pharmacology bioinformatics technology and combines experimental data to respectively analyze the candidate target point, the biological function and the molecular action way of the active component-disease, and finally determines the main core targets of the pachyman for resisting glandular cystitis, including 10 target points of ALB, VEGFA, TNF, EGF, HRAS, ACE, MMP9, STAT3, ABCB1 and LGALS 3. VEGFA is reported to be a transmembrane glycoprotein that, when stimulated by the cell's external environment, activates several key signaling cascades, such as the MAPK signaling pathway [14 ]. Furthermore, transactivation of VEGFA may trigger stress-induced inflammation [15 ]. Proinflammatory family TNF, such as TNF- α and IL-1 β, may be involved in intracerebral inflammation induced by pneumococcal meningitis [16 ]. Epidermal growth factor EGF is a functional hormone that promotes the proliferation of epidermal and epithelial tissues and some fibroblasts [17 ]. STAT3 is a nuclear phosphorylated protein whose function is associated with the regulation of specific gene expression in cell proliferation and differentiation in tissues. It is also commonly used as a DNA damage sensor for identifying genotoxic stress and cellular necrosis [18-19 ]. ABCB1 is essentially a cysteine protease that mediates TNF signaling pathways leading to activation of apoptosis-related proteases [20-21 ]. So far, there are no relevant reports on the relationship between ALB, HRAS, ACE, ABCB1, LGALS3 and glandular cystitis. Under the combined action of bioinformatics data and enrichment analysis, the invention discloses a gene target, a biological process and a pharmacological path involved in the pachyman anti-glandular cystitis, and is characterized by having specific inhibition effect on signal pathways related to cell necrosis and inflammation.
4. Conclusion
In summary, the network pharmacological technology can be used for researching the candidate and core target, biological process and molecular action mechanism of pachyman for resisting glandular cystitis. The invention discloses a core target of pachyman for resisting glandular cystitis for the first time, which comprises a plurality of new targets for resisting glandular cystitis: ALB, HRAS, ACE, ABCB1, LGALS 3.
It should be understood that the above embodiments are only for understanding the technical solution and the core principle of the present invention, and are not to be construed as limiting the scope of the present invention. For those skilled in the art, the conditions and parameters of the present embodiment can be changed according to the needs based on the core principle of the present invention, but these equivalent changes and modifications still belong to the protection scope of the present invention.
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Claims (3)
1. A method for analyzing the action mechanism of pachyman against glandular cystitis based on network pharmacology is provided. The method is characterized by comprising the following steps:
s1 screening of active ingredient action targets
Screening criteria were set according to the study objectives. Screening pachyman action Target point with online database (TCMSP, Swiss Target Prediction, BATMAN and HITPICK).
S2 disease candidate target recognition
In the disease target database (DisGeNET, Genecard and Malarard), search for glandular Cystitis candidate targets using "Cystis glandularis" as a keyword. And then carrying out intersection mapping with the component action target obtained in S1 to obtain a component-disease intersection target gene, namely the action target of the pachyman for resisting glandular cystitis.
S3, constructing component target-disease target network and screening core target
And analyzing the intersection target of the S2 by using a STRING database to obtain a target protein interaction network relation graph (PPI network) and tsv data. And (3) analyzing the topological structure characteristic parameters of the network nodes by using cytoscape3.7.1 software, determining the core target screening conditions and carrying out subsequent screening analysis.
S4, enrichment analysis of core target to discuss action mechanism of medicine component
Performing GO biological process and KEGG channel annotation enrichment analysis on a core target by utilizing an R language related packet, outputting a corresponding chart, and analyzing an action mechanism of pachyman for resisting glandular cystitis in a contrast manner.
S5, construction and visualization of 'component-target-pathway-disease' network
Constructing a drug-target-pathway-disease visual graph by using Cytoscape according to the result of S4; the method specifically applies a Pathview package in the R language to map the related target points of the KEGG enrichment channel to a channel map, so as to facilitate subsequent analysis.
2. The method of claim 1, wherein the BATMAN database screening threshold in S1 is score cutoff >20, P < 0.05.
3. The method of claim 1, wherein the core target screening range in S3 has an upper limit of a maximum Degree value in the topology data and a lower limit of a median Degree value.
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