An analysis method for the mechanism of action of Tianma III formula in the treatment of colorectal cancer

Abstract

An analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer, including: (1) screening disease targets of colorectal cancer; (2) retrieving the drug composition of Tianma III formula to obtain the targets of the effective active ingredients of Tianma III formula; (3) taking the intersection to obtain the intersection targets; (4) constructing a "component-target-disease" co-expression network diagram and multiple protein-protein interaction network diagrams to obtain potential core targets; performing GO and KEGG pathway enrichment analysis on the intersection targets; performing molecular docking on the potential core targets and key compound molecules; verifying in vitro that Tianma III formula inhibits the proliferation of colorectal cancer cells and promotes apoptosis; verifying the effect of Tianma III formula on the mRNA expression level of potential core targets by real-time fluorescence quantitative method. The method of the present invention is comprehensive in analysis, has less error, high prediction speed and efficiency, reduces the costs of drug screening and development, provides a scientific basis for the prevention and treatment of colorectal cancer, and provides reference value for the research of other compound formulas.

Description

Technical Field

[0001] The present invention relates to a method for analyzing the mechanism of action of a drug in treating cancer, and specifically to a method for analyzing the mechanism of action of Tianma III formula in treating colorectal cancer. Background Art

[0002] It is of great practical significance to clarify the molecular mechanism of the occurrence and development of colorectal cancer (CRC) and to find drugs with significant curative effects, low prices, and few toxic and side effects.

[0003] Tianma III formula is a new traditional Chinese medicine formula based on traditional Chinese medicine theory and combined with modern medical research, mainly used to treat specific types of tumors or related diseases.

[0004] Network pharmacology refers to the use of high-throughput technology, systems biology technology, and network analysis technology under the guidance of multi-omics technology. By constructing the relationships among drug components, targets, diseases, and pathways, the mechanism of action between drugs and diseases is determined. The research methods of traditional Chinese medicine and network pharmacology are compatible. By combining the two, it provides a strong guarantee and new ideas for studying the mechanism of action and scientific connotation of traditional Chinese medicine and its compound prescriptions.

[0005] Currently, the methods for screening disease targets in the prior art are mostly limited to obtaining data from one or two databases, and there are significant differences in data sources, update frequencies, and the scope of disease targets covered by these databases. For example, CN117352045A discloses a method for analyzing the molecular mechanism of action of Xinmaishu No. 1 oral liquid in treating heart disease, which screens the treatment targets of heart disease by using the Gene Cards database; CN117409854A discloses a method for analyzing the mechanism of action of chrysin in treating colorectal cancer based on network pharmacology and molecular docking, which selects the GEO, DisGENET, PharmGkb, and TTD databases to screen the targets of colorectal cancer. However, due to the data inconsistency and incomplete coverage between these databases, the colorectal cancer genes obtained by the above methods are not comprehensive. The former only uses a single database, Gene Cards. Although the latter selects more databases, there is still a problem of incomplete coverage, especially the largest disease target database, GeneCards, is not included, and the screening results of the GEO database may have large errors due to the selection of different datasets. In addition, the screening results of the GEO database may have large errors due to the selection of different datasets, increasing the uncertainty of the analysis. Therefore, the existing methods not only have defects in coverage, but also are prone to instability of screening results due to internal and cross-database differences.

[0006] Therefore, in view of the incomplete selection of existing disease targets, it is urgent to find an analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer, which has a comprehensive analysis system, less analysis error, high prediction speed and efficiency, reduces the costs of drug screening and development, provides a scientific basis for the prevention and treatment of colorectal cancer, and provides reference value for the research of other compound prescriptions. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to overcome the above-mentioned defects existing in the prior art and provide an analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer, which has a comprehensive analysis system, less analysis error, high prediction speed and efficiency, reduces the costs of drug screening and development, provides a scientific basis for the prevention and treatment of colorectal cancer, and provides reference value for the research of other compound prescriptions.

[0008] The technical solution adopted by the present invention to solve its technical problems is as follows: An analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer, comprising the following steps:

[0009] (1) First, screen colorectal cancer disease targets from multiple databases respectively, and then delete the duplicate values of the colorectal cancer disease targets obtained from the above-mentioned multiple databases to obtain the screened colorectal cancer disease targets;

[0010] (2) First, retrieve the drug composition of Tianma III formula through multiple databases to obtain the effective active ingredients and their targets respectively, and then integrate and delete the duplicate values of the effective active ingredients and their targets obtained from the above-mentioned multiple databases to obtain the targets of the effective active ingredients of Tianma III formula;

[0011] (3) Take the intersection of the screened colorectal cancer disease targets obtained in step (1) and the targets of the effective active ingredients of Tianma III formula obtained in step (2) to obtain the intersection targets;

[0012] (4) Construct a "component-target-disease" co-expression network diagram of Tianma III formula in treating colorectal cancer for the colorectal cancer disease targets obtained in step (1) and the active ingredients and their targets of Tianma III formula obtained in step (2) to obtain co-expression targets; perform protein-protein interaction analysis on the co-expression targets to obtain multiple protein-protein interaction network diagrams, and further use plug-in analysis to obtain the potential core targets of Tianma III formula in treating colorectal cancer;

[0013] Analysis method 1: First, transform the intersection targets obtained in step (3) into target IDs, then perform GO and KEGG pathway enrichment analysis on the transformed IDs, and further perform visual analysis on the KEGG enrichment network relationship;

[0014] Analysis method 2: Perform molecular docking on the 3D structure of the potential core targets obtained in step (4) and the key compound molecules, and visualize the docking results;

[0015] Analysis method three: in vitro experiments were used to verify the inhibitory effect of Tianma III prescription on the proliferation of colorectal cancer cells and its promoting effect on the apoptosis of colorectal cancer cells;

[0016] Analysis method four: real-time fluorescence quantitative method was used to verify the effect of Tianma III prescription on the mRNA expression levels of the potential core targets obtained in step (4).

[0017] The inventive concept of the method of the present invention is as follows: the core of the method of the present invention lies in comprehensively utilizing multiple disease target databases and network pharmacology means to systematically screen the active ingredients and targets in Tianma III prescription that have potential effects on colorectal cancer; through cross-validation and integrated analysis of multiple databases, the problems of incomplete information or large deviations in a single database can be overcome, ensuring more comprehensive and accurate target data; combined with network pharmacology tools, a multi-level network of compound components-targets-pathways can be constructed to systematically analyze the pharmacological action pathways of Tianma III prescription. In order to determine whether this combined analysis method is close to the real biological mechanism, the present invention further verifies it through in vitro experiments; in vitro experiments can verify whether the inhibitory effect of the prescription on colorectal cancer cells at the cellular level is consistent with the targets and pathways predicted by network pharmacology analysis, so that the accuracy of theoretical analysis can be supported and verified by experimental data, making the revealed mechanism closer to the real biological process. Therefore, through comprehensive analysis and experimental verification of the synergistic effects of multiple targets, multiple pathways, and multiple approaches, the method of the present invention can effectively reveal the real mechanism of Tianma III prescription in inhibiting colorectal cancer and improve the scientificity and credibility of mechanism research.

[0018] Preferably, in step (1), the databases include: TCGA, GEO, GeneCards, OMIM, PharmGkb, TTD, and DisGeNET, etc. Compared with the databases selected in the prior art, the method of the present invention significantly differs from the prior art research that only integrates one or more databases by comprehensively integrating the disease target data of TCGA, GEO, and the other five databases (GeneCards, OMIM, PharmGkb, TTD, and DisGeNET) for the first time. This integration not only introduces high-quality patient sample data but also enhances the ability to compare cross-platform data, promoting the understanding of disease mechanisms and the efficiency of target identification. In addition, the analysis technology combining multiple data sources not only contributes to basic research but also can promote the development of clinical applications.

[0019] Preferably, the screening method for the TCGA database is as follows: Download the RNA sequencing data of colorectal cancer patients from the TCGA database, process the transcriptome data using Perl scripts, convert it into gene symbols, extract mRNA data, and further use Log |FC|≥1 and adjP≤0.05 as screening criteria. Through R language analysis, differentially expressed disease targets are obtained. The method of the present invention first collects TCGA data as network pharmacology disease data.

[0020] Preferably, the screening method for the GEO database is as follows: In the GEO database, use "colorectal cancer" as the search term to obtain the GSE37364 dataset, download the gene expression data of normal adjacent tissues and tumor tissues. When further grouping through Perl software and analyzing with R language, use Log |FC|≥1 and adjP≤0.05 as screening criteria to obtain the differentially expressed genes in the tissues of colorectal cancer patients, and use the up-regulated genes and down-regulated genes among them as potential disease targets of GEO.

[0021] Preferably, the screening method for the GeneCards, OMIM, PharmGkb, TTD, or DisGeNET database is as follows: In the above five databases, use "colorectal cancer" as the search term respectively, and use the R language Venn package to take the union of the relevant genes obtained from the five databases to obtain the colorectal cancer disease targets respectively.

[0022] Preferably, in step (2), the database includes one or more of the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, CNKI Database, Wanfang Database, VIP Database, Chinese Biomedical Literature Database, PubChem Database, or PubMed Database, etc.

[0023] Preferably, in step (2), retrieve using oral bioavailability≥30% and drug similarity≥0.18 as filtering criteria.

[0024] Preferably, in step (2), the drug composition of Tianma III Prescription is: Pinellia ternata, Hedyotis diffusa, Scutellaria barbata, Sparganium stoloniferum, Sargassum, Astragalus membranaceus, and Rheum palmatum.

[0025] Preferably, in step (2), use Perl scripts to integrate and delete the duplicate values of the effective active ingredients and their targets obtained from the above multiple databases.

[0026] Preferably, in step (3), use the R language Venn package to take the intersection.

[0027] Preferably, in step (4), the construction refers to: integrating and classifying the effective active ingredients, their targets, and the targets of colorectal cancer diseases of Tianma III formula into genome, type group, and network relationship files through Perl scripts, and integrating the above groups using Cytoscape software.

[0028] Preferably, in step (4), the co-expressed targets are analyzed for protein-protein interaction through the STING database, with the species information in the settings selected as human and the unconnected nodes hidden.

[0029] Preferably, in step (4), the cytoHubba plugin of Cytoscape software is used for analysis.

[0030] Preferably, in step (4), the top 5 in the centrality Degree analysis ranking are taken as potential core targets.

[0031] Preferably, in analysis method 1, the intersection targets obtained in step (3) are transformed for target IDs using the R language org.hs.eg package.

[0032] Preferably, in analysis method 1, the clusterProfiler, DOSE, and enrichment plot packages are used with a screening condition of p < 0.05 to perform GO and KEGG pathway enrichment analysis on the transformed IDs.

[0033] Preferably, in analysis method 1, the KEGG enrichment network relationship is further visually analyzed using Cytoscape software. Visual analysis of the KEGG enrichment network using Cytoscape software can identify key targets and the interactions between different pathways, revealing the complex biological regulatory mechanism of Tianma III formula in treating colorectal cancer. By analyzing the nodes in the network, the targets with the most significant impact on specific biological processes can be determined. At the same time, the topological structure of the network shows the relationships between signaling pathways, helps to locate functional modules, discovers potential biomarkers for Tianma III formula in treating colorectal cancer, and provides new hypotheses for subsequent research.

[0034] Preferably, in the second analysis method, the 3D structures of the potential core targets obtained in step (4) are downloaded from the Pubchem database. The AutoDockTools 1.5.6 software is used to remove the crystal water and the original ligands in the protein receptor from the protein and perform hydrogenation on the receptor protein. Then, the AutoDock Vina 1.1.2, Pymol 2.1, and Discovery studio V2019 software are used to perform molecular docking between the 3D structures of the potential core targets and the key compound molecules. The docking results are evaluated based on the binding free energy to assess the binding degree with the key compound molecules. The binding affinity between the potential core targets and the key compounds is evaluated. The redder the color, the more stable the binding. In addition, compounds with high affinity for the core targets can be screened out through the docking results to help identify potential drug candidate molecules.

[0035] Preferably, in the second analysis method, the key compound molecules include one or more of quercetin, luteolin, kaempferol, wogonin, baicalein, or beta sitosterol, etc. The number of key compounds screened can be determined by oneself. For example, the method of the present invention selects the top six in terms of the content of active ingredients.

[0036] Preferably, in the second analysis method, the visualization includes: visualizing the binding free energy through a heat map using the R language pacman package, and visualizing the docking modes between the potential core targets obtained in step (4) and the key compound molecules respectively.

[0037] Preferably, in the third analysis method, the CCK8 method is used to verify the inhibitory effect of Tianma III formula on the proliferation of colorectal cancer cells. Verifying the inhibitory effect of Tianma III formula on the proliferation of colorectal cancer cells by the CCK8 method can quantitatively evaluate its anti-cancer activity, including the inhibitory effect and dose-dependence. The experimental results will reveal that Tianma III formula shows significant inhibition of cell proliferation and provide a preliminary basis for its potential as a therapeutic drug. In addition, this study can provide further support for exploring its mechanism of action and help understand the biological pathways through which it inhibits cell proliferation.

[0038] Preferably, the CCK8 method is specifically as follows: The colorectal cancer cells are seeded at a density of 1×10 3 ~10×10 3Cells were inoculated on a 96-well plate at a density of [number of cells] / well and divided into multiple groups with the preset concentrations of Tianma III prescription-containing serum ranging from 0% to 20%. Each group had 4 to 6 replicate wells. After overnight culture, grouping interventions were carried out according to the preset concentrations of the drug-containing serum. After 20 to 28 hours of intervention, CCK8 solution prepared with complete medium was added at 80 to 120 μL / well. Then, it was incubated for 1 to 2 hours at 35 to 39 °C and 4 to 6% CO2. Subsequently, the absorbance values at 450 nm were analyzed respectively, and the mean value of the replicate wells within the group was taken.

[0039] Preferably, in analysis method three, flow cytometry was used to verify the promotion of apoptosis of colorectal cancer cells by Tianma III prescription. Verifying the promoting effect of Tianma III prescription on colorectal cancer cell apoptosis by flow cytometry can quantitatively evaluate the percentage and type of cell apoptosis, and reveal its pro-apoptotic effect. This analysis can show a significant increase in the apoptosis rate of cells after treatment with Tianma III prescription, provide preliminary clues to relevant signaling pathways, and lay a foundation for further exploring its mechanism of action. These results contribute to establishing the potential application value of Tianma III prescription in the treatment of colorectal cancer.

[0040] Preferably, the specific flow cytometry method is as follows: Colorectal cancer cells and negative control group cells were intervened with Tianma III prescription-containing serum at gradient concentrations from 0% to 20% for 20 to 28 hours. After that, the intervened colorectal cancer cells and negative control group cells were washed 2 to 3 times with pre-cooled PBS respectively. Then, 180 to 220 μL of 1× Annexin V binding solution was added to resuspend the cells respectively, and the concentration was adjusted to 1×10 6 ~5×10 6 cells / mL. Then, 8 to 12 μL of Annexin V-FITC staining solution was added to the cell suspension, gently mixed, and incubated for 5 to 10 minutes at 3 to 5 °C in the dark. Finally, 8 to 12 μL of PI staining solution was added, gently mixed, and incubated for 5 to 10 minutes at 3 to 5 °C in the dark. Immediately, it was detected by flow cytometry.

[0041] Preferably, the pretreatment method of the negative control group cells is as follows: Cells were digested with trypsin and washed with PBS. Then, they were centrifuged at 35 to 39 °C and 800 to 1200 rpm / min for 8 to 12 minutes to collect the trypsin-digested cells.

[0042] Preferably, in analysis method three, the colorectal cancer cells include one or several of HCT116, SW480, DLD1, SW620, HT29, etc.

[0043] Preferably, in the fourth analysis method, the specific method for verifying by real-time fluorescence quantitative method is as follows: Collect the colorectal cancer cells after the intervention of Tianma III prescription obtained by the third analysis method, extract total RNA using Trizol, and further perform reverse transcription reaction according to the cDNA reverse transcription kit. The total reaction system volume is 18 - 22 μL, and pre-denaturation treatment is carried out at 23 - 27 °C for 8 - 12 min. The amplification conditions are: at 93 - 97 °C, react for 25 - 35 s, and at 55 - 65 °C, anneal for 25 - 35 s for 35 - 45 cycles; Take β-actin as the internal reference gene, and use the 2-ΔΔCt method to analyze the relative expression level of mRNA. By verifying the intervention effect of Tianma III prescription on colorectal cancer cells by real-time fluorescence quantitative method, the relative expression levels of mRNA of BCL2, JUN, Caspase3, XIAP, and Caspase9 after intervention can be quantitatively analyzed. The results will reveal the influence of Tianma III prescription on the expression of specific genes, provide important information for understanding its anti-cancer mechanism, and help identify potential biomarkers. Since β-actin has a stable expression level in various cell types and different treatment conditions and is not affected by experimental conditions, β-actin is selected as the internal reference gene.

[0044] The beneficial effects of the method of the present invention are as follows: The method of the present invention makes full use of bioinformatics methods and computer technology, for the first time combines seven disease-related databases to obtain targets, reduces the subsequent analysis errors caused by imperfect screening, demonstrates new research means, and for the first time constructs a "component-target-disease" network diagram of Tianma III prescription for treating colorectal cancer, indicating that the process of its exerting pharmacodynamic effects involves multiple processes, mainly involving multiple targets such as BCL2, JUN, Caspase3, XIAP, and Caspase9, and the main pathways include multiple pathways such as PI3K-Akt, IL-17, TNF, MAPK, p53, cellular senescence and apoptosis, etc. The core compounds playing roles include quercetin, luteolin, kaempferol, wogonin, baicalein, and β-sitosterol, etc. It provides a new research idea for exploring the mechanism of action of Tianma III prescription in inhibiting colorectal cancer, and combined with experimental verification, systematically and comprehensively reveals the mechanism of Tianma III prescription in inhibiting colorectal cancer through "multiple targets, multiple pathways, and multiple ways" synergistic effects. It not only improves the prediction speed and efficiency, but also reduces the costs of drug screening and development. These results will be further verified in subsequent studies, thus providing a scientific basis for the prevention and treatment of colorectal cancer, and at the same time providing reference value, as well as new ideas and insights for the research of other compound prescriptions.

[0045] Abbreviation Explanation in the Present Invention: CRC: Colorectal Cancer; TMⅢ: Tianma Ⅲ Formula; ID: Identity Identification Number; Degree: Degree Value; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; TCGA: The Cancer Genome Atlas; GEO: Gene Expression Omnibus; GeneCards: Human Genome Database; OMIM: Online Mendelian Inheritance in Man; PharmGkb: Pharmacogenomics Knowledge Base; TTD: Therapeutic Target Database; DisGeNET: Disease Gene Network Database; Perl: Practical Extraction and Report Language; Log |FC|: Logarithm of Fold Change; adjP: Adjusted P - value; TCMSP: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform; Pubchem: PubChem; PubMed: NCBI PubMed Biomedical Information Retrieval Platform; STING: Stimulator of Interferon Genes; CCK8: Cell Counting Kit - 8; 2 - ΔΔCt method: 2 to the negative power of ΔΔCt method; β - actin: β - Actin; BP: Biological Process; CC: Cellular Component; MF: Molecular Function; PI3K - Akt: Phosphatidylinositol 3 - kinase - Protein Kinase B Pathway; IL - 17: Interleukin - 17; TNF: Tumor Necrosis Factor; MAPK: Mitogen - Activated Protein Kinase; P53: Tumor Suppressor Gene P53; BCL2: B - cell lymphoma 2; JUN: JUN Protein; Caspase3 (CASP3): Caspase 3; XIAP: X - linked inhibitor of apoptosis protein; Caspase9 (CASP9): Caspase 9; PBS: Phosphate Buffered Saline. Brief Description of the Drawings

[0046] Figure 1 It is the mRNA heat map of differentially expressed disease targets of colorectal cancer screened from the TCGA database in step (1) of Example 1 of the present invention;

[0047] Figure 2 It is the volcano plot of differentially expressed genes in the tissues of colon cancer patients screened from the GSE37364 dataset of the GEO database in step (1) of Example 1 of the present invention;

[0048] Figure 3 It is the heat map of differentially expressed genes in the tissues of colon cancer patients screened from the GSE37364 dataset of the GEO database in step (1) of Example 1 of the present invention;

[0049] Figure 4 It is the Venn diagram of the union of colorectal cancer disease targets obtained from five databases in step (1) of Example 1 of the present invention;

[0050] Figure 5It is the Venn diagram of the intersection targets between the colorectal cancer disease targets and the effective active ingredient targets of Tianma III Prescription in step (3) of Embodiment 1 of the present invention;

[0051] Figure 6 It is the "ingredient-target-disease" co-expression network diagram of Tianma III Prescription in treating colorectal cancer obtained in step (4) of Embodiment 1 of the present invention;

[0052] Figure 7 It is multiple protein-protein interaction network diagrams obtained in step (4) of Embodiment 1 of the present invention;

[0053] Figure 8 It is the potential core targets of Tianma III Prescription in treating colorectal cancer obtained in step (4) of Embodiment 1 of the present invention;

[0054] Figure 9 It is the bubble chart of GO pathway enrichment analysis of the intersection targets obtained in step (3) of Analysis Method 1 in Embodiment 1 of the present invention;

[0055] Figure 10 It is the KEGG pathway enrichment analysis and target network diagram of the intersection targets obtained in step (3) of Analysis Method 1 in Embodiment 1 of the present invention;

[0056] Figure 11 It is the heat map visualization diagram of the binding free energy of molecular docking in Analysis Method 2 of Embodiment 1 of the present invention;

[0057] Figure 12 It is the visualization conformation diagram of the molecular docking mode of BCL2 and luteolin in Analysis Method 2 of Embodiment 1 of the present invention;

[0058] Figure 13 It is the visualization conformation diagram of the molecular docking mode of Caspase3 and luteolin in Analysis Method 2 of Embodiment 1 of the present invention;

[0059] Figure 14 It is the visualization conformation diagram of the molecular docking mode of Caspase3 and β-sitosterol in Analysis Method 2 of Embodiment 1 of the present invention;

[0060] Figure 15 It is the visualization conformation diagram of the molecular docking mode of Caspase3 and quercetin in Analysis Method 2 of Embodiment 1 of the present invention;

[0061] Figure 16 It is the visualization conformation diagram of the molecular docking mode of JUN and luteolin in Analysis Method 2 of Embodiment 1 of the present invention;

[0062] Figure 17 It is the visualization conformation diagram of the molecular docking mode of XIAP and luteolin in Analysis Method 2 of Embodiment 1 of the present invention;

[0063] Figure 18 It is a line graph showing the verification of the inhibitory effect of Tianma III Prescription on the proliferation of colorectal cancer cells by the CCK8 method in the third analysis method of Example 1 of the present invention;

[0064] Figure 19 It is a flow cytometry graph showing the verification of the promotion of apoptosis of colorectal cancer cells by Tianma III Prescription by flow cytometry in the third analysis method of Example 1 of the present invention;

[0065] Figure 20 It is a bar graph of relative expression showing the verification of the effect of Tianma III Prescription on the mRNA level of the potential core targets obtained in step (4) by real-time fluorescence quantitative method in the fourth analysis method of Example 1 of the present invention. Detailed implementation manners

[0066] The present invention will be further described below in conjunction with examples and drawings.

[0067] The drug composition of Tianma III Prescription used in the examples of the present invention is: Pinellia ternata, Hedyotis diffusa, Scutellaria barbata, Sparganium stoloniferum, Sargassum, Astragalus membranaceus, and Rheum officinale, purchased from the Affiliated Hospital of Hunan Academy of Chinese Medicine; the raw materials or chemical reagents used in the examples of the present invention are obtained through conventional commercial channels without special instructions.

[0068] Reference Example 1 for the preparation method of freeze-dried powder of Tianma III Prescription

[0069] Add 10 g of Rhizoma Pinelliae Praeparatum, 20 g of Hedyotis diffusa, 20 g of Scutellaria barbata, 10 g of Sparganium stoloniferum processed with vinegar, 10 g of Sargassum, 30 g of Astragalus membranaceus, and 10 g of Rheum officinale, a total of 110 g, add 15 times the amount of water, decoct for 1.5 h, filter while it is hot, add 12 times the amount of water to the filter residue, decoct for 1 h, filter while it is hot, combine the filtrates, concentrate to a small volume, and freeze-dry to obtain the extract powder of Tianma III Prescription, and store it under room temperature and dry conditions.

[0070] Reference Example 2 for the preparation method of drug-containing serum of Tianma III Prescription

[0071] Thirty SPF-grade male SD rats were evenly divided into a medicated serum group of 20 rats and a blank serum group of 10 rats; the dose of Tianma III formula was equivalent to the dose for a 70-kg adult. According to the human-animal body surface area conversion (human-animal body surface area conversion is used to convert the drug dose in animal experiments into human doses, which ensures a reasonable physiological basis for the derivation of drug doses from animal models to humans. Through this conversion, the effective drug dose in animal experiments can be obtained corresponding to the appropriate human dosage, ensuring the safety and effectiveness of subsequent dosages), distilled water was used to prepare the concentration of Tianma III liquid medicine as 0.24 g of Tianma III formula extract powder / mL, the gavage dose was 12.5 mL / kg, twice a day, and continuous gavage was carried out for 7 days. The blank group was given distilled water by gavage, and the gavage dose, frequency, and number of days were the same; 2 hours after gavage on the 7th day, abdominal aortic blood was collected, left to stand at room temperature for 2 hours, centrifuged, serum was extracted, the complement was inactivated by water bath at 56°C for 30 minutes, filtered and sterilized with a 0.2-μm microporous filter membrane, then aliquoted and stored at -80°C.

[0072] Example 1

[0073] (1) First, colorectal cancer disease targets were screened from the TCGA, GEO, GeneCards, OMIM, PharmGkb, TTD, and DisGeNET databases respectively:

[0074] The screening method for the TCGA database was as follows: Download the sequencing data of colorectal cancer RNA patients from the TCGA database (https: / / portal.gdc.cancer.gov), process the transcriptome data using Perl scripts, convert it into gene symbols, and extract mRNA data. Further, with Log |FC|≥1 and adjP≤0.05 as the screening conditions, 3,681 differentially expressed disease targets were obtained through R language analysis, among which 2,180 were up-regulated genes and 1,501 were down-regulated genes, and an mRNA heat map was drawn, as Figure 1 shown; through screening, not only the changes in gene expression were intuitively displayed, but also it was helpful to identify potential biomarkers and therapeutic targets, indicating that there were significant gene expression differences in colorectal cancer;

[0075] The screening method for the GEO database is as follows: In the GEO database (https: / / www.ncbi.nlm.nih.gov / gds / ), using "colorectal cancer" as the search term for colon cancer, the GSE37364 dataset is obtained, and the gene expression data of normal adjacent tissues and tumor tissues are downloaded. This method ensures the pertinence of the research and the reliability of the data. Further, when grouping by Perl software and analyzing with R language, with Log |FC|≥1 and adjP≤0.05 as the screening conditions, it indicates that the screened genes have significant expression differences (Log |FC| represents fold change, and adjP is the corrected P-value, ensuring that the screening results have statistical significance). 31,290 differentially expressed genes in the tissues of colon cancer patients are obtained, among which, 5,736 are up-regulated genes and 4,625 are down-regulated genes, and a volcano plot of differentially expressed genes (as shown in Figure 2 ) and a gene heatmap (as shown in Figure 3 ) are drawn; the volcano plot of differentially expressed genes shows the number and distribution of up-regulated and down-regulated genes, while the gene heatmap further demonstrates the expression patterns of these genes in different samples; taking the 5,736 up-regulated genes and 4,625 down-regulated genes, a total of 10,361 genes, as potential disease targets of GEO. Through this screening method, the study identified a large number of differentially expressed genes related to CRC, and these genes may play a key role in the occurrence, development of tumors and their differences from normal tissues. The screened genes are helpful for subsequent functional studies to further understand the molecular mechanism of Tianma III formula in treating CRC;

[0076] The screening method for the GeneCards, OMIM, PharmGkb, TTD or DisGeNET database is as follows: In the GeneCards (https: / / www.genecards.org / ), OMIM (https: / / www.omim.org / ), PharmGkb (https: / / www.pharmgkb.org / ), TTD (https: / / db.idrblab.net / ttd / ) and DisGeNET (https: / / www.disgenet.org / ) databases, using "colorectal cancer" as the search term for colon cancer respectively, the relevant genes obtained from the five databases are respectively taken as the union through the R language Venn package. 12,054 colorectal cancer disease targets are obtained from the GeneCards database, 411 from the OMIM database, 287 from the PharmGkb database, 99 from the TTD database, and 5,473 from the DisGeNET database;

[0077] Then, the duplicate values of the colorectal cancer disease targets obtained from the above seven databases were removed, resulting in 18,480 screened colorectal cancer disease targets, as Figure 4 shown; this method ensured the comprehensive screening of relevant genes from multiple authoritative databases, providing a broad library of potential targets for colorectal cancer for subsequent research and analysis;

[0078] (2) First, through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, https: / / old.tcmsp-e.com / tcmsp.php), CNKI Database, Wanfang Database, VIP Database, China Biology Medicine Database, PubChem Database, and PubMed Database, with the oral bioavailability ≥ 30% and drug similarity ≥ 0.18 as the filtering conditions, the drug components of Tianma III Formula were retrieved: Pinellia ternata, Hedyotis diffusa, Scutellaria barbata, Sparganium stoloniferum, Sargassum fusiforme, Astragalus membranaceus, and Rheum palmatum, and the effective active ingredients and their targets were obtained respectively. A total of 94 chemical active ingredients were collected, among which there were 13 for Pinellia ternata, 7 for Hedyotis diffusa, 29 for Scutellaria barbata, 5 for Sparganium stoloniferum, 4 for Sargassum fusiforme, 20 for Astragalus membranaceus, and 16 for Rheum palmatum. Then, the duplicate values of the effective active ingredients and their targets obtained from the above six databases were integrated and removed through Perl scripts, resulting in 190 effective active ingredient targets of Tianma III Formula;

[0079] The acquisition of the above effective active ingredient targets was obtained by predicting and screening the targets of the 94 collected chemical active ingredients; the targets corresponding to each drug's effective active ingredient can be obtained through literature retrieval and database queries (such as TCMSP, PubChem, etc.); finally, the targets of all drug effective active ingredients were integrated and duplicates were removed, resulting in 190 effective active ingredient targets. The data volume is large and cannot be fully displayed, but this step was completed through standardized script data processing, ensuring the accuracy and integrity of the targets;

[0080] (3) The 18,480 screened colorectal cancer disease targets obtained in step (1) and the 190 effective active ingredient targets of Tianma III Formula obtained in step (2) were intersected using the R language Venn package, resulting in 181 intersection targets, as Figure 5 shown, which indicates that the active ingredients of Tianma III Formula play a potential therapeutic role in colorectal cancer through these intersection targets;

[0081] (4)Integrate and classify the effective active ingredients of Tianma III formula, their targets, and the targets of colorectal cancer disease into genomic, type group, and network relationship files through Perl scripts, and integrate the above groups using Cytoscape software (http: / / www.cytoscape.org / ). Construct the "ingredient-target-disease" co-expression network diagram of Tianma III formula for treating colorectal cancer between the colorectal cancer disease targets obtained in step (1) and the active ingredients and their targets of Tianma III formula obtained in step (2), as Figure 6 shown. The co-expressed targets are Figure 6 The middle rectangular part is obtained by integrating the overlapping parts of the colorectal cancer disease targets and the active ingredient targets of Tianma III formula. These targets refer to the genes with intersections between the two. The circular nodes of different colors represent different drug compositions and colorectal cancer disease targets. Among them, blue represents Pinellia ternata, red represents Hedyotis diffusa, green represents Scutellaria barbata, purple represents Sparganium stoloniferum, blue-green represents Sargassum, orange represents Astragalus membranaceus, rose red represents Rheum palmatum. The connecting lines in the network represent the connection relationships between the active ingredients of these drugs and the co-expressed targets, showing the potential interactions and action mechanisms between each drug and the colorectal cancer-related targets;

[0082] Perform protein-protein interaction analysis on the co-expressed targets through the STING database (https: / / cn.string-db.org / ), select the species information as human in the settings, and hide the unconnected nodes to obtain multiple protein-protein interaction network diagrams, as Figure 7 shown. This diagram shows the interaction relationships between these targets, reveals their synergistic effects or potential regulatory networks in cells, shows the key targets with strong associations, and indicates that these proteins play important roles in the treatment of colorectal cancer by Tianma III formula;

[0083] Further use the cytoHubba plugin of Cytoscape software for analysis, select the top 5 in the centrality Degree analysis ranking, and obtain the potential core targets BCL2, JUN, Caspase3 (CASP3), XIAP, and Caspase9 (CASP9) of Tianma III formula for treating colorectal cancer, as Figure 8 shown. The redder the color of the rectangular box, the higher the possibility of this gene as a core target, indicating that it has higher centrality and importance in the network.

[0084] Analysis method 1: First, use the org.hs.eg package in R language to convert the intersection targets obtained in step (3) into target IDs, and then use the clusterProfiler, DOSE, and enrichment plot packages to perform GO (gene ontology) and KEGG (Kyoto encyclopedia of genes and genomes) pathway enrichment analysis on the converted IDs with a screening condition of p < 0.05;

[0085] As Figure 9 shown, through GO analysis, 2615 related entries are obtained. Among them, there are 2283 biological process (BP) related entries, 110 cell component (CC) related entries, and 220 molecular function (MF) related entries. The bubble chart shows the top ten expressions of BP, CC, and MF. Among them, the bubble color is related to the corrected P value, and the smaller the value, the redder the color. The bubble size is proportional to the enrichment number; BP is mainly reflected in aspects such as reactive oxygen species, oxidative stress, and oxygen metabolism; CC is mainly reflected in various membranes such as the cytoplasm and the outer mitochondrial membrane; MF is mainly reflected in transcription factors, indicating that these entries play an important role in the treatment of colorectal cancer by Tianma III formula;

[0086] Further use Cytoscape software to perform visual analysis on the KEGG enrichment network relationship. The KEGG pathway enrichment analysis and the target network diagram are as Figure 10 shown. Among them, 37 related entries are obtained by KEGG enrichment. The expression levels of the targets and pathways are proportional to the size of the icons. The connecting lines represent the correlation between the two, indicating the association between the targets and the pathways, indicating that some targets play a regulatory role in multiple signaling pathways; the red rectangles represent the targets, indicating the potential core targets identified in the study, and these targets are closely related to the disease or specific biological processes; the orange V shapes represent the pathway expression levels, representing the enrichment results of the KEGG pathways, and the size of the pathways is proportional to the expression level, meaning that the higher the expression level, the more important the pathway is in the biological process; the main pathway-related enrichments obtained include PI3K-Akt, IL-17, TNF, MAPK, p53, cell senescence and apoptosis, etc., indicating that these pathways are closely related to the functions of the targets, and these signaling pathways play important roles in various pathophysiological states such as cancer, cell damage, and metabolic regulation; the association between the targets and the pathways not only reflects the regulatory network at the molecular level but also reveals the regulatory role of the targets in important signaling pathways, which has important guiding significance for understanding the disease mechanism and discovering potential therapeutic targets.

[0087] Analysis method 2: Download the 3D structures of the potential core targets BCL2, JUN, Caspase3, XIAP, and Caspase9 obtained in step (4) through the Pubchem database (https: / / pubchem.ncbi.nlm.nih.gov / ). Use the AutoDockTools 1.5.6 software to remove the crystal water and the original ligands in the protein receptor from the protein, and perform hydrogenation operations on the receptor protein. Then, use the AutoDock Vina 1.1.2, Pymol 2.1, and Discovery studio V2019 software (Dassault Systemes Biovia, San Diego, CA, USA) to perform molecular docking of the 3D structures of the potential core targets with the key compound molecules quercetin, luteolin, kaempferol, wogonin, baicalein, and β-sitosterol. The docking results are evaluated based on the binding free energy, with the higher the binding free energy indicating a stronger binding to the key compound molecule; use the R language pacman package to visualize the binding free energy through a heat map, as Figure 11 shown; visualize the docking modes of the potential core targets obtained in step (4) with the key compound molecules, which are the docking of BCL2 with luteolin molecule (as Figure 12 shown), the docking of Caspase3 with luteolin molecule (as Figure 13 shown), the docking of Caspase3 with β-sitosterol molecule (as Figure 14 shown), the docking of Caspase3 with quercetin molecule (as Figure 15 shown), the docking of JUN with luteolin molecule (as Figure 16 shown), the docking of XIAP with luteolin molecule (as Figure 17 shown); through the heat map of the binding free energy of molecular docking, select the core targets with higher binding free energy for docking with the key compounds; the selection of different targets and compounds is based on their molecular structure and functional compatibility. At the same time, the difference in the binding free energy between different targets and compounds reflects their interaction affinity. Therefore, the binding free energy can help explain why certain compounds are selected for docking with specific targets; evaluate the binding affinity between the potential core targets and the key compounds. The redder the color, the more stable the binding. It can be seen that quercetin and Caspas9 bind most stably, followed by luteolin and Caspas3; in addition, through the docking results, compounds with high affinity for the core targets can be screened out, helping to identify potential drug candidate molecules as quercetin, luteolin, kaempferol, wogonin, baicalein, and β-sitosterol.

[0088] Analysis method 3: The CCK8 method was used to verify the inhibitory effect of Tianma III formula on the proliferation of colorectal cancer cells. Specifically, HCT116, HT29, SW480, SW620, and DLD1 colorectal cancer cells were seeded in 96-well plates at a density of 5×10 3 cells / well and divided into six groups with the preset concentrations of Tianma III formula-containing serum being 0%, 2.5%, 5%, 10%, 15%, and 20% respectively. Each group had 5 replicate wells. After overnight culture, the groups were intervened according to the preset concentrations of the drug-containing serum. After 24 hours of intervention, CCK8 solution prepared with complete medium was added at 100 μL / well. Then, the cells were incubated at 37°C and 5% CO2 for another 2 hours. After that, the absorbance values at 450 nm were analyzed using a Bio-Tek microplate reader. The mean value of the replicate wells within each group was taken. As Figure 18 shown, the results indicated that the higher the concentration of Tianma III formula-containing serum, the stronger the inhibitory effect on the proliferation of multiple strains of intestinal cancer cells;

[0089] Flow cytometry was used to verify the promotion of apoptosis of colorectal cancer cells by Tianma III formula. Specifically, HCT116 and SW480 colorectal cancer cells and negative control group cells were intervened with Tianma III formula-containing serum at gradient concentrations of 0, 10%, 15%, and 20% for 24 hours. The intervened colorectal cancer cells and negative control group cells were washed twice with pre-cooled PBS respectively, and then 220 μL of 1× Annexin V binding solution was added to resuspend the cells. After adjusting the concentration to 1×10 6 cells / mL, 10 μL of Annexin V-FITC staining solution was added to the cell suspension. After gently mixing, the cells were incubated at 4°C in the dark for 10 minutes. Finally, 10 μL of PI staining solution was added, and after gently mixing, the cells were incubated at 4°C in the dark for 5 minutes. Then, they were immediately detected using a flow cytometer. The pretreatment method for the negative control group cells was as follows: The cells were digested with trypsin and washed with PBS, centrifuged at 36°C and 1000 rpm / min for 10 minutes, and the trypsin-digested cells were collected. As Figure 19 shown, the results indicated that with the increase in the concentration of Tianma III formula, the apoptosis ratio of the two strains of intestinal cancer cells also increased continuously.

[0090] Analysis method 4: The real-time fluorescence quantitative method was used to verify the effect of Tianma III prescription on the mRNA expression levels of the potential core targets obtained in step (4). The specific method was as follows: The HCT116 colorectal cancer cells intervened by Tianma III prescription obtained in analysis method 3 were collected, and total RNA was extracted using Trizol. Further, reverse transcription reaction was carried out according to the cDNA reverse transcription kit. The total reaction system volume was 20 μL, and pre-denaturation treatment was carried out at 25 °C for 10 min. The amplification conditions were: at 95 °C for 30 s, and 40 cycles of annealing at 60 °C for 25 s; β-actin was used as the internal reference gene, and the 2-ΔΔCt method was used to analyze the relative expression level of mRNA; as Figure 20 shown, the mRNA results showed that the expression levels of BCL2 and JUN were lower than those of the control group (p < 0.05), and the expression levels of Caspase3, XIAP and Caspase9 were higher than those of the control group (p < 0.05); these results indicated that Tianma III prescription could effectively regulate the expression of genes related to the core targets in colorectal cancer cells, mainly inhibiting the expression of oncogenes BCL2 and JUN, and promoting the mRNA expression of tumor suppressor genes Caspase3, XIAP and Caspase9, thereby inhibiting the progression of colorectal cancer.

Claims

1. An analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer, characterized in that, It includes the following steps: (1) First, screen colorectal cancer disease targets from multiple databases respectively, and then delete the duplicate values of the colorectal cancer disease targets obtained from the above multiple databases to obtain the screened colorectal cancer disease targets; The databases include: TCGA, GEO, GeneCards, OMIM, PharmGkb, TTD, and DisGeNET; The screening method for the TCGA database is as follows: Download the sequencing data of colorectal cancer RNA patients from the TCGA database, process the transcriptome data using Perl scripts, convert it into gene symbols, extract mRNA data, and further use Log |FC|≥1 and adjP≤0.05 as the screening conditions, and analyze through R language to obtain differentially expressed disease targets; The screening method for the GEO database is as follows: In the GEO database, use "colorectal cancer" as the search term to obtain the GSE37364 dataset, download the gene expression data of normal adjacent tissues and tumor tissues, and further use Perl software for grouping and R language analysis. When using Log |FC|≥1 and adjP≤0.05 as the screening conditions, obtain the differentially expressed genes in the tissues of colorectal cancer patients, and use the up-regulated genes and down-regulated genes among them as the potential disease targets of GEO; (2) First, retrieve the drug composition of Tianma III Formula through multiple databases to obtain the effective active ingredients and their targets respectively, and then integrate and delete the duplicate values of the effective active ingredients and their targets obtained from the above multiple databases to obtain the targets of the effective active ingredients of Tianma III Formula; (3) Take the intersection of the screened colorectal cancer disease targets obtained in step (1) and the targets of the effective active ingredients of Tianma III Formula obtained in step (2) to obtain the intersection targets; (4) Construct a "component-target-disease" co-expression network diagram of Tianma III Formula for treating colorectal cancer with the colorectal cancer disease targets obtained in step (1) and the active ingredients and their targets of Tianma III Formula obtained in step (2) to obtain co-expression targets; Perform protein-protein interaction analysis on the co-expression targets to obtain multiple protein-protein interaction network diagrams, and further use plug-in analysis to obtain the potential core targets of Tianma III Formula for treating colorectal cancer; The construction refers to: Integrate and classify the effective active ingredients and their targets of Tianma III Formula and colorectal cancer disease targets into genome, type group, and network relationship files through Perl scripts, and integrate the above groups using Cytoscape software; Perform protein-protein interaction analysis on the co-expression targets through the STING database, select human species information in the set conditions, and hide the unconnected nodes; Use the cytoHubba plug-in of Cytoscape software for analysis; Select the top 5 in the centrality Degree analysis ranking as potential core targets; Analysis method 1: First, convert the intersection targets obtained in step (3) into target IDs, and then perform GO and KEGG pathway enrichment analysis on the converted IDs, and further perform visual analysis on the KEGG enrichment network relationship; Analysis method 2: Perform molecular docking on the 3D structures of the potential core targets obtained in step (4) and the key compound molecules, and visualize the docking results; Analysis method 3: Use in vitro experiments to verify the inhibition of colorectal cancer cell proliferation and the promotion of colorectal cancer cell apoptosis by Tianma III formula; use the CCK8 method to verify the inhibition of colorectal cancer cell proliferation by Tianma III formula; use flow cytometry to verify the promotion of colorectal cancer cell apoptosis by Tianma III formula; Analysis method 4: Use real-time fluorescence quantitative method to verify the effect of Tianma III formula on the mRNA expression levels of the potential core targets obtained in step (4).

2. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 1, wherein In step (1), the screening method for the GeneCards, OMIM, PharmGkb, TTD, or DisGeNET database is as follows: In the above five databases, use "colorectal cancer" as the search term respectively, and take the union of the relevant genes obtained from the five databases through the R language Venn package to obtain the colorectal cancer disease targets respectively.

3. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 1 or 2, characterized in that, In step (2), the database includes one or more of the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, CNKI Database, Wanfang Database, VIP Database, Chinese Biomedical Literature Database, PubChem Database, or PubMed Database; retrieve with the filtering conditions of oral bioavailability ≥ 30% and drug similarity ≥ 0.18; the drug composition of Tianma III formula is: Pinellia ternata, Hedyotis diffusa, Scutellaria barbata, Sparganium stoloniferum, Sargassum, Astragalus membranaceus, and Rheum palmatum; use Perl script to integrate and delete the duplicate values of the effective active ingredients and their targets obtained from the above multiple databases.

4. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 1 or 2, characterized in that In step (3), take the intersection through the R language Venn package.

5. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 3, wherein In step (3), take the intersection through the R language Venn package.

6. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 1 or 2, characterized in that, In analysis method 1, use the R language org.hs.eg package to convert the intersection targets obtained in step (3) into target IDs; use the clusterProfiler, DOSE, and enrichment plot packages to perform GO and KEGG pathway enrichment analysis on the converted IDs with the screening condition of p < 0.05; further use Cytoscape software to perform visual analysis on the KEGG enrichment network relationship.

7. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 3, wherein, In analysis method 1, use the R language org.hs.eg package to convert the intersection targets obtained in step (3) into target IDs; use the clusterProfiler, DOSE, and enrichment plot packages to perform GO and KEGG pathway enrichment analysis on the converted IDs with the screening condition of p < 0.05; further use Cytoscape software to perform visual analysis on the KEGG enrichment network relationship.

8. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 4, characterized in that, In analysis method one, the R language org.hs.eg package is used to convert the intersection target points obtained in step (3) into target IDs; the clusterProfiler, DOSE, and enrichment plot packages are used to perform GO and KEGG pathway enrichment analysis on the converted IDs with the screening condition of p < 0.05; and the Cytoscape software is further used to visually analyze the KEGG enrichment network relationship.

9. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 1 or 2, characterized in that In analysis method two, the 3D structures of the potential core target points obtained in step (4) are downloaded from the Pubchem database. The AutoDockTools 1.5.6 software is used to remove the crystal water and the original ligands in the protein receptor and perform hydrogenation on the receptor protein. Then, the AutoDock Vina 1.1.2, Pymol 2.1, and Discovery studio V2019 software are used to perform molecular docking on the 3D structures of the potential core target points and the key compound molecules. The docking results are evaluated by the level of the binding free energy as the degree of binding to the key compound molecules; the key compound molecules include one or several of quercetin, luteolin, kaempferol, wogonin, baicalein, or β-sitosterol; the visualization includes: using the R language pacman package to visualize the binding free energy through a heat map, and visualizing the docking modes of the potential core target points obtained in step (4) and the key compound molecules respectively.

10. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 3, characterized in that, In analysis method two, the 3D structures of the potential core target points obtained in step (4) are downloaded from the Pubchem database. The AutoDockTools 1.5.6 software is used to remove the crystal water and the original ligands in the protein receptor and perform hydrogenation on the receptor protein. Then, the AutoDock Vina 1.1.2, Pymol 2.1, and Discovery studio V2019 software are used to perform molecular docking on the 3D structures of the potential core target points and the key compound molecules. The docking results are evaluated by the level of the binding free energy as the degree of binding to the key compound molecules; the key compound molecules include one or several of quercetin, luteolin, kaempferol, wogonin, baicalein, or β-sitosterol; the visualization includes: using the R language pacman package to visualize the binding free energy through a heat map, and visualizing the docking modes of the potential core target points obtained in step (4) and the key compound molecules respectively.

11. The analysis method for the mechanism of action of Tianma III in the treatment of colorectal cancer according to claim 4, wherein In the second analysis method, the 3D structures of the potential core targets obtained in step (4) are downloaded from the Pubchem database. The AutoDockTools 1.5.6 software is used to remove the crystal water and the original ligands in the protein receptor from the protein and to hydrogenate the receptor protein. Then, the AutoDock Vina 1.1.2, Pymol 2.1, and Discovery studio V2019 software are used to perform molecular docking between the 3D structures of the potential core targets and the key compound molecules. The docking results are evaluated by the magnitude of the binding free energy as the criterion for the binding degree with the key compound molecules. The key compound molecules include one or more of quercetin, luteolin, kaempferol, wogonin, baicalein, or β-sitosterol. The visualization includes: visualizing the binding free energy through a heat map using the R language pacman package, and visualizing the docking modes of the potential core targets obtained in step (4) with the key compound molecules respectively.

12. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 6, wherein In the second analysis method, the 3D structures of the potential core targets obtained in step (4) are downloaded from the Pubchem database. The AutoDockTools 1.5.6 software is used to remove the crystal water and the original ligands in the protein receptor from the protein and to hydrogenate the receptor protein. Then, the AutoDock Vina 1.1.2, Pymol 2.1, and Discovery studio V2019 software are used to perform molecular docking between the 3D structures of the potential core targets and the key compound molecules. The docking results are evaluated by the magnitude of the binding free energy as the criterion for the binding degree with the key compound molecules. The key compound molecules include one or more of quercetin, luteolin, kaempferol, wogonin, baicalein, or β-sitosterol. The visualization includes: visualizing the binding free energy through a heat map using the R language pacman package, and visualizing the docking modes of the potential core targets obtained in step (4) with the key compound molecules respectively.

13. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 1 or 2, characterized in that, In the third analysis method, the CCK8 method is specifically as follows: The colorectal cancer cells are inoculated on a 96-well plate at a density of 1×10 3 ~10×10 3 cells / well, and divided into multiple groups with the preset concentrations of Tianma III prescription-containing serum ranging from 0 to 20%. Each group has 4 to 6 replicate wells. After culturing overnight, grouping interventions are carried out according to the preset concentrations of the drug-containing serum. After 20 to 28 hours of intervention, CCK8 solution prepared with complete medium is added at 80 to 120 μL / well, and incubated at 35 to 39 °C and 4 to 6% CO2 for 1 to 2 hours. Then, the absorbance values at 450 nm are analyzed respectively, and the mean value of the replicate wells within the group is taken; The flow cytometry is specifically as follows: The Tianma III prescription-containing serum intervenes in colorectal cancer cells and negative control group cells for 20 to 28 hours at a gradient concentration of 0 to 20%. The intervened colorectal cancer cells and negative control group cells are washed 2 to 3 times with pre-cooled PBS respectively, and 180 to 220 μL of 1×Annexin V binding solution is added to resuspend the cells, and the concentration is adjusted to 1×10 6 ~5×10 6 cells / mL. Then, 8 to 12 μL of Annexin V-FITC staining solution is added to the cell suspension, gently mixed, and incubated at 3 to 5 °C in the dark for 5 to 10 minutes. Finally, 8 to 12 μL of PI staining solution is added, gently mixed, and incubated at 3 to 5 °C in the dark for 5 to 10 minutes, and immediately detected with a flow cytometer; The pretreatment method of the negative control group cells is: Wash the trypsin-digested cells with PBS, centrifuge at 35 to 39 °C and 800 to 1200 rpm / min for 8 to 12 minutes, and collect the trypsin-digested cells; The colorectal cancer cells include one or several of HCT116, SW480, DLD1, SW620 or HT29.

14. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 3, characterized in that, In the third analysis method, the specific CCK8 method is as follows: The colorectal cancer cells are seeded on a 96-well plate at a density of 1×10 3 ~10×10 3 cells / well, divided into multiple groups with the preset concentrations of Tianma III prescription-containing serum ranging from 0 to 20%, and each group has 4 to 6 replicate wells. After overnight culture, group interventions are performed according to the preset concentrations of the drug-containing serum. After 20 to 28 hours of intervention, CCK8 solution prepared with complete medium is added at 80 to 120 μL / well, and then incubated at 35 to 39 °C and 4 to 6% CO2 for 1 to 2 hours. Then, the absorbance values at 450 nm are analyzed respectively, and the mean value of the replicate wells within the group is taken; the specific flow cytometry method is as follows: The Tianma III prescription-containing serum intervenes in colorectal cancer cells and negative control group cells for 20 to 28 hours at gradient concentrations of 0 to 20%. The intervened colorectal cancer cells and negative control group cells are washed 2 to 3 times with pre-cooled PBS respectively, and then 180 to 220 μL of 1×Annexin V binding solution is added to resuspend the cells, and the concentration is adjusted to 1×10 6 ~5×10 6 cells / mL. Then, 8 to 12 μL of Annexin V-FITC staining solution is added to the cell suspension, gently mixed, and incubated at 3 to 5 °C in the dark for 5 to 10 minutes. Finally, 8 to 12 μL of PI staining solution is added, gently mixed, and incubated at 3 to 5 °C in the dark for 5 to 10 minutes, and then immediately detected with a flow cytometer; the pretreatment method for the negative control group cells is: The cells are digested with trypsin and washed with PBS, and then centrifuged at 35 to 39 °C and 800 to 1200 rpm / min for 8 to 12 minutes to collect the trypsin-digested cells; the colorectal cancer cells include one or more of HCT116, SW480, DLD1, SW620, or HT29.

15. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 4, characterized in that, In the third analysis method, the CCK8 method is specifically as follows: The colorectal cancer cells are inoculated on a 96-well plate at a density of 1×10 3 ~10×10 3 cells / well, divided into multiple groups with the preset concentrations of Tianma III prescription-containing serum ranging from 0 to 20%, and 4 to 6 replicate wells are set in each group. After culturing overnight, grouping interventions are carried out according to the preset concentrations of the drug-containing serum. After 20 to 28 hours of intervention, CCK8 solution prepared with complete medium is added at 80 to 120 μL / well, and then incubated at 35 to 39 °C and 4 to 6% CO2 for 1 to 2 hours. Then, the absorbance values at 450 nm are analyzed respectively, and the mean value of the replicate wells within the group is taken; The flow cytometry is specifically as follows: The Tianma III prescription-containing serum intervenes the colorectal cancer cells and the negative control group cells for 20 to 28 hours at gradient concentrations of 0 to 20%. The intervened colorectal cancer cells and the negative control group cells are washed 2 to 3 times with pre-cooled PBS respectively, and then 180 to 220 μL of 1×Annexin V binding solution is added to resuspend the cells, and the concentration is adjusted to 1×10 6 ~5×10 6 cells / mL. Then, 8 to 12 μL of Annexin V-FITC staining solution is added to the cell suspension, gently mixed, and incubated at 3 to 5 °C in the dark for 5 to 10 minutes. Finally, 8 to 12 μL of PI staining solution is added, gently mixed, and incubated at 3 to 5 °C in the dark for 5 to 10 minutes, and then immediately detected with a flow cytometer; The pretreatment method of the negative control group cells is: The cells are digested with trypsin and washed with PBS, and then centrifuged at 35 to 39 °C and 800 to 1200 rpm / min for 8 to 12 minutes to collect the trypsin-digested cells; The colorectal cancer cells include one or more of HCT116, SW480, DLD1, SW620, or HT29.

16. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 6, characterized in that, In the third analysis method, the CCK8 method is specifically as follows: The colorectal cancer cells are inoculated on a 96-well plate at a density of 1×10 3 ~10×10 3 cells / well, and divided into multiple groups with the preset concentrations of Tianma III prescription-containing serum ranging from 0 to 20%. Each group is set with 4 to 6 replicate wells. After overnight culture, group intervention is carried out according to the preset concentration of the drug-containing serum. After 20 to 28 hours of intervention, CCK8 solution prepared with complete medium is added at 80 to 120 μL / well, and then incubated at 35 to 39 °C and 4 to 6% CO2 for 1 to 2 hours. Then, the absorbance values at 450 nm are analyzed respectively, and the mean value of the replicate wells within the group is taken; The flow cytometry is specifically as follows: Tianma III prescription-containing serum is used to intervene the colorectal cancer cells and the cells of the negative control group at gradient concentrations of 0 to 20% for 20 to 28 hours. The intervened colorectal cancer cells and the cells of the negative control group are washed 2 to 3 times with pre-cooled PBS respectively, and then 180 to 220 μL of 1× Annexin V binding solution is added to resuspend the cells, and the concentration is adjusted to 1×10 6 ~5×10 6 cells / mL. Then, 8 to 12 μL of Annexin V-FITC staining solution is added to the cell suspension, gently mixed, and incubated at 3 to 5 °C in the dark for 5 to 10 minutes. Finally, 8 to 12 μL of PI staining solution is added, gently mixed, and incubated at 3 to 5 °C in the dark for 5 to 10 minutes, and then immediately detected with a flow cytometer; The pretreatment method of the cells of the negative control group is: The cells are digested with trypsin and washed with PBS, and then centrifuged at 35 to 39 °C and 800 to 1200 rpm / min for 8 to 12 minutes to collect the trypsin-digested cells; The colorectal cancer cells include one or several of HCT116, SW480, DLD1, SW620 or HT29.

17. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 9, characterized in that, In the third analysis method, the CCK8 method is specifically as follows: The colorectal cancer cells are inoculated on a 96-well plate at a density of 1×10 3 ~10×10 3 cells / well, and divided into multiple groups with the preset concentrations of Tianma III prescription-containing serum ranging from 0 to 20%. Each group is set with 4 to 6 duplicate wells. After culturing overnight, grouping interventions are carried out according to the preset concentrations of the drug-containing serum. After all interventions for 20 to 28 h, CCK8 solution prepared with complete medium is added at 80 to 120 μL / well, and then incubated at 35 to 39 °C and 4 to 6% CO2 for 1 to 2 h. Then, the absorbance values at 450 nm are analyzed respectively, and the mean value of the duplicate wells within the group is taken; The flow cytometry is specifically as follows: The Tianma III prescription-containing serum is used to intervene the colorectal cancer cells and the cells of the negative control group at gradient concentrations of 0 to 20% for 20 to 28 h. The intervened colorectal cancer cells and the cells of the negative control group are washed 2 to 3 times with pre-cooled PBS respectively, and then 180 to 220 μL of 1×Annexin V binding solution is added to resuspend the cells. After adjusting the concentration to 1×10 6 ~5×10 6 cells / mL, 8 to 12 μL of Annexin V-FITC staining solution is added to the cell suspension, gently mixed, and then incubated at 3 to 5 °C in the dark for 5 to 10 min. Finally, 8 to 12 μL of PI staining solution is added, gently mixed, and then incubated at 3 to 5 °C in the dark for 5 to 10 min. Immediately, it is detected by a flow cytometer; The pretreatment method of the cells of the negative control group is: The cells are digested with trypsin and washed with PBS, and then centrifuged at 35 to 39 °C and 800 to 1200 rpm / min for 8 to 12 min to collect the trypsin-digested cells; The colorectal cancer cells include one or several of HCT116, SW480, DLD1, SW620 or HT29.

18. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 1 or 2, characterized in that, In the fourth analysis method, the specific method for verification by real-time fluorescence quantitative method is as follows: The colorectal cancer cells after intervention with Tianma III formula obtained in the third analysis method are collected. Total RNA is extracted using Trizol, and further reverse transcription reaction is carried out according to the cDNA reverse transcription kit. The total reaction system volume is 18 - 22 μL, and pre-denaturation treatment is carried out at 23 - 27 °C for 8 - 12 min. The amplification conditions are: at 93 - 97 °C for 25 - 35 s, and at 55 - 65 °C for annealing for 25 - 35 s for 35 - 45 cycles. β-actin is used as the internal reference gene, and the 2-ΔΔCt method is used to analyze the relative expression level of mRNA.

19. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 3, characterized in that, In Analytical Method 4, the specific method for verifying the real-time fluorescence quantitative method is as follows: Collect the colorectal cancer cells after the intervention with Tianma III Prescription obtained in Analytical Method 3, extract the total RNA using Trizol, and further perform a reverse transcription reaction according to the cDNA reverse transcription kit. Establish a total reaction system volume of 18 - 22 μL, and perform a pre-denaturation treatment at 23 - 27 °C for 8 - 12 min. The amplification conditions are: reaction at 93 - 97 °C for 25 - 35 s, annealing at 55 - 65 °C for 25 - 35 s for 35 - 45 cycles; Use β-actin as the internal reference gene and analyze the relative expression level of mRNA using the 2-ΔΔCt method.

20. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 4, characterized in that, In Analytical Method 4, the specific method for verifying the real-time fluorescence quantitative method is as follows: Collect the colorectal cancer cells after the intervention with Tianma III Prescription obtained in Analytical Method 3, extract the total RNA using Trizol, and further perform a reverse transcription reaction according to the cDNA reverse transcription kit. Establish a total reaction system volume of 18 - 22 μL, and perform a pre-denaturation treatment at 23 - 27 °C for 8 - 12 min. The amplification conditions are: reaction at 93 - 97 °C for 25 - 35 s, annealing at 55 - 65 °C for 25 - 35 s for 35 - 45 cycles; Use β-actin as the internal reference gene and analyze the relative expression level of mRNA using the 2-ΔΔCt method.

21. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 6, wherein, In Analytical Method 4, the specific method for verifying the real-time fluorescence quantitative method is as follows: Collect the colorectal cancer cells after the intervention with Tianma III Prescription obtained in Analytical Method 3, extract the total RNA using Trizol, and further perform a reverse transcription reaction according to the cDNA reverse transcription kit. Establish a total reaction system volume of 18 - 22 μL, and perform a pre-denaturation treatment at 23 - 27 °C for 8 - 12 min. The amplification conditions are: reaction at 93 - 97 °C for 25 - 35 s, annealing at 55 - 65 °C for 25 - 35 s for 35 - 45 cycles; Use β-actin as the internal reference gene and analyze the relative expression level of mRNA using the 2-ΔΔCt method.

22. The analysis method for the mechanism of action of Tianma III formula in treating colorectal cancer according to claim 9, wherein, In Analytical Method 4, the specific method for verifying the real-time fluorescence quantitative method is as follows: Collect the colorectal cancer cells after the intervention with Tianma III Prescription obtained in Analytical Method 3, extract the total RNA using Trizol, and further perform a reverse transcription reaction according to the cDNA reverse transcription kit. Establish a total reaction system volume of 18 - 22 μL, and perform a pre-denaturation treatment at 23 - 27 °C for 8 - 12 min. The amplification conditions are: reaction at 93 - 97 °C for 25 - 35 s, annealing at 55 - 65 °C for 25 - 35 s for 35 - 45 cycles; Use β-actin as the internal reference gene and analyze the relative expression level of mRNA using the 2-ΔΔCt method.

23. The analysis method for the mechanism of action of Tianma III in treating colorectal cancer according to claim 13, wherein In the fourth analytical method, the specific method for verifying the real-time fluorescence quantitative method is as follows: Collect the colorectal cancer cells after the intervention with Tianma III formula obtained in the third analytical method, extract total RNA using Trizol, and further perform a reverse transcription reaction according to the cDNA reverse transcription kit. The total reaction system volume is 18 - 22 μL, and pre-denaturation treatment is carried out at 23 - 27 °C for 8 - 12 min. The amplification conditions are: at 93 - 97 °C for 25 - 35 s, and 35 - 45 cycles of annealing at 55 - 65 °C for 25 - 35 s; Using β-actin as an internal reference gene, the 2-ΔΔCt method is used to analyze the relative expression level of mRNA.

Images