Method for establishing the binding of active ingredients of ganfuwu decoction to wd-copper death target genes

Abstract

To establish the method of the active ingredients of Gan Dou Fu Mu Decoction binding with WD-copper death target genes, the differential genes of WD patients and normal people were obtained from the database, the copper death related genes were obtained from the database and published literature, and the WD-copper death target genes were obtained by intersection. The serum of healthy controls and WD patients before and after treatment was collected, the expression level of target genes was verified by WB and qRT-PCR, and the rationality of WD-copper death target genes screened was determined; the expression level of WD-copper death target genes was basically consistent with the expression of the screened genes. Using molecular docking and PyMOL visualization analysis technology, the common target genes of Gan Dou Fu Mu Decoction and WD-copper death-PDK1, SERPINE1, VEGF-A, AOC3 were established, and they had good binding. Therefore, the copper death mechanism can provide new targets / directions for the diagnosis / treatment of WD.

Description

Technical Field

[0001] This invention relates to the field of bioinformatics analysis and verification technology for Wilson's disease, specifically to a method for establishing the binding affinity of the active ingredient of Hepatolenticular Decoction to WD-copper death target genes. Background Technology

[0002] Hepatolenticular degeneration (HLD), also known as Wilson's disease (WD), is a hereditary disorder of copper metabolism that leads to cirrhosis of the liver and brain degeneration, primarily affecting the basal ganglia. Mutations in the ATP7B gene are the primary cause of this disease, resulting in partial or complete loss of function of its expression product, the P-type copper ATP transporter, which is unable to transport excess copper ions (Cu). 2+ Cu is transported out of the cell, causing excess Cu to be transported out. 2+ The disease is caused by copper deposition in tissues such as the liver, brain, kidneys, and cornea; clinical features include progressively worsening extrapyramidal symptoms, psychiatric symptoms, cirrhosis, kidney damage, and corneal pigmentation rings. Treatment principles include a low-copper diet and medications to reduce copper absorption and increase copper excretion. Commonly used medications include zinc preparations, ammonium tetramercaptomolybdate, D-penicillamine, and sodium dimercaptopropanesulfonate.

[0003] Copper death is a Cu 2+ Cu-dependent regulatory cell death pathway 2+ By directly binding to the esterified portion of the tricarboxylic acid cycle, copper induces the aggregation of esterified proteins and the instability of iron-sulfur cluster proteins, leading to proteotoxic stress and thus inducing cell death. Peter Tsvetkov et al. found that the cellular effects induced by copper overload in WD were the same as those induced by copper death, manifested as the aggregation of esterified proteins and the instability of iron-sulfur cluster proteins; Xu Lewen et al. found that the loss of lipoylation-related proteins and iron-sulfur proteins jointly induced mitochondrial damage in WD to further induce cell death.

[0004] Currently, the traditional Chinese medicine formula Gan Dou Fu Mu Tang, composed of white peony root, wolfberry, bupleurum root, turmeric, smilax glabra, and notoginseng, shows good therapeutic effects for Wilson's disease. This invention aims to study and identify differentially expressed copper death-related genes in WD, providing new gene targets for the treatment of this disease. Bioinformatics methods will be used to screen WD-copper death target genes, analyze the biological processes, functions, or metabolic pathways involved, and screen copper death target genes in the development and progression of WD from different perspectives, and conduct clinical validation. Summary of the Invention

[0005] The purpose of this invention is to propose a method for establishing the binding affinity between the active ingredients of Gandou Fumu Decoction and WD-copper death target genes. By conducting bioinformatics analysis and clinical verification of WD-copper death-related genes, the role of copper death in the occurrence and development of WD can be explored, and key targets can be identified, providing new ideas and directions for the diagnosis and treatment of WD.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] The method for establishing the binding affinity between the active components of Gan Dou Fu Mu Tang and WD-copper death target genes includes the following steps:

[0008] Step S1, Screening for WD-copper death target genes:

[0009] Differential genes between WD patients and healthy individuals were obtained from the GeneCards database. Copper death-related genes were obtained from the Gene Expression Omnibus (GEO) database and published literature. The intersection of these genes was used to obtain the WD-copper death target gene.

[0010] Step S2, Validation of WD-copper death target genes:

[0011] Serum samples were collected from healthy controls and WD patients before and after treatment. The expression levels of the target gene were verified by Western Blot and qRT-PCR to determine the rationality of the selected WD-copper death target gene.

[0012] Step S3: Molecular docking verification and visualization analysis of liver bean curd decoction with WD-copper death target gene:

[0013] Using molecular docking and PyMOL visualization analysis, the common target gene of the active ingredient of Gandoufumu Decoction and WD-copper death was identified, and the binding between the two was analyzed.

[0014] As a preferred technical solution of the present invention, step S1 is specifically as follows:

[0015] Step S11, Obtaining copper death-related genes:

[0016] Using "copper death" as a keyword, we used the GeneCards database to mine relevant human disease gene targets, and obtained known copper death-related genes by searching the literature, and summarized them to obtain copper death-related genes.

[0017] Step S12, screening for WD-copper death target genes:

[0018] Differential gene analysis was performed using the GSE107323 dataset from the Gene Expression Omnibus (GEO) database and the GEO2R dataset. P < 0.05 and |log2FC| > 1 were used as the criteria for differential gene identification. The target genes for WD-copper death were identified using Venny plots. Three genes were upregulated: SQSTM1, MIF1, and TAX1BP1; nine genes were downregulated: CP, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, PDK1, and ATP7B.

[0019] Step S13, GO function and KEGG enrichment analysis of WD-copper death target genes:

[0020] Gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis were performed on the target genes of WD-copper death using the Metascape database. GO analysis included cellular component (CC), molecular function (MF), and biological process (BP). KEGG was used to screen for important signaling pathways, with a screening criterion of P < 0.05.

[0021] As a preferred technical solution of the present invention, step S2 is specifically as follows:

[0022] Step S21: Collect approximately 5 ml of fasting peripheral venous blood from the healthy control group and the patient group before and after treatment, and centrifuge the blood using an H1850 medical centrifuge to obtain serum.

[0023] Step S22, Western Blot (WB) relative expression level detection:

[0024] The expression of CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 proteins was detected. An appropriate amount of serum sample was weighed, and 600 μl of RIPA protein lysis buffer was added for complete lysis. Proteins were extracted, and sample buffer was added. The mixture was then denatured in a boiling water bath for 15 min. SDS-PAGE electrophoresis was performed, and the sample was transferred to a PVDF membrane and blocked with 5% skim milk powder for 2 h. Antibodies for CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 were added, and the membrane was incubated overnight at 4 ℃. After rinsing, secondary antibody was added, and the membrane was blocked at room temperature for 1.2 h. ECL reaction was then performed, followed by exposure and development. The bands were analyzed using β-actin and GAPDH as internal controls.

[0025] Step S23, qRT-PCR verification:

[0026] The expression of CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 mRNA in serum samples was detected. An appropriate amount of serum sample was weighed, and RNA was extracted using Trizol. 1 μL of RNA sample was used as a template for reverse transcription to obtain cDNA. Using the cDNA as a template, the corresponding quantitative real-time PCR reaction parameters were set as follows: 95 ℃, 5 min, 95 ℃, 10 s, 60 ℃, 30 s, 40 cycles. The Ct value was obtained based on the amplification curve. Using 2... -ΔΔCt Calculate the relative expression level.

[0027] As a preferred technical solution of the present invention, step S3 is as follows:

[0028] Step S31: Use the TCMSP database to search for the active ingredients of Gan Dou Fu Mu Tang, and further screen them based on oral bioavailability (OB) ≥30% and drug-likeness (DL) ≥0.18.

[0029] Step S32: Obtain the gene targets of the screened components through the herb database and Swisstarget platform; enter the target name in the Uniport database to find the Entry, and enter the Entry number in the PDB database to find and download the PDB file that meets the criteria.

[0030] Step S33: Locate the InCheky of the active ingredient in the TCMSP database and input it into PubChem. Download the 3D structure file of the compound. Import the ligand and receptor into the CB-DOCK2 website for molecular docking and test the binding ability. Affinity < -5.0 kcal / mol indicates that the component has a certain binding activity with the receptor protein. The smaller the binding energy, the stronger the binding activity.

[0031] This invention explores the role of copper death in the development and progression of WD through bioinformatics analysis and clinical validation of WD-copper death-related genes, thereby identifying key targets and providing new ideas and directions for the diagnosis and treatment of WD.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0033] (1) Using the GSE107323 dataset in the Gene Expression Omnibus (GEO) database, 3607 differentially expressed genes for WD were obtained. A total of 68 copper death-related genes were obtained from the GeneCards database and published literature. The intersection of the differentially expressed genes for WD and copper death genes yielded 12 target genes for WD-copper death, including 3 upregulated genes (SQSTM1, MIF1, TAX1BP1) and 9 downregulated genes (CP, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, PDK1, ATP7B). GO function and KEGG enrichment analysis showed that the target genes for WD-copper death mainly participate in metabolic processes such as monocarboxylic acid metabolism, oxidoreductase activity, and negative regulation of molecular function, involving signaling pathways such as HIF-1 and Ferrotosis.

[0034] (2) A total of 30 clinical blood samples were collected, including 15 WD patients and 15 healthy individuals. WB results showed that the expression level of the target gene was consistent with the expression of the selected gene. RT-qPCR results showed that, compared with the healthy control group, the expression levels of SERPINE1, GPX4, SLC27A5, and VEGF-A mRNA in WD patients were lower, while the expression levels of SQSTM1 and MIF1 mRNA were higher.

[0035] (3) Molecular docking and visualization analysis showed that Gan Dou Fu Mu Tang had good binding ability with PDK1, SERPINE1, VEGF-A and AOC3, which are target genes of WD-copper death.

[0036] The present invention finally determines that Gandou Fumu Decoction has good binding ability to the common target genes of WD-cuproptosis, namely PDK1, SERPINE1, VEGF-A and AOC3. The expression levels of cuproptosis target genes in WD patients are basically consistent with the expression of the screened genes, and Gandou Fumu Decoction, a characteristic preparation of Xin'an medicine, exhibits good binding ability to WD-cuproptosis target genes; the cuproptosis mechanism may play a key role in the pathophysiological mechanism of WD, and can provide new targets / directions for the diagnosis / treatment of WD. Description of Drawings

[0037] Figure 1 is a Venn diagram (a) and a volcano plot (b) of WD-cuproptosis target genes.

[0038] Figure 2 is an analysis diagram of GO function (a) and KEGG enrichment (b) of WD-cuproptosis target genes.

[0039] Figure 3 is an analysis diagram of relative WB expression of target genes.

[0040] Figure 4 is an analysis diagram of relative qRT-PCR expression of target genes.

[0041] Figure 5 is a molecular docking analysis diagram of active components of Gandou Fumu Decoction and WD-cuproptosis target genes. Wherein, A represents the docking of SERPINE1 and Ginsenoside F2; B represents the docking of PDK1 and Ginsenoside F2; C represents the docking of AOC3 and Benzoylpaeoniflorin; D represents the docking of VEGF-A and Lactiflorin. Detailed Description of Embodiments

[0042] The present invention is further described in detail below with reference to embodiments and the accompanying drawings.

[0043] 1 Materials and Methods

[0044] 1.1 Screening of WD-cuproptosis target genes

[0045] 1.1.1 Acquisition of cuproptosis-related genes

[0046] With "cuproptosis" as the keyword, the corresponding human disease gene targets are mined by using the GeneCards database, and known cuproptosis-related genes are obtained by searching literatures, and the cuproptosis-related genes are obtained by summarization.

[0047] 1.1.2 Screening of WD-cuproptosis target genes

[0048] Using the GSE107323 dataset from the Gene Expression Omnibus (GEO) database (the dataset contains 12 samples, with 3 wild-type HepG2 cell lines selected as controls and copper-induced ATP7B gene knockout HepG2 cell lines used for subsequent analysis), differential gene analysis was performed using the GEO2R dataset. P < 0.05 and |log2FC| > 1 were used as the criteria for identifying differentially expressed genes. The target genes for WD-copper death were obtained through Venny plots.

[0049] 1.1.3 GO function and KEGG enrichment analysis of WD-copper death target genes

[0050] Gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis were performed on the target genes of WD-copper death using the Metascape database. GO analysis included cellular component (CC), molecular function (MF), and biological process (BP); KEGG was used to screen for important signaling pathways. The screening criterion was P < 0.05.

[0051] 1.2 Validation of WD-Copper Death Target Genes

[0052] 1.2.1 General Information

[0053] From January 2023 to December 2023, the Department of Neurology at the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine admitted 15 patients with neuropathic dysplasia (WD), including 7 males (46.67%) and 53.33% females; their ages ranged from 17 to 33 years, with a mean age of (25.33 ± 6.28) years; the duration of disease ranged from 0.01 to 20 years, with a mean duration of (8.17 ± 6.36) years; the clinical classification was predominantly hepatic type in 7 cases (46.67%), followed by cerebral type in 4 cases (26.67%), and cerebral-visceral type in 4 cases (26.67%); the mean BMI was (21.74 ± 3.56) kg / m². 2 .

[0054] Table 1 Comparison of clinical data of enrolled patients

[0055] gender male 7（46.67） female 8（53.33） Age (years) 25.33 ± 6.28 Disease duration (years) 8.17 ± 6.36 Classification liver type 7（46.67） brain type 4（26.67） Brain-visceral type 4（26.67） <![CDATA[BMI(kg / m 2 )]]> 21.74 ± 3.56 Allergy history have 2（13.33） none 13（86.67）

[0056] 1.2.2 Diagnostic Criteria

[0057] Follow the relevant diagnostic criteria.

[0058] 1.2.3 Inclusion Criteria

[0059] (1) No age or gender restrictions; (2) Meets the Western medicine diagnostic criteria for WD; (3) Has not received regular copper chelation therapy before admission; (4) This study has been approved by the Medical Ethics Committee of the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine (Approval No.: 2023AH-03), and the patient or his / her family members voluntarily participate in the clinical trial and sign a written informed consent form.

[0060] 1.2.4 Exclusion Criteria

[0061] (1) Those who have been diagnosed with and received regular copper chelation therapy; (2) Those with fulminant hepatic failure (with or without hemolytic anemia); (3) Those with cognitive impairment (Simplified Mental State Scale score ≤ 22 or Montreal Cognitive Assessment score < 26); (4) Those with severe neurological impairment such as torsion dystonia; (5) Those with serious diseases (such as opportunistic infections, tumors, hematological diseases); (6) Pregnant and lactating women.

[0062] 1.2.6 Observation Indicators

[0063] Approximately 5 ml of fasting peripheral venous blood was collected from healthy controls and patients before and after treatment. Serum was obtained by centrifugation using an H1850 medical centrifuge (Hunan Xiangyi Laboratory Instrument Development Co., Ltd.).

[0064] 1) Western Blot: To detect the expression of CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 proteins, an appropriate amount of serum sample was weighed, and 600 μl of RIPA protein lysis buffer was added for complete lysis. Proteins were extracted, and sample buffer was added, followed by denaturation in a boiling water bath for 15 min. SDS-PAGE electrophoresis was performed, and the sample was transferred to a PVDF membrane and blocked with 5% skim milk powder for 2 h. Antibodies for CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 were added, and the membrane was incubated overnight at 4 ℃. After rinsing, secondary antibody was added, and the membrane was blocked at room temperature for 1.2 h. ECL reaction was then performed, followed by exposure and development. The bands were analyzed using β-actin and GAPDH as internal controls.

[0065] 2) qRT-PCR: To detect the mRNA expression of CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 in serum samples, an appropriate amount of serum sample was weighed, and RNA was extracted using Trizol. 1 μL of RNA sample was used as a template for reverse transcription to obtain cDNA. Using the cDNA as a template, the corresponding quantitative PCR reaction parameters were set as follows: 95 ℃, 5 min; 95 ℃, 10 s; 60 ℃, 30 s; 40 cycles. The Ct value was obtained based on the amplification curve. Using 2... -ΔΔCt Calculate the relative expression level.

[0066] 1.3 Molecular docking verification and visualization analysis of liver bean sprout decoction with WD-copper death target gene

[0067] The active ingredients of Gan Dou Fu Mu Tang were retrieved from the TCMSP database, with oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18 used for further screening. The gene targets of the screened ingredients were obtained through the Herb database and the Swisstarget platform. The target name was entered into the Uniport database to find the Entry, and the Entry number was entered into the PDB database to find and download matching PDB files. The InCheky structure of the active ingredient was found in the TCMSP database and entered into PubChem to download the compound's 3D structure file. The ligand and receptor were imported into the CB-DOCK2 website for molecular docking to test binding affinity. Generally, affinity < -5.0 kcal / mol indicates a certain binding activity between the ingredient and the receptor protein; the lower the binding energy, the stronger the binding activity.

[0068] 2 Results

[0069] 2.1 Target gene screening

[0070] 2.1.1 Acquisition of WD-Copper Death Target Genes

[0071] After screening, 68 copper death-related genes and 3607 differentially expressed genes for disease (WD) were identified from the GeneCards database and published literature. Of these, 1772 were downregulated and 1835 were upregulated. Using the Venny tool, the intersection of these genes yielded 12 target genes, including 3 upregulated genes (SQSTM1, MIF1, TAX1BP1) and 9 downregulated genes (CP, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, PDK1, ATP7B). See [link to relevant documentation]. Figure 1 As shown in Table 2.

[0072] Table 2. Target Genes of WD-Copper Death

[0073] SQSTM1 sequestosome 1 3.2747694 MTF1 Tax1 binding protein 1 1.4266681 TAX1BP1 metal regulatory transcription factor 1 2.0178916 CP Serpin family E member 1 -2.7968625 SERPINE1 ceruloplasmin -4.3441687 AOC3 glutathione peroxidase 4 -1.6562698 GPX4 vascular endothelial growth factor A -1.3446869 SLC27A5 pyruvate dehydrogenase E1 subunit beta -1.3274688 VEGF-A amine oxidase copper containing 3 -2.0948375 PDHB pyruvate dehydrogenase kinase 1 -1.2418738 PDK1 ATPase copper transporting beta -1.2400907 ATP7B solute carrier family 27 member 5 -1.4629475

[0074] 2.1.2 GO function and KEGG enrichment analysis of WD-copper death target genes

[0075] GO biological function analysis showed that CC mainly involves mitochondria, exosomes, endoplasmic reticulum, and autophagosomes; BP involves detoxification reactions, monocarboxylic acid metabolism, and negative regulation of molecular functions; and MF involves copper ion binding and oxidoreductase activity. KEGG analysis revealed two pathways, mainly involving HIF-1 and ferroptosis signaling pathways. See Figure 2 Table 3.

[0076] Table 3. Enrichment analysis of target gene pathways for WD-copper death

[0077] hsa04066 HIF-1 signaling pathway 4 2.18E-04 SERPINE1, PDHB, PDK1, VEGF-A hsa04216 Ferroptosis 2 4.75E-02 GPX4, CP hsa05230 Central carbon metabolism in cancer 2 7.80E-02 PDHB, PDK1

[0078] 2.2 Validation of WD-Copper Death Target Genes

[0079] 2.2.1 Relative expression level in Western blotting (WB)

[0080] Compared with healthy controls, the expression levels of CP, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 were significantly downregulated in WD patients, while the expression levels of SQSTM1, MIF1, and TAX1BP1 were significantly upregulated (P < 0.05). See Figure 4 Table 4.

[0081] Table 4. Relative expression levels of target genes by Western blot (WB)

[0082] SQSTM1 0.13 ± 0.04 <![CDATA[0.84 ± 0.10 # ]]> MIF1 0.34 ± 0.11 <![CDATA[0.85 ± 0.11 # ]]> TAX1BP1 0.08 ±0.03 <![CDATA[0.68 ± 0.05 # ]]> SERPINE1 0.83 ± 0.11 <![CDATA[0.34 ± 0.10 # ]]> AOC3 0.73 ± 0.10 <![CDATA[0.27 ± 0.08 # ]]> GPX4 0.97 ± 0.11 <![CDATA[0.28 ± 0.07 # ]]> SLC27A5 0.84 ± 0.11 <![CDATA[0.31 ± 0.09 # ]]> VEGF-A 1.03 ± 0.11 <![CDATA[0.39 ± 0.08 # ]]> PDHB 0.88 ± 0.09 <![CDATA[0.39 ± 0.10 # ]]> PDK1 0.85 ± 0.11 <![CDATA[0.24 ± 0.07 # ]]> CP 0.71 ± 0.09 <![CDATA[0.31 ± 0.11 # ]]>

[0083] Note: WD, Wilson's disease; HC, health control; compared with the healthy control group. # P < 0.05.

[0084] 2.2.2 qRT-PCR Validation

[0085] Compared with healthy controls, the expression levels of CP, SERPINE1, GPX4, SLC27A5, and VEGF-A mRNA were significantly downregulated in WD patients, while the expression levels of SQSTM1 and MIF1 mRNA were significantly upregulated (P < 0.05). See Figure 5 Table 5.

[0086] Table 5. Relative Expression Levels of Target Genes by qRT-PCR

[0087] SQSTM1 1.11 ± 0.25 <![CDATA[1.70 ± 0.32 # ]]> MIF1 0.94 ± 0.19 <![CDATA[1.48 ± 0.36 # ]]> TAX1BP1 0.72 ± 0.20 0.92 ± 0.37 SERPINE1 0.97 ± 0.13 <![CDATA[0.73 ± 0.07 # ]]> AOC3 0.95 ± 0.16 0.80 ± 0.30 GPX4 1.46 ± 0.35 <![CDATA[0.90 ± 0.13 # ]]> SLC27A5 1.26 ± 0.12 <![CDATA[0.92 ± 0.18 # ]]> VEGF-A 1.10 ± 0.22 <![CDATA[0.73 ± 0.18 # ]]> PDHB 1.11 ± 0.12 0.95 ± 0.20 PDK1 1.01 ± 0.09 0.93 ± 0.05 CP 0.96 ± 0.25 <![CDATA[0.47 ± 0.05 # ]]>

[0088] Note: WD, Wilson's disease; HC, health control; compared with the healthy control group. # P < 0.05

[0089] 2.3 Molecular docking verification and visualization analysis of liver bean sprout decoction with WD-copper death target gene

[0090] The main active ingredients of Liver Bean Fumu Decoction are:

[0091] Ethyl linoleate (Mandenol), lactiflorin, (E)-5-Hydroxy-7-(4-hydroxyphenyl)-1-phenyl-1-heptene, quercetin, paeoniflorin, benzoyl paeoniflorin, and ginsenoside F2. Analysis showed that the common target genes for WD-copper death, as identified by Gan Dou Fu Mu Tang, are PDK1, SERPINE1, VEGF-A, and AOC3. The effective active ingredients of Gan Dou Fu Mu Tang exhibited good binding affinity to these WD-copper death target genes. See [link to relevant documentation]. Figure 3 Table 6.

[0092] Table 6. Molecular docking analysis of active components of Gan Dou Fu Mu Tang with WD-copper death target genes.

[0093] Mandenol -5.6 -6.4 -6.2 -5.6 Lactiflorin -7.1 -8.7 -10.5 -8.0 (E)-5-Hydroxy-7-(4-hydroxyphenyl)-1-phenyl-1-heptene -6.6 -8.0 -9.0 -6.0 Quercetin -6.2 -7.5 -8.9 -7.1 Paeoniflorin -7.0 -8.3 -8.9 -6.7 Benzoyl paeoniflorin -7.1 -8.3 -12.1 -8.2 Ginsenoside F2 -7.9 -9.0 -8.2 -8.0

[0094] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in the claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for establishing the binding affinity between the active components of Gan Dou Fu Mu Tang and WD-copper death target genes, characterized in that, Includes the following steps: Step S1, Screening for WD-copper death target genes: Differentially occurring genes between WD patients and healthy individuals were obtained from the GeneCards database. Copper death-related genes were identified using the Gene ExpressionOmnibus database and published literature. The intersection of these findings yielded the WD-copper death target gene. The specific steps are as follows: Step S11, Obtaining copper death-related genes: Using "copper death" as a keyword, we used the GeneCards database to mine corresponding human disease gene targets, and obtained known copper death-related genes by searching the literature, and summarized them to obtain copper death-related genes. Step S12, screening for WD-copper death target genes: Differential gene analysis was performed using the GSE107323 dataset from the Gene Expression Omnibus database and the GEO2R dataset. P < 0.05 and |log2FC| > 1 were used as the criteria for differential gene identification. The target genes for WD-copper death were identified using Venny plots. Three genes were upregulated: SQSTM1, MIF1, and TAX1BP1; nine genes were downregulated: CP, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, PDK1, and ATP7B. Step S13, GO function and KEGG enrichment analysis of WD-copper death target genes: Gene ontology function analysis and Kyoto Encyclopedia of Genomes enrichment pathway analysis were performed on the target genes of WD-copper death using the Metascape database. Gene ontology function analysis included cellular components, molecular functions, and biological processes. Kyoto Encyclopedia of Genomes enrichment pathway analysis was used to screen important signaling pathways, with a screening criterion of P < 0.

05. Step S2, Validation of WD-copper death target genes: Serum samples were collected from healthy controls and WD patients before and after treatment. The expression levels of the target gene were verified by Western blotting and qRT-PCR to determine the rationality of the selected WD-copper death target gene. The specific steps are as follows: Step S21: Collect approximately 5 ml of fasting peripheral venous blood from the healthy control group and the patient group before and after treatment, and centrifuge the blood using an H1850 medical centrifuge to obtain serum. Step S22, Western blotting for relative expression level detection: The expression of CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 proteins was detected. An appropriate amount of serum sample was weighed, and 600 μl of RIPA protein lysis buffer was added for complete lysis. Proteins were extracted, and sample buffer was added. The mixture was then denatured in a boiling water bath for 15 min. SDS-PAGE electrophoresis was performed, and the sample was transferred to a PVDF membrane and blocked with 5% skim milk powder for 2 h. Antibodies for CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 were added, and the membrane was incubated overnight at 4 ℃. After rinsing, secondary antibody was added, and the membrane was blocked at room temperature for 1.2 h. ECL reaction was then performed, followed by exposure and development. The bands were analyzed using β-actin and GAPDH as internal controls. Step S23, qRT-PCR verification: The expression of CP, SQSTM1, MIF1, TAX1BP1, SERPINE1, AOC3, GPX4, SLC27A5, VEGF-A, PDHB, and PDK1 mRNA in serum samples was detected. An appropriate amount of serum sample was weighed, and RNA was extracted using Trizol. 1 μL of RNA sample was used as a template for reverse transcription to obtain cDNA. Using the cDNA as a template, the corresponding quantitative real-time PCR reaction parameters were set as follows: 95 ℃, 5 min, 95 ℃, 10 s, 60 ℃, 30 s, 40 cycles. The Ct value was obtained based on the amplification curve. Using 2... -ΔΔCt Calculate relative expression levels; Step S3: Molecular docking verification and visualization analysis of liver bean curd decoction with WD-copper death target gene: Using molecular docking and PyMOL visualization analysis techniques, the common target gene between the active ingredients of Gan Dou Fu Mu Tang and WD-copper death was identified, and the binding affinity between the two was analyzed. The specific steps are as follows: Step S31: Use the TCMSP database to search for the active ingredients of Gan Dou Fu Mu Tang, and further screen them based on oral bioavailability ≥30% and drug-likeness ≥0.

18. Step S32: Obtain the gene targets of the screened components through the herb database and Swisstarget platform; enter the target name in the Uniport database to find the Entry, and enter the Entry number in the PDB database to find and download the PDB file that meets the criteria. Step S33: Locate the InCheky of the active ingredient in the TCMSP database and input it into PubChem to download the 3D structure file of the compound; The ligand and receptor were introduced into the CB-DOCK2 website for molecular docking, and the binding ability was tested. Affinity < -5.0 kcal / mol indicates that the component has a certain binding activity with the receptor protein. The smaller the binding energy, the stronger the binding activity.

2. The method as described in claim 1, characterized in that, Step S3 determined that the common target genes of liver bean fumu decoction and WD-copper death—PDK1, SERPINE1, VEGF-A, and AOC3—have good binding affinity.

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