Method for analyzing drug therapy mechanism of central nervous system based on system biological analysis

Abstract

The invention relates to the technical field of biomedicine, and particularly discloses a central nervous system drug therapy mechanism analysis method based on system biological analysis. According to the invention, systematic biological analysis including transcriptomics, proteomics and receptor kinetics is adopted to research a therapeutic mechanism of a central nervous system drug. The combination of the three can be used for analyzing an action path through a whole chain of'gene transcription-protein function-receptor interaction ', so that the one-sidedness of a single technology is avoided, and a theoretical support is provided for system construction of central nervous system drug mechanism research. According to the invention, oxiracetam is taken as an example for explaining that the cognitive disorder improvement effect of the medicine is closely related to NMDA receptor related pathways and receptor functions through multi-omics analysis, then receptor kinetic analysis verifies that oxiracetam can inhibit NMDA receptor current and accelerate NMDA receptor desensitization, and finally inhibits NMDA receptor functions, so that the cognitive disorder improvement effect of the medicine is improved. Therefore, cognitive impairment is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biomedical technology, and particularly discloses an analysis method for central nervous system drug treatment mechanism based on system biology analysis. BACKGROUND

[0002] Central nervous system (CNS) diseases are diverse and the number of patients is showing a significant growth trend. The complexity and social burden of CNS diseases have become a global public health challenge. According to the global burden of disease research framework, CNS diseases can be mainly divided into the following categories: neurodegenerative diseases (such as Alzheimer's disease, Parkinson's disease and Huntington's disease), cerebrovascular diseases (such as stroke), mental disorders (such as depression, anxiety and schizophrenia), epilepsy and seizure disorders, neuroimmunological diseases (such as multiple sclerosis or neuromyelitis optica spectrum disorder), neurodevelopmental disorders (such as autism spectrum disorder or spinal muscular atrophy), infections and trauma (such as meningitis or brain trauma), etc.

[0003] Cognitive impairment, ranging from mild memory decline to severe cognitive impairment, is not only a core symptom of many CNS diseases, but also an important driving factor for disease progression, significantly affecting the quality of life and social function. Among the many causes of cognitive impairment, Alzheimer's disease (AD) and vascular dementia (VaD) are particularly prominent. AD is characterized by beta-amyloid deposition and tau protein hyperphosphorylation leading to neuronal death, causing progressive cognitive decline. VaD is caused by cerebrovascular lesions, such as cerebral infarction, ischemia and hypoxia caused by hemorrhage, and nerve damage, often accompanied by executive function impairment. Currently, the incidence of cognitive impairment is showing an increasing trend year by year, making the prevention and treatment of cognitive impairment a major public health problem that needs to be addressed.

[0004] Although the mechanisms of some central nervous system treatment drugs have been identified, the current mechanism research in this field is still relatively superficial, and the research is often focused on single target and ignores the network pathology of CNS diseases, which cannot reveal the mechanism of related drugs in depth, and thus cannot provide theoretical support for the development of more targeted treatment strategies. SUMMARY

[0005] In view of the deficiencies in the prior art, the present application provides an analysis method for central nervous system drug treatment mechanism based on system biology analysis based on system analysis including transcriptomics and proteomics and receptor kinetics. The analysis method can break through the limitations and one-sidedness of single technology by analyzing the action path of "gene transcription-protein function-receptor interaction", and can provide theoretical support for the construction of a standardized method system for central nervous system drug mechanism research, and help the efficient discovery of innovative drugs.

[0006] To achieve the above-mentioned purposes, the present application adopts the following technical solutions:

[0007] In a first aspect, the present application provides an analysis method of central nervous system drug treatment mechanism based on system biology analysis, wherein the system biology analysis comprises transcriptomics analysis, proteomics analysis and receptor kinetics analysis.

[0008] The present application adopts system biology analysis including transcriptomics, proteomics and receptor kinetics to study the treatment mechanism of central nervous system drugs. Among them, transcriptomics can analyze the regulation of mRNA transcription by test drugs from the gene expression level, and screen key signal pathways; proteomics can directly detect protein expression and modification changes, and clearly determine the activity regulation of downstream functional proteins (such as synaptic proteins and receptor proteins); receptor kinetics combines to quantify the binding affinity and kinetic parameters of test drugs and functional proteins, and verifies the direct action target. The combination of the three can analyze the action path from "gene transcription → protein function → receptor interaction", avoiding the one-sidedness of a single technology. The analysis method of drug treatment mechanism provided by the present application provides theoretical support for the construction of a standardized method system for central nervous system drug mechanism research, and helps the efficient discovery of innovative drugs.

[0009] The central nervous system drugs in the present application include drugs for treating neurodegenerative diseases.

[0010] As a first limitation of the above-mentioned analysis method of central nervous system drug treatment mechanism based on system biology analysis, the system biology analysis further comprises transcriptomics and proteomics combined analysis.

[0011] As a second limitation of the above-mentioned analysis method of central nervous system drug treatment mechanism based on system biology analysis, the analysis method comprises the following steps:

[0012] S1. Extracting RNA in the hippocampal tissue of cognitive impairment organism before and after administration of test drugs, screening differentially expressed genes and performing enrichment analysis to obtain differential genes and differential pathways 1;

[0013] Extracting total protein in the hippocampal tissue of cognitive impairment organism before and after administration of test drugs, screening differential proteins and performing functional enrichment analysis to obtain differential proteins and differential pathways 2;

[0014] S2. Based on transcriptomics and proteomics combined analysis, screening associated genes and proteins, and performing functional enrichment analysis and correlation analysis to determine potential functional proteins;

[0015] S3. Using patch clamp technology, verifying the action target of the test drug by using the binding affinity and kinetic parameters of the potential functional protein and the test drug.

[0016] As a second limited further limitation of the above-mentioned analysis method of the central nervous system drug treatment mechanism based on system biology analysis, step S1 specifically comprises: extracting total RNA in the hippocampus tissue of the cognitive impairment organism before and after the administration of the test drug, screening the differentially expressed genes in the hippocampus cells, performing GO function enrichment analysis and KEGG pathway enrichment analysis on the differentially expressed genes, obtaining differential genes and differential pathways 1;

[0017] Extracting total protein in the hippocampus tissue of the cognitive impairment organism before and after the administration of the test drug, screening the differentially expressed proteins in the hippocampus cells, performing GO function enrichment analysis and KEGG pathway enrichment analysis on the differentially expressed proteins, obtaining differential proteins and differential pathways 2; constructing a PPI network, and then performing enrichment analysis on the domains of the differentially expressed proteins and subcellular localization of the differentially expressed proteins.

[0018] Step S2 specifically comprises: based on the results of the transcriptomic and proteomic joint analysis, obtaining common genes and unique genes of the two omics and performing venn analysis, and performing correlation analysis on the common genes to screen out key genes, key proteins and key signal pathways.

[0019] As a further limitation of the second limitation of the above-mentioned analysis method of the central nervous system drug treatment mechanism based on system biology analysis, in step S1, the screening standard of the differential genes is that in the two groups before and after the administration of the test drug, |log2FC|>1 and p<0.05 after correction.

[0020] In step S1, the screening standard of the differential proteins is that in the two groups before and after the administration of the test drug, |log2FC|≥0.263 and p<0.05 after correction.

[0021] As a second limitation of the second limitation of the above-mentioned analysis method of the central nervous system drug treatment mechanism based on system biology analysis, in step S2, in the transcriptomic and proteomic joint analysis, the associated gene screening standard in the transcriptomic analysis is |log2FC|>1 and p<0.05 after correction; the associated protein screening standard in the proteomic analysis is |log2FC|≥0.263 and p<0.05 after correction.

[0022] In the present application, FC≥1.2 is an up-regulated protein, and FC≤0.83 is a down-regulated protein;

[0023] When FC=1.2, log2FC≈0.263; when FC=0.83, log2FC≈-0.267.

[0024] As a third limitation of the second limitation of the method for analyzing the mechanism of central nervous system drug treatment based on the system biology analysis, the step S3 specifically comprises: constructing a plasmid containing the potential functional protein and transfecting a cell to obtain a cell containing the potential functional protein;

[0025] Using the whole-cell patch clamp technique, the change of the current of the cell before and after adding the test drug is detected to verify whether the test drug has a significant inhibitory or promoting effect on the potential functional protein;

[0026] Using the Outside-out patch clamp technique, the change of the current of the cell before and after adding the test drug in the presence of the agonist containing the potential functional protein is detected to verify whether the test drug can induce the desensitization of the potential functional protein channel.

[0027] As a fourth limitation of the second limitation of the method for analyzing the mechanism of central nervous system drug treatment based on the system biology analysis, the potential functional protein comprises at least one of a potential synaptic protein or a potential receptor protein.

[0028] As a third limitation of the method for analyzing the mechanism of central nervous system drug treatment based on the system biology analysis, the central nervous system drug comprises a cognitive disorder drug.

[0029] As a fifth limitation of the second limitation of the method for analyzing the mechanism of central nervous system drug treatment based on the system biology analysis, the cognitive disorder drug comprises oxiracetam; and the potential functional protein comprises an NMDA receptor.

[0030] This invention uses piracetam as the test drug and employs the aforementioned systemic biology-based analysis of central nervous system drug treatment mechanisms to investigate the mechanism of action of piracetam in treating Alzheimer's disease (AD). Multi-omics analysis aims to elucidate the overall expression patterns and network relationships of biomolecules, using high-throughput technology to screen differentially expressed molecules in AD patients before and after piracetam administration, providing clues for systematically identifying candidate targets. Receptor kinetics, belonging to the molecular functional level, focuses on dynamic processes such as receptor-ligand binding efficiency, conformational changes, and signal transduction rates, serving as a crucial "downstream validation" method for elucidating drug action mechanisms. The effective combination of these two approaches constructs a research loop of "broad screening → precise validation," avoiding the shortcomings of single-omics studies ("broad but vague") or single-kinetic studies ("precise but limited"). Ultimately, multi-omics research clarifies that the effect of piracetam in improving cognitive impairment is closely related to NMDA receptor-related pathways and receptor function. Finally, the kinetic effects of piracetam on NMDA receptors were studied using patch-clamp technique, verifying that piracetam can inhibit NMDA receptor currents and accelerate NMDA receptor desensitization, ultimately inhibiting NMDA receptor function and thus improving cognitive impairment. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1-1 This is a volcano plot for differential expression analysis using transcriptomics in this invention;

[0033] Figure 1-2 Cluster heatmap for transcriptomic differential expression analysis;

[0034] Figure 2-1 This is a bar chart showing the GO functional enrichment analysis of differentially expressed genes in transcriptomics in this invention.

[0035] Figure 2-2 This is a directed acyclic graph for the biological process of GO functional enrichment analysis of differentially expressed genes in transcriptomics in this invention;

[0036] Figure 2-3 This is a bar chart showing the up- and down-regulation of differentially expressed genes in transcriptomics using GO functional enrichment analysis in this invention.

[0037] Figure 2-4 This is a bubble diagram showing the enrichment of differentially expressed genes via the KEGG pathway in transcriptomics in this invention.

[0038] Figure 3Figure for proteomics differential expression analysis in the present application; wherein, Figure 3 A is a proteomics differential protein statistical chart, Figure 3 B is a proteomics differential protein clustering heat map;

[0039] Figure 4-1 Figure for differential protein GO function enrichment column chart (TOP 10) in proteomics analysis in the present application;

[0040] Figure 4-2 Figure for GO function enrichment column chart of up-regulated and down-regulated proteins based on biological process (BP) in the present application;

[0041] Figure 4-3 Figure for GO function enrichment column chart of up-regulated and down-regulated proteins of cellular component (CC) in the present application;

[0042] Figure 4-4 Figure for GO function enrichment column chart of up-regulated and down-regulated proteins based on molecular function (MF) in the present application;

[0043] Figure 4-5 Figure for KEGG pathway enrichment bubble chart (TOP 20) of differential proteins in the present application;

[0044] Figure 4-6 Figure for KEGG pathway enrichment column chart of up-regulated and down-regulated proteins in the present application;

[0045] Figure 5 Figure for protein interaction network analysis result in the present application;

[0046] Figure 6 Figure for differential protein domain enrichment analysis and subcellular localization result in the present application; wherein, Figure 6 A is a protein domain enrichment classification bubble chart (TOP 20), Figure 6 B is a protein subcellular localization distribution chart;

[0047] Figure 7 Figure for differential comparison chart of transcriptomics and proteomics joint analysis in the present application; wherein, Figure 7 A is a differential gene change trend Venn chart, Figure 7 B is a common differential gene clustering analysis heat map;

[0048] Figure 8-1 GO function enrichment Venn chart in the joint analysis of transcriptomics and proteomics in the present application;

[0049] Figure 8-2For the transcriptomics and proteomics combined analysis in the application, GO function enrichment column chart (TOP 10);

[0050] Figure 8-3 For the transcriptomics and proteomics combined analysis in the application, GO function enrichment bubble chart;

[0051] Figure 8-4 For the transcriptomics and proteomics combined analysis in the application, common enrichment GO function column chart (TOP 10);

[0052] Figure 8-5 For the transcriptomics and proteomics combined analysis in the application, BP-based common enrichment GO function network chart;

[0053] Figure 8-6 For the transcriptomics and proteomics combined analysis in the application, CC-based common enrichment GO function network chart;

[0054] Figure 9-1 For the transcriptomics and proteomics combined analysis in the application, KEGG pathway enrichment Venn chart;

[0055] Figure 9-2 For the transcriptomics and proteomics combined analysis in the application, KEGG pathway enrichment bubble chart;

[0056] Figure 9-3 For the transcriptomics and proteomics combined analysis in the application, KEGG pathway enrichment column chart (TOP 10);

[0057] Figure 9-4 For the transcriptomics and proteomics combined analysis in the application, common enrichment KEGG pathway network chart;

[0058] Figure 10 For the HEK 293T cells transfected with NMDA plasmid in the application, the NR1 / NR2A current schematic diagram and statistical results before and after olpracetam administration; wherein, 10A is a typical NR1 / NR2A current schematic diagram before and after olpracetam administration, Figure 10 B is an NR1 / NR2A receptor amplitude statistical chart before and after olpracetam administration;

[0059] Figure 11 For the HEK 293T cells transfected with NMDA plasmid in the application, the NR1 / NR2A receptor kinetics desensitization schematic diagram and the statistical chart of receptor current and Tau value change before and after olpracetam administration; wherein, Figure 11 A is the NR1 / NR2A receptor kinetics desensitization schematic diagram before and after olpracetam administration, Figure 11 B is the statistical chart of NR1 / NR2A receptor current and Tau value change before and after olpracetam administration;

[0060] Prot represents proteomics, trans represents transcriptomics; up is up-regulation, and down is down-regulation. DETAILED DESCRIPTION

[0061] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0062] Unless otherwise specified, the experimental methods, detection methods and preparation methods disclosed in the present application all adopt the conventional techniques in the technical field.

[0063] In order to better illustrate the embodiments of the present application, the following examples are further illustrated.

[0064] Example 1

[0065] The embodiments of the present application take olanzapine as an example to provide an analysis method for the treatment mechanism of central nervous system drugs based on systems biology analysis, and the specific content is as follows:

[0066] The research idea of the present application is as follows: 24 APP / PS1 transgenic mice of 8 months old, female and weighing 22-30 g are randomly divided into a drug administration group and a control group, 12 in each group. The drug administration group is continuously administered with olanzapine by gavage for 4 weeks, and the control group is administered with an equal dose of normal saline by gavage. Among them, olanzapine is administered by gavage, and the administration dose is 600 mg / Kg / time, 2 times / day.

[0067] After 4 weeks of administration, the hippocampus of the mice in the two groups is subjected to transcriptomic analysis (n=6), proteomic analysis (n=6) and combined analysis, the associated genes and proteins are screened, enrichment analysis is performed, and it is determined that the effect of olanzapine on improving cognitive impairment is closely related to the NMDA receptor related pathway and receptor function. Finally, the kinetic effect of olanzapine on NMDA receptor is studied by patch clamp technology, and it is verified that olanzapine can inhibit NMDA receptor current and accelerate the desensitization of NMDA receptor, thereby inhibiting the function of NMDA receptor and improving cognitive impairment.

[0068] I. Transcriptomic analysis

[0069] 1. RNA extraction and quality control

[0070] The total RNA in the hippocampus tissue of the mice in the two groups is extracted by TRIzol method, and the purity (OD 260 / 280RNA integrity (RIN≥8.0) was confirmed using Agilent 2100 Bioanalyzer. High purity, no DNA contamination and good integrity of RNA were obtained.

[0071] 2. Library construction

[0072] Using NEBNext Ultra RNA Library Prep Kit, ≥800 ng of total RNA was used as the starting material, Oligo(dT) magnetic beads were used to enrich polyA mRNA, and double-stranded cDNA was synthesized after fragmentation. After end repair, adapter ligation and PCR amplification, the final library was obtained by screening 200 bp inserts with AMPure XP magnetic beads. The library was quantified by Qubit 2.0, the insert size was detected by Agilent 2100, and the effective concentration (>2 nM) was verified by qRT-PCR.

[0073] 3. Sequencing

[0074] Double-end 150 bp sequencing was performed on the Illumina NovaSeq platform. Through the light signal capture of the fluorescently labeled dNTPs of the sequencer, the computer converts the sequence information into sequencing peaks, thereby obtaining the sequence information of the fragments to be tested.

[0075] 4. Data analysis

[0076] 4.1 Differential expression analysis

[0077] DESeq2 software (v1.16.1) was used for gene expression standardization and differential analysis, and the difference significance was calculated based on the negative binomial distribution model, with the screening criteria being |log2(FoldChange)|>1 and the corrected p<0.05, to obtain the differentially expressed genes (DEGs), and the ggplot2 and pheatmap packages were used to draw volcano plots and heat maps for visualization of differentially expressed genes.

[0078] The results of the transcriptomic differential expression analysis are shown in Figure 1-1 through Figure 1-2 , wherein, Figure 1-1 is the volcano plot of the transcriptomic differential expression analysis, Figure 1-2 is the clustered heat map of the transcriptomic differential expression analysis. Figure 1-1 In the figure, the horizontal axis represents the expression fold change (log2FoldChange), and the vertical axis represents the significance level of the difference (-log 10 pvalue); up-regulated genes are represented by red dots, and down-regulated genes are represented by green dots. Figure 1-2 The redder the color, the higher the expression of the corresponding gene; the greener the color, the lower the expression of the corresponding gene.

[0079] After data analysis combinedFigure 1-1 through Figure 1-2 It can be seen that compared with the APP / PS1 control group, there were 922 differential genes in the ORC administration group (p<0.05), of which 473 were up-regulated genes and 449 were down-regulated genes.

[0080] 4.2 Functional enrichment analysis

[0081] GO functional enrichment: GO (Gene Ontology) is a comprehensive database describing gene function. Through clusterProfiler, DEGs were annotated by Gene Ontology (GO), Biological Process (BP), Molecular Function (MF) and Cellular Component (CC), and significant items with p<0.05 were screened to analyze the receptor-related functional modules.

[0082] KEGG pathway enrichment: KEGG (Kyoto Encyclopedia of Genes and Genomes) is a comprehensive database integrating genomic, chemical and system function information. Based on the KEGG database, clusterProfiler was used to identify the signal pathways enriched by DEGs, with a threshold of p<0.05, to clarify the pathological and treatment-related pathways involved by the receptor.

[0083] The results of GO and KEGG enrichment analysis of differentially expressed genes in transcriptomics are shown in Figure 2-1 through Figure 2-4 , wherein Figure 2-1 is the column chart of GO functional enrichment analysis; Figure 2-2 is the directed acyclic graph of biological process of GO functional enrichment analysis; Figure 2-3 is the up and down column chart of GO functional enrichment analysis; Figure 2-4 is the bubble chart of KEGG pathway enrichment.

[0084] As shown in Figure 2-1 , the most significantly enriched biological processes in the administration group included neuromuscular process regulation balance, dendrite development and calcium ion transport (p<0.05), indicating that oxiracetam can alleviate NMDA receptor-mediated excitotoxicity by reducing synaptic overactivation or calcium overload.

[0085] As shown in Figure 2-2 , the administration group had nerve development and ion transport as the core nodes, and was associated with apoptosis process and inflammation regulation to form a dynamic regulation network.

[0086] As shown in Figure 2-3It can be seen that through the up-regulation and down-regulation analysis of differential genes, it is shown that the genes related to dendritic development and calcium ion transport in ORC are significantly down-regulated, and the negative regulation genes of leukocyte migration are up-regulated, which indirectly protects the neurons by enhancing the immune regulation of olanzapine.

[0087] By Figure 2-4 The effect of olanzapine on the related receptor pathway is shown, and it is found that the ratio of the number of differential genes of olanzapine affecting the AMPA / NMDA pathway to the total number of differential genes is relatively large.

[0088] In summary, it is speculated that olanzapine may target the calcium signal pathway and synaptic structure remodeling related to AMPA / NMDA receptors to synergistically improve the pathological characteristics of the AD model group.

[0089] II. Proteomics analysis

[0090] 1. Extraction and quantification of proteins

[0091] In the present application, the protein is extracted by homogenization combined with SDT lysis method, specifically: 50mg of hippocampus tissue is added into 500ul of SDT lysis solution (4%SDS, 100mM Tris-HCl, pH 7.6), and then broken by MP homogenizer (6.0M / S, 30s x 2 times), boiled for 10min after ultrasonic treatment, centrifuged and filtered to obtain supernatant, and then quantified by BCA method and stored in frozen state.

[0092] In the experiment, 100ug of protein is reduced by DTT, boiled and treated, and then sequentially washed by UA buffer, alkylated by IAA and replaced by NH4HCO3 through 30kD ultrafiltration tube, and then the peptide segments are collected after Trypsin enzymolysis for 16h, C 18 desalination and freeze-drying.

[0093] The target protein is quantified and analyzed by LC-MS / MS method, and the instrument model is Orbitrap Exploris480 (mass spectrometer) + EASY-nLC TM 1200 (liquid phase), and the liquid chromatography uses PepMap RSLC column, 0.1%formic acid aqueous solution (A liquid) and 80%acetonitrile (B liquid) as mobile phase, gradient elution at 300nL / min for 60min, and column temperature box temperature 55℃.

[0094] Mass spectrometry parameters: positive ion mode detection, ion source type is nanospray ion source, positive ion spray voltage is 2100V, ion transmission tube temperature is 320℃, carrier gas total flow is 4.6L / min, FAIMS inner electrode temperature and outer electrode temperature are both 100℃. Primary resolution 120000 (m / z 350-1200), secondary resolution 15000, HCD fragmentation (NCE 33%).

[0095] 2. Processing of protein data

[0096] The present application uses Maxquant to analyze DDA mode mass spectrometry data, and realizes Label-free quantification based on MS1 integration. The software automatically identifies peptide segment characteristics and integrates FDR screening (≤1%) qualitative results, and outputs a comprehensive data table containing intensity, sequence and modification site. The sample is subjected to missing value inspection and processing.

[0097] 3. Data analysis

[0098] 3.1 Significant difference analysis of proteomics

[0099] The t_test function of R software is used to evaluate the significant difference of each protein, and the expression difference is represented by FC change. The screening criteria for differentially expressed proteins are p<0.05 and FC≥1.2 or ≤0.83. FC≥1.2 is taken as the up-regulated protein, FC≤0.83 is taken as the down-regulated protein, and the ggplot2 and pheatmap packages are used to draw bar charts and heat maps.

[0100] The proteomics differential expression analysis result chart is as shown in Figure 3 , wherein Figure 3 A is a proteomics differential protein statistical chart, wherein blue is up-regulated (Up-regulated) and green is down-regulated (Down-regulated). Figure 3 B is a clustering heat map of proteomics differential proteins, wherein the relative content of the differential proteins is represented by different colors, and yellow represents high expression and blue represents low expression.

[0101] Through data analysis and Figure 3 it can be known that compared with the APP / PS1 control group, the drug group has a total of 152 differential proteins (p<0.05), of which 72 are up-regulated and 80 are down-regulated.

[0102] 3.2 Functional enrichment analysis of differential proteins

[0103] The GO and KEGG enrichment analysis results of the differential proteins in proteomics analysis are as shown in Figure 4-1 through Figure 4-6 . Among them, the GO function enrichment bar chart (TOP 10) of the differential proteins is as shown in Figure 4-1 , the GO function enrichment bar chart of the up-regulated and down-regulated proteins based on BP is as shown in Figure 4-2 , the GO function enrichment bar chart of the up-regulated and down-regulated proteins based on CC is as shown in Figure 4-3 , the GO function enrichment bar chart of the up-regulated and down-regulated proteins based on MF is as shown in Figure 4-4 , and the enrichment bubble chart (TOP20) of the KEGG pathway of the differential proteins is as shown in Figure 4-5 , and the KEGG pathway enrichment bar chart of the up-regulated and down-regulated proteins is as shown inFigure 4-6 As shown in FIG. 6, wherein blue represents up-regulation and green represents down-regulation.

[0104] By Figure 4-1 and Figure 4-3 It can be seen that the differential proteins are significantly enriched in histone deacetylase complex;

[0105] Figure 4-2 It is shown that the Wnt signaling pathway is enriched in the administration group, indicating that oxiracetam improves synaptic function by activating the Wnt pathway and epigenetic modification;

[0106] Figure 4-3 and Figure 4-4 Among them, the down-regulation of positive regulation of Wnt signaling pathway and Wnt-activated receptor activity indicates that oxiracetam may regulate synaptic homeostasis by inhibiting the overactivation of the Wnt pathway;

[0107] By Figure 4-5 It is found that the FoxO signaling pathway and the JAK-STAT pathway are significantly enriched in KEGG analysis, and both of them are involved in the regulation of apoptosis in neurodegenerative diseases;

[0108] Figure 4-6 It is shown that the Ferroptosis pathway and the nicotinamide pathway are significantly up-regulated, and the Ferroptosis pathway is closely related to iron accumulation and lipid peroxidation caused by excessive activation of glutamate receptors (NMDA), suggesting that oxiracetam may inhibit NMDA receptor activity to reduce AD pathological conditions.

[0109] 3.3 Protein-protein interaction network analysis of differential proteins

[0110] Protein-protein interaction (PPI) network construction: The protein-protein interaction relationships of differential genes were extracted from the STRING database to construct a PPI network. The proteins with p<0.05 and the most significant expression difference were selected as target proteins for direct interaction network analysis, and the visualization was performed with the help of Cytoscape software.

[0111] The PPI analysis result graph is shown in FIG. 7, wherein the blue nodes are the most up-regulated proteins, and the cyan nodes are the most down-regulated proteins. It can be seen that the hub protein Plp1 may indirectly affect the excitability of neurons and affect the synaptic localization of AMPA receptors by maintaining myelin stability, and Syt2 is involved in synaptic vesicle release and related to NMDA receptor calcium signaling. Figure 5 Figure 5

[0112] ​​3.4 Domain annotation and enrichment analysis of differential proteins

[0113] InterPro database was used to annotate the domains of differential proteins. The conserved domains and functional sites were batch-identified by InterProScan tool. Fisher's exact test was used to compare the distribution frequency of specific domains in differential proteome with the background distribution of whole proteome, and to screen significantly enriched domains (p<0.05).

[0114] 2.3.5 Subcellular localization of differential proteins

[0115] WoLF PSORT 4.0 software was used to predict the subcellular localization of differential proteins based on sorting signals, amino acid composition and functional motifs. The differential protein sequences in FASTA format were input, the species type (animal) was selected, and the subcellular localization results of proteins were output.

[0116] The results of domain enrichment analysis and subcellular localization of differential proteins are shown in Figure 6 , in which the enrichment classification bubble chart of protein domains (TOP 20) is shown in Figure 6 A, in which the circle color represents the -log10 transformed P value, the darker the color, the smaller the P value, and the circle size represents the number of differential proteins contained in the pathway. The distribution chart of protein subcellular localization is shown in Figure 6 B, in which different colors represent different cell sites, and the percentage represents the proportion of proteins belonging to the localization among all differential proteins.

[0117] As shown in Figure 6 , the S100 / CaBP-9k-type calcium binding domain (p<0.05) and Growth factor receptor cysteine domain (p<0.05) significantly recovered after olprinquine treatment, which are closely related to the functional regulation of AMPA / NMDA receptors. The mechanism of olprinquine may be to improve AD pathology by regulating NMDA receptor-dependent calcium signaling and AMPA receptor-mediated synaptic plasticity. In addition, the Sirtuin family catalytic core domain (p<0.01) may improve mitochondrial function and indirectly maintain the normal activity of AMPA / NMDA receptors.

[0118] As shown in Figure 6 , the S100 / CaBP-9k-type calcium binding domain (p<0.05) and Growth factor receptor cysteine domain (p<0.05) significantly recovered after olprinquine treatment, which are closely related to the functional regulation of AMPA / NMDA receptors. The mechanism of olprinquine may be to improve AD pathology by regulating NMDA receptor-dependent calcium signaling and AMPA receptor-mediated synaptic plasticity. In addition, the Sirtuin family catalytic core domain (p<0.01) may improve mitochondrial function and indirectly maintain the normal activity of AMPA / NMDA receptors.It can also be seen that the differential proteins of the administration group and the control group are mainly distributed in the nucleus (28.3%), cytoplasm (19.7%), mitochondria (19.7%) and plasma membrane (17.1%). Among them, the proportion of plasma membrane localization proteins is directly related to the postsynaptic membrane function of AMPA / NMDA receptors. The significant recovery (p<0.05) of the growth factor receptor cysteine in the domain enrichment analysis suggests that the drug may promote the transport of receptors to the plasma membrane and inhibit endocytosis by activating BDNF-TrkB and other neurotrophic signals, thereby enhancing synaptic plasticity. In addition, the decrease in the proportion of extracellular localization proteins (10.5%) may reflect the inhibition of amyloid (Aβ) deposition or inflammatory factor release by the drug, which indirectly protects the receptors from pathological damage.

[0119] III. Combined analysis of transcriptomics and proteomics

[0120] 1. Differential comparison of transcriptomics and proteomics

[0121] Combined omics analysis can more comprehensively screen the key pathways of drug action. Based on the quality inspection of total RNA and proteins extracted from the above samples, the identification results obtained by sequencing, including differentially expressed transcripts and differentially expressed proteins, are subjected to correlation analysis. The differential gene screening criteria are: |log2FC|>1 and corrected p<0.05; the differential protein screening criteria are: |log2FC|≥0.263 and corrected p<0.05. Venn diagram is drawn using ggplot2, and Venn analysis is used to compare the differential gene expression results of the two omics, and the common and unique differential expressed genes of the two omics are directly displayed. The FC values (log2FC) of the common differential genes obtained by Venn analysis in the two omics are subjected to cluster heat map analysis, and pheatmap package is used for visualization. The combined analysis of transcriptomics and proteomics is shown in FIG. 1. Among them, the differential gene change trend Venn diagram is shown in FIG. 1A, and the numbers in the intersection of the Venn diagram are the number of differential molecules with the same or opposite change trend in the two omics; the numbers in other areas represent the number of differential molecules specific to the transcriptome and proteome, respectively. The cluster analysis heat map of common differential genes is shown in FIG. 1B, and each list represents one omics (left for transcriptome and right for corresponding proteome). The color in the figure represents the size of |log2FC| value, and yellow represents the up-regulation of the protein / mRNA in the omics level, and blue represents the down-regulation in the omics level. Figure 7 Figure 7 Figure 7

[0122] As shown in FIG. 1A, the number of differential molecules with the same or opposite change trend in the two omics is 1, and the number of differential molecules specific to the transcriptome and proteome is 1, respectively. As shown in FIG. 1B, the color in the figure represents the size of |log2FC| value, and yellow represents the up-regulation of the protein / mRNA in the omics level, and blue represents the down-regulation in the omics level. Figure 7 ​​​It can be seen that compared with the ORC administration group, the APP / PS1 control group has 473 up-regulated genes and 449 down-regulated genes in the transcriptome, and 72 up-regulated proteins and 80 down-regulated proteins in the proteome. Venn analysis further shows that the combined analysis of the transcriptome and the proteome identifies four common differential molecules, three up-regulated molecules and one down-regulated molecule. These differential molecules are related to the regulation of neuroinflammation (CD34 antigen), mitochondrial autophagy (TBC1 domain family member 13), negative regulation of glutamate receptor signaling (histidine triad nucleotide-binding protein 1), and myelin integrity regulation (oligodendrocyte-specific protein Opalin).

[0123] And there are 918 and 148 unique differential genes in the transcriptome and proteome respectively, indicating that the mechanism of action of oxiracetam is heterogeneous at the gene and protein level. Cluster heat map analysis of the log2FC values of the common differential genes found that their expression trends were highly consistent in the two omics, suggesting a synergistic regulatory mechanism in the action of oxiracetam.

[0124] 2. Functional enrichment analysis of associated genes and proteins

[0125] The above interrelated genes and proteins were further subjected to functional enrichment analysis. Functional enrichment analysis used DGO annotation, covering three categories of biological processes, cellular components and molecular functions; the number of enriched GO functions was displayed using a Venn diagram, the top 10 pathways with the smallest p value in each omics were selected to make a bubble chart, and the number of differential mRNAs and differential proteins enriched in each GO function were summed and statistically analyzed, and the top 10 GO functions with the most total differential molecules (differential mRNAs + differential proteins) were selected to make a column chart. The differential molecules obtained by combined analysis of transcriptomics and proteomics were subjected to KEGG pathway integration analysis, and the screening threshold was set to p<0.05. Visualization was performed using the ggplot2 package and the pheatmap package.

[0126] 2.1 GO function enrichment analysis

[0127] The results of GO function enrichment analysis of the associated genes and proteins are shown in Figure 8-1 through Figure 8-6 . Among them, the GO function enrichment Venn diagram in the combined analysis of transcriptomics and proteomics is shown in Figure 8-1 . The GO function enrichment column chart (TOP 10) in the combined analysis of transcriptomics and proteomics is shown in Figure 8-2 . The GO function enrichment bubble chart in the combined analysis of transcriptomics and proteomics is shown in Figure 8-3Figure 6 shows the GO function enrichment results of the transcriptome and proteome. The vertical axis represents the GO function name; the horizontal axis represents the GeneRatio, which is the ratio of the number of differential molecules enriched in the GO function to the total number of molecules contained in the GO function in the GO database. The triangle is the transcriptome result; the circle is the proteome result. The color in the figure represents the significance of enrichment (-log 10 transformed GO function significance p value), and the closer the color is to purple, the smaller the p value and the higher the significance of enrichment; the shape size represents the number of differential molecules enriched in the GO function, and the larger the shape, the greater the number of differential molecules in the GO function. In the joint analysis of transcriptomics and proteomics, the column chart of common enriched GO functions (TOP 10) is shown in Figure 7. Figure 8-4 In the joint analysis of transcriptomics and proteomics, the network diagram of common enriched GO functions based on BP is shown in Figure 8. Figure 8-5 In the joint analysis of transcriptomics and proteomics, the network diagram of common enriched GO functions based on CC is shown in Figure 9. Figure 8-6 Figure 8-5 through 8-6 In the joint analysis of transcriptomics and proteomics, the network diagram of common enriched GO functions based on BP is shown in Figure 8.

[0128] Figure 8-1 through Figure 8-6 reflects the commonality and specificity of the GO function enrichment results of transcriptomics and proteomics.

[0129] The transcriptome and proteome are enriched in 245 and 290 GO functions, respectively, of which 10 are common pathways (see Figure 8-1 , indicating that there are differences between the two omics at the functional level.

[0130] As can be seen from Figure 8-2 , the significant pathways selected based on differential molecules, calcium ion transport and protein serine / threonine kinase activity, are highly related to the physiological functions of AMPA / NMDA receptors, suggesting that oxiracetam may act by regulating calcium homeostasis and phosphorylated subunit receptors.

[0131] Figure 8-3 Further, the pathways of calcium ion transport and neuromuscular process controlling balance are significantly enriched in the number of differential molecules, suggesting that calcium signaling and neuromuscular process controlling balance are key targets of oxiracetam, and the function of AMPA / NMDA receptors as calcium permeable channels may be affected.

[0132] Figure 8-4 ​The TOP 10 pathways common to both omics, among which neuromuscular process controlling balance, synapse maturation, etc. pathways showed high significance and high number of accumulated molecules in both omics. In the common GO function network graph, synapse maturation was highly associated with calcium regulation genes (Camk2b, Grb2) (see Figure 8-5 ). The postsynaptic density anchored receptors through scaffold proteins (Dlg4) (see Figure 8-6 ), indicating that oxiracetam might maintain receptor function by stabilizing the postsynaptic structure.

[0133] In summary, oxiracetam might target the AMPA / NMDA receptor-mediated neural signaling by regulating calcium ion transport, synapse maturation and postsynaptic density related pathways, thereby improving the pathological phenotype of Alzheimer's disease models.

[0134] 2.2 KEGG enrichment analysis

[0135] The KEGG enrichment analysis results of associated genes and proteins are shown in Figure 9-1 through Figure 9-4 . Among them, the KEGG pathway enrichment Venn diagram in the joint analysis of transcriptomics and proteomics is shown in Figure 9-1 . The number in the intersection of the Venn diagram is the number of KEGG pathways enriched by both omics; the numbers on the two sides represent the number of KEGG pathways specifically enriched by proteomics and transcriptomics, respectively. The KEGG pathway enrichment bubble chart in the joint analysis of transcriptomics and proteomics is shown in Figure 9-2 . Among them, the vertical coordinate is the KEGG pathway name; the horizontal coordinate is GeneRatio, which represents the ratio of the number of differential molecules enriched in the KEGG pathway to the total number of molecules contained in the function in the KEGG database. The triangle is the transcriptomics result; the circle is the proteomics result. The color in the figure represents the significance of enrichment (-log10 transformed KEGG pathway significance p value), the closer to purple color, the smaller the p value, the higher the significance of enrichment; the shape size represents the number of differential molecules enriched in the KEGG pathway, the larger the shape, the more the number of differential molecules in the KEGG pathway. The KEGG pathway enrichment column chart (TOP 10) in the joint analysis of transcriptomics and proteomics is shown in Figure 9-3 . The common enriched KEGG pathway network graph in the joint analysis of transcriptomics and proteomics is shown in Figure 9-4 . Among them, the orange pentagon is the KEGG pathway common to both omics; the green circle is the differential gene / protein; the connection line represents the attribution relationship between the differential molecule and the KEGG enriched pathway.

[0136] Figure 9-1The results showed that the number of KEGG pathways co-enriched by transcriptomics and proteomics was limited, indicating that there were certain differences between the regulation at the transcriptional and protein levels. Figure 9-2 and Figure 9-3 The results showed that oxiracetam was significantly enriched in AD core pathways (such as "Alzheimer disease") and metabolic pathways (such as "Purine metabolism"), suggesting that it plays a role by regulating glutamate metabolism and synaptic plasticity. Figure 9-4 Among the common enriched KEGG pathway network (p<0.01), the "Glycosphingolipid biosynthesis-ganglio series" pathway was closely related to genes Glb1, Hexa, St3gal1 / 2, etc. This pathway is involved in the metabolism of gangliosides, which are key components of neuronal membranes, indicating that oxiracetam may enhance receptor anchoring sites by maintaining neuronal membrane stability, thereby improving synaptic function.

[0137] In summary, the results of functional enrichment analysis of differentially expressed genes in transcriptomics showed that oxiracetam alleviated NMDA receptor-mediated excitotoxicity by reducing synaptic overactivation or calcium overload, and may target the calcium signaling pathway and synaptic structural remodeling related to AMPA / NMDA receptors to improve the pathological characteristics of the AD model group.

[0138] The results of functional enrichment analysis of differentially expressed proteins in proteomics showed that the ferroptosis pathway and the nicotinamide pathway were significantly upregulated in the oxiracetam administration group. The ferroptosis pathway is closely related to iron accumulation and lipid peroxidation caused by excessive activation of glutamate receptors (NMDA), suggesting that oxiracetam may alleviate AD pathology by inhibiting NMDA receptor activity. PPI network analysis showed that the hub protein Plp1 may indirectly affect neuronal excitability and AMPA receptor synaptic localization by maintaining myelin stability, and Syt2 is involved in synaptic vesicle release and related to NMDA receptor calcium signaling. Differential protein domain enrichment analysis showed that the significantly restored S100 / CaBP-9k-type calcium-binding domain (p<0.05) and Growth factor receptor cysteine domain (p<0.05) after oxiracetam treatment were closely related to the functional regulation of AMPA / NMDA receptors.

[0139] The results of joint analysis of transcriptomics and proteomics showed that oxiracetam was significantly enriched in AD core pathways (such as "Alzheimer disease") and metabolic pathways (such as "Purine metabolism") and synaptic-related pathways, suggesting that it plays a role by regulating glutamate metabolism and synaptic plasticity.

[0140] Four, receptor kinetics analysis

[0141] The transcriptomic analysis, the proteomic analysis and the combined analysis of both show that the action of oxiracetam is closely related to NMDA receptor, which is a potential functional protein for the action of oxiracetam. The gating state of NMDA receptor mainly includes three types: closed state, activated state and desensitized state. When an agonist binds to NMDA receptor, the NMDA receptor is rapidly activated, and when the agonist leaves the NMDA receptor, the receptor is rapidly inactivated, and the inactivation constant is generally tens to thousands of milliseconds according to the different types of receptor subtypes; when the agonist and the receptor dissociate, the NMDA receptor enters the desensitized state, and the desensitization process is usually relatively slow. In the present application, patch clamp technology is used to study the receptor kinetics of the potential functional protein NMDA receptor, so as to confirm or verify the action mechanism of oxiracetam.

[0142] 1. NMDA plasmid transfection

[0143] The NMDA plasmid selected in the present application is disclosed in the paper "Chelerythrine inhibits NR2B NMDA receptor independent of PKC activity", and the mass mixing ratio of NR1:NR2A:pEGFP is 1:1:0.13 when the plasmid is constructed.

[0144] HEK 293T cells were seeded into a 24-well cell culture plate containing a 13-mm glass round piece at a density of 7000 cells per well, and the culture system was DMEM medium added with 50 μM AP5, which was cultured overnight at 37°C, 5% CO2. NMDA plasmid transfection was performed using LIPO2000 (Invitrogen, item number 11668019) liposome, and the transfection method was performed according to the LIPO 2000 instruction, and the transfection was performed with serum-free medium Opti-MEM and LIPO 2000 according to the mass ratio of 2:1. The purpose of green fluorescent protein pEGFP participating in transfection is to identify whether HEK 293T cells express recombinant plasmid.

[0145] After 6 hours of plasmid transfection, the cell culture solution was replaced, and the cell culture solution containing the transfection reagent was replaced with complete culture solution containing 500 μM AP5. The cell death caused by excessive activation of NMDA receptor is reduced. After replacing the culture medium, the cells were placed in a 37°C, 5% CO2 incubator for continuous culture for 24 h, and the transfection was observed under a fluorescence microscope, and subsequent whole-cell voltage clamp recording and molecular biology experiments were performed.

[0146] 2. Patch clamp

[0147] The HEK 293T cells transfected with NMDA plasmid were resuspended, and the density was 1×10 42 mL of cell suspension at 1.0 x 106cells / mL was inoculated on 13 mm cell climbing sheet, and placed in 37℃, 5% CO2 incubator for 6 h before subsequent patch clamp experiment. Whole cell voltage clamp was used for recording in this experiment, and the sampling frequency was set to 20 kHz, and the filter was set to 3 kHz. The self-made multi-tube drug delivery system was used for perfusion, and the stable transfected cells induced on the cover glass were transferred to the recording tank, and the prepared magnesium-free NR2A extracellular solution was continuously perfused at a speed of 1 mL / min. 1 mM glutamate (Glu) and 10 μM glycine (Gly) were used as inducers for HEK 293T cells expressing NMDA plasmid to induce receptor current, and whether olanzapine had inhibitory effect on receptor current was investigated.

[0148] The inhibition of olanzapine on NR2A current was analyzed by Igor Pro 6.10A, and the dose-effect curve was analyzed by Hill equation:

[0149] I = Bottom + (Top-Bottom) / (1 + 10 (LgIC50-X)×HillSlope ).

[0150] The time constant of desensitization was fitted by double exponential fitting:

[0151]

[0152] The time constant of desensitization was fitted by the average value of 10 continuous current cycles.

[0153] (1) First, the whole-cell patch clamp technique was used to record the NR1 / NR2A current of HEK 293T cells transfected with NMDA plasmid before and after olanzapine administration. The HEK 293T cells transfected with NMDA plasmid were cultured in olanzapine before and after administration

[0154] The schematic diagram of NR1 / NR2A current and statistical results are shown in Figure 10 . Among them, 10A is the typical

[0155] NR1 / NR2A current diagram, Figure 10 B is the statistical diagram of NR1 / NR2A receptor amplitude before and after olanzapine administration.

[0156] As can be seen from Figure 10 , olanzapine can significantly reduce the current of NR1 / NR2A, and the amplitude is reduced to 82.42 ± 4.078% (n = 7, p < 0.01) of the original, which indicates that olanzapine can directly inhibit the function of NMDA receptor.

[0157] (2) By Outside-out patch clamp technique, the NMDA receptor kinetics desensitization experiment was studied. The NR1 / NR2A receptor kinetics desensitization schematic diagram and the receptor current and Tau value change statistical chart before and after administration of oxiracetam are shown in Figure 11 Figure 11 A is the NR1 / NR2A receptor kinetics desensitization schematic diagram before and after administration of oxiracetam, Figure 11 B is the NR1 / NR2A receptor current and Tau value change statistical chart before and after administration of oxiracetam.

[0158] It can be known from Figure 11 that oxiracetam has a significant effect on the desensitization of NR1 / NR2A in NMDA receptor, and can obviously accelerate the desensitization of NMDA. After administration of oxiracetam, the original Tau value 0.2070±0.024s is significantly reduced to 0.1660±0.012s (n=10, *p<0.05), and the current peak is reduced from the original 458.6±94.45pA to

[0159] 346.5±64.88pA (n=10, *p<0.05). The kinetics research results show that oxiracetam can promote the desensitization of NR2A receptor channel, thereby reducing the cations entering through the NMDA receptor, and finally producing an inhibitory effect on the function of NMDA receptor.

[0160] The above only describes the preferred embodiments of the present application, and is not used to limit the present application, and any modification, equivalent replacement or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.​

Claims

1. An analysis method of a mechanism of a central nervous system drug treatment based on a system biology analysis, characterized by, The system biology analysis comprises transcriptomics analysis, proteomics analysis and receptor kinetics analysis.

2. The method for analyzing the mechanism of central nervous system drug therapy based on systems biology analysis as described in claim 1, characterized in that, The system biology analysis further comprises transcriptomics and proteomics joint analysis.

3. The method for analyzing the mechanism of central nervous system drug therapy based on systems biology analysis as described in claim 1, characterized in that, The analysis method comprises the following steps: S1. Extracting RNA in the hippocampus tissue of the cognitive impairment organism before and after administration of the test drug, screening differentially expressed genes and performing enrichment analysis to obtain differential genes and differential pathways 1; Extracting total protein in the hippocampus tissue of the cognitive impairment organism before and after administration of the test drug, screening differential proteins and performing functional enrichment analysis to obtain differential proteins and differential pathways 2; S2. Based on the transcriptomics and proteomics joint analysis, screening associated genes and proteins, and performing functional enrichment analysis and correlation analysis to determine potential functional proteins; S3. Using patch clamp technology, verifying the target of the test drug by analyzing the binding affinity and kinetic parameters of the potential functional protein and the test drug.

4. The method for analyzing the mechanism of central nervous system drug therapy based on systems biology analysis as described in claim 3, characterized in that, Step S1 specifically comprises: extracting total RNA in the hippocampus tissue of the cognitive impairment organism before and after administration of the test drug, screening differentially expressed genes in hippocampal cells, performing GO functional enrichment analysis and KEGG pathway enrichment analysis on the differentially expressed genes to obtain differential genes and differential pathways 1; extracting total protein in the hippocampus tissue of the cognitive impairment organism before and after administration of the test drug, screening differentially expressed proteins in hippocampal cells, performing GO functional enrichment analysis and KEGG pathway enrichment analysis on the differential proteins to obtain differential proteins and differential pathways 2; constructing a PPI network, and then performing enrichment analysis on the domains of the differential proteins and locating the subcell of the differential proteins; and / or Step S2 specifically comprises: based on the results of the transcriptomics and proteomics joint analysis, obtaining common genes and unique genes of the two omics and performing venn analysis, and performing correlation analysis on the common genes to screen key genes, key proteins and key signal pathways.

5. The method of claim 4, wherein the method is based on a system biology analysis of the mechanism of the central nervous system drug treatment. 5 In step S1, the screening criteria for the differential genes are: |log2FC|>1 and p<0.05 after correction in the two groups before and after administration of the test drug; and / or In step S1, the screening criteria for the differential proteins are: |log2FC|≥0.263 and p<0.05 after correction in the two groups before and after administration of the test drug.

6. The method of claim 3, wherein the method is based on a system biology analysis of the mechanism of the central nervous system drug treatment. In step S2, in the transcriptomics and proteomics joint analysis, the screening criteria for associated genes in the transcriptomics analysis are: |log2FC|>1 and p<0.05 after correction; the screening criteria for associated proteins in the proteomics analysis are: |log2FC|≥0.263 and p<0.05 after correction; and / or Step S3 specifically comprises: constructing a plasmid containing the potential functional protein and transfecting cells to obtain cells containing the potential functional protein; Using whole-cell patch clamp technology, detecting the change of current of the cells before and after adding the test drug to verify whether the test drug has a significant inhibitory or promoting effect on the potential functional protein; and / or The Outside-out patch clamp technique is used to detect the current change of the cell before and after adding the test drug in the presence of the agonist containing the potential functional protein, so as to verify whether the test drug can induce the desensitization of the potential functional protein channel.

7. The method for analyzing the mechanism of central nervous system drug therapy based on systems biology analysis as described in claim 3, characterized in that, The potential functional protein includes at least one of a potential synaptic protein or a potential receptor protein.

8. The method of claim 1 to 7, wherein the method is characterized by, The central nervous system drug includes a cognitive impairment drug.

9. The method of claim 3 to 7, wherein the method is characterized by, The central nervous system drug includes olanzapine. The potential functional protein includes an NMDA receptor.

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