CN111128294A - A method for screening active ingredients for the same treatment of different diseases using a dual-disease model animal model - Google Patents
A method for screening active ingredients for the same treatment of different diseases using a dual-disease model animal model Download PDFInfo
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Abstract
本发明公开了一种利用双疾病模式动物模型筛选异病同治活性成分的方法，对化合物进行初步筛选，获得候选化合物；在线预测候选化合物靶点；建立化合物‑靶点交互作用分子网络；获取同时与OP和AD相关的基因作为后续分析靶点，并建立两种疾病的共同分子网络；将前述分子网络映射到共同分子网络上，筛选活性化合物‑靶点交互网络，对其进行拓扑学参数分析，筛选出关键化合物；构建模式动物并进行双效化合物及其组合物的药效和潜在靶点的验证；富集分析，获得活性化合物作用机制；对化合物结构分类，构建分类药物‑靶点交互网络，获得不同类型化合物作用差异。本发明高效、精准的筛选了双效活性化合物，同时构建了进行异病同治及药效评价系统。
The invention discloses a method for screening active ingredients of different diseases with the same treatment by using a dual-disease model animal model. The compounds are preliminarily screened to obtain candidate compounds; the target points of the candidate compounds are predicted online; the compound-target interaction molecular network is established; Genes related to OP and AD are used as the target for subsequent analysis, and a common molecular network of the two diseases is established; the aforementioned molecular network is mapped to the common molecular network, the active compound-target interaction network is screened, and topological parameter analysis is performed on it , screen out key compounds; construct model animals and verify the efficacy and potential targets of dual-effect compounds and their compositions; enrichment analysis to obtain the mechanism of action of active compounds; classify compound structures and construct classified drug-target interactions network to obtain the differences in the effects of different types of compounds. The invention can efficiently and accurately screen the dual-effect active compounds, and simultaneously construct a system for treating different diseases with the same effect and evaluating the drug effect.
Description
Technical Field
The invention relates to chemical medicine, in particular to a method for screening active ingredients for treating different diseases simultaneously by using a double-disease model animal model.
Background
Osteoporosis (OP) is a systemic skeletal disease characterized by decreased bone mass and impaired bone microarchitecture, with increased bone fragility leading to increased risk of fracture. Alzheimer's Disease (AD) is a common degenerative Disease of the nervous system characterized by the formation of senile plaques and neurofibrillary tangles, leading to loss of memory and other cognitive functions. With the increasing trend of aging of the population, the prevalence of OP and AD increases year by year, bringing about a huge social burden. OP and AD are frequently complicated clinically as very common geriatric diseases, and more studies indicate that there is some connection between the pathogenesis of both. However, due to its complex etiology and pathogenesis, there is currently no effective enough therapy to completely prevent or stop the development of the disease, with common side effects.
The theory of traditional Chinese medicine is taken as guidance, and the characteristics of multiple components, multiple targets and multiple channels of the traditional Chinese medicine are utilized to exert the unique advantages of the traditional Chinese medicine in the aspect of treating some complex chronic diseases. The cistanche or cistanche tubulosa collected in the pharmacopoeia of 2015 edition has sweet, salty and warm properties, enters kidney and large intestine channels, tonifies kidney yang, benefits essence and blood, and relaxes bowel to relieve constipation, can treat kidney yang deficiency, essence and blood deficiency, impotence and infertility, soreness and weakness of waist and knees, and weakness of muscles and bones, and is widely used for treating OP and AD clinically. Modern researches also show that the cistanche or cistanche tubulosa extract or some components have obvious pharmacological activity on bones and nervous systems. However, due to the complex and diverse components, the active ingredients and action mechanisms thereof have not been completely elucidated.
The term "treating different diseases simultaneously" refers to different diseases, and the disease is treated by the same method because the same pathogenesis appears in the course of the development. The kidney stores essence, governs bone, produces marrow, and is communicated with the brain, and OP and AD have homology of pathogenesis of traditional Chinese medicine based on the theory of traditional Chinese medicine of four-in-one of kidney-bone-marrow-brain. The traditional Chinese medicine holds that the basic pathogenesis of the two diseases is the disease caused by the deficiency of kidney essence and no generation of marrow, which indicates that the kidney-tonifying herbs of cistanche or cistanche tubulosa can play the role of 'treating different diseases simultaneously'.
Network pharmacology is based on the theory of system biology, emphasizing multi-pathway regulation of pathways. Network pharmacology follows the mode of 'multiple medicines, multiple genes and multiple diseases', and is in accordance with the principles of holistic concept, syndrome differentiation and treatment, synergistic compatibility and the like of the traditional Chinese medicine, so that the network pharmacology is widely applied to various researches in the field of the traditional Chinese medicine.
Zebrafish, nematodes, fruit flies and the like are model organisms which are widely applied at present. The zebra fish genome is highly similar to human, has a complete skeleton system, has the functions of a main neurotransmitter system similar to those of mammals, and has the advantages of rapid in vitro development of embryos, relatively quick and convenient model establishment and capability of becoming a novel model animal for researching the skeleton and the nervous system. Caenorhabditis elegans has high propagation speed, the genome is similar to that of human beings, and besides, the immune regulation mechanism and the aging-related signal path of the caenorhabditis elegans are similar to those of mammals, so that the caenorhabditis elegans is widely applied as an ideal model animal for researching developmental biology and neurobiology at present. The drosophila melanogaster is small in physique, easy to feed, mature in genetic operation means, and has complex social behaviors, and plays an important role in researches of genetics, developmental biology, neurobiology, cytobiology, immunology and the like.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to provide a method for screening active ingredients for treating different diseases simultaneously by using a double-disease model animal model.
The technical scheme is as follows: the invention provides a method for screening active ingredients for treating different diseases simultaneously by using a double-disease model animal model, which comprises the following steps:
(1) primarily screening the compound by taking relevant pharmacological parameters as indexes to obtain a candidate compound;
(2) predicting candidate compound targets on line;
(3) establishing a compound-target interaction molecular network through computer software;
(4) collecting all genes related to OP and AD from a gene database related to diseases, only reserving the genes related to OP and AD simultaneously as subsequent analysis targets, and establishing a common molecular network of the two diseases through computer software;
(5) mapping the molecular network in the step (3) to the common molecular network in the step (4), and screening an active compound-target interaction network;
(6) performing topological parameter analysis on the active compound-target interaction network, and screening out key compounds;
(7) constructing model animals and verifying the drug effect and potential target of the double-effect compound and the composition thereof;
(8) obtaining an action mechanism of the active compound by combining GO biological function annotation and KEGG signal channel enrichment analysis;
(9) and (4) constructing a classified drug-target interaction network according to the structural classification of the compounds to obtain the action difference of different types of compounds.
Further, the physiologically relevant parameters in the step (1) are Molecular Weight (MW), octanol-water partition coefficient (AlogP), hydrogen donor number (Hdon) and hydrogen acceptor number (Hacc), respectively.
Further, in the step (1), the drug-like property (DL) is not less than 0.18 as the condition for primary screening of the compound.
Further, the active compounds in the step (5) comprise 5 phenylethanoid glycosides, 3 phenylpropionyl oligosaccharides, 3 iridoids and glycosides thereof, 3 lignans and glycosides thereof, 2 flavonoids, 1 alkaloid, 1 triterpene, 1 sterol, 1 fatty alcohol and 1 fatty acid.
Further, the active compounds comprise phenylethanoid glycosides, flavonoids, sterols and triterpenoids.
Further, the active compound is a flavonoid.
Further, the active compounds include:
further, the model animal in the step (8) is a double disease model animal model.
Further, the double-disease model animal model is a zebra fish double-disease model animal model.
The principle of the technical scheme of the invention is explained as follows:
firstly, integrating a plurality of databases based on network pharmacology, carrying out large-scale text mining, collecting chemical components of the traditional Chinese medicine, simultaneously respectively inquiring information of components, OP and AD related genomes and proteomes, mapping the corresponding networks of the components to a common molecular network of OP and AD, so as to screen out active compounds and establish an integrated drug effect interaction network. GO and KEGG enrichment assays were then performed, revealing the biological function and underlying mechanisms of the active compounds. And constructing a classified drug-target interaction network according to the compound classification, and revealing the action difference among different types of compounds. Meanwhile, by calculating topological parameters such as node degree and the like, key compounds of active compounds in the network model are analyzed. Utilizing prednisolone and AlCl3Respectively inducing and establishing OP and AD zebra fish models, then performing drug effect evaluation and potential target point exploration on the screened key compounds by means of alizarin red staining, osteogenesis-osteoclast biochemical index detection, behavioral analysis, nerve conduction biochemical index detection, PCR and the like, and finding and screening double-effect drugs simultaneously resisting osteoporosis and Alzheimer disease by taking the key compounds as indexes. The method of the invention is not only helpful for systematically clarifying the overall action of the multi-component traditional Chinese medicine on the body, but also can reveal the action difference among different types of compounds, and provides research foundation and data support for finding single-effect and multi-effect active monomers from the traditional Chinese medicine and discussing the 'same treatment of different diseases' mechanism. The screening method is matched with the principles of overall appearance, synergistic compatibility and the like in the theory of traditional Chinese medicine, and has important significance for explaining the biological functions of the traditional Chinese medicine and finding the effective components (groups).
Has the advantages that: the screening method is efficient and accurate, and can provide reference and thinking for screening active ingredients of the traditional Chinese medicine for treating different diseases simultaneously, evaluating the drug effect, discovering multi-effect compounds and the like. Furthermore, the results suggest that different types of active compounds may have a synergistic effect while exerting a dual action against osteoporosis and alzheimer's disease.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention.
Detailed Description
Example 1: construction of network pharmacological models
1. Experimental methods
1.1 chemospatial calculations and candidate Compound screening
All chemical composition data of cistanche deserticola or Cistanche Tubulosa (CT) were collected from the Chinese medicine system pharmacological analysis platform (TCMSP, http:// tcmspw. com /). Meanwhile, 4 pharmacologically relevant parameters were collected for Principal Component Analysis (PCA), including Molecular Weight (MW), octanol-water partition coefficient (AlogP), hydrogen donor number (Hdon), and hydrogen acceptor number (Hacc). The chemical spatial distribution of all components of CT was analyzed with the parameters described above using SIMCA14.1 software. Small molecule drugs approved by the FDA for the treatment of AD or OP were collected from DrugBank (https:// www.drugbank.ca /) as reference.
And (3) taking the drug-like property (DL) not less than 0.18 as a screening condition, and reserving candidate compounds meeting the condition for subsequent analysis. The chemical structure is drawn by using ChemDraw Professional 16.0 software, and the 3D structure is subjected to minimum energy optimization.
1.2 OP and AD common target Collection
All genes related to OP and AD were collected in DisGeNET (http:// www.disgenet.org/web/DisGeNET) and GeneCards (https:// www.genecards.org), respectively, and only the genes related to OP and AD at the same time were retained as targets for subsequent analysis.
1.3 Compound target prediction
Targets related to candidate compounds were collected in GeneCards. At the same time, Swiss TargetPrediction (http:// www.swisstargetprediction.ch/index. php) was used to predict targets associated with candidate compounds online. Mapping the collected candidate compound target to the OP and AD common target collected in 1.2 to obtain the active compound.
1.4 protein interaction network construction
The method comprises the steps of establishing a protein-protein interaction (PPI) network by using STRING (https:// STRING-db. org /), visualizing through a Cytoscape (3.7.2), establishing an active compound-target interaction network, calculating topological parameters such as node degree and the like, and marking the importance degree of a target in the network. And (4) continuously establishing a compound-target classification interactive network according to the structure type of the compound.
1.5 GO and KEGG pathway enrichment analysis
GO enrichment analysis was performed on the target using Funrich (http:// www.funrich.org /). KEGG pathway enrichment analysis was performed with ConsenssusPasthDB (CPDB, http:// CPDB. molgen. mpg. de /). Selecting paths related to OP and/or AD according to KEGG path functional classification (https:// www.kegg.jp/KEGG/pathway. html) for classification, and establishing active compound classification-KEGG path functional classification-KEGG path hierarchical interaction network (classified drug-target interaction network) by using Cytoscape.
2. Results of the experiment
In the present study, an effect network of CT was established and mapped onto a constructed common network of OP and AD, resulting in a drug effect network of active compounds with dual effects of anti-OP and anti-AD. The virtual model is screened to obtain 22 active ingredients, as shown in table 1, including 5 phenylethanoid glycosides (PhGs), 3 phenylpropionyl oligosaccharides, 3 iridoids and glycosides, 3 lignans and glycosides, 2 flavonoids, 1 alkaloid, 1 triterpene, 1 sterol, 1 fatty alcohol and 1 fatty acid. Calculated by network topological parameters, the phenylethanoid glycosides, flavonoids, sterols and triterpenoids play the most important role in the network. The enrichment analysis result shows that 22 effective components of CT are related to 16 biological function annotations and 66 channels, and can play the roles of resisting OP and AD singly or synergistically by participating in regulation of signal transduction, endocrine system, immune system, cell growth and death, thereby prompting the possibility of compatibility application of the 22 components as a medicine combination. To reveal the differences in the effects of different types of compounds, the PPI networks constructed were analyzed according to compound classification, and it was found that PhGs, flavones, triterpenes and sterols, particularly flavones, may play an important role in CT's anti-OP and anti-AD effects. The 4 active compounds act on 27 channels, and have synergistic effect in regulating cell growth and death, endocrine system, immune system, signal transduction, growth and development and the like. The embodiment establishes a network pharmacology model which can be used for discovering active ingredients (groups) of the traditional Chinese medicine, discovering double-effect and multi-effect medicines with the effects of resisting Alzheimer disease and osteoporosis, and systematically explaining potential biological functions and action mechanisms of the traditional Chinese medicine and pharmacodynamic differences among different types of ingredients.
Table 1 22 active ingredients co-screened in this example model
Example 2: intervention verification of osteoporosis zebra fish model
1. Experimental methods
1.1 Zebra Fish embryo Collection
The male and female zebra fish are separately raised in a circulating water system at 28 ℃, kept in light for 14h and dark for 10h every day, and fed with fairy shrimp for 2 times. Mating and spawning 3-4 pairs of zebra fish (female: male is 1: 2) of 6 months old, collecting normal embryos to the zebra fish embryo culture solution, and culturing in a constant temperature incubator at 28 ℃ under the same illumination condition.
1.2 Experimental groups
Selecting 3d of zebra fish young fish with good state after fertilization, transferring the zebra fish young fish into a 6-hole plate, wherein each hole has 30 pieces, and each hole has 1 hole.
1.3 alizarin Red staining Observation
The young fish is cultured by feeding according to the group as described in 1.2 until 8 days after fertilization, anesthetized with 0.02% tricaine, fixed with 4% paraformaldehyde for 2H, removed of the fixing solution, and added with freshly prepared bleaching agent (3% H)2O2And 0.5% KOH), bleaching until the fish body is transparent. The bleach was removed, dehydrated with 50% ethanol for 10min, and then stained overnight with 0.1% alizarin red stain in 0.5% KOH. The excess dye liquor was washed off with purified water and permeabilized in 0.5% KOH and glycerol (3: 1, 1: 3) at different ratios. And finally, observing the bone and the belly of the zebra fish stained with alizarin red under a stereoscopic microscope in a prone position, and acquiring images by adopting the same light intensity and exposure setting. Image-Pro Plus 6.0 Image analysis software calculated the area and cumulative optical density of the alizarin red stained area.
1.4 Biochemical index detection of osteogenesis-osteoclasts
The larval fish were dosed and cultured to 8d after fertilization as described in 1.2, the drug solution was removed, washed 2 times with PBS, and the larval fish were collected into a 1.5mL centrifuge tube. According to the weight percentage of the juvenile fish: add pre-cooled PBS at a PBS (w/v) ratio of 1: 9 and grind. Centrifuging at 4 deg.C and 3000r/min for 15min, and collecting supernatant to new centrifuge tube. The activity of zebrafish alkaline phosphatase (ALP) and tartrate-resistant acid phosphatase (TRAP) was determined by enzyme-linked immunosorbent assay (ELISA) according to the kit instructions.
1.5 real-time fluorescent quantitative PCR
Zebrafish larvae were harvested as described in 1.4, 30 per group, and total RNA was extracted from each group using Trizol, chloroform, isopropanol to determine the mRNA expression level of potential targets of the compounds predicted in example one. Total RNA was reverse transcribed to cDNA using a cDNA synthesis kit, and the reverse transcription procedure was 42 ℃ for 15 minutes and 85 ℃ for 5 seconds. Real-time using qPCR kitqPCR experiment in fluorescent quantitative PCR system using β -actin as reference gene and 2-ΔΔCTThe relative expression level of mRNA was calculated.
2. Results of the experiment
In an alizarin red staining experiment, compared with a Ctrl group, the mineralized area and mineralized density of the bones of the zebra fish of the Pre model group are obviously reduced (P is less than 0.001), which prompts the successful construction of the model; compared with the Pre group, the development condition of the head skeleton of the zebra fish of the Ed group and the different administration group tends to Ctrl group, the mineralization area and the mineralization density of the zebra fish are up-regulated to different degrees, and the zebra fish partially show more remarkable increase (P < 0.05, P < 0.01, P < 0.001). The results of biochemical indicators of osteogenesis and osteoclasts also show that compared with the Ctrl group, the ALP activity of the model group is obviously reduced, the TRAP activity is obviously improved, and the Ed and the administration group show opposite trends, and the results are consistent with the alizarin red staining results. The PCR results show that the mRNA level of the predicted target in the example 1 is changed to a different extent than that of the Ctrl group, and the change of the administration treatment is reversed, and the change is partially shown to be significantly different.
The results of this example demonstrate that 4 compounds obtained from example 1 significantly improved the symptoms of osteoporosis in the osteoporotic zebrafish model of the present invention, demonstrating anti-osteoporosis activity, and also suggest the osteoprotegeric activity of the remaining 18 compounds described in example 1 and the possibility of their use as anti-osteoporosis drugs.
Example 3: intervention verification of Alzheimer's disease zebra fish model
1. Experimental methods
1.1 Zebra Fish embryo Collection
Normal embryos were collected and cultured in zebrafish embryo culture broth under the same conditions in a constant temperature incubator at 28 ℃ according to the method described in example 2.
1.2 Experimental groups
And selecting 3d of zebra fish juvenile fish in a good state after fertilization, transferring the zebra fish juvenile fish into 6-hole plates with 30 pieces per hole and 1 hole per group. Randomly grouping according to the following groups: ctrl control, AlCl3Model group, donepezil hydrochloride (DPZ) positive drug group, quercetin(QU) administration group, Genistein (GE) administration group, β -sitosterol (BSS) administration group, and Abietic Acid (AA) administration group.
1.3 behavioural analysis
The zebrafish larvae dosed to post-fertilization 6d were transferred to 48-well plates. The experimental time was 60min, the temperature was maintained at 28 ℃ and a light/dark period of 3 cycles (10min light/10 min dark) was set. And recording the moving distance (D), the average moving speed (AS) and the light/dark cycle speed change (AS) of the zebra fish juvenile fish by a viewpoint behavior analyzer. AS is used to calculate the rate of recovery from Dyskinesia (DRR) and AS is used to calculate the efficiency of Response (RE).
1.4 nerve conduction Biochemical index detection
The larval fish were dosed and cultured to 6d after fertilization as described in 1.2, the drug solution was removed, washed 2 times with PBS, and the larval fish were collected into a 1.5mL centrifuge tube. According to the weight percentage of the juvenile fish: add pre-cooled PBS at a PBS (w/v) ratio of 1: 9 and grind. Centrifuging at 4 deg.C and 3000r/min for 15min, and collecting supernatant to new centrifuge tube. According to the kit specification, enzyme-linked immunosorbent assay (ELISA) is adopted to measure the activity of the acetylcholinesterase (AChE) and the acetylcholinesterase (ChAT) of the zebra fish.
1.5 real-time fluorescent quantitative PCR
Collecting zebrafish larvae as described in 1.4, 30 per group, extracting total RNA from each group of zebrafish larvae with Trizol, chloroform, isopropanol to determine the mRNA expression level of the potential target of the compound predicted in example 1, reverse transcribing the total RNA to cDNA using a cDNA synthesis kit, incubating at 42 ℃ for 15 minutes, heating at 85 ℃ for 5 seconds, performing a qPCR experiment using a qPCR kit in a real-time fluorescent quantitative PCR system, using β -actin as an internal reference gene, and using 2-ΔΔCTThe relative expression level of mRNA was calculated.
2. Results of the experiment
In the behavioral analysis experiments, AlCl was compared with Ctrl group3The AS and the delta S of the zebra fish of the model group are both reduced (P is less than 0.001), and the successful construction of the model is prompted; and with AlCl3Group ratio, the zebra fish of DPZ groups and different administration groups tended to move towards Ctrl group. Calculating DRR and RE to find the dyskinesia and response effect of the zebra fish in the administration groupThe rate is recovered to different degrees, and the significant difference is partially shown (P is less than 0.05, and P is less than 0.01). The results of detecting the nerve conduction biochemical indexes show that compared with the Ctrl group, the AChE activity of the model group is obviously increased, the ChAT activity is obviously reduced, DPZ and the administration group show the opposite trend to the model group, and the results are consistent with the behavioral analysis results. The PCR results show that the mRNA level of the predicted target in the example 1 is changed to a different extent than that of the Ctrl group, and the change of the administration treatment is reversed, and the change is partially shown to be significantly different.
The results of this example demonstrate that 4 compounds obtained from example 1 significantly improve the symptoms of alzheimer's disease in the alzheimer's disease zebrafish model of the present invention, demonstrating anti-alzheimer's disease activity, and also suggest neuroprotective activity of the remaining 18 compounds described in example 1 and their potential as anti-alzheimer's disease drugs.
Examples 2 and 3 respectively construct OP and AD zebra fish models, and the models can be respectively or jointly applied to discovery and screening of drugs with anti-osteoporosis and/or anti-Alzheimer disease activities. QU, GE, BSS and AA can show improvement effects on osteoporosis and Alzheimer disease zebra fish model related quantitative indexes in different degrees, and the 4 compounds are proved to have double effects of resisting osteoporosis and Alzheimer disease, which prompts the double effects of the rest 18 compounds screened in the example 1. In addition, the synergistic effect of the 22 active compounds involved in the invention is also suggested, and the different proportioning and combination of the 22 active compounds can have the effect of reduced synergistic effect.
Claims (9)
1. A method for screening active ingredients for treating different diseases simultaneously by using a double-disease model animal model is characterized by comprising the following steps of: the method comprises the following steps:
(1) searching and collecting corresponding compounds in the traditional Chinese medicine from a database;
(2) primarily screening the compound by taking relevant pharmacological parameters as indexes to obtain a candidate compound;
(3) predicting candidate compound targets on line;
(4) establishing a compound-target interaction molecular network through computer software;
(5) collecting all genes related to OP and AD from a gene database related to diseases, only reserving the genes related to OP and AD simultaneously as subsequent analysis targets, and establishing a common molecular network of the two diseases through computer software;
(6) mapping the molecular network in the step (4) to the common molecular network in the step (5), and screening an active compound-target interaction network;
(7) performing topological parameter analysis on the active compound-target interaction network, and screening out key compounds;
(8) constructing model animals and verifying the drug effect and potential target of the double-effect compound and the composition thereof;
(9) obtaining an action mechanism of the active compound by combining GO biological function annotation and KEGG signal channel enrichment analysis;
(10) and (4) constructing a classified drug-target interaction network according to the structural classification of the compounds to obtain the action difference of different types of compounds.
2. The method of claim 1 for screening active ingredients for both treatment of a different disease using a dual disease model animal model, wherein: the physiologically relevant parameters in the step (2) are respectively the molecular weight, the octanol-water distribution coefficient, the hydrogen donor number and the hydrogen acceptor number.
3. The method of claim 1 for screening active ingredients for both treatment of a different disease using a dual disease model animal model, wherein: and (3) in the step (2), the drug-like property (DL) is not less than 0.18 as the condition for primary screening of the compound.
4. The method of claim 1 for screening active ingredients for both treatment of a different disease using a dual disease model animal model, wherein: the active compounds in the step (6) comprise 5 phenylethanoid glycosides, 3 phenylpropionyl oligosaccharides, 3 iridoids and glycosides thereof, 3 lignans and glycosides thereof, 2 flavonoids, 1 alkaloid, 1 triterpene, 1 sterol, 1 fatty alcohol and 1 fatty acid.
5. The method of claim 4 for screening active ingredients for both treatment of a different disease using a dual disease model animal model, wherein: the active compounds include phenylethanoid glycosides, flavonoids, sterols, and triterpenes.
6. The method of claim 5 for screening active ingredients for both treatment of a different disease using a dual disease model animal model, wherein: the active compound is a flavonoid.
7. The method of claim 4 for screening active ingredients for both treatment of a different disease using a dual disease model animal model, wherein: the active compounds include:
8. the method of claim 1 for screening active ingredients for both treatment of a different disease using a dual disease model animal model, wherein: the model animal in the step (8) is a double-disease model animal model.
9. The method of claim 8 for screening active ingredients for both treatment of a different disease using a dual disease model animal model, wherein: the double-disease model animal model is a zebra fish double-disease model animal model.
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