A method for intelligent screening of active ingredients of traditional Chinese medicine for treating Alzheimer's disease

Abstract

The present invention discloses a method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease. With Olig2 and GSK-3β as targets, accurate design is assisted by artificial intelligence to screen out innovative small molecules of traditional Chinese medicine for reducing phosphorylated tau protein and their combined lead compounds, which can not only reduce investment in drug development, save limited experimental resources, and reduce blind waste, but also improve the success rate and efficiency of drug design on the basis of traditional computer-aided drug design, and shorten the drug development cycle; establish a new in vitro cell model of AD patient neurons, and conduct in vitro efficacy evaluation, which is closer to the real process of Alzheimer's disease, can reveal the major pathological mechanisms concealed in animal models, and help to develop more targeted active compounds of traditional Chinese medicine; establish an AD patient neuron cell chimeric mouse model App / ps1, conduct efficacy evaluation of traditional Chinese medicine in living animals, and find traditional Chinese medicine lead drugs with significant therapeutic effects.

Description

Technical Field

[0001] The present invention relates to the technical field of application of traditional Chinese medicine, and in particular to a method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease. Background Art

[0002] Alzheimer's disease and Parkinson's disease (PD) are typical central nervous system disorders, mainly occurring in the elderly. Currently, they cannot be prevented or cured, and can only alleviate some symptoms. The research and development of innovative Chinese medicine drugs is of great value in the field of central nervous system diseases. According to Chinese medicine records, dozens of Chinese medicines or formulas have a certain effect on Alzheimer's disease, but the pharmacological mechanism and effectiveness have not been objectively identified, so further improvement and innovation are impossible. The reason is the lack of a suitable detection platform.

[0003] The bottleneck of TCM modernization lies in the identification of its functions. The current identification methods are still limited to animal models. The functional variables of TCM are large. If animal models are used for identification, the cost is high and the time is long. Compared with living human cells, the response of animal cells to drugs varies greatly, especially for neurological diseases, so the predictability is poor and the failure rate is high. Summary of the invention

[0004] In order to solve the problems that the pharmacological mechanism and effectiveness of the existing traditional Chinese medicine for treating Alzheimer's disease have not been objectively identified, there is a lack of a suitable detection platform, the use of animal models for identification is costly and time-consuming, the predictability of neurological diseases is poor, and the failure rate is high, the present invention provides a method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease.

[0005] The technical solution of the present invention is achieved in this way:

[0006] A method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease, characterized by comprising the following steps:

[0007] S1. Using oligodendrocyte transcription factor Olig2 and glycogen synthase kinase GSK-3β as targets, we screened out active small molecules and combined biological leads of traditional Chinese medicine that reduce phosphorylated tau protein through supercomputer platforms and multiple large traditional Chinese medicine databases;

[0008] S2. Using artificial intelligence to assist in design prediction of the pharmacokinetic characteristics and adverse reactions of the active small molecules of traditional Chinese medicine and the combined biological lead products screened in step S1;

[0009] S3. Collect urine cells from AD patients, use Sendai virus reprogramming kit to induce iPSC model, establish Aβ42 protein precipitation model related to Alzheimer's disease, analyze the pluripotency of iPSC, and analyze the differentiation and tumorigenicity of iPSC;

[0010] S4, according to the prediction results in step S2, different combinations of small molecule Chinese medicine compounds in step S1 are selected in stages to induce the induced pluripotent stem cells iPSC in step S3 to differentiate into neurons neurons, and a large number of neural cells are produced using induced stem cell technology to establish an in vitro cell model of induced pluripotent stem cell neurons iPSC-neurons;

[0011] S5. Add several kinds of Chinese medicine small molecules and biological lead obtained by virtual screening in step S1 to the in vitro cell model of induced pluripotent stem cell neurons iPSC-neurons, analyze and verify the effects of several kinds of Chinese medicine small molecules and biological lead on the content of pTau protein generated by the in vitro cell model, analyze whether these compounds have the ability to promote the reduction of PTau protein content in vitro, improve the iPSC-neurons in vitro cell model, and further screen out 8-12 kinds of Chinese medicine active compounds that reduce phosphorylated tau protein through structural optimization of Chinese medicine drug design;

[0012] S6. Establish an AD patient neuron cell chimeric mouse model App / ps1, apply the N kinds of Chinese medicine active compounds optimized and screened in step S5 to App / ps1 mice, conduct Chinese medicine efficacy evaluation in living animals, and find Chinese medicine lead drugs with significant therapeutic effects.

[0013] As a further improvement of the present technology, the supercomputer platform in step S1 is the supercomputer platform of Sun Yat-sen University.

[0014] As a further improvement of the present technology, the artificial intelligence-assisted design in step S2 includes a support vector machine algorithm, a Bayesian classification algorithm, a multiple linear regression algorithm, and a random decision forest algorithm.

[0015] As a further improvement of the present technology, in step S3, morphology, immunohistochemistry and PCR techniques are used to detect and analyze the pluripotency of induced pluripotent stem cells iPSC.

[0016] As a further improvement of the present technology, in step S3, the differentiation and tumorigenicity of induced pluripotent stem cells (iPSCs) are analyzed through a somatic three-germ layer differentiation experiment and an in vivo teratoma formation experiment.

[0017] As a further improvement of the present technology, the neural cells in step S4 include neural stem cells, dopaminergic neurons, motor neurons, and astrocytes.

[0018] As a further improvement of the present technology, the analysis and verification in step S5 adopts marker expression method, proliferation and protein analysis method.

[0019] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention can design active Chinese medicine compounds that reduce phosphorylated tau protein in a targeted manner through artificial intelligence-assisted design, and accurately design and screen with Olig2 and GSK-3β as targets, which can not only reduce the investment in drug development, save limited experimental resources, and reduce blind waste, but also improve the success rate and efficiency of drug design on the basis of traditional computer-aided drug design, and shorten the drug development cycle;

[0020] 2. Use induced stem cell technology to mass-produce neural cells and establish a related disease cell model, namely the Aβ42 protein precipitation model of AD. By adding different formulas of active ingredients of traditional Chinese medicine, iPSC cells are induced to differentiate into neural precursor cells, and neural precursors are induced to differentiate into neurons. An efficient in vitro cell model of differentiation from AD-iPSC to neurons is established, which is closer to the actual process of Alzheimer's disease, can reveal major pathological mechanisms hidden in animal models, and help to develop more targeted traditional Chinese medicine active compounds; 3. Establish an AD patient neuronal cell chimeric mouse model App / ps1, conduct efficacy evaluation of traditional Chinese medicine in living animals, and find traditional Chinese medicine lead drugs with significant therapeutic effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a technical roadmap of the embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram of the structure of some innovative small molecule lead compounds that reduce phosphorylated tau protein by using GSK-3β as the target and screening through artificial intelligence-assisted design in an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of establishing an Aβ42 protein precipitation model according to an embodiment of the present invention;

[0024] Figure 4 Schematic diagram of the structures of 10 active natural compounds optimized and screened according to the embodiments of the present invention. DETAILED DESCRIPTION

[0025] The present invention is described in detail below in conjunction with the examples. The following examples will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form.

[0026] like Figures 1 to 4 As shown, the embodiment of the present invention includes the following steps:

[0027] S1. Using oligodendrocyte transcription factor Olig2 and glycogen synthase kinase GSK-3β as targets, a variety of traditional Chinese medicine active small molecules and combined biological leads that reduce phosphorylated tau protein were screened through supercomputer intelligent virtual screening;

[0028] In this embodiment, based on the supercomputer platform of Sun Yat-sen University and the biological innovation platform of the School of Pharmacy of Sun Yat-sen University (Shenzhen), GSK-3β was used as the target to accurately design related breakthrough compounds and innovative biological products through artificial intelligence; according to the GSK-3β protein structure in the literature, multiple large-scale traditional Chinese medicine databases were screened; and a total of more than one billion compounds and biological peptides were preliminarily screened on the Guangzhou "Tianhe-2" supercomputer;

[0029] like Figure 2 The figure shows the schematic diagram of the structure of some innovative small molecule lead compounds that reduce phosphorylated tau protein by targeting GSK-3β through artificial intelligence-assisted design;

[0030] S2, using support vector machine algorithm, Bayesian classification algorithm, multiple linear regression and random decision forest algorithm and other artificial intelligence-assisted design predictions to predict the pharmacokinetic characteristics and adverse reactions of the active small molecules of traditional Chinese medicine and the combined biological lead products screened in step S1;

[0031] In this example, the above-mentioned artificial intelligence-assisted design prediction was used, and then the TCM bioactivity evaluation research method of the "cell-organoid-whole animal" triple model was combined to improve the virtual screening results, and 300 TCM lead drugs were obtained;

[0032] S3. Collect urine cells from AD patients, use Sendai virus reprogramming kit to induce iPSC model, and establish Aβ42 protein precipitation model associated with Alzheimer's disease. Use morphology, immunohistochemistry and PCR technology to detect and analyze the pluripotency of iPSC; analyze the differentiation and tumorigenicity of iPSC through somatic three-germ layer differentiation experiment and in vivo teratoma formation experiment;

[0033] like Figure 3 The figure shows the Aβ42 protein precipitation model of AD. The curved strips in the figure are protein structures, the white part is the important amino acid position, which is also the screening site for active ingredients in traditional Chinese medicine, and the clustered structure is the protein surface.

[0034] S4. According to the prediction results in step S2, different combinations of small molecule Chinese medicine compounds in step S1 are selected in stages to induce the induced pluripotent stem cells iPSC in step S3 to differentiate into neurons neurons, and it is intended to use induced stem cell technology to mass produce neural cells (neural stem cells, dopaminergic neurons, motor neurons, astrocytes), establish an in vitro cell model of induced pluripotent stem cell neurons iPSC-neurons, and establish an Aβ42 protein precipitation model related to Alzheimer's disease;

[0035] S5. Several Chinese medicine small molecules and biological leads obtained by virtual screening in step S1 are added to the induced pluripotent stem cell neuron iPSC-neurons in vitro cell model, and the marker expression method, proliferation and protein analysis method are used to analyze and verify the effects of several Chinese medicine small molecules and biological leads on the pTau protein content generated by the in vitro cell model, and analyze whether these compounds have the ability to promote the reduction of PTau protein content in vitro, improve the iPSC-neurons in vitro cell model, and further screen out 10 Chinese medicine active compounds that reduce phosphorylated tau protein through structural optimization of Chinese medicine drug design (see Figure 4 );

[0036] S6. Establish an AD patient neuron cell chimeric mouse model App / ps1, apply the 10 active Chinese medicine compounds optimized and screened in step S5 to App / ps1 mice, conduct Chinese medicine efficacy evaluation in living animals, and find Chinese medicine lead drugs with significant therapeutic effects.

[0037] The present invention can design traditional Chinese medicine active compounds that reduce phosphorylated tau protein in a targeted manner through artificial intelligence-assisted design, and accurately design and screen with Olig2 and GSK-3β as targets, which can not only reduce the investment in drug development, save limited experimental resources, and reduce blind waste, but also improve the success rate and efficiency of drug design on the basis of traditional computer-aided drug design, and shorten the drug development cycle;

[0038] The present invention uses induced stem cell technology to mass-produce neural cells and establishes a disease cell model related thereto, namely, an Aβ42 protein precipitation model of AD. By adding different formulations of active ingredients of traditional Chinese medicine, iPSC cells are induced to differentiate into neural precursor cells, and neural precursors are induced to differentiate into neurons. An efficient in vitro cell model of differentiation from AD-iPSC to neurons is established, which is closer to the actual process of Alzheimer's disease, can reveal major pathological mechanisms concealed in animal models, and is helpful to develop more targeted active traditional Chinese medicine compounds.

[0039] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art may make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease, characterized in that The steps include: S1. Using oligodendrocyte transcription factor Olig2 and glycogen synthase kinase GSK-3β as targets, we screened out active small molecules and combined biological leads of traditional Chinese medicine that reduce phosphorylated tau protein through supercomputer platforms and multiple large traditional Chinese medicine databases; S2. Using artificial intelligence to assist in the design and prediction of the pharmacokinetic characteristics and adverse reactions of the active small molecules of traditional Chinese medicine and the combined biological lead products screened in step S1; S3. Collect urine cells from AD patients, use Sendai virus reprogramming kit to induce iPSC model, establish Aβ42 protein precipitation model related to Alzheimer's disease, analyze the pluripotency of iPSC, and analyze the differentiation and tumorigenicity of iPSC; S4, according to the prediction results in step S2, different combinations of small molecule Chinese medicine compounds in step S1 are selected in stages to induce the induced pluripotent stem cells iPSC in step S3 to differentiate into neurons neurons, and a large number of neural cells are produced using induced stem cell technology to establish an in vitro cell model of induced pluripotent stem cell neurons iPSC-neurons; S5. Add several kinds of Chinese medicine small molecules and biological lead obtained by virtual screening in step S1 to the in vitro cell model of induced pluripotent stem cell neurons iPSC-neurons, analyze and verify the effects of several kinds of Chinese medicine small molecules and biological lead on the content of pTau protein generated by the in vitro cell model, analyze whether these compounds have the ability to promote the reduction of PTau protein content in vitro, improve the iPSC-neurons in vitro cell model, and further screen out 8-12 kinds of Chinese medicine active compounds that reduce phosphorylated tau protein through structural optimization of Chinese medicine drug design; S6. Establish an AD patient neuron cell chimeric mouse model App / ps1, apply the N kinds of Chinese medicine active compounds optimized and screened in step S5 to App / ps1 mice, conduct Chinese medicine efficacy evaluation in living animals, and find Chinese medicine lead drugs with significant therapeutic effects.

2. The method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease according to claim 1, characterized in that: The supercomputer platform in step S1 is the supercomputer platform of Sun Yat-sen University.

3. The method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease according to claim 1, characterized in that: The artificial intelligence-assisted design in step S2 includes a support vector machine algorithm, a Bayesian classification algorithm, a multiple linear regression algorithm, and a random decision forest algorithm.

4. The method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease according to claim 1, characterized in that: In step S3, morphology, immunohistochemistry and PCR techniques are used to detect and analyze the pluripotency of induced pluripotent stem cells (iPSCs).

5. The method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease according to claim 1, characterized in that: In step S3, the differentiation and tumorigenicity of induced pluripotent stem cells (iPSCs) are analyzed through a somatic three-germ layer differentiation experiment and an in vivo teratoma formation experiment.

6. The method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease according to claim 1, characterized in that: The neural cells in step S4 include neural stem cells, dopaminergic neurons, motor neurons, and astrocytes.

7. The method for intelligently screening active ingredients of traditional Chinese medicine for treating Alzheimer's disease according to claim 1, characterized in that: The analysis and verification in step S5 adopts marker expression method, proliferation and protein analysis method.

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