Computer-aided drug screening method, system and equipment based on LB1 and SRSF2

Abstract

The invention discloses a computer-aided drug screening method, system and equipment based on LB1 and SRSF2. Based on the expression of the laminin B1 (LB1) in the muscle cell nucleus of the Duchenne muscular dystrophy (DMD) found by research and the influence of the laminin B1 (LB1) on the downstream splicing factor SRSF2, the drugs are virtually screened through a computer, the screening efficiency of the drugs is improved, and a new insight is provided for treatment of the Duchenne muscular dystrophy.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent medical treatment, and specifically relates to a computer-aided drug screening method, system and equipment based on LB1 and SRSF2. Background Art

[0002] Duchenne muscular dystrophy (DMD), also known as "Duchenne dystrophy", is the most common type of muscular dystrophy. Its pathogenic mechanism is a mutation in the DMD gene on the X chromosome, which leads to a lack of dystrophin on the skeletal muscle cell membrane. Pathological examination of skeletal muscle tissue shows degeneration and necrosis of muscle cells, hyperplasia of fibrous tissue, abnormal morphology and distribution of nuclei, and immature muscle fibers. DMD patients generally have normal muscle strength after birth, but as they age, their skeletal muscles gradually weaken and become damaged, often leading to respiratory failure or lung infection, which are the main causes of death in patients. There is currently no effective treatment, and the life expectancy of most patients is about 25 years. Although the genetic basis of DMD has been determined, the mechanism that leads to progressive muscle damage and weakness remains unclear. Therefore, studying the pathogenic mechanism of DMD and finding potential therapeutic targets are current clinical issues that need to be urgently addressed.

[0003] With the development of technologies such as big data, cloud computing, and hardware acceleration, computer-aided drug design (CADD) has gradually become an important means of new drug research and development. Based on computer computing and simulation technology, by learning the prior knowledge contained in massive drug data and mining the interaction relationship between target targets and candidate drugs, active drug molecules with drug-like properties can be quickly selected from millions of molecules. This greatly reduces the blindness of screening candidate drug molecules and improves the efficiency of research and development and drug screening. Summary of the invention

[0004] To overcome the deficiencies of the prior art, the present invention provides a computer-aided drug screening method, system and device based on LB1 and SRSF2.

[0005] To achieve the above purpose, the present invention adopts the following technical solution.

[0006] The first aspect of the present invention provides a method for computer-assisted drug screening based on LB1 and SRSF2, the method comprising:

[0007] Obtain LB1 protein and SRSF2 protein data;

[0008] Determine the binding sites of the two proteins based on the data of the LB1 protein and the SRSF2 protein;

[0009] Candidate drugs targeting the binding sites of the two were obtained through computer-assisted screening.

[0010] Further, the process of computer-assisted screening is:

[0011] Screening of small molecule compounds based on the spatial structure of the binding sites of LB1 protein and SRSF2 protein;

[0012] The small molecule compounds obtained by screening are molecularly docked with the binding sites to obtain the scores of the docking molecules;

[0013] The candidate drugs are obtained by sorting according to the scores.

[0014] Further, the process of computer-assisted screening is:

[0015] The molecular structures of LB1 protein and SRSF2 protein are obtained and input into the pharmacophore module library for matching, and all the action sites are clustered based on the interaction mode with LB1 and SRSF2 to obtain the pharmacophore model;

[0016] The pharmacophore model is input into a molecular compound database for high throughput screening to obtain candidate drugs.

[0017] Further, the process of computer-assisted screening is:

[0018] Obtain the molecular structure of the LB1 small molecule inhibitor and / or the molecular structure of the SRSF2 small molecule promoter;

[0019] Based on the molecular structure of the small molecule inhibitor / promoter, a small molecule library with similar structure is obtained by screening;

[0020] Performing molecular docking on the small molecule library with similar structures and the binding site to obtain a score of the docked molecule;

[0021] The candidate drugs are obtained by sorting according to the scores.

[0022] Furthermore, the candidate drugs include protein analogs, antibodies, and RNA drugs.

[0023] A second aspect of the present invention provides a system for computer-assisted drug screening based on LB1 and SRSF2, the system comprising:

[0024] Acquisition unit: acquire LB1 protein and SRSF2 protein data;

[0025] Site determination unit: determining the binding sites of the two proteins according to the data of the LB1 protein and the SRSF2 protein;

[0026] Screening unit: Obtain candidate drugs targeting the binding sites of the two through computer-assisted screening.

[0027] The third aspect of the present invention provides a device for computer-assisted drug screening based on LB1 and SRSF2, the device comprising:

[0028] A memory and a processor, wherein the memory is used to store program instructions; the processor is used to call the program instructions, and when the program instructions are executed, the computer-assisted drug screening method based on LB1 and SRSF2 described in the first aspect of the present invention is implemented.

[0029] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program thereon, the computer-readable storage medium comprising:

[0030] When the computer program is executed by a processor, the computer-assisted drug screening method based on LB1 and SRSF2 described in the first aspect of the present invention is implemented.

[0031] The fifth aspect of the present invention provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the method for computer-assisted drug screening based on LB1 and SRSF2 described in the first aspect of the present invention.

[0032] A sixth aspect of the present invention provides any of the following applications:

[0033] (1) Use of a promoter of SRSF2 in the preparation of a pharmaceutical composition for treating Duchenne muscular dystrophy;

[0034] (2) Use of an agent that inhibits the binding of LB1 and SRSF2 in the preparation of a pharmaceutical composition for treating Duchenne muscular dystrophy;

[0035] (3) Use of an agent that promotes the binding of SRSF2 and BCL-xl in the preparation of a pharmaceutical composition for treating Duchenne muscular dystrophy;

[0036] (4) Application of the complex formed by the binding of SRSF2 and BCL-xl in screening candidate drugs for the treatment of Duchenne muscular dystrophy; (5) Application of LB1 in the preparation of SRSF2 expression regulators in cells;

[0037] (6) Application of LB1 in preparing cell models with low SRSF2 expression.

[0038] Furthermore, promoters of SRSF2 include substances that can promote the expression level / activity of SRSF2.

[0039] Furthermore, the substance that promotes the expression level / activity of SRSF2 includes a vector for overexpression of SRSF2.

[0040] Furthermore, the pharmaceutical composition also includes pharmaceutically acceptable excipients.

[0041] The seventh aspect of the present invention provides a complex comprising LB1 and SRSF2, or SRSF2 and BCL-xl.

[0042] An eighth aspect of the present invention provides a method for screening candidate drugs for treating Duchenne muscular dystrophy, the method comprising the following steps:

[0043] (1) contacting a substance to be detected with a system expressing or containing SRSF2;

[0044] (2) detecting the expression level of SRSF2 in the system;

[0045] (3) selecting substances that can promote the expression level / activity of SRSF2 as candidate drugs for the treatment of Duchenne muscular dystrophy;

[0046] Or the method comprises the following steps:

[0047] (1) contacting a substance to be detected with a system containing a complex formed by LB1 and SRSF2;

[0048] (2) detecting the binding level of LB1 and SRSF2 in the system;

[0049] (3) selecting substances that inhibit the binding of LB1 and SRSF2 as candidate drugs for the treatment of Duchenne muscular dystrophy;

[0050] Or the method comprises the following steps:

[0051] (1) contacting a substance to be detected with a system containing a complex formed by SRSF2 and BCL-xl;

[0052] (2) detecting the binding level of SRSF2 and BCL-xl in the system;

[0053] (3) Select substances that promote the binding of SRSF2 and BCL-xl as candidate drugs for the treatment of Duchenne muscular dystrophy.

[0054] A ninth aspect of the present invention provides a method for regulating the expression of SRSF2 in a cell, the method comprising changing the expression / activity of LB1 in the cell.

[0055] Furthermore, the method of inhibiting SRSF2 expression in a cell comprises promoting the expression / activity of LB1 in the cell.

[0056] Furthermore, promoting the expression / activity of LB1 in the cell includes administering a promoter of LB1 to the cell.

[0057] Furthermore, a promoter of LB1 was administered to the cell nucleus.

[0058] Furthermore, the method for promoting SRSF2 expression in a cell comprises inhibiting the expression / activity of LB1 in the cell.

[0059] Further, inhibiting the expression / activity of LB1 in a cell comprises administering an inhibitor of LB1 to the cell.

[0060] Furthermore, an inhibitor of LB1 was administered to the cell nucleus.

[0061] Further, the cells are selected from C2C12 cells.

[0062] The tenth aspect of the present invention provides a method for constructing a cell model with low SRSF2 expression or high SRSF2 expression, the method comprising regulating the expression / activity of LB1 in the cell.

[0063] Furthermore, the method for constructing a cell model with low SRSF2 expression includes promoting the expression / activity of LB1 in the cell.

[0064] Furthermore, promoting the expression / activity of LB1 in the cell includes administering a promoter of LB1 to the cell.

[0065] Furthermore, a promoter of LB1 was administered to the cell nucleus.

[0066] Furthermore, the method for constructing a cell model with high expression of SRSF2 includes inhibiting the expression / activity of LB1 in the cells.

[0067] Further, inhibiting the expression / activity of LB1 in a cell comprises administering an inhibitor of LB1 to the cell.

[0068] Furthermore, an inhibitor of LB1 was administered to the cell nucleus.

[0069] Further, the cells are selected from C2C12 cells.

[0070] Advantages and beneficial effects of the present invention:

[0071] This application is based on the research findings of lamin B1 (LB1) expression in the nuclei of Duchenne muscular dystrophy (DMD) muscle cells and its effect on the downstream splicing factor SRSF2. Through computer virtual screening of drugs, it helps to improve the efficiency of drug screening and provide new insights into the treatment of Duchenne muscular dystrophy. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 It is a schematic diagram of the method flow of computer-assisted drug screening based on LB1 and SRSF2;

[0073] Figure 2 It is a schematic diagram of the computer-assisted drug screening system based on LB1 and SRSF2;

[0074] Figure 3 It is a schematic diagram of the equipment for computer-assisted drug screening based on LB1 and SRSF2;

[0075] Figure 4 Figure 4 is the abnormal morphology of DMD muscle cell nuclei and the accumulation of LB1 in DMD skeletal muscle. 4A is the HE staining of HP and DMD human biopsy tissues, 4B is the immunostaining of dystrophin-N, dystrophin-C and dystrophin-R, 4C is the detection of cell nuclei immunostained with LB1 (red) using DAPI (purple) (4C, left), the bar graph represents the relative fluorescence intensity of the merge (yellow) (4C, right), 4D is the protein LB1 and GAPDH 4E is a graph of the ratio of LB1 / H3 in HP (white bars) and DMD (black bars), WB analysis of the LB1 / H3 ratio in isolated nuclei and protein extracts of C57 mice and mdx mice, 4F is a graph of RT-PCR analysis of LB1 relative to C57 mice, mdx mice and HP (white bars), and DMD (DMD mice n=5; HP mice n=4; mdx mice n=3; C57 mice n=3), *P≤0.05, **P≤0.01, ***P≤0.001;

[0076] Figure 5 Figure 5 is a graph showing accumulation of autophagosomes and impairment of the autophagic pathway in DMD skeletal muscle tissue, wherein 5A is a graph showing the RT-PCR results of TFEB\PINK1\PARKIN\LC3\P62 relative to HP and DMD, 5B is a graph showing the RT-PCR results of TFEB\PINK1\PARKIN\LC3\P62 relative to C57 and mdx mice, 5C is a graph showing the LC3Ⅱ / GAPDH protein ratio relative to C57 and mdx mice, 5D is a graph showing the P62 protein / GAPDH ratio relative to C57 and mdx mice, 5E is a graph showing the LC3Ⅱ / GAPDH protein ratio relative to HP and DMD, 5F is a graph showing the protein ratio of P62 / GAPDH relative to HP and DMD, 5G is a graph showing the fluorescence intensity of P62 / LC3 relative to C57 mice and mdx mice, and 5H is a graph showing the fluorescence intensity of P62 / LC3 relative to HP and DMD;

[0077] Figure 6Figure 6 is a diagram showing the accumulation of LB1 due to impaired nuclear autophagy in DMD skeletal muscle tissue, where 6A is a diagram showing LB1 (red), LC3Ⅱ (green) immunostaining and confocal mode (yellow) (the dotted line indicates the position of the intensity graph) of HP and DMD human biopsies, 6B is a diagram showing LB1 (red), P62 (green) immunostaining and confocal mode (yellow) (the dotted line indicates the position of the intensity graph), 6C is a diagram showing LB1 (red), LC3 (green) immunostaining and confocal mode (yellow) of C57 and mdx mouse biopsies, 6D is a diagram showing LB1 (red), P62 (green) immunostaining and confocal mode (yellow) of C57 and mdx mouse biopsies. (green) Immunostaining and confocal mode (yellow) images, 6E is a graph of the LC3Ⅱ / H3 ratio, 6F is a graph of the P62 / H3 ratio, 6G is a graph of the ratios of LC3Ⅱ / P62 / LB1 and β-actin relative to the control group and the CQ group, 6H is a graph of the fluorescence intensity of the cell nuclei detected by DAPI (purple) in the CQ group and the control group using LC3 (green) immunostaining, 6I is a graph of the cell nuclei detected by DAPI (purple) in the CQ group and the control group using P62 (green) immunostaining, 6J is a graph of the cell nuclei detected by DAPI (purple) in the CQ group and the control group using LB1 (green) immunostaining;

[0078] Figure 7 is a graph showing a decrease in SRSF2 expression level caused by overexpression of LB1, wherein 7A is a graph showing the overexpression efficiency of LB1 overexpression plasmid transfected into C2C12 cells, 7B is a graph showing the fluorescence intensity of LB relative to the control and OE, 7C is a heat map showing genes with differential expression between the control and experimental groups, 7D is a graph showing the functional enrichment of upregulated genes in the sequencing results, 7E is a graph showing the functional enrichment of downregulated genes in the sequencing results, 7F is a graph showing the RT-PCR results of SRSF2 relative to the control and OE, 7G is a graph showing the ratio of SRSF2 and β-actin detected by protein extracts of the control and OE, 7H is a graph showing the RT-PCR results of SRSF2 relative to HP and DMD, C57 and mdx mice, and 7I is a graph showing the ratio of SRSF2 / H3 relative to C57 and mdx mice;

[0079] Figure 8 is a graph showing that LB1 overexpression inhibits SRSF2 expression through abnormal LAD organization, wherein 8A is a graph showing the number of LADs in the control group and OE genome, 8B is a graph showing the length of LADs (N=1) in the control group and OE genome, 8C is a graph showing the cut tag analysis of the peak distribution of the SRSF2 locus bound to LB1, 8D is a graph showing the genomic regions containing LADs in the control group and OE group, 8E is a graph showing the KEGG classification of 441 upregulated genes, and 8F is a graph showing the GO enrichment analysis of the 441 upregulated genes;

[0080] Fig. 9Figure 9 is a diagram showing that SRSF2 is involved in the apoptosis pathway of DMD skeletal muscle cells by regulating the expression of BCL-xl, wherein 9A is a diagram showing the expression efficiency of SRSF2 knockout plasmid transfected into C2C12 cells, 9B is a diagram showing the apoptosis of C2C12 cells in the control group and the si-SRSF2 group detected by TUNEL method, 9C is a diagram showing the RT-PCR results of BCL-xl relative to the control group and the si-SRSF2 group, 9D is a diagram showing the RT-PCR results of BCL-xl relative to C57 and mdx mice, 9E is a diagram showing the RT-PCR results of BCL-xl relative to HP and DMD, 9F is a diagram showing the BCL-xl level relative to NC and si-SRSF2 mice, and 9 G is a graph showing the transfection efficiency of SRSF2 overexpression plasmid transfected into C2C12 cells, 9H is a graph showing the apoptosis of C2C12 cells in the control group and OE-SRSF2 group detected by TUNEL method, 9I is a graph showing the RT-PCR detection results of BCL-xl in C2C12 cells in the control group and OE-SRSF2 group, 9J is a graph showing the expression efficiency of SRSF2 overexpression adenovirus vector injected into the tibialis anterior (TA) muscle of mdx mice, 9K is a graph showing the RT-PCR detection results of BCL-xl against AAV9-vector and AAV9-SRSF2, and 9L is a graph showing the apoptosis of skeletal muscle cells in the AAV9-vector group and AAV9-SRSF2 group detected by TUNEL method;

[0081] Fig.10 The figures show that upregulating the expression level of SRSF2 in the skeletal muscle of mdx mice improves the motor function and skeletal muscle pathological characteristics of mice, wherein 10A is an analysis diagram of the wheel running results of mdx mice in the AAV9-vector group and the AAV9-SRSF2 group at different time points (1w, 2w, 3w and 4w) (n=5, each group), 10B is a diagram of the proportion of centrally nucleated muscle fibers compared with AAV9-vector and AAV9-SRSF2 mice, and 10C is a diagram of the ratio of Caspase3 / GAPDH and cleaved Caspase3 / GAPDH relative to AAV9-vector, AAV9-SRSF2 mice and C57 mice (n=3, each group). DETAILED DESCRIPTION

[0082] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0083] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0084] Figure 1 The figure is a flow chart of the method for computer-assisted drug screening based on LB1 and SRSF2 provided by the present invention, which specifically includes:

[0085] 101: Obtaining LB1 protein and SRSF2 protein data

[0086] In some embodiments, the LB1 protein and SRSF2 protein data include the molecular structure and binding site of the LB1 protein and SRSF2 protein.

[0087] In one embodiment, the sources of the mouse model include: conventional wild-type C57 / BL6 (WT) and C57 / BLl0 / mdx (mdx) mice were purchased from Nanjing Institute of Biomedical Sciences (Nanjing, China). WT and mdx mice were analyzed at 6 months. At the designated time, the tibialis anterior muscle (TA) was collected from the mice immediately after killing. Mice were bred and raised according to standard animal facility procedures, and all experimental protocols were approved by the internal animal research ethics committee according to the regulations of the Ethics Committee of the Second Hospital of Hebei Medical University and complied with the NIH Guide for the Care and Use of Laboratory Animals (License No.: 2024-AE175).

[0088] In one embodiment, the pathological muscle tissue and hematoxylin-eosin staining method include: the DMD patient muscle samples in this study were obtained from the hospital pathology department, including clinically confirmed DMD patient samples and healthy muscle samples. The DMD patient vastus medialis muscle biopsy samples and the tibialis anterior (TA) muscles of wild-type (WT) and mdx mice were quickly frozen in liquid nitrogen-cooled isopentane and 10 μm transverse frozen sections were cut. The muscle tissue sections of DMD patients were subjected to the following staining procedures: (1) stained with hematoxylin for 10 minutes; (2) rinsed in running water for 10 minutes to restore blue; (3) stained with eosin for 50 seconds; (4) rapidly dehydrated through an ethanol gradient; (5) sealed.

[0089] In one embodiment, the method of cell culture, cell nucleus and cytoplasm separation includes: C2C12 myoblasts (Zqxzbio) are cultured in Dulbecco's modified Eagle medium (DMEM, Gibco), and 1% antibiotic antimycotic solution (Gibco) and 10% fetal bovine serum (FBS, ZETA) are added to the medium. According to the instructions of the nuclear and cytoplasmic protein extraction kit (Beyotime), each group of tissue fragments is mixed with cytoplasmic protein extraction reagents A and B (20:1), and PMSF is added to a final concentration of 1mmol / L. Fully homogenized at 4°C. The homogenate is transferred to a centrifuge tube and centrifuged. The supernatant contains the extracted cytoplasmic protein. For precipitated or collected C2C12 cells, 200μL of cytoplasmic protein extraction reagent A and PMSF are added to each 20μL cell precipitate. After ice bathing, 10μL of cytoplasmic protein extraction reagent B is added, centrifuged at 4°C, and the supernatant is the extracted cytoplasmic protein. Add 50 μL of nuclear protein extraction reagent and PMSF to the precipitate, incubate on ice for 30 minutes, vortex intermittently, centrifuge at 4°C, and collect the supernatant, which is the nuclear protein.

[0090] In one embodiment, the TUNEL staining method includes: detecting cell apoptosis using TUNEL staining. The operation steps are as follows: (1) Collect cells, wash once with PBS, fix with 4% paraformaldehyde for 30 minutes, and wash once with PBS. (2) Permeabilize cells with 0.3% Triton X-100 at room temperature for 5 minutes. (3) Add the prepared TUNEL detection solution, incubate at 37°C in the dark for 60 minutes, and then wash twice with PBS. (4) Seal the slide with anti-fading mounting medium (Solarbio) in a dark environment. (5) Observe and take pictures with a fluorescence microscope.

[0091] In one embodiment, the Western Blot (WB) method includes: extracting total cell protein using a cell lysate, determining protein concentration using the BCA method (Thermo Scientific), taking equal amounts of protein samples for SDS-polyacrylamide gel electrophoresis (SDS-PAGE), transferring the gel to a PVDF membrane (Millipore) using a semi-dry transfer method after electrophoresis, blocking with a 5% skim milk solution at room temperature for 2 hours, then adding primary and secondary antibodies for incubation, and finally detecting antibody-bound bands using a membrane scanner.

[0092] The primary antibodies used in the experiment are as follows: anti-LMNB1 (12987-1-A\66095-1-Ig, Proteintech), anti-GAPDH (BS65483M, Bioworld), anti-HistoneH3 (7168-1-AP, Proteintech), anti-LC3 (SAB4300571, Sigma), anti-P62 / SQSTM1 (P0067, Sigma), anti-β-Actin (AP0731, Bioworld), anti-SRSF2 (20371-1-AP, Proteintech), anti-Caspase 3 (66470-2-Ig, Proteintech). The secondary antibodies used are as follows: Dylight 800, goat anti-rabbit IgG (A23920, Abbkine), Dylight 680, goat anti-mouse IgG (A23710, Abbkine).

[0093] In one embodiment, the method of immunofluorescence staining includes: for tissue samples, frozen tissue sections, rinsed 3 times with PBS, punched with 0.03% TritonX-100 (Solarbio), and rinsed 3 times with PBS; for cell samples, collect cells and rinsed 3 times with PBS; add 1 ml of 4% paraformaldehyde to the wells, fix at room temperature, and rinsed 3 times with PBS; punched with 0.5% Triton X-100 at room temperature; rinsed 3 times with PBS; the subsequent processes are all incubated with 10% goat serum (Solarbio); pour off the serum, drop the primary antibody diluted in an appropriate proportion, place the slice flat in a moisturizing box at 4°C overnight, and rinse 3 times with PBS at room temperature the next day. Add fluorescent secondary antibody and incubate at room temperature, rinse with PBS in the dark, add DAPI (Solarbio) working solution, incubate at room temperature, and rinse 5 times with PBS in the dark. Antifade sealing agent (Solarbio) is used to seal the slide in the dark. The pictures are observed and photographed by Olympus fluorescence microscope (Olympus BX51).

[0094] The information of the primary antibodies used is as follows: anti-LMNB1 (12987-1-A, Proteintech), anti-LC3 (SAB4300571, Sigma), anti-P62 / SQSTM1 (P0067, Sigma), anti-SRSF2 (Ab204916, Abcam), CoraLite488 conjugated goat anti-rabbit IgG (SA00013-2, Proteintech), and CoraLite594 conjugated goat anti-mouse IgG (SA00013-3, Proteintech).

[0095] In one embodiment, the method of RNA extraction and real-time fluorescence quantitative PCR analysis includes: extracting total RNA from each group of tissues and cells using the Trizol (Gbico) method, and detecting the purity and concentration of RNA using a nucleic acid quantifier. Take 1-3 μg of total RNA to establish a 20 μl reverse transcription system to synthesize cDNA (R223-01, Vazyme), and then use SYBR Color qPCR Master Mix (Q431-02, Vazyme) for PCR amplification.

[0096] In a specific embodiment, the method for constructing adenovirus includes: cloning SRSF2 into a suitable vector, co-transfecting the recombinant viral vector with genes carrying adenovirus origin and AAV replication and capsid genes into AAV-293 cells (Genechem Co., Ltd., Shanghai); collecting AAV virus particles from the infected AAV-293 cells 2-3 days after transfection and performing preliminary treatment; concentrating and purifying the collected viral supernatant, determining the titer of the obtained virus by quantitative PCR, and finally packaging and storing the virus.

[0097] In one embodiment, the method of AAV9-SRSF2 treatment comprises: performing AAV9-SRSF2 treatment on mdx mice at 3 months and 6 months after birth, firstly anesthetizing the mdx mice, and then using a virus titer of 1×10 13 vg / ml of AAV9-SRSF2 was injected at multiple points in the muscle, and the total amount of virus injected into each TA was 3×10 11 vg, and the mice were fed normally after they woke up. One month later, the motor ability of the transgenic mice was evaluated, and bilateral TA was taken to observe the pathological changes of skeletal muscle and apoptosis of skeletal muscle fibers, and to detect Bcl-xl, confirming the therapeutic value of up-regulating the splicing protein SRSF2 for mdx mice.

[0098] In one embodiment, the method for evaluating the motor function of mice includes: placing mice on a stationary Ugo Basile, and starting to run after all mice are in place. The machine first rotates at a speed of 5rpm for 15 seconds to adapt the mice, and then gradually accelerates from 5rpm to 45rpm within 500 seconds, and the timing starts when the acceleration begins. The running time of the mice is continuously recorded by the software, and the time recording stops when the mouse falls from the tube or the running time reaches 500 seconds. Each mouse undergoes at least 2 trainings before the formal test to adapt to the machine. The formal test time is 2 days, and 3 tests are performed every day. The interval between the 3 tests is greater than 20 minutes, and the longest running time is selected for further analysis.

[0099] In one embodiment, the method of RNA-IP includes: 1) Cell collection: collect cells by trypsin digestion and resuspend the cells in PBS and freshly prepared nuclear isolation buffer. 2) Nuclear lysis and precipitation: centrifuge the cell nuclei and resuspend the cell nuclear pellet in freshly prepared RIP buffer. 3) Chromatin shearing: divide the resuspended cell nuclei into two parts, each 500μl (for control experiments and IP), use a homogenizer to smash, mechanically shear the chromatin, centrifuge the nuclear membrane and fragments, and freeze one lysate in liquid nitrogen for control RNA isolation. 4) RNA immunoprecipitation: add SRSF2 antibody to the supernatant, incubate at 4℃ overnight, add protein A / G magnetic beads and incubate at 4℃. 5) Washing and purification: centrifuge to precipitate the magnetic beads, remove the supernatant, resuspend the magnetic beads with RIP buffer, and repeat washing. Add 1ml TRIzol to resuspend the magnetic beads and separate the co-precipitated RNA. Use RNase free water to elute RNA. Add about 15-25 μl of DEPC-treated TE buffer or water to the RNA precipitate. Proteins separated by magnetic beads can be detected by WB. 6) Detection: RNA is treated with reverse transcriptase, reverse transcribed into cDNA and analyzed.

[0100] In one embodiment, the RNA-seq library construction and sequencing method includes: RNA-seq library construction and sequencing are completed by BGI Genomics (Wuhan, China) Co., Ltd., and the total RNA of three replicate samples is mixed in equal amounts to construct two libraries, namely the experimental group and the control group, and Illumina HiseqTM sequencing is performed. The raw data obtained by sequencing contains low-quality sequences with adapters. In order to ensure the quality of information analysis, Trimmomatic is used to filter the raw data, remove sequences with N bases, remove adapter sequences in reads, remove low-quality bases (Q<20), and use a sliding window method to remove bases with a quality value of less than 20 at the tail of reads to obtain Clean data. Bowtie2 is used to align the Cleanreads to the reference sequence, and then RSEM is used to calculate the expression levels of genes and transcripts. And pheatmap is used to draw a cluster heat map of the expression of genes in different samples. In this study, only the RNA-seq sequencing data obtained was used to identify the differential gene expression of overexpressed LMNB1, and enrichment analysis, clustering and other analyses were performed on the differential genes.

[0101] In one embodiment, the method of cutting and labeling (CUT&Tag) includes: high-throughput CUT&Tag detection is performed at BGI Genomics Co., Ltd. (Wuhan, China), cells overexpressing Lamin B1 are selected, and the cells (1×10 6) were washed and resuspended and incubated with bean protein A-coated magnetic beads. Then, the beads were resuspended with wash buffer and a 1:50 dilution of Lamin B1 antibody (12987-1-AP, Proteintech) or control IgG and incubated overnight on a rotating platform at 4°C. The beads were washed in dig-washbuffer and incubated with secondary antibodies. After incubation, they were washed with dig-Hisalt buffer to remove unbound liquid and incubated with protein A-tn5 transposomes. Next, the cells were resuspended in labeling buffer. Purified DNA fragments were used for sequencing. Sequencing was performed on the DNBSEQ platform. SOAPnuke was used to filter the data. Bowtie2clean reads were used to align with the reference genome sequence, and Picard was used to remove duplicate sequences in the data. To ensure the reliability of the analysis, only reads with MapQ greater than 20 were used for subsequent information analysis. MACS3 software was used for Peak analysis, and MAnorm was used for differential peak analysis between two samples. Use ChipSeeker to associate the peak with nearby genes to predict possible regulatory relationships, and annotate the gene elements where they are located and the distance to the transcription start site (TSS). Annotate the peak-related genes to the GO term database, and find out the GO terms that are significantly enriched in the peak-related genes compared with the whole genome background. Use KEGG Pathway as a unit to find out the pathways that are significantly enriched in the peak-related genes compared with the whole genome background, and also use hypergeometric distribution for enrichment test. Use IGV software to visualize the peak.

[0102] In a specific embodiment, the method of statistical analysis includes: the data are expressed as mean ± standard deviation, and the Western blot and immunofluorescence data are quantitatively analyzed using ImageJ software. The data between two groups are tested by independent sample t test, and the data between multiple groups are tested by one-way analysis of variance, followed by Tukey's multiple comparisons test. All data are analyzed by SPSS software, and P < 0.05 is considered to be statistically significant.

[0103] In one embodiment, abnormal morphology of DMD muscle nuclei and accumulation of LB1 in DMD skeletal muscle: The pathological characteristics of DMD patients are described, and HE staining shows that the distribution, morphology, and number of muscle nuclei in DMD patients are abnormal, and the muscle cells are of different sizes, with necrosis and atrophy ( Figure 4A); Immunohistochemical staining showed that the myocyte membrane of DMD patients lacked dystrophin-N, dystrophin-C, and dystrophin-R proteins ( Figure 4 B).

[0104] The expression level of LB1 protein is closely related to the shape of the cell nucleus. To clarify the expression level of LB1 protein in DMD skeletal muscle, immunofluorescence, WB and PCR detection were performed. The results of immunofluorescence staining showed that the number of myocyte nuclei increased, the distribution and morphology were abnormal, and the LB1 fluorescence intensity increased, indicating that the LB1 content in the cell nucleus increased ( Figure 4 C). WB results showed that the LB1 protein content was higher in DMD patients compared with healthy controls (HP) ( Figure 4 D).

[0105] In the DMD animal model, WB analysis of TA cell nuclei in mdx mice showed that the LB1 protein content in skeletal muscle tissue was increased (P<0.05, Figure 4 E). To further determine the cause of the increased LB1 protein content, LB1 RNA levels were measured. The results showed that LB1 RNA expression levels were reduced in both DMD patients and mdx mice ( Figure 4 F); This indicates that LB1 degradation is impaired, leading to its accumulation in the nucleus of DMD skeletal muscle cells.

[0106] In one embodiment, accumulation of autophagosomes and impairment of the autophagic pathway in DMD skeletal muscle tissue: PCR results showed that the RNA expression levels of TFEB, PINK1, PARKIN, and LC3 in skeletal muscle tissue of DMD patients were reduced compared with healthy controls (HP) ( Figure 5 A). Subsequently, the autophagy pathway involved in LB1 degradation was detected in the DMD mouse model. The results showed that the RNA levels of Pink1, Parkin, and LC3 were downregulated in mdx mice compared with C57 mice ( Figure 5 B).

[0107] WB analysis showed that the expression levels of LC3II / LC3I and P62 in the mdx group mice were increased compared with those in the C57 mice ( Figure 5 C and Figure 5 D). In addition, compared with HP patients, DMD patients also showed increased expression levels of LC3II / LC3I and P62 in skeletal muscle tissue ( Figure 5 E and Figure 5 F).

[0108] Immunofluorescence analysis showed that the immunofluorescence intensity of LC3 and P62 was increased in skeletal muscle cells of mdx mice and DMD patients ( Figure 5 G and Figure 5 H).

[0109] In one embodiment, impaired nuclear autophagy in DMD skeletal muscle tissue leads to LB1 accumulation: LB1 is one of the substrates of selective nuclear autophagy and is degraded by interacting with LC3. To further determine the cause of LB1 accumulation, the nuclear autophagy status in DMD was studied. The autophagosomes were labeled with LC3 antibodies, and the intracellular LB1 protein was labeled with LB1 antibodies. Fluorescence microscopy results showed that LC3 was punctately aggregated in muscle cells of DMD patients and mdx mice; in addition, the co-localization of LC3 and nuclear LB1 protein increased ( Figure 6 A and Figure 6 C). P62 is an important marker for assessing the integrity of the autophagy pathway. Fluorescence microscopy showed increased co-localization of P62 and LB1 in the nuclei of muscle cells from DMD patients and mdx mice, indicating impaired nuclear autophagy ( Figure 6 B and Figure 6 D).

[0110] Tibialis anterior (TA) muscle of mdx mice was selected for further study. WB analysis of isolated nuclei showed that the ratio of LC3II / LC3I and P62 expression levels were significantly increased compared with the control group, further confirming the disruption of the nuclear autophagy pathway (P<0.05, Figure 6 E and Figure 6 F). This finding is consistent with the immunofluorescence results, providing a strong and convincing conclusion.

[0111] The study of this application is of great significance for understanding the relationship between LB1 accumulation and impaired autophagy. This relationship was further elucidated using C2C12 cells. By adding the autophagy inhibitor chloroquine (CQ) and measuring the LB1 protein expression level using WB, it was found that in cells treated with autophagy inhibitors, the expression levels of LC3II / LC3I, P62, and LB1 were all increased ( Figure 6 G). This emphasizes the importance of the findings of this application for understanding the role of autophagy in cellular health. Immunofluorescence results in C2C12 cells after addition of CQ showed punctate aggregation of LC3. This indicates accumulation of autophagosomes, and abnormal nuclear morphology was observed ( Figure 6 H). At the same time, the immunofluorescence intensity of P62 and LB1 in the cells increased ( Figure 6 I and Figure 6 J), indicating that autophagy in the cells was inhibited and nuclear morphology was altered.

[0112] In one embodiment, LB1 overexpression leads to decreased SRSF2 expression level: In order to further clarify the effect of LB1 accumulation on cell function, an LB1 overexpression plasmid was constructed and transfected into C2C12 cells. RNA-seq was used to observe the expression changes of other genes and proteins in cells when LB1 was overexpressed. First, WB and immunofluorescence were used to evaluate the transfection efficiency. The results showed that the expression of LB1 protein in the overexpression group increased, the immunofluorescence intensity increased, and the nuclear morphology was abnormal ( Figure 7 A and Figure 7 B), indicating successful transfection.

[0113] The sequencing results showed that compared with the WT group, there were 1021 up-regulated genes and 589 down-regulated genes in the overexpression group ( Figure 7 C). GO analysis showed that the up-regulated genes were enriched in pathways related to cell growth, differentiation, and apoptosis ( Figure 7 D). There are many down-regulated genes, which are related to RNA splicing, cell cycle, and P53 signaling pathway, including the splicing regulatory factor SRSF2 ( Figure 7 E).

[0114] To verify the results of RNA-seq, WB and PCR were performed, and the results showed that both the protein and RNA expression levels of SRSF2 were decreased in the LB1 overexpression group, which was consistent with the RNA-seq data ( Figure 7 F and Figure 7 G). In addition, the present application confirmed that the RNA expression level of SRSF2 was reduced in skeletal muscle tissue of DMD patients and mdx mice ( Figure 7 H). WB analysis of TA-isolated nuclei from mdx mice showed that the protein expression level of SRSF2 was reduced in the nuclear fraction ( Figure 7 I).

[0115] In one embodiment, LB1 overexpression inhibits SRSF2 expression through abnormal LAD arrangement: This application thoroughly and meticulously studied the distribution characteristics of LAD (layer-associated domain) in C2C12 cells when LB1 was overexpressed. CUT&Tag analysis was performed on LB1 in the control group and the overexpression group to determine the LAD region. Representative LAD analysis showed that gene enrichment in LAD and non-LAD regions was altered ( Figure 8 A). The number of peaks and the total length of the LAD region were altered in both groups ( Figure 8 B), further confirming the change in LAD distribution. The binding sites of the LB1 overexpression group changed and were mainly distributed in the promoter, exon and intron ( Figure 8 C). Notably, the LAD of the LB1 overexpression group gained 441 genomic regions and lost 2,037 genomic regions compared with the control group ( Figure 8D). Overexpression of LB1 leads to rearrangement of 2,478 LAD regions in the genome of C2C12 cells.

[0116] In summary, the number and average length of LAD in the overexpression group were slightly reduced compared with the control group, indicating that the distribution of LAD in the overexpression group was redistributed. The KEGG classification of 441 target genes in the overexpression group showed that these target genes were involved in metabolism, genetic information processing, environmental information processing and cellular processes ( Figure 8 E). GO enrichment analysis showed that the increased genes included the splicing regulatory factor SRSF2 ( Figure 8 F), indicating that the accumulation of LB1 leads to abnormal LAD distribution, thereby inhibiting the expression of SRSF2.

[0117] In one embodiment, SRSF2 regulates BCL-xl expression and leads to apoptosis of DMD skeletal muscle cells: To further clarify the mechanism by which SRSF2 regulates BCL-xl expression, SRSF2 knockdown and overexpression plasmids were constructed and transfected into C2C12 cells to observe the effect of BCL-xl expression on cell apoptosis. WB analysis was performed to detect the knockdown efficiency, and the results showed that the SRSF2 protein level in the knockdown group was reduced ( Fig. 9 A), indicating that the knockdown was successful. TUNEL assay showed that apoptosis in the knockdown group increased significantly ( Fig. 9 B). PCR results showed that the expression of BCL-xl in the muscle tissue of SRSF2 knockdown group, mdx mice and DMD patients was decreased ( Fig. 9 C, 9D, 9E). In RNA-IP experiments with isoform-specific primers, SRSF2 clearly bound to Bcl-xL ( Fig. 9 F).

[0118] Next, the SRSF2 overexpression plasmid was transfected into C2C12 cells, and WB confirmed the effectiveness of overexpression, showing that the SRSF2 protein level was increased ( Fig. 9 G). TUNEL assay showed no difference in apoptosis between the overexpression group and the control group ( Fig. 9 H). PCR analysis showed that the expression level of BCL-xl was increased in the SRSF2 overexpression group ( Fig. 9 I).

[0119] To further verify the role of SRSF2 and BCL-xl in the progression of DMD, an adenoviral vector overexpressing SRSF2 was constructed and injected into the TA muscle of mdx mice to observe the expression and apoptosis of BCL-xl in skeletal muscle cells. The overexpression efficiency results showed that the expression of SRSF2 in the AAV9-SRSF2 group was increased compared with that in the AAV9-Vector group ( Fig. 9 K). PCR analysis showed that the Bcl-xl RNA expression level was higher in the AAV9-SRSF2 group ( Fig. 9 J). TUNEL assay showed that compared with the AAV9-Vector group, the cell apoptosis in the AAV9-SRSF2 group was reduced ( Fig. 9 L). These findings suggest that SRSF2 can regulate BCL-xl expression and participate in the apoptotic pathway of skeletal muscle cells in DMD.

[0120] In one embodiment, upregulation of SRSF2 expression in skeletal muscle of mdx mice can improve motor function and skeletal muscle pathology: an adenoviral vector was constructed to overexpress SRSF2 and injected into the TA muscle of mdx mice to observe the improvement of motor function and skeletal muscle pathology. The results of the Rotarod test showed that the motor function of the mice was significantly improved compared with the control group one week after injection ( Fig.10 A). Skeletal muscle pathology results showed that after upregulation of SRSF2, the proportion of immature muscle fibers in mdx mice was lower than that in the control group, indicating that the maturity of skeletal muscle cells increased ( Fig.10 B). WB analysis showed that the ratio of cleavedcaspase-3 / caspase-3 in the AAV9-SRSF2 group was lower than that in the AAV9-Vector group, indicating that cell apoptosis was reduced ( Fig.10 C) These findings suggest that upregulating SRSF2 expression can reduce skeletal muscle apoptosis, promote myofiber maturation, and improve motor function in mdx mice.

[0121] 102: Determine the binding sites of the LB1 protein and the SRSF2 protein according to the data of the two proteins. In some embodiments, virtual screening is an important method in targeted drug design, and its process is roughly as follows:

[0122] First, based on the known complex structure of the drug and the target protein, the binding mode of the drug and the target protein is studied to determine the key amino acid residues. This step helps to understand how the drug interacts with the target protein and provides a basis for subsequent virtual screening.

[0123] Next, a large number of small molecule compounds are virtually screened using computer-aided drug design methods. In this process, the binding ability of small molecule compounds to target proteins will be predicted and evaluated. Generally, small molecules with low binding energy and good shape complementarity will be selected as potential drug candidates.

[0124] Finally, the screened candidate drugs are further experimentally verified to confirm their interaction with the target protein and their biological activity.

[0125] In some embodiments, the binding site is a specific part of a molecule that can form a stable interaction with a ligand. The binding site of a protein is usually formed by a certain number of separated amino acid residues on a polypeptide chain that are gathered together in space through the folding of the polypeptide chain to form a specific spatial arrangement.

[0126] Once the binding site is determined, the computer-aided drug design method can be used to dock the compounds in the small molecule compound library with the target protein. During the docking process, the computer simulates the interaction between the compound and the binding site and evaluates their binding ability. Based on the docking results, small molecule compounds with strong binding ability to the target protein can be screened as potential drug candidates. The determination of virtual screening binding sites is crucial to the success of drug design. Therefore, when determining the binding site, it is necessary to consider a variety of factors, such as the structural characteristics of the target protein, the binding mode of known ligands, etc. At the same time, in the virtual screening process, the binding site also needs to be reasonably processed and optimized to improve the accuracy and efficiency of the screening.

[0127] In some embodiments, the molecular libraries used in virtual screening mainly include the following:

[0128] ZINC: contains more than 250 million commercially available compounds for small molecule virtual screening.

[0129] PubChem: contains bioactive substances for small molecule virtual screening.

[0130] DrugBank: Contains drugs and small molecules for drug design and discovery.

[0131] ChEMBL: Contains small molecules and is used for drug discovery and chemical genomics research.

[0132] ChemDB: Contains a large number of known small molecules for chemical genomics research and drug discovery.

[0133] HMDB: Contains a large number of known small molecules for use in chemical genomics research and drug discovery.

[0134] BindingDB: Contains a large number of known small molecules for chemical genomics research and drug discovery.

[0135] SMPDB: Contains a large number of known small molecules for chemical genomics research and drug discovery.

[0136] In addition, there are some commercial databases such as ChemDiv, Enamine, Lifechemicals, Specs, Chembridge, Maybridge, Microsource, Vitas-M and Interbioscreen, which are also often used for virtual screening.

[0137] 103: Obtaining candidate drugs targeting the binding sites of the two through computer-assisted screening

[0138] In some embodiments, the process of computer-assisted screening is:

[0139] Screening of small molecule compounds based on the spatial structure of the binding sites of LB1 protein and SRSF2 protein;

[0140] The small molecule compounds obtained by screening are molecularly docked with the binding sites to obtain the scores of the docking molecules;

[0141] The candidate drugs are obtained by sorting according to the scores.

[0142] In other embodiments, the computer-assisted screening process is:

[0143] The molecular structures of LB1 protein and SRSF2 protein are obtained and input into the pharmacophore module library for matching, and all the action sites are clustered based on the interaction mode with LB1 and SRSF2 to obtain the pharmacophore model;

[0144] The pharmacophore model is input into a molecular compound database for high throughput screening to obtain candidate drugs.

[0145] In other embodiments, the computer-assisted screening process is:

[0146] Obtain the molecular structure of a small molecule inhibitor that inhibits LB1 and / or the molecular structure of a small molecule promoter that promotes SRSF2;

[0147] Based on the molecular structure of the small molecule inhibitor / promoter, a small molecule library with similar structure is obtained by screening;

[0148] Performing molecular docking on the small molecule library with similar structures and the binding site to obtain a score of the docked molecule;

[0149] The candidate drugs are obtained by sorting according to the scores.

[0150] In some embodiments, computer-aided drug screening is a technology that uses computer-aided drug design methods to screen drugs. It can help researchers quickly screen candidate drugs with strong binding ability to target proteins and potential efficacy from a large number of small molecule compounds.

[0151] In some embodiments, molecular docking is a method for drug design based on the characteristics of receptors and the interaction between receptors and drug molecules. It mainly studies the interaction between molecules (such as ligands and receptors) and predicts their binding mode and affinity. This method is widely used in the early stages of drug development and can help researchers quickly screen out compounds with potential efficacy.

[0152] Molecular docking methods mainly focus on spatial matching and energy matching. Spatial matching refers to the geometric complementarity between the drug molecule and the receptor protein, while energy matching refers to the minimization of the interaction between the drug molecule and the receptor protein. For the calculation of geometric matching, grid point calculation, fragment growth and other methods are usually used, while energy calculation uses simulated annealing, genetic algorithm and other methods.

[0153] According to the degree and method of simplification, molecular docking methods can be divided into rigid docking, semi-flexible docking and flexible docking. In the rigid docking method, the molecular conformations involved in the docking do not change during the calculation process, only the spatial position and posture of the molecules are changed. Semi-flexible docking allows some conformations to change during the calculation. Flexible docking allows more conformational changes.

[0154] In some embodiments, in molecular docking, affinity refers to how tightly a molecule binds to a receptor. A high affinity means that the binding is more stable, while a low affinity means that the binding is less stable. Affinity is usually calculated, for example, by calculating the binding free energy (ΔG) or the binding constant (Kd).

[0155] In the process of molecular docking, affinity depends on the interaction between molecules and receptors, including hydrogen bonds, van der Waals forces, electrostatic interactions, etc. These interactions jointly determine the binding mode between molecules and receptors, thus affecting affinity.

[0156] In order to evaluate affinity, some scoring systems or scoring methods are usually used to quantify the interaction between molecules and receptors. These scoring methods are based on different algorithms and physical models, which can reflect the binding energy, interaction type and affinity between molecules and receptors.

[0157] In some embodiments, the process and method of designing protein analogs, antibodies and other drugs based on proteins can be summarized as follows:

[0158] Determine the target protein: First, you need to determine the target protein for drug design, that is, the target. The target can be a known disease-related protein, viral antigen or other biological molecule.

[0159] Protein structure analysis: Perform structural analysis on the target protein to understand its three-dimensional conformation, surface configuration, subdomain structure and other characteristics. This can be obtained through X-ray crystal diffraction, nuclear magnetic resonance and other technologies.

[0160] Determine drug-protein interactions: Study the interaction mechanism between the drug and the target protein, including binding sites, binding modes, and binding kinetics. This can be done through computer simulations, laboratory experiments, and other methods.

[0161] Drug design: Based on the interaction mechanism between the drug and the target protein, design drug molecules that can specifically bind to the target protein. This includes selecting the appropriate drug type, designing the chemical structure of the molecule, and optimizing the drug efficacy and pharmacokinetic properties of the molecule.

[0162] Synthesize and validate drugs: Prepare drug molecules through chemical synthesis and other methods, and validate their biological activity, safety and pharmacokinetic properties. This includes different stages such as cell experiments, animal experiments and clinical trials.

[0163] In some embodiments, the candidate drugs include protein analogs, antibodies, and RNA drugs.

[0164] In some embodiments, protein analogs refer to substances that have similar structures and functions to certain proteins in the body. They can mimic the functions of proteins and thus play an important role in disease treatment.

[0165] Antibodies are immunoglobulins produced by plasma cells differentiated from B lymphocytes under antigen stimulation, which can specifically bind to the corresponding antigen. The structure of antibodies is mainly divided into two parts: constant region and variable region. In a given species, the constant regions of different antibody molecules have the same or almost the same amino acid sequence. The variable region is located at the ends of the two arms of the "Y".

[0166] RNA drugs are a class of drugs designed based on the properties of RNA and its mechanism of action in cells. RNA can act as messenger RNA (mRNA) to guide protein synthesis in cells, or as microRNA (miRNA) to regulate gene expression. Therefore, rationally designed RNA drugs can be used to regulate gene expression in cells to achieve the purpose of treating diseases. For example, many studies are exploring the use of mRNA vaccines to prevent and treat various infectious diseases.

[0167] In some embodiments, the general steps for performing an inhibitory activity experiment on a small molecule compound are as follows:

[0168] Select the appropriate target protein: According to the research purpose and disease target, select the appropriate target protein as the experimental object. Make sure that the target protein has potential interaction with the small molecule compound being studied.

[0169] Preparation of small molecule compounds: Synthesize or purchase the required small molecule compounds and ensure their purity and structural accuracy. If necessary, the small molecule compounds can be modified or transformed to optimize their inhibitory activity.

[0170] Enzyme activity assay: Design appropriate enzyme activity assays to evaluate the inhibitory activity of small molecule compounds on target proteins. This can be achieved through techniques such as fluorescence resonance energy transfer (FRET), radioisotope labeling, and enzyme-linked immunosorbent assay (ELISA). Ensure that the assay is reliable, sensitive, and can accurately reflect the interaction between small molecule compounds and target proteins.

[0171] Experimental operation: Mix small molecule compounds of different concentrations with the target protein, incubate for a period of time under appropriate conditions, and then measure the enzyme activity. According to the experimental design, a control group and an experimental group can be set up to compare the inhibitory activity of different small molecule compounds.

[0172] Data analysis: The IC50 value of the small molecule compound (i.e., the concentration of the compound required to inhibit 50% of the enzyme activity) is determined by statistical analysis of the experimental data. The smaller the IC50 value, the stronger the inhibitory activity of the small molecule compound. In addition, a dose-effect curve can be drawn to intuitively display the inhibitory activity of the small molecule compound.

[0173] Interpretation and discussion of results: Based on the experimental results, analyze the inhibitory activity of small molecule compounds on target proteins and discuss them in combination with their structures and properties. Explore possible binding modes, mechanisms of action, and comparisons with known inhibitors. In addition, the effects of small molecule compounds on cells or organisms can be further studied to evaluate their potential drug candidates.

[0174] In some embodiments, the computer-assisted drug screening technology for drug screening includes one or more of the following: protein-small molecule docking, protein-protein docking, protein-nucleic acid docking.

[0175] In some embodiments, protein-small molecule docking refers to a computational simulation process of docking the structures of proteins and small molecules (such as drug molecules) together through certain algorithms and programs. This process can be used to study the interactions between proteins and small molecules, as well as possible biological functions.

[0176] In protein-small molecule docking, software such as DOCK is usually used for computational simulation. DOCK is a highly automated drug design software that can achieve docking between small molecule ligands and biomacromolecule receptors. It uses a fragment-based scoring method to achieve fast and accurate docking. The basic algorithm of DOCK software includes two stages. The first stage is the low-precision stage, which mainly searches for a rough match between small molecule ligands and biomacromolecule receptors. The second stage is the high-precision stage, in which all side chain conformations are considered to calculate more accurate interaction energy. In the low-precision stage, DOCK software will randomly translate and rotate small molecule ligands, perform a certain number of rigid body moves, and then calculate the interaction energy. After outputting the lowest conformation, it enters the high-precision stage. In the high-precision stage, the program will perform more optimization and adjustments to achieve more accurate docking.

[0177] In some embodiments, protein-protein docking refers to a computational simulation process of docking the structures of two proteins together through certain algorithms and programs. This process can be used to study the interactions between proteins and possible biological functions.

[0178] RosettaDock is a commonly used protein-protein docking software that uses a fragment-based scoring method to achieve fast and accurate protein docking. The software can achieve precise adjustment of side chain conformations during docking and consider a variety of complex interactions, such as hydrogen bonds, ionic bonds, hydrophobic interactions, etc. The basic algorithm of RosettaDock includes two stages. The first stage is the low-precision stage, which mainly searches for the degree of adaptation of the backbone shapes between the two proteins. The second stage is the high-precision stage, in which all side chain conformations are considered to calculate more accurate interaction energies. In the low-precision stage, the program randomly translates and rotates a component of a protein molecule, performs a certain number of rigid body moves, and then calculates the interaction energy. After outputting the lowest conformation, it enters the high-precision stage. In the high-precision stage, the program performs 50 MCMPCycles: rearranges the conformation and minimizes the interaction energy, which is used as the initial starting conformation.

[0179] In some embodiments, protein-nucleic acid docking refers to a computational simulation process of docking the structures of proteins and nucleic acids (such as DNA or RNA) together through certain algorithms and programs. This process can be used to study the interactions between proteins and nucleic acids, as well as possible biological functions.

[0180] In protein-nucleic acid docking, software such as NAflex is usually used for computational simulation. NAflex is a software developed specifically for nucleic acid structure prediction and design, which can achieve accurate modeling and docking of DNA or RNA molecules. NAflex software uses a fragment-based scoring method to achieve fast and accurate docking. It takes into account a variety of complex interactions, such as hydrogen bonds, ionic bonds, hydrophobic interactions, etc., and can achieve precise adjustment of side chain conformations during docking. The basic algorithm of NAflex software includes two stages. The first stage is the low-precision stage, which mainly searches for rough matches between proteins and nucleic acids. The second stage is the high-precision stage, in which all side chain conformations are considered and more accurate interaction energies are calculated. In the low-precision stage, NAflex software randomly translates and rotates nucleic acid molecules, performs a certain number of rigid body moves, and then calculates the interaction energy. After outputting the lowest conformation, it enters the high-precision stage. In the high-precision stage, the program will perform more optimization and adjustments to achieve more accurate docking.

[0181] Figure 2 It is a schematic diagram of a system for computer-assisted drug screening based on LB1 and SRSF2 provided by the present invention, specifically comprising: 201: an acquisition unit: acquiring LB1 protein and SRSF2 protein data;

[0182] 202: site determination unit: determining the binding site of the two proteins according to the data of the LB1 protein and the SRSF2 protein;

[0183] 203: Screening unit: Obtain candidate drugs targeting the binding sites of the two through computer-assisted screening.

[0184] Figure 3 It is a schematic diagram of the device for computer-assisted drug screening based on LB1 and SRSF2 provided by the present invention, which specifically includes: a memory and a processor, wherein the memory is used to store program instructions; the processor is used to call program instructions, and when the program instructions are executed, the above-mentioned computer-assisted drug screening method based on LB1 and SRSF2 is implemented.

[0185] The present invention provides the use of a promoter of SRSF2 in preparing a pharmaceutical composition for treating Duchenne muscular dystrophy.

[0186] The pharmaceutical composition also includes pharmaceutically acceptable excipients.

[0187] In some embodiments, a pharmaceutically acceptable excipient is used to refer to a material that is compatible with a recipient, preferably a mammal, more preferably a human, and is suitable for delivering an active agent to a target site without terminating the activity of the agent. Toxicity or side effects (if any) associated with the pharmaceutically acceptable excipient are preferably commensurate with a reasonable risk / benefit ratio for the intended use of the active agent.

[0188] Pharmaceutically acceptable excipients include, but are not limited to, diluents, adhesives, surfactants, wetting agents, adsorption carriers, lubricants, fillers, and disintegrants. These excipients are used to help the stability of the formulation or to help improve the activity or its biological effectiveness or to produce an acceptable taste or smell in the case of oral administration. The preparations that can be used in this medicine can be in the form of the original compound itself or optionally in the form of a pharmaceutically acceptable salt thereof. The pharmaceutical composition thus prepared can be administered in any appropriate manner known to those skilled in the art as needed.

[0189] Among them, the diluent includes but is not limited to lactose, sodium chloride, glucose, urea, starch, and water.

[0190] Binders include, but are not limited to, starch, pregelatinized starch, dextrin, maltodextrin, sucrose, gum arabic, gelatin, methylcellulose, carboxymethylcellulose, ethylcellulose, polyvinyl alcohol, polyethylene glycol, polyvinylpyrrolidone, alginic acid and alginates, xanthan gum, hydroxypropyl cellulose and hydroxypropyl methylcellulose.

[0191] Surfactants include, but are not limited to, polyoxyethylene sorbitan fatty acid esters, sodium lauryl sulfate, stearic acid monoglyceride, and cetyl alcohol.

[0192] Humectants include, but are not limited to, glycerin.

[0193] Adsorption carriers include, but are not limited to, bentonite, silica gel, kaolin, and bentonite.

[0194] Lubricants include, but are not limited to, zinc stearate, glyceryl monostearate, polyethylene glycol, talc, calcium and magnesium stearate, polyethylene glycol, boric acid powder, hydrogenated vegetable oil, sodium stearyl fumarate, polyoxyethylene monostearate, monolauric sucrose ester, sodium lauryl sulfate, magnesium lauryl sulfate, and magnesium dodecyl sulfate.

[0195] Fillers include, but are not limited to, mannitol (granular or powdered), xylitol, sorbitol, maltose, erythrose, microcrystalline cellulose, polymeric sugars, coupling sugars, glucose, lactose, sucrose, dextrin, starch, sodium alginate, laminarin powder, agar powder, calcium carbonate, and sodium bicarbonate.

[0196] Disintegrants include, but are not limited to, cross-linked vinyl pyrrolidone, sodium carboxymethyl starch, low-substituted hydroxypropyl methyl, cross-linked sodium carboxymethyl cellulose, and soybean polysaccharides.

[0197] The verification results of this verification embodiment show that assigning inherent weights to indications can improve the performance of the method relative to the default setting. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units. A person of ordinary skill in the art may understand that all or part of the steps in the various methods of the above-mentioned embodiments may be completed by instructing the relevant hardware through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0198] A person of ordinary skill in the art can understand that all or part of the steps in the above-mentioned embodiment method can be implemented by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. The above-mentioned medium storage can be a read-only memory, a disk or an optical disk, etc.

[0199] The above is a detailed introduction to a computer device provided by the present invention. For a person skilled in the art, according to the concept of the embodiments of the present invention, there may be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for computer-assisted drug screening based on LB1 and SRSF2, characterized in that: The method comprises: Obtain LB1 protein and SRSF2 protein data; Determine the binding sites of the two proteins based on the data of the LB1 protein and the SRSF2 protein; Through computer-assisted screening, candidate drugs targeting the binding sites of the two were obtained; Preferably, the process of computer-assisted screening is: Screening of small molecule compounds based on the spatial structure of the binding sites of LB1 protein and SRSF2 protein; The small molecule compounds obtained by screening are molecularly docked with the binding sites to obtain the scores of the docking molecules; Sorting according to the scores to obtain candidate drugs; Preferably, the process of computer-assisted screening is: The molecular structures of LB1 protein and SRSF2 protein are obtained and input into the pharmacophore module library for matching, and all the action sites are clustered based on the interaction mode with LB1 and SRSF2 to obtain the pharmacophore model; Inputting the pharmacophore model into a molecular compound database for high-throughput screening to obtain candidate drugs; Preferably, the process of computer-assisted screening is: Obtain the molecular structure of the LB1 small molecule inhibitor and / or the molecular structure of the SRSF2 small molecule promoter; Based on the molecular structure of the small molecule inhibitor / promoter, a small molecule library with similar structure is obtained by screening; Performing molecular docking on the small molecule library with similar structures and the binding site to obtain a score of the docked molecule; Sorting according to the scores to obtain candidate drugs; Preferably, the candidate drugs include protein analogs, antibodies, and RNA drugs.

2. A computer-assisted drug screening system based on LB1 and SRSF2, characterized in that: The system comprises: Acquisition unit: acquire LB1 protein and SRSF2 protein data; Site determination unit: determining the binding sites of the two proteins according to the data of the LB1 protein and the SRSF2 protein; Screening unit: Obtain candidate drugs targeting the binding sites of the two through computer-assisted screening.

3. A computer-assisted drug screening device based on LB1 and SRSF2, characterized in that: The device comprises: A memory and a processor, wherein the memory is used to store program instructions; the processor is used to call the program instructions, and when the program instructions are executed, the computer-assisted drug screening method based on LB1 and SRSF2 as described in claim 1 is implemented.

4. A computer-readable storage medium having a computer program thereon, characterized in that: The computer readable storage medium comprises: When the computer program is executed by a processor, the computer-assisted drug screening method based on LB1 and SRSF2 according to claim 1 is implemented.

5. A computer program product, characterized in that The product comprises a computer program, which, when executed by a processor, implements the steps of the method for computer-assisted drug screening based on LB1 and SRSF2 as claimed in claim 1.

6. Any of the following applications: (1) Use of a promoter of SRSF2 in the preparation of a pharmaceutical composition for treating Duchenne muscular dystrophy; (2) Use of an agent that inhibits the binding of LB1 and SRSF2 in the preparation of a pharmaceutical composition for treating Duchenne muscular dystrophy; (3) Use of an agent that promotes the binding of SRSF2 and BCL-xl in the preparation of a pharmaceutical composition for treating Duchenne muscular dystrophy; (4) Application of the complex formed by the binding of SRSF2 and BCL-xl in screening candidate drugs for the treatment of Duchenne muscular dystrophy; (5) Application of LB1 in the preparation of SRSF2 expression regulators in cells; (6) Application of LB1 in the preparation of cell models with low SRSF2 expression; Preferably, the promoter of SRSF2 includes a substance capable of promoting the expression level / activity of SRSF2; Preferably, the substance that promotes the expression level / activity of SRSF2 includes a vector for overexpression of SRSF2; Preferably, the pharmaceutical composition further comprises a pharmaceutically acceptable excipient.

7. A composite, characterized in that The complex includes LB1 and SRSF2, or SRSF2 and BCL-xl.

8. A method for screening candidate drugs for treating Duchenne muscular dystrophy, characterized in that: The method comprises the following steps: (1) contacting a substance to be detected with a system expressing or containing SRSF2; (2) detecting the expression level of SRSF2 in the system; (3) selecting substances that can promote the expression level / activity of SRSF2 as candidate drugs for the treatment of Duchenne muscular dystrophy; Or the method comprises the following steps: (1) contacting a substance to be detected with a system containing a complex formed by LB1 and SRSF2; (2) detecting the binding level of LB1 and SRSF2 in the system; (3) selecting substances that inhibit the binding of LB1 and SRSF2 as candidate drugs for the treatment of Duchenne muscular dystrophy; Or the method comprises the following steps: (1) contacting a substance to be detected with a system containing a complex formed by SRSF2 and BCL-xl; (2) detecting the binding level of SRSF2 and BCL-xl in the system; (3) Select substances that promote the binding of SRSF2 and BCL-xl as candidate drugs for the treatment of Duchenne muscular dystrophy.

9. A method for regulating SRSF2 expression in a cell, characterized in that: The method comprises altering the expression / activity of LB1 in a cell; Preferably, the method of inhibiting SRSF2 expression in a cell comprises promoting the expression / activity of LB1 in the cell; Preferably, promoting the expression / activity of LB1 in the cell comprises administering a promoter of LB1 to the cell; Preferably, a promoter of LB1 is administered to the nucleus; Preferably, the method for promoting SRSF2 expression in a cell comprises inhibiting the expression / activity of LB1 in the cell; Preferably, inhibiting the expression / activity of LB1 in the cell comprises administering an inhibitor of LB1 to the cell; Preferably, an inhibitor of LB1 is administered to the nucleus; Preferably, the cells are selected from C2C12 cells.

10. A method for constructing a cell model with low SRSF2 expression or high SRSF2 expression, characterized in that: The method comprises regulating the expression / activity of LB1 in a cell; Preferably, the method for constructing a cell model with low SRSF2 expression comprises promoting the expression / activity of LB1 in the cell; Preferably, promoting the expression / activity of LB1 in the cell comprises administering a promoter of LB1 to the cell; Preferably, a promoter of LB1 is administered to the nucleus; Preferably, the method for constructing a cell model with high expression of SRSF2 comprises inhibiting the expression / activity of LB1 in the cell; Preferably, inhibiting the expression / activity of LB1 in the cell comprises administering an inhibitor of LB1 to the cell; Preferably, an inhibitor of LB1 is administered to the nucleus; Preferably, the cells are selected from C2C12 cells.

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