A small molecule polypeptide interfering with the binding of CD44 and STAT3, a pharmaceutical composition thereof and application thereof

Abstract

A small molecule polypeptide interfering with the combination of CD44 and STAT3, a pharmaceutical composition thereof and application, the amino acid sequence of the polypeptide is shown as SEQ ID NO: 1 (TGNYKALHPHNG-DQFMTADE). The polypeptide is based on the polypeptide fragment homologous to the intracellular segment of CD44, and the brain-targeting cell-penetrating peptide (TGNYKALHPHNG) is connected to the N-terminal of the polypeptide fragment, and the polypeptide fragment homologous to the intracellular segment of CD44 is the sequence DQFMTADE at positions 722-729 and can specifically bind to STAT3. The polypeptide specifically interferes with the combination of CD44 and STAT3, inhibits the phosphorylation of STAT3, down-regulates the apoptosis-related signal pathway, reduces the apoptosis of hippocampal neurons, thereby improves diabetic cognitive impairment, and has the advantages of high specificity, low toxicity, good penetration and the like, and provides a new strategy for the treatment of diabetic cognitive impairment.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically relating to a small molecule polypeptide that interferes with the binding of CD44 and STAT3, its pharmaceutical composition, and its application. Background Technology

[0002] Diabetes mellitus is a metabolic disorder characterized by persistent hyperglycemia, which can cause serious complications in multiple tissues and organs throughout the body. With the continuous increase in the incidence of diabetes, the prevalence of cognitive impairment and dementia caused by diabetes has surged, and dementia is now one of the leading causes of death among diabetic patients. Studies have shown that diabetic cognitive impairment is closely related to damage to the hippocampus in the brain caused by hyperglycemia. However, the pathogenesis of diabetes-related cognitive impairment remains unclear, and no specific methods for diagnosing and treating this disease have been found. Therefore, identifying new targets for brain damage caused by hyperglycemia is of great significance for the development of new therapeutic drugs.

[0003] Protein-protein interactions are considered one of the core mechanisms underlying diabetic cognitive impairment. CD44 plays a crucial role in multiple physiological processes, including cell adhesion, immune response, and cell migration. STAT3 plays a key role in physiological processes such as cell growth, immune response, and neural development. While STAT3 activation is very brief under physiological conditions, it is persistently activated under pathological conditions, leading to numerous diseases. Targeting STAT3 phosphorylation is a hot research topic for new drugs. However, due to poor selectivity, significant toxicity, and low compound permeability, no STAT3 inhibitors have yet been approved for marketing. Furthermore, other treatment methods have unsatisfactory clinical efficacy, low safety profiles, and insufficient evidence to support their long-term effectiveness. Therefore, there is an urgent need to develop a new treatment approach that is highly specific, safe, and effectively improves diabetic cognitive impairment. Summary of the Invention

[0004] The purpose of this invention is to provide a small molecule polypeptide that interferes with the binding of CD44 and STAT3, its pharmaceutical composition, and its application. This small molecule polypeptide and pharmaceutical composition can specifically block the interaction between CD44 and STAT3, inhibit STAT3 phosphorylation, downregulate apoptosis-related signaling pathways, reduce hippocampal neuron apoptosis, thereby improving diabetic cognitive impairment. It also has the advantages of high specificity, low toxicity, and good penetration.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: a small molecule polypeptide that interferes with the binding of CD44 and STAT3, the amino acid sequence of which is shown in SEQ ID NO:1.

[0006] Furthermore, the small molecule peptide is based on a polypeptide fragment homologous to the intracellular segment of CD44, and a brain-targeting cell-penetrating peptide is linked to the N-terminus of the polypeptide fragment to construct a small molecule peptide that interferes with the binding of CD44 and STAT3, namely the interfering peptide CD44-Peptide; the polypeptide fragment homologous to the intracellular segment of CD44 has an amino acid sequence DQFMTADE at positions 722-729 and can specifically bind to STAT3; the amino acid sequence of the brain-targeting cell-penetrating peptide is TGNYKALHPHNG.

[0007] Furthermore, the small molecule peptide inhibits STAT3 phosphorylation by interfering with the binding of CD44 and STAT3, downregulates apoptosis-related signaling pathways, and reduces hippocampal neuron apoptosis.

[0008] To achieve the above objectives, the present invention also provides a pharmaceutical composition comprising a small molecule polypeptide with the amino acid sequence shown in SEQ ID NO:1 and a pharmaceutically acceptable carrier.

[0009] To achieve the above objectives, the present invention also provides the use of the above-mentioned small molecule peptides or the above-mentioned pharmaceutical compositions in the preparation of a drug for treating cognitive impairment in diabetes.

[0010] like Figure 1 As shown, the mechanism of action of this invention is as follows: Under a high-glucose environment, CD44 can directly bind to STAT3, causing its phosphorylation and promoting the release of apoptosis-related factors such as Cleaved Caspase-3, Bax, and Bcl-2, thereby inducing hippocampal neuronal apoptosis and impairing cognitive function. The interfering peptide CD44-Peptide can specifically block the binding of these two molecules, inhibiting STAT3 phosphorylation, thereby improving cognitive impairment in diabetic mice and providing a potential target and strategy for the intervention of diabetic cognitive impairment.

[0011] Compared with the prior art, the present invention has the following beneficial effects:

[0012] (1) High specificity: The small molecule peptide CD44-Peptide designed in this invention can specifically interfere with the binding of STAT3 and CD44 without affecting other physiological functions of STAT3 and CD44, thus avoiding the toxic side effects caused by directly inhibiting key proteins.

[0013] (2) Good penetration and persistence: The small molecule peptide CD44-Peptide diffuses well in the mouse brain and can last for at least 7 days, effectively reaching the site of action to exert its effect.

[0014] (3) Significant therapeutic effect: The small molecule peptide CD44-Peptide can reduce the expression of P-STAT3, Cleaved Caspase-3 and Bax in hippocampal neurons under high glucose environment, increase the expression of Bcl-2, reduce hippocampal neuronal apoptosis, and improve cognitive dysfunction in diabetic mice. Attached Figure Description

[0015] Figure 1 This is a schematic diagram illustrating the working principle of the present invention;

[0016] Figure 2 The diagrams shown are related to the verification results of the CD44-peptide specific binding to the STAT3 SH2 domain in Example 1; (a) is a schematic diagram of the molecular docking of the CD44-specific interfering peptide sequence (based on amino acids 722-729) with the STAT3 SH2 domain; (b) is a vacuum electrostatic diagram; (c) is a response curve of the interaction between CD44-peptide and STAT3; (d) is an affinity fitting curve corresponding to the CD44-peptide concentration reporter point; (e) is a response curve of the interaction between Scramble-peptide and STAT3; (f) is an affinity fitting curve corresponding to the Scramble-peptide concentration reporter point; and (g) is a Gibbs free energy landscape diagram of the CD44-peptide-STAT3 complex.

[0017] Figure 3 This is a schematic diagram showing the results of CD44-Peptide inhibiting apoptosis in HT22 cells under high glucose conditions in Example 4; where (a) is a schematic diagram of the experimental design; (b) is a laser scanning confocal microscope image after transfecting CD44-Peptide and out-of-order peptide into HT22 cells; (c) is a statistical analysis of the overlap values ​​of co-localization of CD44-Peptide and out-of-order peptide with STAT3; (d) is a graph of Western blot detection results using immunoprecipitation combined with STAT3 antibody; (e) is a statistical graph of immunoprecipitation; (f) is a graph of phosphorylated STAT3 detection results using Western blot; (g) is a statistical graph of phosphorylated STAT3 expression levels; (h) is a representative immunofluorescence image of high glucose-induced apoptosis detected by TUNEL staining; (i) is a statistical graph of apoptosis rate using TUNEL staining; (j) is a representative cell flow cytometry sorting image; and (k) is a statistical graph of flow cytometry results.

[0018] Figure 4The results of hippocampal neuronal apoptosis in each group of mice in Example 5 are as follows: (a) Schematic diagram of in vivo experimental design; (b) Graph of Western blot detection results using co-immunoprecipitation combined with STAT3 antibody; (c) Statistical graph of co-immunoprecipitation results; (d) Graph of Western blot detection results using co-immunoprecipitation combined with CD44 antibody; (e) Statistical graph of co-immunoprecipitation results; (f) Graph of Western blot detection using p-STAT3 antibody and STAT3 antibody; (g) Statistical graph of p-STAT3 antibody and STAT3 protein blot; (h) Representative immunofluorescence images of hyperglycemia-induced hippocampal neuronal apoptosis detected by TUNEL staining; (i) Statistical graph of TUNEL staining apoptosis rate.

[0019] Figure 5 The following are schematic diagrams related to the synaptic function detection of each group of mice in Example 6: (a) representative input-output curves of fEPSPs recorded in the CA1 region of the hippocampus in four groups; (b) quantitative analysis diagram of input / output (I / O); (c) representative post-pulse recovery period (PPR) of fEPSPs calculated with a 50-millisecond pulse interval; (d) schematic diagram of the quantitative analysis results of PPR; (e) typical curve of fEPSP slope during LTP recording; (f) statistical graph of the time process of fEPSP slope during LTP recording; (g) quantitative analysis diagram of LTP fEPSP in different groups.

[0020] Figure 6 The following are schematic diagrams related to the detection of synaptic-related indicators in each group of mice in Example 7: (a) Typical transmission electron microscopy images show the ultrastructure of hippocampal synapses, with red arrows indicating synapse locations; (b) Statistical diagram of the number of hippocampal synapses in each group; (c) Representative images of PSD thickness and synaptic cleft width in each group; (d) Quantitative analysis diagram of postsynaptic dendritic spine (PSD) thickness after CD44-Peptide treatment; (e) Quantitative analysis diagram of postsynaptic dendritic spine (PSD) synaptic cleft width after CD44-Peptide treatment; (f) Dendritic spine morphology and density distribution diagram; (g) Statistical diagram of the number of dendritic spines in the 80μm region; (h) Typical protein blot band diagrams of synaptophysin and PSD95; (i) Statistical diagram of protein blot bands of synaptophysin and PSD95. Figure 7The following are schematic diagrams related to the behavioral experiments of mice in Example 8: (a) Trajectory diagram of mice finding the platform on the fifth day of training, with green dots indicating the start and red dots indicating the end; (b) Statistical graph of the average escape latency of mice reaching the platform on the fifth day of training in the Morris water maze experiment; (c) Trajectory diagram of the probe test on the sixth day (green dots indicate the starting point and red dots indicate the ending point); (d) Statistical graph of swimming speed in the probe test without a platform on the sixth day; (e) Statistical graph of the percentage of time mice spend in the target quadrant; (f) Statistical graph of the percentage of distance mice spend in the target quadrant; (g) Statistical results of the number of times mice cross the platform area; (h) Schematic diagram of the new object recognition experiment; (i) Quantitative analysis graph of discrimination index; (j) Experimental flowchart of situational fear conditioning and cue-based fear conditioning; (k) Statistical graph of freeze time in the situational fear conditioning experiment. Detailed Implementation

[0021] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] Comparative Example

[0023] The amino acid sequence DQFMTADE of the polypeptide fragment homologous to the intracellular segment of CD44 in Example 1 was randomly rearranged to design a scramble-peptide as a control peptide.

[0024] The two peptides in Example 1 and the comparative example were synthesized using a solid-phase peptide synthesis method. After synthesis, they were desalted and labeled with FITC.

[0025] Example 1

[0026] A small molecule polypeptide that interferes with the binding of CD44 and STAT3, the amino acid sequence of which is shown in SEQ ID NO.1, specifically: TGNYKALHPHNG-DQFMTADE; the small molecule polypeptide is based on a polypeptide fragment homologous to the intracellular segment of CD44, and a brain-targeting cell-penetrating peptide is linked to its N-terminus to construct a small molecule polypeptide that interferes with the binding of CD44 and STAT3, namely the interfering peptide CD44-Peptide; the polypeptide fragment homologous to the intracellular segment of CD44 is the amino acid sequence DQFMTADE located at positions 722-729 and can specifically bind to STAT3; the amino acid sequence of the brain-targeting cell-penetrating peptide is TGNYKALHPHNG.

[0027] This invention is based on the interaction between interfering proteins. By consulting literature, the binding sequence of CD44 and STAT3 was determined, and the final small polypeptide sequence was determined based on this binding sequence, enabling it to bind to STAT3. Since the small polypeptide designed solely based on this sequence cannot enter the cell to function, this invention adds a cell-penetrating peptide sequence to one end of the small polypeptide. The final designed small polypeptide can enter the cell via the cell-penetrating peptide sequence at one end, while the other part can compete with CD44 for STAT3 binding, thereby reducing the binding of CD44 and STAT3.

[0028] Figure 2 This is a schematic diagram illustrating the verification results of the CD44-peptide specifically binding to the STAT3 SH2 domain in this embodiment. Figure 2 In diagram a, the CD44-Peptide sequence is presented as a rod-like structure, with binding sites marked in dark pink; the STAT3 SH2 domain is shown as a dark green band-like structure, with binding sites marked in light brown, and polar contact sites between the peptide and STAT3 are indicated by yellow dashed lines; from Figure 2 As can be seen from a, CD44-Peptide can specifically bind to the STAT3 SH2 domain.

[0029] Figure 2 b is a vacuum electrostatic plot, which shows the binding of the interfering peptide sequence to the SH2 domain. Positively charged surfaces in the complex appear blue, negatively charged surfaces appear red, and neutral surfaces appear white. Figure 2 As can be seen in b, the electrostatic driving factors and specific charge matching are combined.

[0030] This embodiment uses STAT3 and different concentrations of CD44-Peptide to conduct surface plasmon resonance (SPR) experiments. The response values ​​of the interaction between CD44-Peptide and STAT3 were recorded on the CM5 chip, and the results are as follows: Figure 2 As shown in Figure c, the interaction between the two increases with increasing peptide concentration, indicating a concentration-dependent binding process. Figure 2 As can be seen from d, CD44-Peptide has a certain affinity for STAT3.

[0031] This embodiment also conducted surface plasmon resonance (SPR) experiments using STAT3 and different concentrations of Scramble-Peptide. The response values ​​of the interaction between Scramble-Peptide and STAT3 were recorded on the CM5 chip, and the results are as follows: Figure 2As shown in Figure e, it can be seen from the figure that Scramble-Peptide binds weakly to STAT3, while CD44-Peptide can specifically bind to STAT3. Figure 2 f can further illustrate that CD44-Peptide can specifically bind to STAT3.

[0032] Figure 2 g is a landscape diagram of the Gibbs free energy of the CD44-Peptide and STAT3 complex. The left panel uses principal component 1 (PC1) and principal component 2 (PC2) as the x and y axes, respectively, for a three-dimensional visualization, with the z-axis representing the Gibbs free energy (unit: kcal / mol). The right panel shows a two-dimensional projection with principal component 1 (PC1) as the x-axis, with color coding representing the energy distribution characteristics, clearly showing the energy state and relative stability of the sampled conformations in the conformational space. The middle panel shows the lowest energy conformation derived from this landscape diagram, with CD44-Peptide represented in blue and STAT3 in green. The diagram shows that there are low-energy and concentrated regions (darker colored regions) in the conformational space of the CD44-Peptide and STAT3 complex, corresponding to the lowest energy conformation. This indicates that the two can form a relatively stable complex structure after binding. This stable conformation provides a thermodynamic basis for the specific binding of the two and also provides energy-based evidence for the specificity and stability of the binding between CD44-Peptide and the STAT3 SH2 domain.

[0033] Example 2

[0034] This embodiment provides a pharmaceutical composition comprising the small molecule peptide described in Example 1 and a pharmaceutically acceptable carrier. Mannitol is used as a filler and does not interact with the small molecule peptide; the pH is adjusted to 7.2-7.4 to maintain the stability of the peptide's secondary structure; sterile water is used as a solvent to avoid the risk of peptide denaturation that may be caused by other organic solvents, while also meeting the requirements for sterility and pyrogen-free injections, ensuring the safety of in vivo administration.

[0035] Example 3

[0036] This embodiment provides the application of the small molecule polypeptide described in Example 1 or the pharmaceutical composition described in Example 2 in the preparation of a drug for treating cognitive impairment in diabetes.

[0037] Example 4: CD44-Peptide inhibits apoptosis in HT22 under high glucose environment

[0038] like Figure 3As shown in a, immunoprecipitation: First, prepare cell samples and extract proteins using RIPA (weak) lysis. Then, add 25 μL of Protein A / G magnetic beads and 350 μL of protein sample to each tube, and add the corresponding antibody according to the dilution ratio. Incubate overnight at 4°C in a cold storage room with a fan to allow the magnetic beads to fully bind to the protein. After incubation, discard the supernatant using a magnetic rack, and gently wash with 1×TBS, repeating 4-5 times. After washing, add 40 μL of 2×Loading buffer and mix with the magnetic beads, place in a metal bath, and incubate at 100°C for 10 min. After boiling, analyze using Western blotting.

[0039] After transfecting CD44-Peptide and disordered peptides into HT22 cells, the laser scanning confocal microscope images are as follows: Figure 3 As shown in b. Figure 3 b shows co-localization with STAT3 under high glucose conditions. In the figure, CD44-Peptide and out-of-order peptides are marked in green, STAT3 is marked in red, and the cell nucleus is stained blue with DAPI. The co-localization region with STAT3 is marked in yellow. The scale bar is 50 μm (magnification × 400). Figure 3 The overlap values ​​in c indicate the co-localization of the small peptide with STAT3. The figure shows that CD44-Peptide specifically binds to and co-localizes with STAT3. The results were analyzed using a t-test (t = 0.527), with a sample size of n = 8 per group.

[0040] Western blotting using immunoprecipitation combined with STAT3 antibody verified the co-precipitation effect of CD44-Peptide or disordered peptide on CD44 and STAT3. The results are as follows: Figure 3 As shown in d and 3e, CD44-Peptide can effectively promote the co-precipitation of CD44 and STAT3 and enhance their binding effect; Figure 3 In e, the optical density values ​​of STAT3 were expressed as a fold change relative to the blank control group. The results were analyzed using one-way ANOVA combined with Tukey's test; F(3,12)=7.769. ***p<0.001; sample size n=4 per group.

[0041] Phosphorylated STAT3 was detected by Western blotting, and the results are as follows: Figure 3 As shown in f and 3g, CD44-Peptide inhibits STAT3 phosphorylation activation by blocking the binding of CD44 to STAT3; Figure 3 In g, relative intensity is expressed as a multiple of change relative to the NG group; data were analyzed using one-way ANOVA followed by Tukey's test, and results are presented as mean ± standard error; F(3,12)=66.05. ***p<0.001; n=4 per group.

[0042] like Figure 3 As shown in Figure a, the TUNEL assay was performed as follows: First, the cell slides were washed three times with PBS buffer. To facilitate the entry of TdT enzyme and labeled dUTP into the cells, the slides were treated with 0.1%–0.5% Triton X-100 for 10–15 minutes, followed by washing three times with PBS buffer. The slides were then blocked and incubated at room temperature for 30 minutes to reduce nonspecific staining. The blocking solution was then discarded, and the TUNEL reaction mixture was added directly. The slides were placed in a humidified chamber and incubated at 37°C for 60 minutes. The slides were washed three times with PBS buffer to terminate the TUNEL reaction. Mounting was performed using a mounting medium containing DAPI, and the slides were observed under a microscope.

[0043] High glucose-induced apoptosis was detected by TUNEL staining, and representative immunofluorescence images are shown below. Figure 3 As shown in figure h, the apoptosis status of HT22 cells in each group is displayed. The cell nucleus (DAPI) is shown in blue, and the nucleus of apoptotic cells is shown in green; scale bar = 20 μm (magnification × 200). Figure 3 i represents the Tunel staining statistical plot, with n=8 for each group; data were analyzed using one-way ANOVA followed by Tukey test; F(3,28)=28.84; ***p<0.001; the plot shows that CD44-Peptide can significantly inhibit high glucose-induced apoptosis in HT22 cells.

[0044] like Figure 3 As shown in Figure a, flow cytometry analysis was performed as follows: HT22 cells were allowed to grow to 70%-80% confluence. After washing twice with sterile PBS, the cells were digested with EDTA-free trypsin for 20 seconds, centrifuged at 1000 rpm for 5 minutes, and 1 × 10⁵ cells were collected from each group. 500 μL of Binding Buffer was added, and the cell pellet was gently pipetted until a single-cell suspension was formed. Then, 5 μL of Annexin V-APC was added, and the mixture was pipetted and incubated at room temperature in the dark for 10 minutes before flow cytometry observation and detection. Representative flow cytometry images are shown below. Figure 3 As shown in Figure j, apoptosis is observed in the figure. The proportion of cells in the apoptotic quadrant (such as early apoptosis of Annexin V+ / PI- and late apoptosis of Annexin V+ / PI+) in the HG group was significantly higher than that in the NG group. The proportion of apoptotic cells in the CD44-Peptide group was significantly reduced, while there was no significant improvement in the disordered peptide group. Figure 3k represents the flow cytometry statistics. A one-way ANOVA was performed followed by the Tukey test; F(3,28) = 31.48. ***p < 0.001 (high glucose group vs. NG group); **p = 0.002 (high glucose group and CD44-Peptide group vs. high glucose group); *p = 0.026 (high glucose group and Scr-Peptide group vs. high glucose group and CD44-Peptide group); n = 8 for each group. The figure shows that CD44-Peptide effectively blocks apoptosis in HT22 cells under high glucose conditions.

[0045] Example 5: Detection of CD44-Peptide binding to STAT3 and apoptosis in mouse hippocampal neurons

[0046] like Figure 4 As shown in a, for immunoprecipitation: First, prepare tissue samples and extract proteins using RIPA for weak lysis. Then, add 25 μL of Protein A / G magnetic beads and 350 μL of protein sample to each tube, and add the corresponding antibody according to the dilution ratio. Incubate overnight at 4°C in a fan-operated cold storage to allow the magnetic beads to fully bind to the protein. After incubation, discard the supernatant using a magnetic rack, and gently wash with 1×TBS, repeating 4-5 times. After washing, add 40 μL of 2×Loading Buffer and mix with the magnetic beads, place in a metal bath, and incubate at 100°C for 10 min. After the sample is boiled, analyze using Western blotting.

[0047] The co-precipitation effect of CD44 and STAT3 was verified by Western blotting using immunoprecipitation combined with STAT3 antibody. The results are as follows: Figure 4 As shown in b and 4c, the results indicate that CD44-Peptide can promote the binding of CD44 to STAT3 in vivo. Figure 4 The statistical analysis in c showed the fold change in the optical density value of STAT3 protein compared to the db / m group; the data analysis was performed using one-way ANOVA combined with Tukey's multiple comparison test, F(3,12)=30.72; *** indicates p<0.001; ** indicates p<0.002; the sample size for each group was n=4.

[0048] Western blot analysis using CD44 antibody yielded the following results: Figure 4 As shown in d, the results confirm that the binding of CD44 to STAT3 is bidirectional and specific; Figure 4 The statistical analysis showed that the pull-down effect of STAT3 on CD44 varied in multiples relative to the db / m group; the data analysis was performed by one-way ANOVA combined with Tukey's test, F(3,12)=42.22, **p=0.001; ***p<0.001, n=4.

[0049] The expression levels of p-STAT3 and STAT3 were detected by Western blotting using p-STAT3 antibody and STAT3 antibody, respectively. The results are as follows: Figure 4 As shown in f and 4g, CD44-Peptide can indirectly inhibit STAT3 phosphorylation; Figure 4 The optical density values ​​of p-STAT3 in g are expressed as multiples relative to the db / m group. The data were analyzed by one-way ANOVA and then subjected to Tukey test. F(3,12)=210.00, ***p<0.001, n=4 for each group.

[0050] like Figure 4 As shown in Figure a, the TUNEL assay was performed as follows: First, the sections were washed three times with PBS buffer. To facilitate the entry of TdT enzyme and labeled dUTP into cells, the sections were treated with 0.1%–0.5% Triton X-100 for 10–15 minutes, followed by washing three times with PBS buffer. The sections were then blocked and incubated at room temperature for 30 minutes to reduce nonspecific staining. The blocking solution was then discarded, and the TUNEL reaction mixture was added directly. The sections were placed in a humidified chamber and incubated at 37°C for 60 minutes. The sections were washed three times with PBS buffer to terminate the TUNEL reaction. Mounting was performed using a mounting medium containing DAPI, and the sections were observed under a microscope.

[0051] Hippocampal neuronal apoptosis induced by hyperglycemia was detected by TUNEL staining. Representative images are shown below. Figure 4 As shown in h, the figure shows the apoptosis of neurons in the CA1 subregion of each group. The CD44-Peptide group showed a significant reduction in apoptotic neurons, while the disordered peptide group showed no improvement. In the figure, cell nuclei (DAPI staining) are blue, and apoptotic neuron nuclei are green. Scale bar = 50 μm (magnification × 400). Figure 4 i represents the Tunel quantitative statistical plot. Data analysis was performed using one-way ANOVA combined with Tukey's test. F(3,32) = 131.00, ***p < 0.001, n = 9 for each group. As can be seen from the figure, CD44-Peptide can significantly block hyperglycemia-induced hippocampal neuronal apoptosis.

[0052] Example 6: LTP Experiment

[0053] First, prepare artificial cerebrospinal fluid (ACSF) and saturate it with a mixture of 95% O2 and 5% CO2. Pre-cool 150 mL of ACSF in an ice-water bath while continuously aerating it with O2. Incubate 200 mL of ACSF in a 28°C water bath while continuously aerating it with the mixed gas to stabilize the pH and O2 saturation, facilitating brain slice incubation. After anesthetizing mice, quickly decapitate them and remove the brain, immersing it in pre-cooled ACSF for 2-3 minutes. Remove the cerebral hemispheres, trim the brain tissue, and retain the hippocampus region. Fix the brain tissue to the base of a vibratory microtome with a small amount of super glue and perform horizontal sectioning (400 μm) in pre-cooled ACSF. After the sections stabilize for 90 minutes, transfer them to a room-temperature thermostat bath and perfuse with artificial cerebrospinal fluid. Stimulate Schaeffer's collateral fibers with a single-stage tungsten wire and use concentric stimulation electrodes filled with artificial cerebrospinal fluid in the dendritic layer of the hippocampus. Use 50% of the intensity that elicits the maximum response as the stimulation intensity, stimulating every 20 seconds. Then, high-frequency stimulation (HFS, 100 Hz, 1 s) was given to induce LTP, and LTP was recorded for 60 min.

[0054] Figure 5 a represents the representative input-output curves of fEPSPs recorded in the CA1 subregion of the hippocampus in four groups; Figure 5 b represents quantitative analysis of inputs and outputs. Data were analyzed using a two-way ANOVA combined with the Sidak test. The q values ​​were (49, 168) = 4.351 (db / m vs db / db), 5.648 (db / db vs db / db+CD44-Peptide), and 8.726 (db / db+CD44-Peptide vs db / db+Scr-Peptide). *p = 0.013 (db / m vs db / db); ***p < 0.001 (db / db vs db / db+CD44-Peptide and db / db+CD44-Peptide vs db / db+Scr-Peptide), with n = 3 for each group. As shown in the figure, CD44-Peptide specifically improves hyperglycemia-induced synaptic basal transmission impairment.

[0055] Figure 5 c is a representative PPR calculated using fEPSPs with a pulse interval of 50 milliseconds. Figure 5d represents the quantitative analysis of PPR. Data were analyzed using one-way ANOVA combined with Tukey's test. F(3,24)=7.383. **p=0.005(db / m group vs db / db group), 0.001(db / db group vs db / db group + CD44-Peptide); *p=0.034(db / db group + CD44-Peptide vs db / db group + Scr-Peptide), n=3 for each group; the results indicate that CD44-Peptide can specifically improve hyperglycemia-induced presynaptic release dysfunction.

[0056] Figure 5 e and Figure 5 f shows the typical trajectory and temporal variation of the fEPSP slope during long-term augmentation (LTP) recording; Figure 5 g represents a quantitative statistical graph. Data analysis was performed using one-way ANOVA combined with Tukey's test. F(3,24) = 19.260. *** indicates p < 0.001; * indicates p = 0.036 (db / db+CD44-Peptide group vs. db / db+Scr-peptide group). n = 3 for each group. The results indicate that CD44-Peptide successfully rescued LTP fEPSP deficiency in db / db mice.

[0057] Example 7: Effects of CD44-Peptide on Synaptic Related Indicators

[0058] The changes in synaptic morphology and related proteins were detected by Golgi staining and Western blotting, as follows:

[0059] Golgi staining: Prepare AB mixture solution (3 mL each of solutions A and B, prepared 24 hours in advance) one day before sampling. Store at room temperature, protected from light. Prepare AB mixture solution again after sampling. After sampling, rinse the tissue with pre-cooled PBS and place it in the AB mixture solution prepared the day before. Replace the AB solution after 24 hours. After soaking for 14 days, discard the AB solution and replace it with 6 mL of solution C. Replace the solution C solution every other day. After 3 days, prepare gelatin mounts by dissolving 1.5 g gelatin and 0.15 g potassium chromium sulfate in 300 mL of ultrapure water at 60°C. After the gelatin dissolves, add the potassium chromium sulfate and soak the slides for 1 minute to ensure gelatin coating. Dry in a 65°C oven for later use. Fix the sample in the center of the sample stage. After fixing, pour in PBS, set the section thickness to 100 μm, the sectioning speed to medium, and start continuous shaking sectioning after setting the start and end points. Place the sectioned slides on a glass slide pre-coated with gelatin, add a small amount of solution C to prevent the sections from drying and cracking, and air-dry the sections at room temperature away from light. Prepare the DE mixture (D:E:ulpure water = 1:1:2), and wash the dried sections with pre-cooled PBS for 5 min each time, for 4 washes. After washing, wipe off the residual PBS, add the DE mixture for staining, and stop staining after 10-15 min. After staining, wash with pre-cooled PBS for 5 min each time, for 4 washes. Dehydrate and clear in a fume hood: 50% ethanol for 5 min, 75% ethanol for 5 min, 95% ethanol for 5 min, and anhydrous ethanol for 4 times for dehydration, 5 min each time; xylene for clearing 3 times for 5 min each time; mount with neutral resin, add nail polish for fixation, observe and photograph under bright field and save.

[0060] Figure 6 a is a transmission electron microscope image of the ultrastructure of the hippocampal synapse, with red arrows indicating synapse locations, scale bar = 500 nm; Figure 6 b represents the statistical results of hippocampal synapse counts in each group. Data were analyzed using one-way ANOVA combined with Tukey's test, with an F-value of (3,28) = 15.93. ***p < 0.001; **p = 0.007 (comparison between db / db and db / db+CD44-Peptide) and 0.005 (comparison between db / db+Scr-Peptide and db / db+CD44-Peptide), with n = 4 for each group. The results indicate that CD44-Peptide can salvage hyperglycemia-induced synapse count reduction.

[0061] Figure 6 c represents the thickness of each group of postsynaptic dendritic spines (PSDs) and synaptic clefts, with a scale bar of 200 nm. Figure 6 d and Figure 6Figure e represents a quantitative analysis of PSD thickness and synaptic cleft width after CD44-Peptide treatment. A one-way ANOVA combined with Tukey's test was used. In Figure d, F(3,28) = 9.491, and in Figure e, F = 0.119. **p = 0.002 (comparison between db / db and db / m, and between db / db and db / db+CD44-Peptide groups); *p = 0.040 (comparison between db / db+Scr-peptide and db / db+CD44-Peptide groups), n = 8. The results indicate that CD44-Peptide mainly improves postsynaptic structure by repairing PSD thickness, rather than affecting cleft width.

[0062] Figure 6 f represents the morphology and density of dendritic spines, scale bar = 20μm (magnification × 600); Figure 6 g represents the number of dendritic spines within an 80 μm region, determined using ImageJ software. Data were analyzed using one-way ANOVA combined with Tukey's test. F(3,28) = 25.46. ***p < 0.001; **p = 0.006 (comparison between db / db and db / db+CD44-Peptide groups) and 0.001 (comparison between db / db+Scr-peptide and db / db+CD44-Peptide groups), with n = 8 for each group. The results indicate that CD44-Peptide can specifically increase the density of hippocampal dendritic spines in hyperglycemic mice and improve the presynaptic structural basis.

[0063] Figure 6 h and Figure 6 i shows typical Western blotting patterns of synaptophysin and PSD95, and a comparison with the db / m group. Data are expressed as mean ± standard error. Statistical analysis was performed using one-way ANOVA combined with Tukey's test. F(3,12) were 37.32 (synaptophysin) and 16.57 (PSD95), respectively, with ***p<0.001. The sample size for each group was n=4. The results indicate that CD44-Peptide can specifically restore hippocampal synaptic protein expression in hyperglycemic mice and repair the molecular basis related to synaptic function.

[0064] Example 8: Effects of interfering peptides on cognitive function in diabetic mice

[0065] Behavioral tests were conducted on mice in four groups: db / m, db / db, db / db+CD44-Peptide, and CD44+Scramble-Peptide. The learning and memory functions of the mice were assessed using the Morris water maze test, the novel object recognition test, and the situational fear test. The specific experimental procedures are as follows:

[0066] The Morris water maze experiment trains animals' spatial learning and memory abilities by forcing them to swim. The Morris water maze pool had a radius of 0.8m and a height of 0.5m, with a water depth of 0.3m set in the experiment. Anymaze software was used to set up and record the steps. Different shaped and colored markers were placed in each of the four quadrants. A platform (a circle with a radius of 4cm) was set in the center of the fourth quadrant, with its top 2-3cm below the water surface in the fifth quadrant. Mice were first allowed to acclimatize in clean water. After acclimatization, pure milk was added to make the water murky, obscuring the mice's vision and preventing them from directly seeing the platform. The training lasted for five days, with the same training time each day. Each day, the mice started from a different quadrant to find the platform. The time taken from entering the water to finding the platform was recorded as the escape latency period during the training. After finding the platform, the mice were allowed to acclimatize on it for 20-30 seconds. If the mice could not find the platform within 60 seconds, they were guided to the platform to acclimatize for another 20-30 seconds. The sixth day is the testing period. Ideally, the testing period should be consistent with the training period. Remove the platform and let the mice enter the water from the quadrant opposite to the platform. Record the time the mice spend crossing the platform and staying in the fourth quadrant as an indicator of the mice's memory ability and cognitive level.

[0067] New Object Recognition Experiment: The new object recognition experiment consisted of two parts: training and formal experiment. One day before training, mice were placed in an empty test box for 5 minutes to acclimatize. During training, two identical objects were placed parallel to each other on the same side of the test box (5 cm from the box wall). The mice were then placed back in the box and allowed to explore freely for 5 minutes, with the exploration time for each object recorded. Two hours after the training ended, before the formal experiment, one of the objects was replaced with a new object of different color and shape. The mice were placed in the test box and allowed to explore freely for 5 minutes, with the exploration time for each object recorded. The recognition index was calculated as (new object exploration time - old object exploration time / total exploration time).

[0068] Conditioned fear experiment: The conditioned fear experiment consists of two parts: contextual fear conditioning and conditioned fear conditioning. Sound (neutral stimulus) and electric shock (aversive stimulus) are presented in pairs. Mice are first allowed to acclimatize to the environment in a sterile test chamber. After acclimatization, conditioned reflex training begins. Mice are first allowed to explore the test chamber for 3 minutes, followed by sound stimulation (2000Hz, 80dB, 30s). After the sound stimulation, foot electric stimulation (0.8mA, 2s) is applied. The two stimuli are presented in pairs, repeated 3 times, with a 60s interval between each pair. After changing mice, the test chamber is cleaned before the next training or experiment. The two stimuli are presented in pairs, allowing the mice to associate sound with electric stimulation, and upon hearing the sound again, they enter a fear state. The next day, the mice's environment-induced rigidity is tested using the same test chamber, without any stimulation. The duration of rigidity within 3 minutes is recorded. Two hours after the test, the environment in the enclosure was changed to allow the mice to adapt to the new environment. After adaptation, the test of sound-induced rigidity was started. Sound stimulation was applied for 3 minutes, and the rigidity time of the mice within 3 minutes was recorded. The percentage of rigidity time to total time was calculated.

[0069] Figure 7 a is a schematic diagram of the mouse's trajectory in finding the platform on the fifth day of training. The green dot represents the starting point and the red dot represents the ending point. Figure 7 b represents the average escape latency of mice reaching the platform during the fifth day of training in the Morris water maze. Results were analyzed using one-way ANOVA combined with Tukey's test. F(3,28) = 28.50. ***p < 0.001; **p = 0.003 (db / db+CD44-peptide group vs. db / db group), n = 8 for each group; Figure 7 c is the probe test trajectory diagram on the sixth day (green dots represent the starting point, and red dots represent the ending point); Figure 7 d represents the swimming speed during the probe test (without a platform) on day 6. There were no significant differences among the groups, excluding the influence of exercise capacity on the results. Data were analyzed using one-way ANOVA and Tukey's test. For each group, n=8, F(3,28)=2.098. Figure 7 e and Figure 7 f represents the time spent in the target quadrant and the percentage of distance traveled. Data are presented as mean ± standard error and analyzed using one-way ANOVA combined with Tukey's test. F(e) = 55.58, f = 45.56. ***p < 0.001. n = 8; Figure 7g represents the number of platform crossings. One-way ANOVA combined with Tukey's test was used, and F(3,28) = 34.43. ***p < 0.001; **p = 0.002 (db / db + CD44-Peptide vs db / db) and 0.06 (db / db + Scr-Peptide vs db / db + CD44-Peptide). The results indicate that CD44-Peptide can specifically restore spatial memory in hyperglycemic mice and repair hippocampus-dependent learning and memory function.

[0070] Figure 7 h. Schematic diagram of the new object recognition task; Figure 7 i represents the discrimination index of each group. The analysis was performed using one-way ANOVA combined with Tukey's test. F(3,28)=15.51, ***p<0.001; **p=0.002(db / db+CD44-Peptide vs db / db), n=8 for each group. The results indicate that CD44-Peptide can specifically improve non-spatial recognition memory in hyperglycemic mice.

[0071] Figure 7 j represents the experimental design for situational fear conditioning; Figure 7 k represents the freeze time in the situational fear conditioning experiment. Analysis using one-way ANOVA combined with Tukey's test showed that n=8 for each group. For the situational fear conditioning group, F(3,28)=49.72, ***p<0.001; **p=0.004(db / db+CD44-Peptide vs db / db) and 0.002(db / db+Scr-Peptide vs db / db+CD44-Peptide). For the cue-based fear conditioning group, F(3,28)=41.70, ***p<0.001. The results indicate that CD44-Peptide can restore associative learning and memory in hyperglycemic mice and repair fear memory function.

[0072] In summary, this invention uses db / db mice as a model to inject small molecule peptides into mice at appropriate doses via tail vein injection. The results show that the small molecule peptides of this invention improve cognitive dysfunction in db / db mice and reduce apoptosis of hippocampal neurons, providing an experimental basis and direction for drug application.

[0073] This invention focuses on a series of studies on small molecule peptides that interfere with the binding of CD44 and STAT3. From the molecular mechanism to the overall animal behavior level, it systematically verifies their effect on improving cognitive dysfunction in diabetes. The specific conclusions are as follows: (1) Molecular interaction level: Through molecular docking, SPR and Gibbs free energy analysis, it is clear that CD44-Peptide can specifically bind to the STAT3SH2 domain. Its binding has a concentration-dependent characteristic, and the formed complex has low energy and stable conformation. From the thermodynamic and spatial structure perspective, it is confirmed that the two interact specifically, laying the foundation for subsequent functional studies; (2) Cellular function level: In the HT22 cell high glucose model, CD44-Peptide can inhibit the phosphorylation activation of STAT3 by binding to it, thereby significantly reducing high glucose-induced apoptosis. Immunoprecipitation, TUNEL staining and flow cytometry experiments were used to verify the effect of CD44-Peptide in blocking the CD44 / STAT3 pathway and protecting neurons from multiple dimensions such as protein interaction, morphology and apoptosis quantification. Disordered peptides did not have this effect, highlighting the target specificity; (3) Animal tissue level: CD44-Peptide inhibited STAT3 phosphorylation and reduced apoptosis of neurons in the CA1 region of the hippocampus in db / db diabetic mice. Tunel staining results visually show the changes in the number of apoptotic neurons, verifying its protection against hyperglycemic neuronal damage at the tissue level, consistent with the cell experiment mechanism; (4) Synaptic function level: With the help of electrophysiological (LTP experiment), morphological (Golgi staining, transmission electron microscopy) and protein expression (Western Blot) detection, it was found that CD44-Peptide can repair synaptic damage in the CA1 region of the hippocampus of hyperglycemic mice: improve basic synaptic transmission (fEPSP), correct presynaptic release function (PPR), restore long-term potentiation (LTP); rescue the number of synapses, repair PSD thickness, increase dendritic spine density; restore the expression of synaptic proteins (Synapsin, PSD95). From the perspective of synaptic structure-function association, the neurobiological basis of its cognitive improvement is explained; (5) Overall behavioral level: Through Morris water maze, new object recognition, and conditioned fear experiments, it is confirmed that CD44-Peptide can comprehensively repair the cognitive function of db / db mice: improve spatial learning (escape latency) and memory (target quadrant stay, platform crossing), enhance non-spatial recognition memory (discrimination index), and restore associative fear memory (freeze time). Behavioral data and molecular, cellular, and tissue-level results work together to present a complete chain of action.

[0074] In summary, the CD44-Peptide designed in this invention can improve cognitive dysfunction in diabetic mice at the molecular and systemic levels by specifically interfering with the CD44 / STAT3 pathway, providing a novel target and candidate drug for the treatment of diabetic encephalopathy, and possessing both mechanistic innovation and application potential.

Claims

1. A small molecule polypeptide that interferes with the binding of CD44 and STAT3, characterized in that, The amino acid sequence is shown as SEQ ID NO: 1; the small molecular polypeptide is based on a polypeptide fragment homologous to the intracellular segment of CD44, a brain-targeting cell-penetrating peptide is connected to the N-terminal of the polypeptide fragment, a small molecular polypeptide interfering with the combination of CD44 and STAT3, i.e. an interfering peptide CD44-Peptide, is constructed; the polypeptide fragment homologous to the intracellular segment of CD44 is the amino acid sequence DQFMTADE at positions 722-729 and can specifically bind to STAT3; the amino acid sequence of the brain-targeting cell-penetrating peptide is TGNYKALHPHNG; the small molecular polypeptide inhibits the phosphorylation of STAT3 by interfering with the combination of CD44 and STAT3, down-regulates the apoptosis-related signal pathway, and reduces the apoptosis of hippocampal neurons.

2. A pharmaceutical composition, characterized by, The pharmaceutical composition comprises the small molecular polypeptide of claim 1 and a pharmaceutically acceptable carrier.

3. Use of the small molecular polypeptide of claim 1 or the pharmaceutical composition of claim 2 in the preparation of a medicament for treating diabetic cognitive dysfunction.

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