Small molecule polypeptides targeting pd-l1 and uses thereof

Abstract

The present application belongs to the field of biotechnology, and particularly relates to a small molecule polypeptide targeting PD-L1 and application thereof. Based on machine learning and virtual screening technology, a series of small molecule polypeptides targeting PD-L1 are screened, and the in-vivo and in-vitro biological activities thereof are determined. It is found that the small molecule polypeptide has the ability to induce PD-L1 to form dimerization and good anti-tumor activity, and the anti-tumor activity thereof is superior to that of PD-L1 monoclonal antibody and complex inhibitors. Meanwhile, the small molecule polypeptide targeting PD-L1 of the present application has no obvious toxicity and has certain safety, and can be developed into a new small molecule polypeptide PD-L1 inhibitor drug.

Description

Technical Field

[0001] This invention belongs to the field of biotechnology, specifically relating to a small molecule polypeptide targeting PD-L1 and its applications. Background Technology

[0002] Cancer, or malignant tumor, is a complex disease caused by a variety of factors, including genetics, pathogenic microorganisms such as viruses, environmental risk factors, and unhealthy lifestyles. It commonly affects middle-aged and young adults, and treatment outcomes are often unsatisfactory, with a high mortality rate. In recent years, the global annual cancer mortality rate has exceeded ten million cases, seriously impacting public health and increasing the social burden. Currently, various treatment methods are used clinically, including radiotherapy, chemotherapy, targeted therapy, and immunotherapy. In recent years, immunotherapy has made significant progress in the field of cancer treatment. Immunotherapy can activate the patient's own immune system, enabling it to more effectively recognize and destroy cancer cells. Compared to traditional radiotherapy and chemotherapy, this treatment method has the advantages of high specificity and fewer side effects, and has attracted widespread attention.

[0003] Immunotherapy for tumors is a treatment method that artificially enhances or suppresses the body's immune function to achieve the purpose of treating the disease, targeting the body's weakened or overactive immune state. Although it also has toxic side effects, it is more effective and has fewer side effects than traditional treatment methods (KENNEDY LK, SALAMAAK S. A review of cancer immuno-therapy toxicity[J]. CA Cancer J Clin, 2020, 70(2):86-104; FARKONA S, DIAMANDIS EP, BLASUTIG I M. Cancer immuno-notherapy: the beginning of the end of cancer[J]. BMC Med, 2016, 14:73). Changes in the tumor microenvironment are an essential factor in the occurrence and development of tumors. During the development of tumors, tumor-infiltrating lymphocytes (TILs) are ineffective in clearing tumor cells in the body, but when the immunosuppression in the tumor microenvironment is removed, these cells exert their ability to proliferate and kill tumors. Therefore, therapeutic approaches that target molecules or related influencing factors in the tumor microenvironment to alter the tumor microenvironment play an important role in the treatment of cancer (ARNETH B. Tumor microenvironment[J].Medicine, 2019, 56(1): 15.).

[0004] In tumor immunotherapy, the discovery of tumor immune checkpoint inhibitors is considered one of the milestone breakthroughs in tumor treatment. Immune checkpoints are a class of protein molecules expressed on immune cells that play an inhibitory role in signal transduction. By transmitting inhibitory signals into immune cells, they can suppress the over-activated immune response in the human body, thereby maintaining immune tolerance and avoiding the occurrence of autoimmune diseases (KITAMURAT, QIAN BZ, POLLARD JW. Immune cell promotion of metastasis[J].Nat Rev Immunol,2015,15(2):73-86; SCHUMACHER TN, KESMIR C, VANBUUREN MM. Biomarkers in cancer immunotherapy[J].Cancer Cell,2015,27(1):12-14; KIM N, KIM HS. Targeting checkpoint receptors and molecules for therapeutic modulation of natural killer cells[J].Front Immunol,2018,9:2041). Tumor cells utilize this mechanism to express corresponding ligands that bind to immune checkpoint molecules, thereby inhibiting the activation of the immune system and achieving immune escape (MOTZ GT, COUKOS G. Deciphering and reversing tumor immune suppression[J]. Immunity, 2013, 39(1):61-73.). Immune checkpoint blockade (ICB) refers to an immunotherapy method that uses immune checkpoint inhibitors (ICIs) to block the binding of immune checkpoint molecules to their ligands, thereby reactivating suppressed immune cells and restoring their tumor-killing effect (Xu Xiangning, Wang Yindi, Lü Zhen, et al. Research progress on anti-tumor therapy based on PD-1 / PD-L1 immune checkpoint pathway of integrated traditional Chinese and Western medicine[J]. Journal of Basic Chinese Medicine, 2024, 30(07):1258-1264.). PD-1 and PD-L1 are two common immune checkpoint proteins. The binding of PD-1 to its ligand PD-L1 can inhibit T cell activation and promote tumor immune escape. Therefore, blocking the PD-1 / PD-L1 interaction is an important means of treating tumors.

[0005] Research on tumor drugs targeting these two targets is insufficient. Although inhibitors targeting PD-L1 have achieved certain therapeutic effects, most of them are monoclonal antibody compounds. Monoclonal antibody drugs have some disadvantages, such as strong immunogenicity, low tissue / tumor penetration, poor oral bioavailability, difficult storage and transportation, and high production costs (Chen Guangfeng, Xie Yanping, Shuai Yongkang, et al. Preliminary study on the performance of novel breast cancer-targeting small molecule peptides [J]. Anatomical Research, 2024, 46(03): 193-199.). Peptides are amino acid chains of several to up to 50 amino acids linked by peptide bonds. Compared with antibodies, they have advantages such as low manufacturing cost, high stability, high affinity, small relative molecular mass, strong tissue penetration, fast blood clearance, low immunogenicity and toxicity, and easy preparation and modification (Sun X, Li Y, Liu T, et al. Peptide-based imaging agents for cancer detection [J]. Adv Drug Deliv Rev, 2017, 110-111: 38-51.). Therefore, the development of small molecule peptide inhibitors targeting PD-L1 is of great significance for enriching the means of tumor treatment. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention uses machine learning and virtual screening technology to screen out a small molecule peptide that targets PD-L1. Its in vivo and in vitro bioactivity was measured, and it was found that the small molecule peptide has the ability to induce PD-L1 dimerization and has good anti-tumor activity. Based on this, the invention was completed.

[0007] In a first aspect, the present invention provides a small molecule polypeptide targeting PD-L1, wherein the sequence of the small molecule polypeptide targeting PD-L1 is selected from SEQ ID NO.1-SEQ ID NO.82.

[0008] Furthermore, the small molecule polypeptide targeting PD-L1 is a mutant polypeptide obtained by amino acid scanning mutation based on SEQ ID NO.1-SEQ ID NO.30.

[0009] Furthermore, the amino acid scanning mutations include positively charged amino acid scanning mutations, negatively charged amino acid scanning mutations, neutral amino acid scanning mutations, rare amino acid substitution mutations, and D-type amino acid substitution mutations.

[0010] Furthermore, the amino acid sequences of the small molecule polypeptides targeting PD-L1 after the amino acid scanning mutation are shown in SEQ ID NO.31-SEQ ID NO.82.

[0011] Furthermore, the small molecule peptide targeting PD-L1 is an extension or truncation of the N-terminus or C-terminus based on SEQ ID NO.1-SEQ ID NO.30.

[0012] Furthermore, the extended or truncated amino acid sequences of the small molecule polypeptides targeting PD-L1 are shown in SEQ ID NO.31-SEQ ID NO.82.

[0013] Preferably, the sequence of the small molecule polypeptide targeting PD-L1 is SEQ ID NO.45.

[0014] Secondly, this invention provides a method for screening small molecule peptides based on machine learning and virtual screening technology:

[0015] S1. Construct a three-dimensional structure database: Generate the sequences and files of tetrapeptides, optimize the energy of the peptide system, and construct a tetrapeptide database;

[0016] S2. Download ligands from the database as active molecules to prepare for virtual screening;

[0017] S3. Extract three-dimensional structural features and perform clustering to screen for compounds with potential activities similar to the extracted ligands;

[0018] S4. The peptides obtained from clustering are then screened using molecular docking and binding free energy calculations.

[0019] S5. Perform solid-phase synthesis and bioactivity testing on the top-ranked peptides to screen out the peptides with the best activity;

[0020] S6. The peptides screened in S5 are structurally modified, and the peptide molecules with the best activity are screened based on the binding free energy.

[0021] Furthermore, in step S1, the sequence of the tetrapeptide is generated using Amber's tleap program, covering random combinations of 20 natural amino acids at 4 positions, for a total of 204 combinations.

[0022] Furthermore, in step S1, the tetrapeptide file includes the tetrapeptide's prmtop file and inpcrd file.

[0023] Furthermore, the tetrapeptide file is imported using the tleap program to obtain the required protein and small molecule force field, and Na is added. + and Cl - The peptide was obtained by maintaining the system charge at 0 and then solvating it.

[0024] Furthermore, during the solvation process, a TIP3PBOX water box is added around the peptide.

[0025] Furthermore, in step S1, the energy optimization of the peptide system is performed using Amber's pmemd program.

[0026] Furthermore, the optimization process is divided into two steps. The first step is to add solute constraint forces to prevent significant changes in solute molecules during solvent optimization. The second step is to optimize and eliminate solute constraint forces to optimize the entire system. At the same time, an rst file is generated.

[0027] Furthermore, the second step of optimizing the entire system used the steepest descent method and the conjugate gradient method.

[0028] Furthermore, in step S1, the construction of the tetrapeptide database includes two steps: extracting the three-dimensional structure of the peptide and removing water molecules from the three-dimensional structure, containing 160,000 tetrapeptides.

[0029] Furthermore, the extraction of the three-dimensional structure of the peptide refers to using Amber's ambpdb program to extract the three-dimensional structure of the peptide from the prmtop and rst files and output the peptide's PDB file.

[0030] Furthermore, removing water molecules from the three-dimensional structure refers to using the pdb4amber program to remove water molecules from the three-dimensional structure extracted in the previous step and generate the final structure files in PDB and MOL2 formats.

[0031] Furthermore, in step S2, the ligand refers to the ligand in the three-dimensional structure of the PD-L1 protein.

[0032] Furthermore, in step S3, the extraction of features of the three-dimensional structure includes acquiring and converting peptide data information.

[0033] Furthermore, acquiring peptide data information refers to using PyUUL's parsePDB module to read the PDB file of the three-dimensional structure, obtain peptide data information, and transfer this information to CUDA.

[0034] Furthermore, the polypeptide data information includes coordinates, atom names, channels, and atomic radii.

[0035] Furthermore, the conversion of peptide data information refers to using PyUUL's point cloud conversion module to convert the read peptide file information into surface area point cloud data.

[0036] Furthermore, in step S3, considering that the number of atoms contained in a tetrapeptide is less than 500, the maximum number of spots in each batch is set to 500 to ensure a balance between processing efficiency and resource utilization.

[0037] Furthermore, in step S6, the structural modification refers to modifying the amino acids in the polypeptide.

[0038] Thirdly, the present invention provides a fusion protein comprising the active polypeptide sequence described in the first aspect, wherein the fusion protein has the function of targeting PD-L1.

[0039] Fourthly, the present invention provides a polymer composed of two or more polypeptide monomers, wherein at least one polypeptide monomer is the small molecule polypeptide described in the first aspect; the polypeptide monomers of the polymer are covalently linked.

[0040] Furthermore, the polymer is a homodimer or a heterodimer.

[0041] Fifthly, the present invention provides a nucleic acid molecule that encodes the small molecule polypeptide described in the first aspect or the fusion protein or conjugate described in the third aspect.

[0042] In a sixth aspect, the present invention provides a construct comprising the nucleic acid molecule described in the fifth aspect.

[0043] In a seventh aspect, the present invention provides a host cell comprising the nucleic acid molecule described in the fifth aspect and / or the construct described in the sixth aspect, wherein the host cell is transformed or transfected by the nucleic acid molecule described in the third aspect and / or the construct described in the fourth aspect.

[0044] In an eighth aspect, the present invention provides a pharmaceutical composition comprising the small molecule polypeptide of the first aspect, the fusion protein of the third aspect, the polymer of the fourth aspect, the nucleic acid molecule of the fifth aspect, the construct of the sixth aspect and / or the host cell of the seventh aspect, and optionally pharmaceutically acceptable excipients.

[0045] In a ninth aspect, the present invention provides the use of the small molecule polypeptide of the first aspect, the fusion protein of the third aspect, the polymer of the fourth aspect, the nucleic acid molecule of the fifth aspect, the construct of the sixth aspect, or the host cell of the seventh aspect in the preparation of medicaments for the prevention and / or treatment of tumor-related diseases.

[0046] Furthermore, the tumor-related diseases include, but are not limited to, squamous cell carcinoma of the head and neck, nasopharyngeal carcinoma, triple-negative breast cancer, non-small cell lung cancer (NSCLC), small cell lung cancer, esophageal cancer, pleural mesothelioma, gastric cancer, hepatocellular carcinoma, cholangiocarcinoma, renal cancer, urothelial carcinoma, cervical cancer, ovarian cancer, melanoma, squamous cell carcinoma of the skin, certain special types of soft tissue sarcomas, solid tumors with dMMR / MSI-H including colorectal cancer, and solid tumors with TMB ≥ 10 mut / Mb.

[0047] Beneficial effects

[0048] 1. This invention utilizes machine learning and virtual screening methods to obtain a series of polypeptide molecules SEQ ID NO.1-SEQ ID NO.82; among them, the polypeptide SEQ ID NO.45 exhibits the highest activity, can bind to PD-L1 at the molecular level, and has a KD of 9.121 × 10⁻⁶. -7 .

[0049] 2. The small molecule peptides screened in this invention have the effect of inducing PD-L1 dimerization at both the molecular and cellular levels.

[0050] 3. The small molecule peptides screened in this invention have great potential in enhancing the killing effect of immune cells on tumor cells. In animal experiments, at the same concentration, the small molecule peptides showed better inhibitory activity than the PD-L1 monoclonal antibody control group and the small molecule inhibitor control group (BMS202), and the inhibition rate of tumors increased in a dose-dependent trend. When the concentration was 20 mg / kg, the inhibition rate of tumor weight reached 83%.

[0051] 4. During the experiment, the weight of mice in the small molecule peptide treatment group hardly changed, indicating that the small molecule peptide had no obvious toxicity and had a certain degree of safety.

[0052] 5. PD-L1 is a tumor-related target. The obtained small molecule peptides can inhibit the binding of PD-L1 and PD-1, and are expected to be developed into new small molecule peptide PD-L1 inhibitor drugs. Attached Figure Description

[0053] Figure 1 This is a flowchart of the screening method based on machine learning and virtual screening according to the present invention.

[0054] Figure 2 This is a schematic diagram of the alpha screen assay for peptide activity provided in SEQ ID NO.1-SEQ ID NO.45 according to an embodiment of the present invention.

[0055] Figure 3 This is a schematic diagram of the alpha screen assay for peptide activity provided in SEQ ID NO.45 of this invention.

[0056] Figure 4 This is the SPR binding curve of SEQ ID NO.45 and PD-L1 provided in the embodiments of the present invention.

[0057] Figure 5 This is a schematic diagram of FRET experiments verifying the molecular-level induction of PD-L1 dimerization by SEQ ID NO.45 and BMS202.

[0058] Figure 6This is a schematic diagram of non-denaturing gel electrophoresis experiments verifying SEQ ID NO.45 and BMS202 cell-level PD-L1 dimerization.

[0059] Figure 7 This is a schematic diagram illustrating SEQ ID NO.45's enhancement of NK-92 cells' ability to kill tumor cells.

[0060] Figure 8 This is a schematic diagram of the tumor inhibition rate of SEQ ID NO.45 provided in an embodiment of the present invention. Detailed Implementation

[0061] The specific embodiments of the present invention will be further described below. It should be noted that these descriptions are for the purpose of aiding understanding the present invention, but do not constitute a limitation thereof. Furthermore, the technical features involved in the embodiments described below can be combined with each other as long as they do not conflict with each other.

[0062] Unless otherwise specified, the experimental methods used in the following embodiments are conventional methods, and the experimental materials used in the following embodiments are all available through conventional commercial channels.

[0063] Terminology Explanation

[0064] Immune checkpoint inhibitors (ICIs) are a class of monoclonal antibodies. Immune checkpoint molecules and their ligands are negative regulatory molecules expressed in normal tissue cells and immune cells, such as cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1). Their basic mechanism of action is to block the binding between the receptors and ligands of immune checkpoint molecules, thereby activating immune effector cells, mainly effector T lymphocytes. The activated immune effector cells then suppress tumors.

[0065] Programmed death receptor ligand 1 (PD-L1): PD-1 is a type I transmembrane protein composed of 288 amino acids, including extracellular IgV and IgC regions, a transmembrane region, and an intramembrane region. It is mainly expressed by various immune cells, including B cells, T cells, natural killer cells, dendritic cells, and tumor-infiltrating lymphocytes. PD-L1, as an endogenous ligand of PD-1, is also a type I transmembrane protein, including an extracellular IgV region, a transmembrane region, and an intramembrane region that bind to PD-1. It is frequently expressed in various tumor cells, such as melanoma, colon cancer, lung cancer, pancreatic cancer, and ovarian cancer. Under normal physiological conditions, the main function of the PD-1 / PD-L1 pathway is to regulate the intensity of the immune response to an appropriate level, enabling the body to successfully complete the immune response while avoiding harmful effects. However, in the tumor microenvironment, PD-L1 on the surface of tumor cells interacts with PD-1 on the surface of T cells, leading to a decrease in effector T cell function, suppression of the anti-tumor immune response, and thus allowing tumor growth. Blocking the binding of PD-1 and PD-L1 can restore T cell activity and enhance the body's ability to kill tumors.

[0066] BMS202: An effective non-peptide PD-1 / PD-L complex inhibitor that can directly bind to PD-L1 and block the interaction between human PD-1 / PD-L, exhibiting anti-tumor activity.

[0067] Example 1: Screening of small molecule peptides

[0068] A three-dimensional structure database containing 160,000 peptides was constructed using the xleap program in Amber software, which will serve as a database of small molecule compounds for subsequent screening.

[0069] To perform virtual screening, small molecule ligands from the 3D protein structure of PD-L1 (PDBID: 5N2F) were downloaded from the PDB database as active molecules and mixed into a pre-constructed tetrapeptide database. Subsequently, the 3D features of each peptide and active molecule in the database were extracted using the PyUUL library and used as input for the downstream K-means algorithm. K-means clustering was then performed with a cluster size of 2, and the cluster containing the active molecule was selected for subsequent molecular docking. Ledock was used for the initial docking stage, followed by further docking of the first 300 entries using Glide. Finally, the first 100 entries were selected and the MM / GBSA ratio was calculated using Schrödinger's Prime module.

[0070] The first 30 peptides were selected from the first 100 for solid-phase synthesis and bioactivity assay (Table 1).

[0071] Peptide solid-phase synthesis: First, the resin was immersed in a solvent of N,N-dimethylformamide and dichloromethane in a 1:1 volume ratio to allow for full resin swelling for 4 hours. Next, the first amino acid was introduced and allowed to react with the resin for 1 hour. After completion, end-capping was performed using a mixed solvent of methanol, dichloromethane, and N,N-diisopropylethylamine (2:2:1 ratio). Then, the correct amino acids were added sequentially, using DMF as the solvent for amino acid coupling. HTCU and DIPEA acted as condensing agents and activators of the amino acids, respectively, for 1 hour. Subsequently, the Fmoc protecting group on the amino acids was removed, and the next amino acid was coupled, repeating the cycle until the last amino acid. After the peptide sequence was synthesized, the peptide was cleaved from the resin using a lysis buffer of trifluoroacetic acid:triisopropylsilane:water = 9:0.5:0.5 for 3 hours. The synthesized peptide was then precipitated using diethyl ether and purified using a C18 reverse-phase column. Electrospray mass spectrometry was used to verify the correct molecular weight of the peptide, and high performance liquid chromatography was used to identify a purity of >95%.

[0072] Bioactivity assays: Bioactivity was determined using Alpha Screen technology. PD-L1 protein was diluted to 10 nM with 1×Assay buffer. 5 μL of PD-L1 protein dilution and 5 μL of positive control BMS202 or the test peptide were added to each well of a 384-well plate and incubated (BMS202 and the screened peptide were both at 500 nM). 5 μL of 1×Assay buffer was used as a blank control, i.e., no compound was added to the wells. PD-1 protein was diluted to 15 nM with 1×Assay buffer. 5 μL of PD-1 protein dilution was added to each well, and incubation continued. Receptor beads were diluted 50-fold with 1×Assay buffer, and 5 μL of the recipient bead dilution was added to each well for incubation. Donor beads were diluted 50-fold with 1×Assay buffer, and 5 μL of the donor bead dilution was added to each well for incubation. Finally, the OD value at 680 nM in the 384-well plate was read using a microplate reader. The results showed that SEQ ID NO.1 had the best activity, therefore SEQ ID NO.1 was modified. Figure 2 ).

[0073] Table 130: Activity and MM / GBSA of peptides

[0074]

[0075] Twenty common amino acids were classified according to their side chains (Table 2), resulting in nine categories. An amino acid was randomly selected from each category as a representative for elongation, and AlphaFold2 was used to predict the complex model of the elongated peptide and PD-L1. Subsequently, 10 ns molecular dynamics simulations were performed using Amber software, and the MM / GBSA ratio was calculated. The results are shown in Table 3. The three peptides with the best activity were SEQ ID NO.31, SEQ ID NO.32, and SEQ ID NO.33.

[0076] The amino acids in the extended portions of the three peptides with the best activity were mutated to the same amino acids, and a complex model was predicted and the binding affinity based on MM / GBSA was calculated. The results are shown in Table 4, with SEQ ID NO.40 and SEQ ID NO.41 showing relatively better binding affinity.

[0077] SEQ ID NO.40 and SEQ ID NO.41 were extended using the same strategy, and the results are shown in Tables 5 and 6. The two sequences with the best scores were SEQ ID NO.44 and SEQ ID NO.45, and peptide solid-phase synthesis and bioactivity assays were performed.

[0078] Table 2 Amino Acid Classification

[0079]

[0080] Table 3 Pentapeptide MM / GB(PB)SA

[0081]

[0082] Table 4. Pentapeptide mutants MM / GB(PB)SA

[0083]

[0084] Table 5 Hexapeptide MM / GB(PB)SA

[0085]

[0086]

[0087] Table 6 Hexapeptide mutants MM / GB(PB)SA

[0088]

[0089] SEQ ID NO.1 was mutated to obtain SEQ ID NO.45 (WMHFNR) and SEQ ID NO.44 (RLHFNR), and the activity was further determined using Alpha Screen technology.

[0090] The results are as follows Figure 3 As shown, SEQ ID NO.45 exhibits superior activity compared to SEQ ID NO.44 and SEQ ID NO.1, with its IC50 value being significantly higher. 50 It is 0.336 μM.

[0091] Example 2: SPR investigation of the binding dissociation constant of small molecule peptides with PD-L1

[0092] Using BMS202 as a positive control, the binding effect of PD-L1 and SEQ ID NO.45 was detected using the SPR method.

[0093] The results are as follows Figure 4 As shown, SEQ ID NO.45 can bind to PD-L1 at the molecular level, with a KD value of 912.1 nM.

[0094] Example 3: FRET investigation of the dimerization of small molecule peptides

[0095] First, the dimerization effect of SEQ ID NO.45 was verified at the molecular level. FRET (fluorescein resonance energy transfer) experiments were performed, in which PD-L1 was coupled with FAM (carboxyfluorescein) and TAMRA (tetramethylrhodamine) in a 1:1 ratio of PD-L1 to the two labeled substances.

[0096] The results are as follows Figure 5 As shown, the dimerization ratio of PD-L1 gradually increased as the concentration of SEQ ID NO.45 increased from 250 μM to 2 mM. At the 2 mM concentration, the dimerization ratio was close to 1.4. This indicates that SEQ ID NO.45 has the potential to induce PD-L1 dimerization.

[0097] Secondly, the PD-L1 dimerization effect induced by different concentration gradients of SEQ ID NO.45 was verified at the cellular level using non-denaturing gel electrophoresis. First, protein samples were collected: logarithmically growing MDA-MB-231 cells were digested, centrifuged, resuspended, and counted. Different concentrations of SEQ ID NO.45 were added to final concentrations of 0.1, 1, and 10 μM, with solvent control wells and positive control wells set up and incubated. Cells were collected, centrifuged, and the supernatant was discarded, followed by washing with PBS. 150 μL of non-denaturing lysis buffer was added to the cell pellet, and the mixture was thoroughly mixed and placed on ice for lysis. The sample was then mixed and stored for later use. Next, PD-L1 was detected using Native-Page technology: based on the molecular weight of the target protein, a Tris-Gly 10% precast gel was selected for gel electrophoresis. After protein quantification, 20 μg of protein sample was loaded into each well for Native-PAGE gel electrophoresis. After electrophoresis, carefully remove the gel and place it on the wet transfer apparatus in the order of "transfer paper - gel - NC membrane transfer paper". After transfer, remove the NC membrane and stain it in Ponceau S solution on a shaker until a clear red protein band appears on the NC membrane. Place the entire membrane in an antibody incubation box. After washing away residual Ponceau S staining solution with TBST solution, add 5% skim milk powder to the box and incubate at room temperature with gentle shaking for blocking. After blocking, add TBST and wash away the blocking solution with rapid shaking. Take 2 μL of PD-L1 primary antibody according to experimental requirements and dilute it with TBST at a ratio of 1:1000. Place the incubation box on a shaker with slow shaking at low temperature. The next day, wash away the primary antibody on the membrane with TBST and wash with rapid shaking. Add 1-2 μL of the corresponding HRP-labeled secondary antibody (diluted with TBST according to the manufacturer's instructions) and incubate at room temperature with gentle shaking. Then wash away the secondary antibody in the same way. After washing, apply an appropriate amount of developer to the NC membrane containing the target protein (prepare the ECL chemiluminescence solution in the dark, mixing Regent A and B in a 1:1 ratio according to the instructions). Then place the strip in a Tanon developer for exposure and development, and analyze the results.

[0098] The results are as follows Figure 6 As shown, in the presence of SEQ ID NO.45 and BMS202 (1 μM), in addition to the electrophoretic band of monomeric PD-L1, an additional electrophoretic band at the dimer site appeared. This result clearly indicates that SEQ ID NO.45 also has the effect of inducing PD-L1 dimerization at the cellular level.

[0099] Example 4: Investigating the in vitro immunomodulatory and antitumor effects of small molecule peptides

[0100] Literature reports that NK cells in cancer patients can express PD-1 protein, and the application of PD-L1 inhibitors can block the inhibitory effect of tumor cells on NK cells, restoring the anti-tumor activity of NK cells. To evaluate the in vitro immunotherapeutic effect of SEQ ID NO.45, this study conducted an experiment to enhance the NK-92 cell killing ability of SEQ ID NO.45. First, tumor cells were treated with different concentrations of SEQ ID NO.45, and then the killing effect of NK cells on MDA-MB-231 and HCC827 was detected using the LDH method.

[0101] The results are as follows Figure 7 As shown, SEQ ID NO.45 exhibited superior activity compared to BMS202 (1 μM), and SEQ ID NO.45 significantly enhanced the killing ability of NK cells against MDA-MB-231 (human breast cancer cells) and HCC827 (human lung cancer cells) in a dose-dependent manner. 10 μM of SEQ ID NO.45 increased the killing rate of NK-92 against MDA-MB-231 and HCC827 from approximately 35% to approximately 60%. These results demonstrate the significant potential of SEQ ID NO.45 in enhancing the killing effect of immune cells against tumor cells.

[0102] Example 5: Antitumor effect of small molecule peptides in tumor-bearing mice

[0103] The antitumor effect of SEQ ID NO.45 in MC-38 tumor-bearing mice was investigated. After successful modeling, the tumor-bearing mice were randomly divided into six groups: low-dose SEQ ID NO.45 group (5 mg / kg), medium-dose SEQ ID NO.45 group (10 mg / kg), high-dose SEQ ID NO.45 group (20 mg / kg), PD-L1 monoclonal antibody control group (α-PD-L1, 5 mg / kg), small molecule inhibitor control group (BMS202, 20 mg / kg), and saline group. Subsequently, the corresponding drugs were administered intraperitoneally every two days. During the drug administration process, the tumor volume and body weight of the tumor-bearing mice were monitored every two days. When the tumor volume reached 1000 mm², the tumor was expelled from the control group. 3 At that time, we euthanized the mice by cervical dislocation, dissected the mice, photographed the tumors, and calculated the tumor inhibition rate.

[0104] The results are as follows Figure 8As shown, SEQ ID NO.45 exhibited good anti-tumor activity even at low doses. It was superior to the PD-L1 monoclonal antibody control group (α-PD-L1), the small molecule inhibitor control group (BMS202), and the saline group in both the rate of tumor volume increase and the inhibition of tumor weight. SEQ ID NO.45 increased the tumor weight inhibition rate (TGI) in a dose-dependent manner, reaching 83% in the high-dose group. Furthermore, the body weight of mice in the SEQ ID NO.45 treatment group remained almost unchanged during the experiment. These results indicate that SEQ ID NO.45 has a significant inhibitory effect on tumor proliferation in vivo and no obvious toxicity.

Claims

1. A small molecule polypeptide targeting PD-L1, wherein the amino acid sequence of the small molecule polypeptide targeting PD-L1 is shown in SEQ ID NO.

45.

2. A homodimer, formed by the polymerization of two polypeptide monomers, wherein the polypeptide monomers are the small molecule polypeptides of claim 1; the polypeptide monomers of the homodimer are covalently linked.

3. A nucleic acid molecule, said nucleic acid molecule encoding the small molecule polypeptide of claim 1.

4. A construct comprising the nucleic acid molecule of claim 3.

5. A host cell comprising the nucleic acid molecule of claim 3 and / or the construct of claim 4, said host cell being transformed or transfected by the nucleic acid molecule of claim 3 and / or the construct of claim 4.

6. A pharmaceutical composition comprising the small molecule polypeptide of claim 1, the homodimer of claim 2, the nucleic acid molecule of claim 3, the construct of claim 4, and / or the host cell of claim 5, and optionally pharmaceutically acceptable excipients.

7. The use of the small molecule polypeptide of claim 1, the homodimer of claim 2, the nucleic acid molecule of claim 3, the construct of claim 4, and / or the host cell of claim 5 in the preparation of a medicament for the prevention and / or treatment of tumor-related diseases; wherein the tumor-related diseases include triple-negative breast cancer, non-small cell lung cancer (NSCLC), and colorectal cancer.

Images