A system, method and device for screening drugs for treating periodontitis based on KAT6A and H3 interaction

Abstract

The application discloses a system, a method and equipment for screening periodontitis treatment drugs based on KAT6A and H3 interaction, and discloses, for the first time, the interaction between KAT6A and H3, and based on the interaction, provides a computer-aided drug screening method, system and equipment based on KAT6A and H3 and a computer readable storage medium for the field, and provides an efficient, accurate and rapid screening method for new drug research and development of periodontitis treatment, and provides a new clinical idea for drug treatment of periodontitis.

Description

Technical Field

[0001] This invention belongs to the field of computer-aided drug screening technology, specifically, it relates to a system, method and device for screening drugs for the treatment of periodontitis based on the interaction of KAT6A and H3. Background Technology

[0002] Periodontitis is the sixth leading cause of disease worldwide and a major cause of tooth loss in adults in my country. It is estimated that approximately 50% of the global population suffers from periodontitis to varying degrees, with about 1.1 billion people suffering from severe periodontitis. Severe periodontitis not only affects oral and maxillofacial function, speech, and aesthetics but also impacts overall health. Currently, clinical treatments for severe periodontitis mainly include periodontal regeneration surgery, periodontal tissue engineering, and adjuvant drug therapy. Periodontal regeneration surgery primarily refers to bone grafting and guided tissue regeneration (GTR) performed under the premise of basic periodontal treatment. Bio-Oss bone powder is the most widely used bone defect filling material in clinical practice. However, its preparation process is complex, its price is high, its biodegradation rate in the body is lower than that of autologous tooth bone powder, and it carries the risk of immune rejection. Due to surgical limitations, GTR is only suitable for patients with vertical or angular resorption, and its effectiveness for horizontal resorption is limited. Therefore, there is an urgent need to develop a new technology to address the shortcomings of periodontal regeneration surgery.

[0003] Medication is an important means of treating periodontitis. Drug therapy has unparalleled advantages over other treatment methods, such as ease of administration and lower cost. However, it is limited by the localized periodontal tissue environment and its susceptibility to gingival crevicular fluid and saliva erosion. Conventional administration methods, such as oral administration, are difficult to reach the site of periodontal inflammation and can easily induce systemic symptoms; local injection has limited effect on the periodontium. Therefore, drug therapy is currently only used as an adjunct treatment in clinical practice. How to achieve precise drug administration and improve drug efficacy and duration of action is one of the urgent problems to be solved. Computer-aided drug design (Computer...) Aided Drug Design (CADD) is based on computer computation and simulation technology. By learning from the prior knowledge contained in massive amounts of drug data, it can uncover the interaction relationships between target molecules and candidate drugs, and rapidly select drug-like active drug molecules from millions of molecules. This greatly reduces the blind spots in screening candidate drug molecules and improves research and development efficiency. Summary of the Invention

[0004] In view of this, and to overcome the shortcomings of the prior art, the purpose of this invention is to provide a system, method, and apparatus for screening drugs for treating periodontitis based on the interaction of KAT6A and H3. Computer-aided drug screening technology is used to screen drugs that can be used to treat periodontitis.

[0005] The first aspect of the present invention provides a computer-aided drug screening method based on KAT6A and H3.

[0006] Furthermore, the method includes: Obtain KAT6A protein structure and histone H3 structure data; The spatial structure of the complex formed by the interaction between the KAT6A protein and the histone H3 was selected, and the binding sites of the KAT6A protein and the histone H3 in the complex were determined as the binding sites of the targeted drug. Candidate drugs targeting the binding site were obtained using a computer-aided drug screening method.

[0007] Furthermore, the binding site is H3K9.

[0008] Furthermore, the candidate drug is a drug that can inhibit the progression of periodontitis.

[0009] Furthermore, the computer-aided drug screening method includes: Obtain the binding sites of the KAT6A protein and histone H3 in the complex; Based on the spatial structure of the binding sites of the KAT6A protein and histone H3 in the complex, small molecule compounds with similar structures were screened from molecular databases. The selected functional molecules are molecularly docked with the KAT6A protein or histone H3 and scored to obtain a comprehensive score for the functional molecules. Candidate drugs are obtained by ranking the comprehensive scores.

[0010] Furthermore, the functional molecules include small molecule compounds, peptide analogs, polypeptides, antibodies, and protein analogs.

[0011] Furthermore, the small molecule compounds include inorganic small molecule compounds, siRNA, shRNA, dsRNA, microRNA, or antisense nucleic acids.

[0012] Furthermore, the binding sites of the KAT6A protein and histone H3 in the complex were predicted using bioinformatics prediction methods.

[0013] Furthermore, the bioinformatics prediction method includes molecular docking methods, prediction methods based on sequence and structural information, or multi-scale protein sequence structure comparison and learning methods.

[0014] Furthermore, the method also includes performing an inhibition binding experiment on the candidate drug. After the candidate drug is mixed with KAT6A protein solution and H3 protein solution, the binding force of KAT6A and H3 after the addition of the candidate drug is calculated using any one or more of the following methods: surface plasmon resonance, biolayer interference, and isothermal titration calorimetry. Candidate drugs that can inhibit the binding of KAT6A and H3 are then screened.

[0015] A second aspect of the present invention provides a computer-aided drug screening system based on KAT6A and H3.

[0016] Furthermore, the system includes: The data acquisition unit acquires structural data of KAT6A protein and histone H3. The site determination unit selects the spatial structure of the complex formed by the interaction between the KAT6A protein and the histone H3, and determines the binding sites of the KAT6A protein and histone H3 sites in the complex as the binding sites of the targeted drug. The drug screening unit uses a computer-aided drug screening method to obtain candidate drugs that target the binding site; Furthermore, the binding site is H3K9; Furthermore, the candidate drug is a drug capable of inhibiting the progression of periodontitis; Furthermore, the computer-aided drug screening method includes: Obtain the binding sites of the KAT6A protein and histone H3 in the complex; Based on the spatial structure of the binding sites of the KAT6A protein and histone H3 in the complex, small molecule compounds with similar structures were screened from molecular databases. The screened functional molecules are molecularly docked with the KAT6A protein or histone H3 and scored to obtain a comprehensive score for the functional molecules. Candidate drugs are obtained by sorting the comprehensive scores. Furthermore, the functional molecules include small molecule compounds, peptide analogs, antibodies, polypeptides, and protein analogs; Furthermore, the small molecule compounds include inorganic small molecule compounds, siRNA, shRNA, dsRNA, microRNA, or antisense nucleic acids; Furthermore, the binding sites of the KAT6A protein and histone H3 in the complex were predicted using bioinformatics prediction methods; Furthermore, the bioinformatics prediction method includes molecular docking methods, prediction methods based on sequence and structural information, or multi-scale protein sequence structure comparison and learning methods; Furthermore, the method also includes an effectiveness verification unit, and further includes performing an inhibition binding experiment test on the candidate drug. After the candidate drug is mixed with KAT6A protein solution and H3 protein solution, the change in the binding force of KAT6A and H3 after the addition of the candidate drug is calculated using any one or more of the following methods: surface plasmon resonance, biolayer interference, and isothermal titration calorimetry, and candidate drugs that can inhibit the binding of KAT6A and H3 are screened.

[0017] A third aspect of the present invention provides a computer-aided drug screening device based on KAT6A and H3.

[0018] Furthermore, the device includes: The invention includes a memory and a processor, wherein the memory is used to store program instructions; and the processor is used to invoke the program instructions, which, when executed, implement the computer-aided drug screening method based on KAT6A and H3 provided in the first aspect of the invention.

[0019] A fourth aspect of the present invention provides a computer-readable storage medium.

[0020] Furthermore, the computer-readable storage medium stores a computer program that, when executed by a processor, implements the computer-aided drug screening method based on KAT6A and H3 provided in the first aspect of the present invention.

[0021] The fifth aspect of the present invention provides any of the following products: (1) A complex formed by the interaction of KAT6A protein and histone H3; (2) A drug screened by a computer-aided drug screening method based on KAT6A and H3 according to the first aspect of the present invention; Furthermore, the drug also includes additives acceptable in the medical field.

[0022] Furthermore, the additives include one or more of the following: starch, powdered sugar, mannitol, starch paste, cellulose derivatives, magnesium stearate, micronized silica gel, talc, gelatin, water, ethanol, polyethylene glycol, magnesium lauryl sulfate, and hydrogenated vegetable oil.

[0023] A sixth aspect of the present invention provides an application of the compound.

[0024] Furthermore, the complex is a complex formed by the interaction of KAT6A protein and histone H3 as described in the fifth aspect of the present invention.

[0025] Furthermore, the application includes the use of the complex in screening drugs for inhibiting the progression of periodontitis.

[0026] The advantages and beneficial effects of this invention are as follows: This invention is the first to discover the interaction between WM1119 and the JAK / STAT1 pathway, which inhibits the progression of periodontal inflammation by inhibiting KAT6A acetylation of histone H3K9. Based on this, this invention provides a computer-aided drug screening method, system, device, and computer-readable storage medium based on KAT6A and H3. This invention provides an efficient, accurate, and rapid screening method for the development of new drugs for the treatment of periodontitis, and offers a new clinical approach to the drug treatment of periodontitis. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 A schematic diagram of a computer-aided drug screening method based on KAT6A and H3 provided by the present invention; Figure 2 A schematic diagram of a computer-aided drug screening system based on KAT6A and H3 provided by the present invention; Figure 3 A schematic diagram of a computer-aided drug screening device based on KAT6A and H3 provided by the present invention; Figure 4To validate the effects of single-cell sequencing on macrophages and KAT6A, the results showed an increased proportion of macrophages and increased KAT6A expression in human periodontitis. Figure A is a UMAP visualization of single-cell RNA sequencing data (GSE152042 and GSE171213) from healthy donors (n=6) and periodontitis patients (n=6), identifying nine major cell clusters from a total of 29,023 cells. Figure B is a bubble chart of gene expression, a classic marker for identifying major cell lineages (the size of the dot indicates the percentage of cells expressing the gene; the color intensity indicates the average expression level). Figure C is a stacked bar chart showing the proportional distribution of cell types in the healthy and periodontitis groups. Figure 1; Figure D is a bar chart showing the average number of cells per sample for each cell type in the healthy and periodontitis groups; Figure E is a UMAP visualization of the re-clustering of Mono-Macro_cell (monocyte-macrophage) subsets, revealing five myeloid subsets (macrophages, monocytes, dendritic cells 1, dendritic cells 2, and mature dendritic cells); Figure F is a heatmap of differentially expressed marker genes in each myeloid subset; Figure G is a heatmap of the relative expression of KAT family genes (KAT5, KAT6A, KAT6B, KAT7, KAT8) in each myeloid subset under healthy and periodontitis conditions, highlighting the increased expression of KAT6A in periodontitis macrophages compared to healthy macrophages. Statistical significance was calculated using the Wilcoxon rank-sum test. p<0.05 indicates a statistically significant difference, and ns indicates no significant difference; Figure 5To demonstrate the elevated KAT6A phenotype and macrophage polarization to M1 type in a mouse periodontitis and inflammatory cell model, Figure A shows a schematic diagram of the mouse periodontitis model construction; Figure B shows the Micro-CT 3D reconstruction images of the successfully constructed mouse periodontitis model and the healthy mouse control group, as well as the quantitative results of alveolar bone resorption; Figure C shows HE and IL-1β histochemical staining of periodontal tissues from healthy mouse controls and periodontitis mice; Figure D shows the quantitative results of IL-1β-positive cells in periodontal tissues from healthy mouse controls and periodontitis mice; Figure E shows the quantitative results of KAT6A-positive cells / CD68-positive cells in periodontal tissues from healthy mouse controls and periodontitis mice; Figure F shows the quantitative results of KAT6A-positive cells / CD68-positive cells in periodontal tissues from healthy mouse controls and periodontitis mice; Figure F shows the quantitative results of KAT6A-positive cells / CD68-positive cells in periodontal tissues from healthy mouse controls and periodontitis mice. The results of KAT6A and CD68 fluorescence staining in periodontal tissues of mice with periodontitis; Figure G shows the protein expression of KAT6A, IL-1β, inos, and Arg-1 in RAW264.7 after LPS stimulation; Figure H shows the mRNA expression of KAT6A, IL-1β, inos, and Arg-1 in RAW264.7 after LPS stimulation; Figure I shows the immunofluorescence staining of inos / CD68 and Arg-1 / CD68 in RAW264.7 after LPS stimulation; Figure J shows the immunofluorescence quantitative results of inos+ / CD68+ and Arg-1+ / CD68+ in RAW264.7 after LPS stimulation. Figure 6 In a mouse model of periodontitis, WM1119 inhibition of KAT6A prevented macrophages from polarizing to the M1 type under inflammatory stimulation, thus inhibiting the progression of periodontitis to some extent. Figure A shows a schematic diagram of the mouse periodontitis model after WM1119 / DMSO injection; Figure B shows the Micro-CT 3D reconstruction and quantitative results of alveolar bone resorption in mice with periodontitis after WM1119 or DMSO injection; Figure C shows the HE staining results in mice with periodontitis after WM1119 or DMSO injection; Figure D shows the inos / CD68 and Arg-1 / CD68 fluorescence staining results in mice with periodontitis after WM1119 or DMSO injection; Figure E shows the RA... The protein expression of IL-1β, inos, and Arg-1 in W264.7 mice stimulated with LPS and without WM1119 were compared. Figure F shows the quantitative fluorescence results of inos+ / CD68+ and Arg-1+ / CD68+ in mice with periodontitis and after injection of WM1119 / DMSO. Figure G shows the mRNA expression of IL-1β, inos, and Arg-1 in RAW264.7 mice stimulated with LPS and without WM1119. Figure H shows the immunofluorescence staining and quantitative results of inos / CD68 and Arg-1 / CD68 in RAW264.7 mice stimulated with LPS and without WM1119. Figure 7WM1119 competitively inhibits KAT6A acetylation of H3K9 to H3K9ac, inhibiting the JAK / STAT1 pathway and M1 polarization in mouse macrophages. 2-NP is a STAT1 agonist. Figure A shows the protein expression and quantification results of JAK, Stat1, and p-Stat1 in RAW264.7 cells stimulated with and without WM1119 under LPS stimulation; Figure B shows the immunofluorescence staining results of Stat1 / CD68 and p-Stat1 / CD68 in RAW264.7 cells stimulated with and without WM1119 under LPS stimulation; Figure C shows the Stat1+ / CD68+ and p-Stat1+ / CD68+ in RAW264.7 cells stimulated with and without WM1119 under LPS stimulation. The results of CD68+ fluorescence quantification; Figure D shows the mRNA expression of IL-1β, inos, and Arg-1 in RAW264.7 after stimulation with LPS and WM1119 and without the addition of 2-NP; Figure E shows the protein expression of IL-1β, inos, and Arg-1 in RAW264.7 after stimulation with LPS and WM1119 and without the addition of 2-NP; Figure F shows the protein expression of H3K9ac, H3K14ac, and H3K27ac in RAW264.7 after stimulation with LPS and without the addition of WM1119; Figure G shows the mRNA expression of Stat1 bound to H3K9ac in RAW264.7 after stimulation with LPS and without the addition of WM1119. Figure 8 To investigate how KAT6A promotes osteoclast differentiation and periodontitis progression in raw264.7 cells under inflammatory conditions, Figure A shows the TRAP staining and quantification results of RAW264.7 cells with and without WM1119 after stimulation with RANKL and LPS; Figure B shows the mRNA expression of NFATC1, TRAP, and CTSK in RAW264.7 cells with and without WM1119 after stimulation with RANKL and LPS; Figure C shows the TRAP staining and quantification results of periodontitis mice injected with DMSO or WM1119; Figure D shows the TRAP staining results of periodontitis mice injected with DMSO or WM1119; and Figure E is a schematic diagram of the mechanism of action of WM1119. Figure 9To further inhibit the progression of periodontitis, WM1119@BPs@MM was used. Figure A shows the absorbance of each component of WM1119@BPs@MM; Figure B shows the particle size of each component; Figure C shows the Zeta potential values ​​of each component; Figure D shows the targeting-related immunofluorescence results of WM1119@BPs@MM on macrophages; Figure E shows the expression and quantification results of inflammatory proteins in RAW264.7 cells cultured under five conditions; Figure F shows the HE and IL-1β staining results, Micro-CT three-dimensional reconstruction results, and alveolar bone resorption quantification results of periodontitis mice injected with DPBS, WM1119, WM1119@BPs@MM, and WM1119@BPs@MM+NIR. Figure 10 A schematic diagram illustrating the construction method and mechanism of WM1119@BPs@MM; Figure 11 This is the single-cell sample quality control indicator of the present invention; Figure 12 The sample source for single-cell sequencing in this invention; Figure 13 The total number of cells in the single-cell sequencing of this invention (healthy controls and periodontitis). Figure 14 Number of samples for each cell type; Figure 15 To show the preference of each cell type in healthy and periodontitis tissues; Figure 16 The results show the protein quantification of KAT6A, inos, IL-1β, and Arg-1 in RAW265.7 under LPS stimulation. Figure 17 The protein quantification results of RAW265.7 with and without WM1119 under LPS stimulation, including inos, IL-1β, and Arg-1; Figure 18 The results of protein quantification of inos, IL-1β, and Arg-1 in RAW265.7 with and without 2-NP under LPS and WM1119 stimulation; Figure 19 The protein quantification results of RAW265.7 with and without WM1119 in the presence of H3K9ac, H3K14ac, and H3K27ac under LPS stimulation; Figure 20 The protein expression of histone deacetylase 3 (HDAC3) and histone deacetylase 4 (HDAC4) in RAW265.7 with and without WM1119 under LPS stimulation was compared. Figure 21The WM1119 standard curve and encapsulation efficiency were calculated based on the absorbance of WM1119. Figure 22 Transmission electron micrographs of BPs and MMs; Figure 23 The cell viability of RAW264.7 cells in WM1119 at concentration gradients ranging from 15 to 30 µM, and under conditions of irradiation with or without far-infrared light, was determined. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0030] In some of the processes described in the specification, claims, and accompanying drawings of this invention, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be performed in the order they appear herein, or may be performed in parallel. The operation numbers, such as S101, S102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be performed sequentially or in parallel.

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Figure 1 This is a schematic flowchart of a computer-aided drug screening method based on KAT6A and H3 provided by the present invention. Specifically, the method includes the following steps: S101: Obtain KAT6A protein structure and histone H3 structure data; In one embodiment, KAT6A refers to lysine acetyltransferase 6A, a nuclear-localized histone acetyltransferase belonging to the MYST family of proteins, encoded by the human KAT6A gene. The KAT6A protein contains a conserved MYST acetyltransferase domain, a C2H2 zinc finger domain, and multiple protein-protein interaction regions. It can use acetyl-CoA as an acetyl donor to catalyze the acetylation of lysine residues (including H3K9 and H3K14) at specific sites on histone H3, thereby regulating chromatin conformation and the transcriptional activity of target genes.

[0033] In one embodiment, histone H3 refers to one of the core structural proteins of the eukaryotic nucleosome, which is encoded and translated by multiple copies of histone H3 coding genes, including replication-dependent histone genes (such as HIST1H3A–HIST1H3J, HIST2H3A–HIST2H3C, etc.) and replication-independent histone variant genes (such as H3-3A, H3-3B), whose protein products together constitute the main source of H3 protein in chromatin nucleosomes.

[0034] In one embodiment, H3K9 refers to the 9th lysine residue of histone H3 (histone H3 lysine9), located in the N-terminal tail region of the histone H3 protein, and is a conserved lysine site carried by the histone H3 protein translated from the H3 coding gene. H3K9 is a lysine site that can undergo various post-translational modifications. Its ε-amino group can be catalyzed by different enzyme systems to undergo epigenetic modifications such as acetylation and methylation. Among these modifications, acetylation (H3K9ac) is usually associated with chromatin open state and transcriptional activation.

[0035] In one embodiment, the KAT6A protein structure data can be obtained using conventional methods for obtaining protein structure information known to those skilled in the art.

[0036] For example, the KAT6A protein structure data can be obtained using the following methods: obtaining the KAT6A protein structure from the RCSB PDB database (https: / / www.rcsb.org / ), obtaining the KAT6A protein structure from the AlphaFold protein structure database (https: / / alphafold.ebi.ac.uk), or using ColabFold online prediction of the KAT6A protein structure (https: / / github.com / sokrypton / ColabFold).

[0037] In one embodiment, the histone H3 structure data can be obtained using conventional methods for obtaining protein structure information known to those skilled in the art.

[0038] For example, the structural data of histone H3 can be obtained by the following methods: obtaining the structure of histone H3 from the RCSB PDB database (https: / / www.rcsb.org / ), obtaining the structure of histone H3 from the AlphaFold protein structure database (https: / / alphafold.ebi.ac.uk), or using ColabFold online prediction of the structure of histone H3 (https: / / github.com / sokrypton / ColabFold).

[0039] In specific embodiments of the present invention, the research content of the present invention includes: (1) the role and mechanism of KAT6A and its inhibitor WM1119 in the development of periodontitis; (2) the construction and testing of drug-loaded black phosphorus nanoparticles (MM@BPs@WM-1119) encapsulated in macrophage membranes; and (3) the in vivo anti-inflammatory ability of WM1119@BPs@MM.

[0040] In a specific embodiment of the present invention Figure 11 The single-cell sample quality control indicators provided by this invention; Figure 12 The sample source for single-cell sequencing in this invention; Figure 13 The total number of cells in the single-cell sequencing of this invention (healthy controls and periodontitis); Figure 14 Number of samples for each cell type; Figure 15 The preference of each cell type in healthy and periodontitis tissues.

[0041] In one embodiment, the experimental cells were cultured using the following steps: Mouse macrophages (RAW264.7) were used for cell experiments. Cell morphology was observed daily, and the medium was changed every 2-3 days. When the cell confluence reached 90%, the cells were passaged. The cell suspension was gently pipetted and collected into 15 mL centrifuge tubes. The cells were centrifuged at 1000 rpm for 5 min, the supernatant was discarded, and fresh growth medium was added. The cells were passaged at a ratio of 1:3.

[0042] In one embodiment, RNA-seq experiments were performed on the experimental cells. RAW264.7 cells were divided into three groups: a control group, an LPS group, and an LPS+WM1119 group. RNA was extracted from the cells in the three groups using the phenol-chloroform-ethanol method, and sent to a sequencing company for sequencing and analysis to identify the genes and pathways most sensitive to changes under the influence of LPS and WM1119. This validated the accuracy of the preliminary experimental results. The single-cell sequencing results are shown below. Figure 4As shown, macrophages play a crucial role in human periodontitis, and KAT6A expression is elevated in both periodontitis and LPS-induced RAW264.7 cells. Simultaneously, under inflammatory stimulation, macrophages polarize to the M1 type. In other embodiments, LPS-stimulated experimental cells were subjected to Western blotting. The specific steps included protein extraction using the RIPA method, protein concentration determination using the BCA method, electrophoresis, membrane transfer, milk blocking, incubation with primary and secondary antibodies, and chemiluminescence detection of protein expression. The results are as follows... Figure 5 As shown in Figure G, the protein expression levels of KAT6A, IL-1β, and inos in RAW264.7 cells were significantly increased after LPS stimulation compared to the control group. Simultaneously, this study also examined the expression of various genes in the experimental cells after LPS stimulation. Specifically, RNA was extracted using the TRIZOL-isopropanol-ethanol method, and the experimental system was prepared according to a reverse transcription kit to obtain cDNA. Primers were designed to prepare the PCR experimental system, and the expression of each gene was detected using the PCR instrument. The experimental results are shown below. Figure 5 As shown in Figure H, the mRNA expression levels of KAT6A, IL-1β, and inos in RAW264.7 were significantly increased after LPS stimulation compared to the control group, consistent with changes in protein levels. Finally, RAW264.7 cells stimulated by LPS were stained and quantified using immunofluorescence. The specific steps were as follows: RAW264.7 cells were fixed, permeabilized with Triton immunofluorescence, blocked with serum, incubated with primary antibody, added with fluorescent secondary antibody, stained with DAPI, mounted, and observed under a fluorescence microscope. The results are shown below. Figure 5 As shown in Figures I and 5, the expression level of the pro-inflammatory cytokine iNOS was increased and the expression level of the anti-inflammatory marker Arg-1 was decreased in RAW264.7 cells.

[0043] In other embodiments, following the Western blotting, mRNA level detection, and immunofluorescence staining steps described above, the expression levels of relevant factors in RAW264.7 cells of the LPS+WM1119 group were further detected, and the protein expression levels were compared with, for example... Figure 6 As shown in E, the mRNA expression level is as follows: Figure 6 As shown in G, the immunofluorescence staining and quantitative results are as follows: Figure 6 As shown in Figure H, based on the above experimental results, it can be concluded that WM1119 can effectively reduce the increase in inflammation level of RAW264.7 cells caused by LPS stimulation.

[0044] In one embodiment, to investigate the mechanism of action of WM1119, the expression levels of JAK / STAT1 pathway and M1 polarization-related markers in RAW264.7 cells of each group were studied according to the above-described Western blotting, mRNA level detection, and immunofluorescence staining procedures. The experimental results are as follows: Figure 7 As shown, 2-NP is a STAT1 agonist. Figure 7 The specific steps of the ChIP experiment involved in G are as follows: formaldehyde fixation of RAW264.7 cells, collection of cells, addition of cell lysis buffer to cut DNA in chromatin complex, sonication to disrupt cell nuclei, centrifugation to obtain chromatin fragments, addition of H3K9ac antibody to bind to the target protein-DNA complex, addition of Protein G microbeads to bind to the antibody-target protein-DNA complex and precipitate it, washing of the precipitated complex to remove some non-specific bindings—elution, obtaining enriched target protein-DNA complex—decrosslinking, purification of the enriched DNA fragments for PCR detection. Figure 7 A represents the protein expression and quantification results of JAK, Stat1, and p-Stat1 in RAW264.7 cells stimulated with LPS and without WM1119. Figure 7 B represents the immunofluorescence staining results of Stat1 / CD68 and p-Stat1 / CD68 in RAW264.7 with and without WM1119 under LPS stimulation; Figure 7 C represents the fluorescence quantitative results of Stat1+ / CD68+ and p-Stat1+ / CD68+ of RAW264.7 with and without WM1119 under LPS stimulation; Figure 7 D represents the mRNA expression of IL-1β, inos, and Arg-1 in RAW264.7 after stimulation with LPS and WM1119 and without the addition of 2-NP. Figure 7 E represents the protein expression of IL-1β, inos, and Arg-1 in RAW264.7 after stimulation with LPS and WM1119 and without the addition of 2-NP. Figure 7 F represents the protein expression of H3K9ac, H3K14ac, and H3K27ac in RAW264.7 with and without WM1119 under LPS stimulation. Figure 7 G represents the mRNA expression of Stat1 bound to H3K9ac in RAW264.7 after LPS stimulation with and without WM1119. Based on the comparison of protein expression levels, mRNA expression levels, and quantitative fluorescence, the mechanism of action of WM1119 in treating periodontitis can be concluded that WM1119 competitively inhibits KAT6A acetylation of H3K9 to H3K9ac, thereby inhibiting the JAK / STAT1 pathway and M1 polarization in mouse macrophages.

[0045] In one embodiment, by constructing a mouse periodontitis model and comparing different indicators of periodontitis tissues in healthy mice and periodontitis mice, it was found that the expression level of KAT6A was increased in the mouse periodontitis model. Figure 5A is a schematic diagram of the mouse periodontitis model. After approval from the Animal Ethics Committee of Central South University, this study used seven male C57 mice. The periodontitis model was established using silk ligation, with the mice serving as self-controls. Left side: control group; Right side: ligated side. The ligated side was cleaned after 7 days. Micro-CT analysis was then performed. Specifically, the hard tissues of the teeth and maxilla were fixed overnight with 10% formalin and analyzed using Micro-CT. Three-dimensional reconstruction and image analysis were performed using CTVox and Data Viewer software. The distance between the alveolar ridge and the cementoenamel junction was measured using Image-pro-plus software. The bone volume around the second molar was analyzed using parameters such as bone volume (BV), tissue volume (TV), and the BV / TV ratio. The analysis results are shown below. Figure 5 As shown in Figure B, it can be seen that the periodontal tissue on the ligated side of the mouse showed significant lesions compared to the control side. Subsequently, alveolar bone fixation, decalcification, and sectioning were performed. HE and IL-1β staining were used to assess the bone tissue and inflammation progression levels on the control and ligated sides. The staining results are shown in Figure B. Figure 5 As shown in C, combined with Figure 5 Quantitative results of positive cells for the pro-inflammatory factor IL-1β and Figure 5 The comparison of the proportion of KAT6A-expressing cells in E showed that the inflammation level on the ligated side of the mouse was significantly higher than that on the control side. In some embodiments, the expression of KAT6A in macrophages was observed by histofluorescence staining of mouse periodontitis tissue. The specific steps were as follows: Mouse maxillary bone samples were collected, alveolar bone was fixed, decalcified, and sectioned; the sections were baked at 60°C for 30 min; then the sections were placed in xylene for 10 min twice. Next, they were sequentially incubated in 100%, 95%, 85%, and 75% ethanol, each for 5-10 min. Afterwards, they were washed with distilled water for 5 min; then, heat antigen retrieval was performed by adding 3% H2O2 and incubating at room temperature for 10 min to inactivate endogenous enzymes. Serum blocking was performed, followed by incubation with primary antibody, addition of fluorescent secondary antibody, staining of the nuclei with DAPI, mounting, and observation under a fluorescence microscope. The staining results are shown below. Figure 5 As shown in Figure F, the proportion of CD68-labeled macrophages expressing KAT6A is increased in the mouse periodontitis model.

[0046] In some embodiments, protein bands in Western blotting results from different treatment groups are quantified. ImageJ is used to calculate the grayscale value of each band. The grayscale values ​​of each target protein are then normalized with GAPDH, and the grayscale values ​​of each target protein are compared. One-way ANOVA is used for comparisons among multiple groups. The final quantitative results are as follows: Figures 16-19 As shown, where, Figure 16 correspond Figure 5 The protein expression results of G, Figure 17 Corresponding to the protein expression results of 6E, Figure 18 correspond Figure 7 The protein expression results of E, Figure 19 correspond Figure 7 Protein expression results for F.

[0047] In another embodiment, following the Western blotting procedure described above, the protein expression levels of histone deacetylase 3 (HDAC3) and histone deacetylase 4 (HDAC4) in RAW265.7 cells stimulated with LPS and without WM1119 were investigated. The results are as follows: Figure 20 As shown, HDAC3 expression decreased after LPS stimulation and increased after the addition of WM1119, indicating that deacetylation was weakened under inflammatory stimulation, while WM1119 could enhance the deacetylation of HDAC3.

[0048] S102: Select the spatial structure of the complex formed by the interaction of the KAT6A protein and the histone H3, and determine the binding sites of the KAT6A protein and the histone H3 in the complex as the binding sites of the targeted drug; In one embodiment, the binding sites of the KAT6A protein and histone H3 in the complex are predicted using bioinformatics prediction methods. Specifically, the bioinformatics prediction methods include molecular docking methods, prediction methods based on sequence and structural information, or multi-scale protein sequence structure comparison and learning methods.

[0049] In one embodiment, molecular docking is a computational chemistry method used to simulate the binding patterns between small molecules and proteins. This method predicts binding sites by placing small molecule compounds at the binding sites of proteins and calculating their interaction energies. The DFSite algorithm combines molecular docking with local features, describing features at three levels: amino acids, atoms, and the binding site itself. It uses a linear regression algorithm to train a scoring function, improving prediction accuracy.

[0050] In one embodiment, the sequence and structure-based prediction method combines a structure-based prediction method (such as RNAsite_str) and a sequence-based prediction method (such as RNAsite_seq). First, multiple sequence alignment is performed using the BLASTN tool, then weights are assigned using the Henikoff–Henikoff scheme, ultimately forming the sequence and structure-based prediction method RNAsite, which achieves relatively ideal results.

[0051] In one embodiment, the multi-scale protein sequence structure contrast learning method utilizes a contrastive learning framework (PSC). PSC-CPI (Compound-Protein Interaction) is used to predict the interaction between compounds and proteins. The PSC-CPI model consists of two parts: a compound encoder and a protein encoder, which extract characterizations from molecular maps and protein sequence structures, respectively. By predicting the contact map between protein residues and compound atoms, the model learns the interaction between compounds. Pairwise characterization of proteins is performed, and an interaction strength prediction module is introduced to predict binding affinity.

[0052] In some embodiments, to evaluate the therapeutic effect of WM1119 on periodontitis, this study used seven male C57 mice after obtaining approval from the Animal Ethics Committee of Central South University. A periodontitis model was established using silk ligation, with the mice serving as self-controls. Figure 6 A shows the corresponding model construction diagram. The left side was a periodontitis + DMSO injection group, serving as the control side, while the right side was a periodontitis + WM1119 treatment group. In the left suture ligation group, the sutures were removed after 7 days, and DMSO injection was administered for 7 days, with samples collected after a total of 14 days. In the treatment group, sutures were first ligated for 7 days, then removed, and periodontal ligament injection was administered for 7 days, with samples collected after a total of 14 days. Subsequently, micro-CT analysis was performed on the periodontal tissues of the mice from different treatment sides. Specifically, the hard tissues of the teeth and maxilla were fixed overnight with 10% formalin and analyzed using micro-CT. Three-dimensional reconstruction and image analysis were performed using CTVox and Data Viewer software. The distance between the alveolar ridge and the cementoenamel junction was measured using Image-pro-plus software. The bone mass around the second molar was analyzed using parameters such as bone volume (BV), tissue volume (TV), and the BV / TV ratio. The experimental results are as follows: Figure 6 As shown in Figure B, WM1119 exhibits a significant therapeutic effect on periodontitis. Subsequently, HE staining was performed, specifically following alveolar bone fixation, decalcification, and sectioning. The level of bone loss was assessed using HE staining, and the results are as follows: Figure 6 As shown in C, WM1119 can effectively alleviate bone loss caused by periodontitis. Following the above-described steps for tissue fluorescence staining, periodontal tissues of mouse periodontitis models treated with WM1119 or DMSO were observed. The staining results and fluorescence quantification are as follows. Figure 6 As shown in D and 6F, the level of inflammation after WM1119 injection was significantly lower than that in the DMSO control group.

[0053] In another embodiment, RAW264.7 cells were grouped and stimulated for 24 hours with RANKL, RANKL+LPS, and RANKL+LPS+WM1119, respectively. Cells were then fixed with paraformaldehyde and subjected to TRAP staining. The staining and quantitative results are as follows. Figure 8 As shown in A and 8C. The experimental procedures for detecting mRNA expression are as described above. The mRNA expression levels of NFATC1, TRAP, and CTSK are as follows. Figure 8 As shown in B, Figure 8 D shows the results of TRAP staining using a TRAP staining kit after alveolar bone fixation, decalcification, and sectioning. Based on the above experimental data, it can be found that KAT6A can promote osteoclast differentiation of raw264.7 cells under inflammatory conditions and the progression of periodontitis. A schematic diagram of the mechanism of action of WM1119 is shown below. Figure 8 As shown in E.

[0054] In one embodiment, this study prepared macrophage membrane-encapsulated WM1119 black phosphorus nanoparticles (WM1119@BPs@MM) ​​and performed related characterization experiments. The preparation process of WM1119@BPs@MM was described in [reference needed]. Figure 10 The specific steps in Figures A and B are as follows: (1) Preparation and characterization of black phosphorus nanosheets (BPs): The preparation method of BPs was published in Biomaterials, 2023, 297:122096 (DOI: 10.1016 / j.biomaterials.2023.122096). Weigh 20 mg of bulk BPs and place them in a small mortar. Add 20 mL of N-methyl-2-pyrrolidone (NMP) and grind for 30 min. Sonicate the solution with probe at 600 W for 3 hours in an ice bath. Centrifuge the solution at 7000 rpm for 20 minutes to remove large BP flakes. Collect the supernatant and centrifuge it further at 12000 rpm for 20 minutes to obtain BPs. Wash the precipitate three times with deionized water, freeze-dry the product and store it for further use. Morphological characterization of BPs: 10 μL of BPs solution was dropped onto a copper grid, dried, allowed to stand for 2 min, excess liquid was removed, and the solution was allowed to air dry naturally. The morphology of BPs was observed and photographed under a transmission electron microscope.

[0055] (2) Extraction of macrophage membranes (MMs): RAW264.7 cells were seeded into 10 cm petri dishes, allowing them to cover the bottom for growth. Cells were pretreated with 1 μg / mL LPS for 24 hours, then trypsinized, harvested, and resuspended in hypotonic lysis buffer at 4°C overnight. The suspension was sonicated at 4°C for 20 min to produce cell debris, which was then removed by gentle centrifugation (3200 g, 5 min) to remove heavy organelles. Cell membranes were then collected by vigorous centrifugation (20000 rcf, 20 min). The membranes were stored at -80°C until use, and then resuspended in isotonic buffer (3 × 10⁻⁶ cells / mL per 300 μL cell membrane). 7 (Number of cells) were collected for further use. Membrane material was stored at -80°C for future research. The BCA protein assay was used to determine the protein content of macrophage membranes. The specific procedure was as follows: Reagent A and Reagent B were prepared at a volume ratio of 50:1 and used immediately; protein standards were diluted to a series of concentrations according to the instructions and set aside; 25 μL of protein standard was added to each well of a sterile 96-well plate; the sample was diluted to a suitable concentration and added to the 96-well plate; 200 μL of working solution was added to each well and mixed; the sealed 96 μL plate was incubated at 37°C for 30 min. The morphological characterization of MMs was performed using the same procedure as for BPs.

[0056] (3) Preparation of WM1119@BPs@MM. The construction method of BPs@WM1119 is as follows: WM1119 was dissolved in DMSO to prepare WM1119 solution. 500ul 50ug / mL BP solution and 500uL 400uM WM1119 solution were incubated with a rotary mixer for 24 hours. Then, the unloaded WM1119 was removed by centrifugation. WM1119@BPs@MM was constructed by extrusion film method. The specific method is as follows: equal amounts of macrophage membrane and BPs@WM1119 are passed through polycarbonate membranes of 800 nm and 400 nm in sequence multiple times, and then subjected to ice bath sonication for 1 h to obtain WM1119@BPs@MM; (4) Encapsulation efficiency and drug loading of WM1119@BPs@MM: The construction method of WM1119@BPs@MM is as described above. Free WM1119 is determined according to the absorption of dialysate at 280 nm. Drug encapsulation efficiency (EE) and drug loading (DLC) were calculated using the following formulas: EE (%) = loading WM1119 / total WM1119 × 100%, DLC (%) = loading WM1119 / (total BPs + total WM1119) × 100%; (5) Sustained release of WM1119@BPs@MM: The release curves of WM1119 in WM1119@BPs@MM were studied at different concentrations of H2O2 (0, 0.1 and 1 mM, respectively). WM1119 (10 mg) dispersed in deionized water (4 mL) was placed in a dialysis bag (MWCO = 12000), and then the dialysis bag was placed in 35 mL of buffer solution (placed in a shaker at 37°C with a shaking rate of 30 × g). At different time intervals, 2 mL of culture medium was taken out for HPLC analysis, and 2 mL of fresh culture medium was refilled into the buffer solution. The cumulative release rate of WM1119 was calculated using the following equation: Cumulative drug release (%) = Mt / M0 100% cumulative drug release, where Mt is the amount of drug released at time t, and M0 is the initial amount of drug in BPs. The release experiment was repeated three times. (4) Characterization indicators of each component of WM1119@BPs@MM: Absorbance was measured using an enzyme-linked immunosorbent assay (ELISA) reader, and the particle size and zeta potential of each component were measured using a particle size potentiometer. Absorbance data are as follows: Figure 9 As shown in Figure A, the absorbance of WM1119 is around 275 nm, the absorbance of BPs is in the range of 400-900 nm, and the absorbance of MM is 256 nm. The absorbance of WM1119@BPs@MM includes three peaks: 256 nm, 275 nm, and 400-900 nm, indicating that MM effectively encapsulates both BPs and WM1119. Particle size data are as follows: Figure 9As shown in Figure B, the particle size of BPs is approximately 150 nm, the particle size of MM is approximately 300 nm, the particle size of WM1119@BPs is 180 nm, and the particle size of WM1119@BPs@MM is approximately 140 nm; the Zeta potential data are as follows. Figure 9 As shown in Figure C, the potentials of BPs are approximately -22 mV, MMs are approximately -18 mV, WM1119@BPs are approximately -22 mV, and WM1119@BPs@MM are approximately -23 mV. Following the immunofluorescence assay described above, the targeting of WM1119@BPs@MM to macrophages was detected, and the results are as follows... Figure 9 As shown in Figure D, the red fluorescence intensity of the BPs@MM@Cy3 group was significantly stronger than that of the BPs@Cy3 group, indicating that MM encapsulation enhanced the targeting of BPs to macrophages.

[0057] (5) The photothermal effect and in vitro anti-inflammatory ability of WM1119@BPs@MM were detected by Western blot. RAW264.7 cells were cultured in petri dishes. DMSO, LPS+DMSO, LPS+WM1119, LPS+WM1119@BPs@MM, and LPS+WM1119@BPs@MM+NIR (photothermal) were added to the blank control, negative control, and experimental groups, respectively. The expression of inflammatory proteins such as iNOS and IL-1β in the five groups of cells was detected and compared with the internal control. Qualitative and quantitative analyses were performed, and the final protein expression levels and quantitative analyses are as follows: Figure 9 As shown in E, the results indicate that WM1119@BPs@MM has the best therapeutic effect on inflammation levels under near-infrared irradiation conditions; (6) Cytotoxicity of WM1119@BPs@MM: The cytotoxicity of WM1119@BPs@MM nanoparticles was detected by the MTT assay. Cells were stored at 1.0 × 10⁶ cells per well. 3 RAW264.7 cells were seeded at a density of 0.5% in 96-well plates and incubated overnight. Then, they were co-cultured with different concentrations of WM1119@BPs nanoparticles (0, 100, 250 μg / mL) for 0, 6, 12, 24, and 36 h. At the sample collection time, 100 μL of detection solution was added to each well. After adding the solution, the wells were incubated in the dark for 30 minutes. Finally, the absorbance at 450 nm was measured using a microplate reader. The MTT assay was used to calculate the cell viability of RAW264.7 cells under near-infrared and non-near-infrared irradiation with different concentration gradients of WM1119@BPs@MM to determine the appropriate concentration of WM1119@BPs@MM for use. Figure 23The calculation results show that, considering the lack of statistically significant differences in cell viability among the groups, the final concentration used for both WM1119@BPs@MM and WM1119@BPs@MM+NIR was 20 μm.

[0058] In another embodiment, this study demonstrated the in vivo anti-inflammatory ability of WM1119@BPs@MM. The specific steps were as follows: (1) A mouse periodontitis model was constructed. After obtaining approval from the Animal Ethics Committee of Central South University, 28 male C57 mice were used in this study. In order to evaluate the therapeutic effect of WM1119@BPs@MM on periodontitis, the experimental animals were randomly divided into 4 groups (N=7 mice / group). The periodontitis model was constructed by ligation with silk thread, and the mice were self-controls. Group 1 (silk thread ligation group): left silk thread ligation / right blank control; Group 2 (WM1119 treatment group): left silk thread ligation + right silk thread ligation followed by direct injection of WM1119; Group 3 (WM1119@BPs@MM treatment group): left silk thread ligation + right silk thread ligation followed by injection of WM1119@BPs@MM. Group 4 (Photothermal therapy group): Left side silk ligation + right side silk ligation followed by injection of WM1119@BPs@MM + infrared irradiation. The silk ligation group had the silk ligation removed after 7 days, and samples were collected after 14 days. The treatment group had silk ligation for 7 days, the silk ligation was removed, and periodontal ligament injection was used for 7 days, and samples were collected after a total of 14 days. The photothermal therapy group received infrared irradiation once every day on the basis of periodontal ligament injection of WM1119@BPs@MM. Samples were then collected, Micro CT analysis was performed, and alveolar bone fixation, decalcification, and sectioning were performed. The bone tissue and inflammation progression level were assessed by HE and IL-1β staining; (2) Micro CT analysis: The hard tissues of the teeth and maxilla were fixed overnight with 10% formalin and analyzed by Micro CT. Three-dimensional reconstruction and image analysis were performed using CTVox and Data viewer software. The distance between the alveolar ridge and the cementoenamel junction was measured using Image-pro-plus software. Bone volume (BV), tissue volume (TV), and the BV / TV ratio were used to analyze the bone mass around the second molar. Staining and analysis results are shown below. Figure 9 As shown in Figure F, it can be seen that WM1119@BPs@MM can further inhibit the progression of periodontitis.

[0059] In some embodiments, relevant parameters of the prepared WM1119@BPs@MM are measured. Specifically, the OD275 values ​​of WM1119 at different concentrations are measured using a UV spectrophotometer, and a standard curve for WM1119 is calculated. Based on the standard curve and the OD275 value of residual WM1119 in the WM1119@BPs@MM solution, the encapsulation efficiency of WM1119 is calculated. The resulting standard curve and encapsulation efficiency are shown below. Figure 21 As shown; 10µL of BPs, MM and WM1119@BPs@MM were dropped onto a copper grid covered with a carbon film, dried at room temperature and then subjected to transmission electron microscopy (TEM) to observe their appearance, morphological characteristics and distribution. The morphological characteristics of WM1119@BPs@MM under the electron microscope are shown below. Figure 22 As shown.

[0060] In a specific embodiment of the present invention, all experimental results were derived from three or more independent replicate experiments. Data are expressed as mean ± standard deviation. SPSS 25 and Prism 9 software were used for statistical analysis. Independent samples t-tests were used to compare data between two groups, and one-way ANOVA was used to compare data among multiple groups. A p-value < 0.05 was considered statistically significant.

[0061] S103: A candidate drug targeting the binding site is obtained by using a computer-aided drug screening method.

[0062] In one embodiment, the computer-aided drug screening method includes: Obtain the binding sites of the KAT6A protein and histone H3 in the complex; Based on the spatial structure of the binding sites of the KAT6A protein and histone H3 in the complex, functional molecules with similar structures were screened from molecular databases. The selected functional molecules are molecularly docked with the binding sites, and the functional molecules are scored. Candidate drugs are obtained by sorting the scores.

[0063] In one embodiment, the functional molecule includes small molecule compounds, peptide analogs, polypeptides, antibodies, and protein analogs; optionally, the small molecule compound includes inorganic small molecule compounds, siRNA, shRNA, dsRNA, microRNA, or antisense nucleic acid. It should be noted that the present invention does not impose any particular limitation on the specific type of the small molecule compound; any small molecule compound that may be used in the computer-aided drug screening method provided by the present invention and may produce corresponding effects falls within the protection scope of the present invention.

[0064] In one embodiment, the method further includes: Obtain systems expressing KATA6 or H3; The effectiveness of the small molecule compound was verified by treating the system containing KATA6 or H3 with the functional molecules obtained from the screening. Screening for functional molecules that inhibit KATA6 or H3 protein expression as candidate drugs; Optionally, the system expressing KATA6 or H3 includes a cellular system, a subcellular system, a tissue system, a solution system, an organ system, and an animal system.

[0065] In one embodiment, in molecular docking, affinity refers to the tightness with which a molecule binds to a receptor. High affinity means a more stable binding, while low affinity indicates a less stable binding. Affinity is typically calculated, for example, by calculating the binding free energy (ΔG) or the binding constant (Kd).

[0066] In molecular docking, affinity depends on the interactions between the molecule and the acceptor, including hydrogen bonds, van der Waals forces, and electrostatic interactions. These interactions collectively determine the binding mode between the molecule and the acceptor, thus affecting affinity.

[0067] To assess affinity, scoring systems or methods are typically used to quantify the interaction between molecules and receptors. These scoring methods are based on different algorithms and physical models and can reflect the binding energy, interaction type, and affinity between molecules and receptors.

[0068] In one embodiment, the mode of screening drugs using computer-aided drug screening technology includes one or more of the following: proteins Small molecule docking, protein Protein docking, protein Nucleic acid testing docking.

[0069] In one embodiment, the protein Small molecule docking refers to the computational simulation process of docking the structures of proteins and small molecules (such as drug molecules) together using specific algorithms and programs. This process can be used to study the interactions between proteins and small molecules, as well as their potential biological functions.

[0070] In protein In small molecule docking, software such as DOCK is commonly used for computational simulation. DOCK is a highly automated drug design software capable of docking small molecule ligands with biomolecular receptors. It employs a fragment-based scoring method, enabling fast and accurate docking. The basic algorithm of DOCK consists of two stages. The first stage is a low-precision stage, primarily searching for a coarse match between the small molecule ligand and the biomolecular receptor. The second stage is a high-precision stage, which considers all side-chain conformations and calculates more precise interaction energies. In the low-precision stage, DOCK randomly translates and rotates the small molecule ligand and performs a certain number of rigid body movements before calculating the interaction energy. After outputting the lowest conformation, it proceeds to the high-precision stage. In the high-precision stage, the program performs further optimization and adjustments to achieve more accurate docking.

[0071] In one embodiment, the protein Protein docking is a computational simulation process that uses specific algorithms and programs to dock the structures of two proteins together. This process can be used to study protein-protein interactions and their potential biological functions.

[0072] In protein RosettaDock is a commonly used docking software for protein docking. It employs a fragment-based scoring method to achieve fast and accurate protein docking. This software can precisely adjust the side-chain conformation during docking and considers various complex interactions, such as hydrogen bonds, ionic bonds, and hydrophobic interactions. RosettaDock's basic algorithm consists of two stages. The first stage is a low-precision stage, which mainly searches for the degree of skeletal shape compatibility between the two proteins. The second stage is a high-precision stage, which considers all side-chain conformations and calculates more precise interaction energies. In the low-precision stage, the program randomly translates and rotates a component of a protein molecule and performs a certain number of rigid body movements, 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 MCMPCCcle cycles: rearranging the conformations and minimizing the interaction energy, using this as the initial starting conformation.

[0073] In one embodiment, the protein Nucleic acid docking refers to the computational simulation process of aligning the structures of proteins and nucleic acids (e.g., DNA or RNA) using specific algorithms and procedures. This process can be used to study the interactions between proteins and nucleic acids, as well as their potential biological functions.

[0074] In protein In nucleic acid docking, software such as NAflex is commonly used for computational simulation. NAflex is a software specifically developed for nucleic acid structure prediction and design, capable of accurate modeling and docking of DNA or RNA molecules. NAflex employs a fragment-based scoring method, enabling fast and accurate docking. It considers various complex interactions, such as hydrogen bonds, ionic bonds, and hydrophobic interactions, and can precisely adjust the side-chain conformation during docking. The basic algorithm of NAflex consists of two stages. The first stage is a low-precision stage, which mainly searches for a coarse match between the protein and nucleic acid. The second stage is a high-precision stage, which considers all side-chain conformations and calculates more precise interaction energies. In the low-precision stage, NAflex randomly translates and rotates the nucleic acid molecule and performs a certain number of rigid body movements before calculating the interaction energy. After outputting the lowest conformation, it enters the high-precision stage. In the high-precision stage, the program performs further optimization and adjustments to achieve more accurate docking.

[0075] In one embodiment, virtual drug screening is an important method in the field of targeted drug design and is also a drug screening method well-known to those skilled in the art. Its process is roughly as follows: First, based on the known structures of drug-target protein complexes, the binding modes of the drug and target protein are studied to identify 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.

[0076] Next, computer-aided drug design methods are used to virtually screen a large number of small molecule compounds. During this process, the binding affinity of the small molecule compounds to the target protein is predicted and evaluated. Typically, small molecules with low binding energies and good shape complementarity are selected as potential drug candidates.

[0077] Finally, the selected candidate drugs were further experimentally validated to confirm their interaction with the target protein and their biological activity.

[0078] In one embodiment, in drug virtual screening, the binding site refers to the region on the target protein that binds to a small molecule compound. To perform receptor-based virtual screening, it is first necessary to determine the binding site of the target protein. This is typically achieved through analysis and study of the target protein's structure.

[0079] Once the binding sites are identified, computer-aided drug design methods can be used to dock compounds from a small molecule library with the target protein. During docking, the computer simulates the interaction between the compound and the binding site and evaluates their binding affinity. Based on the docking results, small molecule compounds with strong binding affinity to the target protein can be screened as potential drug candidates. The determination of binding sites in virtual drug screening is crucial to the success of drug design. Therefore, multiple factors need to be considered when determining binding sites, such as the structural characteristics of the target protein and the binding modes of known ligands. Simultaneously, the binding sites need to be appropriately processed and optimized during virtual screening to improve the accuracy and efficiency of the screening.

[0080] In one embodiment, computer-aided drug screening is a technique that uses computer-aided drug design methods to screen drugs. It can help researchers quickly screen a large number of small molecule compounds for candidate drugs that have strong binding affinity to target proteins and potential pharmacological effects.

[0081] In one embodiment, molecular docking is a method for drug design based on the characteristics of the receptor and the interaction between the receptor and drug molecules. It is a theoretical simulation method that primarily studies intermolecular interactions (such as ligand-receptor interactions) and predicts their binding modes and affinities. This method is widely used in the early stages of drug development to help researchers quickly screen compounds with potential pharmacological effects.

[0082] Molecular docking methods primarily 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. Geometric matching calculations typically employ methods such as grid-based computation and fragment growth, while energy calculations utilize methods such as simulated annealing and genetic algorithms.

[0083] Based on the degree and method of simplification, molecular docking methods can be divided into rigid docking, semi-flexible docking, and flexible docking. In rigid docking, the conformation of the docking molecules remains unchanged during the calculation; only their spatial position and orientation are altered. Semi-flexible docking allows for partial conformational changes during the calculation. Flexible docking allows for even more conformational changes.

[0084] In one embodiment, the molecular libraries used in virtual drug screening mainly include the following: ZINC: Contains over 250 million commercially available compounds for virtual screening of small molecules.

[0085] PubChem: Contains bioactive substances for virtual screening of small molecules.

[0086] DrugBank contains drugs and small molecules for drug design and discovery.

[0087] ChEMBL: Contains small molecules for drug discovery and chemical genomics research.

[0088] ChemDB contains a large number of known small molecules for chemical genomics research and drug discovery.

[0089] HMDB: Contains a large number of known small molecules used for chemical genomics research and drug discovery.

[0090] BindingDB contains a large number of known small molecules for chemical genomics research and drug discovery.

[0091] SMPDB contains a large number of known small molecules for chemical genomics research and drug discovery.

[0092] In addition, there are some commercial databases such as ChemDiv, Enamine, Lifechemicals, Specs, Chembridge, Maybridge, Microsource, Vitas Databases such as M and Interbioscreen are also frequently used for virtual drug screening.

[0093] Figure 2 This invention provides a computer-aided drug screening system based on KAT6A and H3. Specifically, the system includes: The data acquisition unit acquires structural data of KAT6A protein and histone H3. The site determination unit selects the spatial structure of the complex formed by the interaction between the KAT6A protein and the histone H3, and determines the binding sites of the KAT6A protein and histone H3 sites in the complex as the binding sites of the targeted drug. The drug screening unit uses a computer-aided drug screening method to obtain candidate drugs that target the binding site; Optionally, the computer-aided drug screening method includes: Obtain the binding sites of the KAT6A protein and histone H3 in the complex; Based on the spatial structure of the binding sites of the KAT6A protein and histone H3 in the complex, functional molecules with similar structures were screened from molecular databases. The screened functional molecules are molecularly docked with the KAT6A protein or histone H3 and scored to obtain a comprehensive score for the functional molecules. Candidate drugs are obtained by sorting the comprehensive scores. Optionally, the functional molecules include small molecule compounds, peptide analogs, antibodies, polypeptides, and protein analogs; Optionally, the small molecule compound includes inorganic small molecule compounds, siRNA, shRNA, dsRNA, microRNA, or antisense nucleic acid; Optionally, the binding sites of the KAT6A protein and the H3 site in the complex are predicted using bioinformatics prediction methods; Optionally, the bioinformatics prediction method includes molecular docking methods, prediction methods based on sequence and structural information, or multi-scale protein sequence structure comparison and learning methods; Optionally, the method further includes an effectiveness verification unit. The method also includes performing an inhibition binding experiment on the candidate drug. After the candidate drug is mixed with KAT6A protein solution and H3 protein solution, the binding force of KAT6A and H3 after the addition of the candidate drug is calculated using any one or more of the following methods: surface plasmon resonance, biolayer interference, and isothermal titration calorimetry. Candidate drugs that can inhibit the binding of KAT6A and H3 are then screened.

[0094] Figure 3 This invention provides a computer-aided drug screening device based on KAT6A and H3. Specifically, the device includes: The system includes a memory for storing program instructions and a processor for invoking the program instructions, which, when executed, implement the computer-aided drug screening method based on KAT6A and H3 as described above.

[0095] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the computer-aided drug screening method based on KAT6A and H3 as described above.

[0096] The present invention also provides a drug, specifically, the drug being screened by the computer-aided drug screening method based on KAT6A and H3 as described above.

[0097] The present invention also provides an application, which is the computer-aided drug screening method based on KAT6A and H3, the computer-aided drug screening system based on KAT6A and H3, the computer-aided drug screening device based on KAT6A and H3, the computer-readable storage medium, and the application of the drug in the treatment of inflammatory bone resorption-related diseases as described above. In a specific embodiment of the present invention, the inflammatory bone resorption-related disease is periodontitis.

[0098] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0100] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0101] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0102] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0103] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0104] The computer device provided by the present invention has been described in detail above. For those skilled in the art, there will be changes in the specific implementation and application scope based on the ideas of the embodiments of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A computer-aided drug screening method based on KAT6A and H3, characterized in that, The method includes: Obtain KAT6A protein structure and histone H3 structure data; The spatial structure of the complex formed by the interaction between the KAT6A protein and the histone H3 was selected, and the binding sites of the KAT6A protein and the histone H3 in the complex were determined as the binding sites of the targeted drug. Candidate drugs targeting the binding site were obtained using a computer-aided drug screening method. Preferably, the binding site is H3K9; Preferably, the candidate drug is a drug that can inhibit the progression of periodontitis.

2. The computer-aided drug screening method based on KAT6A and H3 according to claim 1, characterized in that, The computer-aided drug screening method includes: Obtain the binding sites of the KAT6A protein and histone H3 in the complex; Based on the spatial structure of the binding sites of the KAT6A protein and histone H3 in the complex, functional molecules with similar structures were screened from molecular databases. The selected functional molecules are molecularly docked with the KAT6A protein or histone H3 and scored to obtain a comprehensive score for the functional molecules. Candidate drugs are obtained by ranking the comprehensive scores.

3. The computer-aided drug screening method based on KAT6A and H3 according to claim 2, characterized in that, The functional molecules include small molecule compounds, peptide analogs, polypeptides, antibodies, and protein analogs; Preferably, the small molecule compound includes inorganic small molecule compounds, siRNA, shRNA, dsRNA, microRNA, or antisense nucleic acid.

4. The computer-aided drug screening method based on KAT6A and H3 according to claim 1, characterized in that, The binding sites of the KAT6A protein and histone H3 in the complex were predicted using bioinformatics prediction methods; the bioinformatics prediction methods include molecular docking methods, prediction methods based on sequence and structural information, or multi-scale protein sequence structure comparison and learning methods.

5. The computer-aided drug screening method based on KAT6A and H3 according to claim 1, characterized in that, The method further includes conducting inhibition binding experiments on the candidate drug. After the candidate drug is mixed with KAT6A protein solution and H3 protein solution, the binding force of KAT6A and H3 after the addition of the candidate drug is calculated using any one or more of the following methods: surface plasmon resonance, biolayer interference, and isothermal titration calorimetry. Candidate drugs that can inhibit the binding of KAT6A and H3 are then screened.

6. A computer-aided drug screening system based on KAT6A and H3, characterized in that, The system includes: The data acquisition unit acquires structural data of KAT6A protein and histone H3. The site determination unit selects the spatial structure of the complex formed by the interaction between the KAT6A protein and the histone H3, and determines the binding sites of the KAT6A protein and histone H3 sites in the complex as the binding sites of the targeted drug. The drug screening unit uses a computer-aided drug screening method to obtain candidate drugs that target the binding site; Preferably, the binding site is H3K9; Preferably, the candidate drug is a drug capable of inhibiting the progression of periodontitis; Preferably, the computer-aided drug screening method includes: Obtain the binding sites of the KAT6A protein and histone H3 in the complex; Based on the spatial structure of the binding sites of the KAT6A protein and histone H3 in the complex, functional molecules with similar structures were screened from molecular databases. The screened functional molecules are molecularly docked with the KAT6A protein or histone H3 and scored to obtain a comprehensive score for the functional molecules. Candidate drugs are obtained by sorting the comprehensive scores. Preferably, the functional molecules include small molecule compounds, peptide analogs, antibodies, polypeptides, and protein analogs; Preferably, the small molecule compound includes inorganic small molecule compounds, siRNA, shRNA, dsRNA, microRNA, or antisense nucleic acid; Preferably, the binding sites of the KAT6A protein and histone H3 in the complex are predicted using bioinformatics prediction methods; Preferably, the bioinformatics prediction method includes molecular docking methods, prediction methods based on sequence and structural information, or multi-scale protein sequence structure comparison and learning methods. Preferably, the method further includes an effectiveness verification unit, and the method further includes performing an inhibition binding experiment test on the candidate drug. After the candidate drug is mixed with KAT6A protein solution and H3 protein solution, the change in the binding force of KAT6A and H3 after the addition of the candidate drug is calculated using any one or more of the following methods: surface plasmon resonance, biolayer interference, and isothermal titration calorimetry, and candidate drugs that can inhibit the binding of KAT6A and H3 are screened.

7. A computer-aided drug screening device based on KAT6A and H3, characterized in that, The device includes: A memory and a processor, wherein the memory is used to store program instructions; and the processor is used to invoke the program instructions, which, when executed, implement claim 1. The computer-aided drug screening method based on KAT6A and H3 as described in any one of the 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements claim 1. The computer-aided drug screening method based on KAT6A and H3 as described in any one of the 5.

9. Any one of the following products: (1) A complex, characterized in that, The complex is formed by the interaction of KAT6A protein and histone H3; (2) A drug screened by a computer-aided drug screening method based on KAT6A and H3 according to any one of claims 1-5; Preferably, the drug also includes additives acceptable in the medical field.

10. The application of a complex, characterized in that, The complex is the complex formed by the interaction of KAT6A protein and histone H3 as described in claim 9, and the application includes: the use of the complex in screening drugs for inhibiting the progression of periodontitis.

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