Computer-aided drug screening method, system or device based on PRPF19, circGFRA3 and NAT10

Abstract

The invention discloses a computer-aided drug screening method, system or device based on PRPF19, circGFRA3 and NAT10, and creatively provides a brand-new computer-aided drug screening method, system and device based on PRPF19, circGFRA3 and NAT10 and a computer readable storage medium for the field for the first time. The invention provides an efficient, accurate and rapid screening method for research and development of new drugs for promoting healing of diabetic wounds, and has a wide application prospect in the technical field of screening of new drugs for promoting healing of diabetic wounds.

Description

Technical Field

[0001] The present invention belongs to the technical field of computer-assisted drug screening, and specifically relates to a computer-assisted drug screening method, system or device based on PRPF19, circGFRA3 and NAT10. Background Art

[0002] Diabetic wounds are a common and serious complication of diabetes and a major cause of disability and mortality. The wound healing process consists of four distinct phases: hemostasis, inflammation, proliferation, and remodeling. The remodeling function is impaired during wound healing in patients with diabetes, manifested by prolonged inflammation and delayed tissue regeneration. Macrophage polarization is critical for the regulation of inflammation during wound healing. Macrophages exist in two main functional states: pro-inflammatory M1 macrophages, which secrete cytokines such as IL-1β and TNF-α, and anti-inflammatory M2 macrophages, which promote tissue repair and inflammation resolution. In diabetic wounds, persistently elevated blood glucose favors the dominance of M1 macrophages, inhibiting their conversion to M2 macrophages, thereby prolonging the inflammatory phase. This dysregulation emphasizes the need for therapeutic strategies to promote M2 polarization of macrophages in order to improve the outcome of diabetic wound healing.

[0003] Difficult-to-heal diabetic wounds are a difficult disease to treat clinically. 25% of diabetic patients have diabetic foot ulcers throughout their lives, and 20% of them must undergo amputation due to severe ulceration and infection complicated by improper care or treatment. The 5-year survival rate of patients with diabetic foot amputation is almost zero. At present, in addition to conventional therapies, new biological technologies such as stem cell technology, exogenous growth factor technology, and gas therapy have a certain degree of effect on improving the local microenvironment of the epidermis, reducing inflammatory reactions, and increasing the rate of wound repair. However, due to the limitations of equipment and technology, the popularity rate is low and has not been widely used in clinical practice. Gene therapy and AGEs removal technology, which are still in the exploratory stage, cannot effectively control the repair stability and immune rejection reaction, and the adverse reactions of changing the local microenvironment are also unclear. It can be seen that the existing treatment methods have limited effects in the treatment of diabetic wounds. The development of new drugs can target specific targets to improve the effectiveness of treatment. At present, this field urgently needs to develop an efficient screening method for new drugs that promote diabetic wound healing. Summary of the invention

[0004] In order to overcome the technical problem that the existing treatment methods in the field have limited effects in the treatment of diabetic wounds, the present invention has developed a new computer-assisted drug screening method, system or device based on PRPF19, circGFRA3 and NAT10. The drugs screened by the screening method provided by the present invention can effectively promote diabetic wound healing.

[0005] The present invention adopts the following technical solutions to achieve the above-mentioned invention objectives:

[0006] The first aspect of the present invention provides a computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10, the screening method comprising:

[0007] Obtain circGFRA3 and PRPF19 protein data, or circGFRA3 and NAT10 protein data;

[0008] Selecting the spatial structure of the circGFRA3 and PRPF19 protein complex, or the spatial structure of the circGFRA3 and NAT10 protein complex, and determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex as the binding site of the targeted drug;

[0009] A computer-assisted drug screening method is used to obtain a candidate drug targeting the binding site, wherein the computer-assisted drug screening method comprises:

[0010] Obtaining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex;

[0011] Based on the spatial structure of the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the spatial structure of the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex, screening small molecule compounds with similar structures in a molecular database;

[0012] The screened small molecule compounds are subjected to molecular docking with NAT10 protein to calculate the affinity or binding energy of the small molecule compounds targeting the receptor NAT10 protein to obtain the score of each small molecule compound, and the candidate drugs for promoting diabetic wound healing are obtained by ranking according to the score.

[0013] Furthermore, the method for determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex comprises:

[0014] Construct n truncated expression mutants of PRPF19 or NAT10, where n is a natural number greater than or equal to 1;

[0015] Based on the n truncated expression mutants, RNA immunoprecipitation experiments were performed to obtain the key regions for the interaction between circGFRA3 and PRPF19 or NAT10;

[0016] The spatial structure of the key region of the interaction between circGFRA3 and PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex;

[0017] The spatial structure of the key region of the interaction between circGFRA3 and NAT10 is the binding site of circGFRA3 and NAT10 proteins in the circGFRA3 and NAT10 protein complex.

[0018] Furthermore, the spatial conformation formed by the interaction between C-113 of circGFRA3 and Arg-190 of PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex;

[0019] The spatial conformation formed by the interaction between C-113 of circGFRA3 and Lys-378 of NAT10 is the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex.

[0020] Furthermore, the screening method further comprises:

[0021] Obtain diabetic wound animal model or diabetic wound cell model;

[0022] The diabetic wound animal model or diabetic wound cell model is treated with the screened candidate drug for promoting diabetic wound healing to verify the effectiveness of the candidate drug for promoting diabetic wound healing.

[0023] The second aspect of the present invention provides a screening system for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10, the screening system comprising:

[0024] A data acquisition unit, which acquires circGFRA3 and PRPF19 protein data, or circGFRA3 and NAT10 protein data;

[0025] a site determination unit, which selects the spatial structure of the circGFRA3 and PRPF19 protein complex or the spatial structure of the circGFRA3 and NAT10 protein complex, and determines the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex as the binding site of the targeted drug;

[0026] The drug screening unit adopts a computer-assisted drug screening method to obtain a candidate drug targeting the binding site, wherein the computer-assisted drug screening method comprises:

[0027] Obtaining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex;

[0028] Based on the spatial structure of the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the spatial structure of the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex, screening small molecule compounds with similar structures in a molecular database;

[0029] The screened small molecule compounds are subjected to molecular docking with NAT10 protein to calculate the affinity or binding energy of the small molecule compounds targeting the receptor NAT10 protein to obtain the score of each small molecule compound, and the candidate drugs for promoting diabetic wound healing are obtained by ranking according to the score.

[0030] Furthermore, the method for determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex comprises:

[0031] Construct n truncated expression mutants of PRPF19 or NAT10, where n is a natural number greater than or equal to 1;

[0032] Based on the n truncated expression mutants, RNA immunoprecipitation experiments were performed to obtain the key regions for the interaction between circGFRA3 and PRPF19 or NAT10;

[0033] The spatial structure of the key region of the interaction between circGFRA3 and PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex;

[0034] The spatial structure of the key region of the interaction between circGFRA3 and NAT10 is the binding site of circGFRA3 and NAT10 proteins in the circGFRA3 and NAT10 protein complex;

[0035] Optionally, the screening system further comprises: a drug effectiveness verification unit for obtaining a diabetic wound animal model or a diabetic wound cell model; treating the diabetic wound animal model or the diabetic wound cell model with the screened candidate drug for promoting diabetic wound healing to verify the effectiveness of the candidate drug for promoting diabetic wound healing.

[0036] The third aspect of the present invention provides a computer device for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10, the computer device comprising:

[0037] A memory and a processor, wherein the memory is used to store program instructions; the processor is used to call the program instructions, and when the program instructions are executed, the computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10 as described in the first aspect is implemented.

[0038] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10 as described in the first aspect is implemented.

[0039] A fifth aspect of the present invention provides any of the following products:

[0040] (1) A diabetic wound healing promoting drug, wherein the diabetic wound healing promoting drug is obtained by screening according to the computer-assisted drug screening method for screening diabetic wound healing promoting drugs based on PRPF19, circGFRA3 and NAT10 as described in the first aspect;

[0041] (2) A pharmaceutical composition comprising circGFRA3 or a circGFRA3 promoter, wherein the sequence of circGFRA3 is shown in SEQ ID NO: 1.

[0042] A sixth aspect of the present invention provides any of the following applications:

[0043] (1) Use of circGFRA3 or a circGFRA3 promoter in the preparation of a drug for promoting diabetic wound healing, wherein the sequence of circGFRA3 is shown in SEQ ID NO: 1;

[0044] (2) Use of PRPF19 or a PRPF19 promoter in the preparation of a drug for promoting diabetic wound healing;

[0045] (3) Use of NAT10 or a NAT10 inhibitor in the preparation of a medicament for promoting diabetic wound healing.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The present invention is the first to provide a new computer-assisted drug screening method, screening system, screening device and computer-readable storage medium based on PRPF19, circGFRA3 and NAT10 in the art. The present invention provides an efficient, accurate and rapid screening method for the development of new drugs to promote diabetic wound healing, and has broad application prospects in the technical field of new drug screening to promote diabetic wound healing. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 : A schematic flow chart of a computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10 provided in an embodiment of the present invention;

[0049] Figure 2 : Schematic diagram of a screening system for promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10 provided in an embodiment of the present invention;

[0050] Figure 3 : A schematic diagram of a computer device for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10 provided in an embodiment of the present invention;

[0051] Figure 4: Characterization of MSC-derived exosomes, including: A: Electron microscopy observation of the shape of exosomes after silver staining; B: Transmission electron microscopy observation of the morphology of Exos and Nr-CWS-Exos; C, D: NTA method was used to determine the particle size and particle concentration of Exos and Nr-CWS-Exos; E: Western blotting detection of Exos and Nr-CWS-Exos specific surface markers (Alix, TSG101, CD9); F: Laser scanning confocal microscopy was used to verify the uptake of Nr-CWS-Exos by THP-1, and the exosomes and cell nuclei were stained red and blue, respectively. GJ figure: flow cytometry was used to detect the percentage of macrophage polarization after exosome treatment, and statistical graphs were drawn. K figure: the correlation of macrophage polarization was verified by Western blotting. LM figure: Elisa method was used to verify the relevant indicators. N = 3 in each group, *p < 0.1, **p < 0.01, ***p < 0.001, ****p < 0.0001;

[0052] Figure 5 : Macrophages are polarized in vivo, including AB: Construction of mouse air pouch model; CF: Flow cytometry was used to detect the polarization ratio of macrophages in the mouse air pouch model; G, H: Elisa method was used to detect inflammatory factors in secretions; I: Western blotting was used to detect the polarization of macrophages in secretions; J: Statistical chart of skin thickness on the 14th day of wound healing; K: Schematic diagram of the construction of diabetic mice; L: Wound pictures of 7-day-old and 14-day-old mice; O, P: HE and Masson results of 7-day-old and 14-day-old mice; M, N: Flow cytometry was used to detect the polarization of macrophages; Q: Fluorescence double staining was used to detect the changes of macrophage markers iNOS and CD163, N=3 in each group, *p<0.1, **p<0.01, ***p<0.001, ****p<0.0001;

[0053] Figure 6:CircGFRA3 is upregulated in Nr-CWS-Exos and regulates macrophage M1 to M2 polarization in vitro, where A: Arraystar Human circRNAs Microarray heat map showing differentially expressed LncRNAs in three samples of hUCMSCs-Exos, Cut off is Log2 (fold change)>1 or <-1.0, P value <0.05; B: Scatter plot of differentially expressed circRNAs, Cut off is Log2 (fold change)>1 or <-1, P value <0.05; C: Differences in circRNAs between the hyperglycemia group and the treatment group; D: Source and circularization verification of circGFRA3; E: Circularization site verification of circGFRA3 by sanger sequencing; F: Detection of circGFRA3 and GFRA3 by adding RNase R mRNA expression level; G: Expression of GFRA3 and circGFRA3 over time; H: Distribution of circGFRA3 in cells; I: Nuclear localization of circGFRA3 identified by confocal microscopy; JM: Flow cytometry showed that circGFRA3 overexpression had a proportional effect on macrophage polarization; N: Western blotting verified the correlation between circGFRA3 overexpression and macrophage polarization; O: Western blotting detected the effect of circGFRA3 low expression on macrophages; P, Q: Flow cytometry detected the polarization of macrophages with low circGFRA3 expression; R: Detection of mRNA levels of related genes in cells; S: Detection of secretion of related inflammatory factors, N = 3 per group, *p < 0.1, **p < 0.01, ***p < 0.001, ****p < 0.0001; Figure 7:CircGFRA3 interacts with NAT10 in THP-1 cells, where A: RNA immunoprecipitation (RIP) experiment verifies the association; B: RNA pull down experiment silver staining results; C: NAT10 protein spectrum screening and peptide scoring; D, E: RNA immunoprecipitation experiment with anti-NAT10 antibody confirmed the interaction between circGFRA3 and NAT10 in THP-1 / 293T cells, MW, molecular weight; F: Confocal microscopy observation of co-localization of circGFRA3 and NAT10, scale: 5μm; G: Western blotting experiment verifies the knockout efficiency of NAT10; H: The binding ability of NAT10 mutants to circGFRA3 was verified by RIP experiment; I: The protein structure was processed by 3D convolutional neural network (CNN) to predict the protein pocket of NAT10, N = 3 per group, *p < 0.1, **p < 0.01, ***p < 0.001, ****p < 0.0001;

[0054] Figure 8 : CircGRAF3 promotes NAT10 ubiquitination and degradation, where A: Western blotting to detect the protein level of NAT10 in THP-1 and 293T cells with circGFRA3 overexpression or knockdown; B: Western blotting to detect the protein level of NAT10 in THP-1 and 293T cells; C: The protein level of NAT10 in THP-1 and 293T cells with circGFRA3 overexpression after MG132 (20 μM) treatment for 12 h; D, E: Co-IP experiments verified the binding of NAT10 and PRPF19 in 293T and THP-1 cells; F, G: Observation of the protein levels of NAT10 and PRPF19 after overexpression in THP-1 and 293T cells; H: The expression of NAT10 protein within 0-24 h after transfection of PRPF19 protein with or without Flag tag in THP-1 cells and addition of CHX; I: Transfection of small interfering gene PRPF19 was performed to observe the stability of NAT10 protein; J, K: Effect of exogenous PRPF19 on the stability of endogenous NAT10 protein in THP-1 and 293T cells; L, M: Exogenous PRPF19 can promote the ubiquitination of exogenous NAT10 protein in THP-1 and 293T cells; O: Protein level of NAT10 in THP-1 cells overexpressing PRPF19 or PRPF19 mutant (PRPF19ΔRing); P: Protein ubiquitination sites were detected in THP-1 and 293T cells, N=3 per group, *p<0.1, **p<0.01, ***p<0.001, ****p<0.0001;

[0055] Fig. 9 : CircGFRA3 enhances the interaction between PRPF19 and NAT10, where A and B: RNA immunoprecipitation experiments using anti-PRPF19 antibodies confirmed the interaction between circGFRA3 and PRPF19 in THP-1 / 293T cells, MW, molecular weight; C: Co-localization of circGFRA3 and PRPF19 observed by confocal microscopy, scale bar: 5μm; D and E: Immunoprecipitation detection of NAT10 ubiquitination modification in THP-1 and 293T cells; F: CircGFRA3 was overexpressed in the IP experiment, and RNsae were added R and A observed protein changes; G, H: knockout of PRPF19 and mutation of circGFRA3 reduced the binding of NAT10 and circGFRA3 in THP-1 and 293T cells; I: 3D convolutional neural network (CNN) was used to process protein structure and predict PRPF19 protein pocket; J: protein-nucleic acid docking scheme and protein pocket effect were used to predict potential sites of PRPF19; K: molecular docking structure diagram, N = 3 in each group, *p < 0.1, **p < 0.01, ***p < 0.001, ****p < 0.0001;

[0056] Fig.10Figure 1: NAT10, as a downstream mediator of circGRAF3, regulates the stability of HK1 mRNA through ac4C modification, where AC: the position and proportion distribution of ac4C modification in overexpressed NAT10 and normal histone coding genes; D: volcano plot of NAT10-mRNA binding region; E: sequence logo of ac4C peak enrichment motif determined by HOMER software; F: database screening of related genes and prediction of their enrichment scores; G: statistical plot of enrichment scores and prediction scores of different genes; H: RNA expression and ac4C peak map near the 5'-UTR codon of human target genes, downloaded from the reference genome; I: after knocking out NAT10, the binding and modification of NAT10 to mRNA HK1 were detected; K: RNA pulldown experiment using potential wild-type binding sequence of HK mRNA, Western blotting to detect NAT10 protein content, GAPDH as nonspecific control; L: RNA pull using potential wild-type binding or mutant sequences down experiment; M: After knocking out NAT10, the regulation of HK1 by different mutants was determined by luciferase; N: mRNA enrichment after NAT10 overexpression; J: 5'UTR region related sequence diagram; O, P: Changes in RNA content over time after adding actinomycin D; Q: Construction of truncations based on NAT10 domains; R: Western blotting verified the truncations of NAT10; S: Verification of the binding of different truncations to mRNAHK1, N = 3 per group, *p < 0.1, **p < 0.01, ***p < 0.001, ****p < 0.0001;

[0057] Fig.11:CircGFRA3 regulates cellular glycolysis through the NAT10 / HK1 axis, where A and G: overexpression and knockdown of circGFRA3, Western blotting to detect four key glycolytic proteins HK1, PKM2, GLUT1, and LDHA; B and G: glycolytic capacity determination, cell glucose uptake capacity statistics; C and H: glycolytic capacity determination, cell metabolite statistics; D and I: hippocampal cell metabolic rate measurement, ECAR statistics; E and J: hippocampal cell metabolic rate measurement, OCR statistics; K: simultaneous knockdown of NAT10 and circGFRA3, determination of cellular glucose uptake capacity; L: simultaneous knockdown of NAT10 and circGFRA3, determination of cellular glucose uptake capacity; M: hippocampal cell metabolic rate measurement, ECAR statistics; N: hippocampal cell metabolic rate measurement, OCR statistics; O: when NAT10 and circGFRA3 were knocked down at the same time, Western Four key glycolytic proteins HK1, PKM2, GLUT1 and LDHA were detected by blotting, N = 3 per group, *p < 0.1, **p < 0.01, ***p < 0.001, ****p < 0.0001;

[0058] Fig.12 : NAT10 participates in circGRAF3 overexpression through HK1 to regulate the polarization of macrophages from M1 to M2. AD: circGFRA3, HK1, and NAT10 were overexpressed simultaneously, and macrophage polarization was detected by flow cytometry, and flow cytometry statistics were performed; E: Western blotting was used to detect the content of macrophage-related proteins; F, G: qPCR was used to detect the content of Arg-1 mRNA and iNOS in cells; HK: Elisa method was used to detect related inflammatory factors (iNOS, IL-1β, IL-10, TNF-α), N=3 per group, *p<0.1, **p<0.01, ***p<0.001, ****p<0.0001;

[0059] Fig.13 :The effect of circGFRA3 on diabetic wound healing by regulating Nr-CWS exosomes through NAT10 in vivo, wherein, Figure A: Experimental flow chart of diabetic mice; Figure B: Wound healing statistics; Figure C: Wound injury pictures of 7-day-old and 14-day-old mice; Figures D and E: Statistics of skin thickness of mice on days 7 and 14, scale bar: 100μm; Figure F: HE and Masson staining of wounds of mice on days 7, scale bar: 100μm; Figure G: iNOS and CD163 fluorescence double staining verified the polarized distribution of macrophages in the wounds of 7-day-old mice, scale bar: 100μm, N=3 in each group, *p<0.1, **p<0.01, ***p<0.001, ****p<0.0001. DETAILED DESCRIPTION

[0060] The present invention will be further described below in conjunction with specific embodiments, which are only used to explain the present invention and are not to be construed as limiting the present invention. It will be appreciated by those of ordinary skill in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and purposes of the present invention. Reagents and raw materials used in the present invention are readily available to those of ordinary skill in the art, and unless otherwise specified, may be obtained from commercial sources, and the experimental methods for which specific conditions are not specified in the present invention are usually tested under conventional conditions or under conditions recommended by manufacturers.

[0061] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. In some of the processes described in the specification and claims of the present invention and the above-mentioned drawings, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or executed in parallel. The serial numbers of the operations, such as S101, S102, S103, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel.

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0063] Figure 1 The present invention provides a computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10. Specifically, the screening method comprises the following steps:

[0064] S101: Obtain circGFRA3 and PRPF19 protein data, or circGFRA3 and NAT10 protein data;

[0065] In some embodiments, the circGFRA3 (hsa_circ_0074097) is derived from exon 4 of the GFRA3 gene, with a length of 313 nucleotides, and its corresponding sequence is as follows: ACTCAGACCTCTGCCTCAAGTTTGCCATG CTGTGTACTCTCAATGACAAGTGTGACCGGCTGCGCAAGGCCTACGGGGAGGCGTGCTCCGGGCCCCACTGCCAGCGCCACGTCTGCCTCAGGCAGCTGCTCACTTTCTTCGAGAAGGCCGCCGAGCCCCACGCGCAGGGCCTGCTACTGTGCCCATGTGCCCCCAACGACCGGGGCTGCGGGGAGCGCCGGCGCAACACCATCGCCCCCAACTGCGCGCTGCCGCCTGTGGCCCCCAACTGCCTGGAGCTGCGGCGCCTCTGCTTCTCCGACCCGCTTTGCAG (SEQ ID NO: 1).

[0066] In some embodiments, the full name of PRPF19 is pre-mRNA processing factor 19 [Homosapiens (human)], and its corresponding Gene ID in NCBI is 27339. Its corresponding detailed information (including sequence information, etc.) can be obtained at https: / / www.ncbi.nlm.nih.gov / gene / .

[0067] In some embodiments, the full name of NAT10 is N-acetyltransferase 10 [Homo sapiens (human)], and its corresponding Gene ID in NCBI is 55226. Its corresponding detailed information (including sequence information, etc.) can be obtained at https: / / www.ncbi.nlm.nih.gov / gene / .

[0068] In some embodiments, the diabetic wound refers to any type of skin injury or ulcer caused by diabetes, including but not limited to: diabetic wound surface.

[0069] In the present invention, it is demonstrated for the first time that circGFRA3 promotes macrophage polarization to M2 phenotype, thereby promoting wound healing; there is an interaction between circGFRA3 and NAT10; circGFRA3 promotes ubiquitination and degradation of NAT10; circGFRA3 promotes macrophage polarization to M2 phenotype, thereby promoting wound healing by enhancing the interaction between PRPF19 and NAT10, that is, the interaction relationship between PRPF19 / circGFRA3 / NAT10 is discovered for the first time, and is confirmed by scientific experiments. Based on this, the present invention provides an effective computer-assisted drug screening method for the art for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10.

[0070] S102: selecting the spatial structure of the circGFRA3 and PRPF19 protein complex or the spatial structure of the circGFRA3 and NAT10 protein complex, and determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex as the binding site of the targeted drug;

[0071] In some embodiments, the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex can be determined by nucleic acid-protein docking or any other method known in the prior art that can be used to determine the interaction site between nucleic acid and protein.

[0072] In some embodiments, the nucleic acid-protein docking refers to a computational simulation process of docking the structures of proteins and nucleic acids (such as DNA or RNA) together through certain algorithms and programs. This process can be used to study the interactions between proteins and nucleic acids, as well as possible biological functions.

[0073] In protein-nucleic acid docking, software such as NAflex is usually used for computational simulation. NAflex is a software developed specifically for nucleic acid structure prediction and design, which can achieve accurate modeling and docking of DNA or RNA molecules. NAflex software uses a fragment-based scoring method to achieve fast and accurate docking. It takes into account a variety of complex interactions, such as hydrogen bonds, ionic bonds, hydrophobic interactions, etc., and can achieve precise adjustment of side chain conformations during docking. The basic algorithm of NAflex software includes two stages. The first stage is the low-precision stage, which mainly searches for rough matches between proteins and nucleic acids. The second stage is the high-precision stage, in which all side chain conformations are considered and more accurate interaction energies are calculated. In the low-precision stage, NAflex software randomly translates and rotates nucleic acid molecules, performs a certain number of rigid body moves, and then calculates the interaction energy. After outputting the lowest conformation, it enters the high-precision stage. In the high-precision stage, the program will perform more optimization and adjustments to achieve more accurate docking.

[0074] In some embodiments, the method for determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex comprises:

[0075] Construct n truncated expression mutants of PRPF19 or NAT10, where n is a natural number greater than or equal to 1;

[0076] Based on the n truncated expression mutants, RNA immunoprecipitation experiments were performed to obtain the key regions for the interaction between circGFRA3 and PRPF19 or NAT10;

[0077] The spatial structure of the key region of the interaction between circGFRA3 and PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex;

[0078] The spatial structure of the key region of the interaction between circGFRA3 and NAT10 is the binding site of circGFRA3 and NAT10 proteins in the circGFRA3 and NAT10 protein complex.

[0079] In some embodiments, the spatial conformation formed by the interaction between C-113 of circGFRA3 and Arg-190 of PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex;

[0080] The spatial conformation formed by the interaction between C-113 of circGFRA3 and Lys-378 of NAT10 is the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex.

[0081] S103: Using a computer-assisted drug screening method to obtain a candidate drug targeting the binding site, the computer-assisted drug screening method comprising:

[0082] Obtaining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex;

[0083] Based on the spatial structure of the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the spatial structure of the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex, screening small molecule compounds with similar structures in a molecular database;

[0084] In some embodiments, the small molecule compound includes, but is not limited to, an inorganic small molecule compound, a protein analog, a nucleic acid analog, a polypeptide, an antibody, a siRNA, a shRNA, a dsRNA, a microRNA or an antisense nucleic acid.

[0085] It should be noted that the present invention has no particular restrictions on the specific types of the small molecule compounds, and any small molecule compounds that may be used in the computer-assisted drug screening method provided by the present invention and may produce corresponding effects fall within the protection scope of the present invention.

[0086] The screened small molecule compounds are subjected to molecular docking with NAT10 protein to calculate the affinity or binding energy of the small molecule compounds targeting the receptor NAT10 protein to obtain the score of each small molecule compound, and the candidate drugs for promoting diabetic wound healing are obtained by ranking according to the score.

[0087] In some embodiments, small molecule compounds with strong affinity or binding energy targeting the receptor NAT10 protein are screened as candidate drugs for promoting diabetic wound healing.

[0088] In some embodiments, during the molecular docking process, affinity refers to the tightness of the molecule binding to the receptor. High affinity means that the binding is more stable, while low affinity means that the binding is less stable. Affinity is usually obtained by calculation, for example, by calculating the binding free energy (ΔG) or the binding constant (Kd).

[0089] In some embodiments, during the molecular docking process, affinity depends on the interaction between the molecule and the receptor, including hydrogen bonding, van der Waals forces, electrostatic interactions, etc. These interactions jointly determine the binding mode between the molecule and the receptor, thereby affecting the affinity. In order to evaluate the affinity, some scoring systems or scoring methods are usually used to quantify the interaction between the molecule and the receptor. These scoring methods are based on different algorithms and physical models, which can reflect the binding energy, interaction type and affinity between the molecule and the receptor.

[0090] In some embodiments, the mode of drug screening using computer-assisted drug screening technology may include any one or more of the following modes depending on the type of small molecule compound (inorganic small molecule compound, protein analog, nucleic acid analog, polypeptide, antibody, siRNA, shRNA, dsRNA, microRNA or antisense nucleic acid, etc.): protein-small molecule docking, protein-protein docking, protein-nucleic acid docking.

[0091] Specifically, 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 through certain algorithms and programs. This process can be used to study the interaction between proteins and small molecules, as well as possible biological functions. Software such as DOCK is usually used for computational simulation. DOCK is a drug design software with a high degree of automation that can achieve docking between small molecule ligands and biomacromolecule receptors. It uses a fragment-based scoring method to achieve fast and accurate docking. The basic algorithm of DOCK software includes two stages. The first stage is the low-precision stage, which mainly searches for a rough match between small molecule ligands and biomacromolecule receptors. The second stage is the high-precision stage, in which all side chain conformations are considered and more accurate interaction energy is calculated. In the low-precision stage, DOCK software will randomly translate and rotate small molecule ligands, perform a certain number of rigid body moves, and then calculate the interaction energy. After outputting the lowest conformation, it enters the high-precision stage. In the high-precision stage, the program will perform more optimization and adjustments to achieve more accurate docking.

[0092] Specifically, the protein-protein docking refers to the computational simulation process of docking the structures of two proteins together through certain algorithms and programs. This process can be used to study the interactions between proteins and possible biological functions. RosettaDock is a commonly used protein-protein docking software that uses a fragment-based scoring method to achieve fast and accurate protein docking. The software can achieve precise adjustment of side chain conformations during docking and take into account a variety of complex interactions, such as hydrogen bonds, ionic bonds, hydrophobic interactions, etc. The basic algorithm of RosettaDock includes two stages. The first stage is the low-precision stage, which mainly searches for the degree of adaptation of the skeleton shapes between the two proteins. The second stage is the high-precision stage, in which all side chain conformations are considered and more accurate interaction energy is calculated. In the low-precision stage, the program randomly translates and rotates a component of a protein molecule, performs a certain number of rigid body moves, and then calculates the interaction energy. After outputting the lowest conformation, it enters the high-precision stage. In the high-precision stage, the program performs 50 MCMPCycles: rearranges the conformation and minimizes the interaction energy, which is used as the initial starting conformation.

[0093] Specifically, the protein-nucleic acid docking refers to the computational simulation process of docking the structures of proteins and nucleic acids (such as DNA or RNA) together through certain algorithms and programs. This process can be used to study the interactions between proteins and nucleic acids, as well as possible biological functions. Software such as NAflex is usually used for computational simulation. NAflex is a software specially developed for nucleic acid structure prediction and design, which can achieve accurate modeling and docking of DNA or RNA molecules. NAflex software uses a fragment-based scoring method to achieve fast and accurate docking. It takes into account a variety of complex interactions, such as hydrogen bonds, ionic bonds, hydrophobic interactions, etc., and can achieve precise adjustment of side chain conformations during docking. The basic algorithm of NAflex software includes two stages. The first stage is the low-precision stage, which mainly searches for rough matches between proteins and nucleic acids. The second stage is the high-precision stage, in which all side chain conformations are considered and more accurate interaction energy is calculated. In the low-precision stage, NAflex software randomly translates and rotates nucleic acid molecules, performs a certain number of rigid body moves, and then calculates the interaction energy. After outputting the lowest conformation, it enters the high-precision stage. In the high-precision stage, the program will perform more optimization and adjustments to achieve more accurate docking.

[0094] In some embodiments, computer-aided drug screening is a technology that uses computer-aided drug design methods to screen drugs. It can help researchers quickly screen candidate drugs that have strong binding ability with target proteins and potential efficacy from a large number of small molecule compounds.

[0095] In one embodiment, molecular docking is a method for drug design based on the characteristics of receptors and the interaction between receptors and drug molecules. It mainly studies the interaction between molecules (such as ligands and receptors) and predicts its binding mode and affinity. This method is widely used in the early stages of drug development and can help researchers quickly screen out compounds with potential efficacy. The molecular docking method mainly focuses on spatial matching and energy matching. Spatial matching refers to the geometric complementarity between drug molecules and receptor proteins, while energy matching refers to the minimization of interactions between drug molecules and receptor proteins. For the calculation of geometric matching, grid point calculation, fragment growth and other methods are usually used, while energy calculation uses simulated annealing, genetic algorithms and other methods. According to the degree and method of simplification, molecular docking methods can be divided into rigid docking, semi-flexible docking and flexible docking. In the rigid docking method, the molecular conformation involved in the docking does not change during the calculation process, only the spatial position and posture of the molecule are changed. Semi-flexible docking allows some conformations to change during the calculation. Flexible docking allows more conformational changes.

[0096] In one embodiment, the molecular libraries used in drug virtual screening are mainly the following: ZINC: contains more than 250 million commercially available compounds for small molecule virtual screening; PubChem: contains bioactive substances for small molecule virtual screening; DrugBank: contains drugs and small molecules for drug design and discovery; ChEMBL: contains small molecules for drug discovery and chemical genomics research; ChemDB: contains a large number of known small molecules for chemical genomics research and drug discovery; HMDB: contains a large number of known small molecules for chemical genomics research and drug discovery; BindingDB: contains a large number of known small molecules for chemical genomics research and drug discovery; SMPDB: contains a large number of known small molecules for chemical genomics research and drug discovery. In addition, there are some commercial databases such as ChemDiv, Enamine, Lifechemicals, Specs, Chembridge, Maybridge, Microsource, Vitas-M and Interbioscreen, which are also often used for drug virtual screening.

[0097] In some embodiments, the screening method further comprises:

[0098] Obtain diabetic wound animal model or diabetic wound cell model;

[0099] The diabetic wound animal model or diabetic wound cell model is treated with the screened candidate drug for promoting diabetic wound healing to verify the effectiveness of the candidate drug for promoting diabetic wound healing.

[0100] In some embodiments, the animal model is not particularly limited and can be constructed using conventional construction methods well known to those skilled in the art. The animals include but are not limited to: mice, rats, guinea pigs, rabbits, pigs, chickens, pigeons, monkeys, dogs and other animals.

[0101] In a specific embodiment, the present invention demonstrates that Nr-CWS-Exos (Nocardia rubrum cell wall skeleton (Nr-CWS)-treated MSC-derived exosomes) inhibit inflammatory response by enhancing the M2-M1 macrophage polarization ratio in vitro.

[0102] Specifically, to investigate the effect of Nr-CWS-treated exosomes (Nr-CWS-Exos) on macrophage polarization, we first isolated exosomes from the conditioned medium of untreated mesenchymal stem cells (MSCs) and Nr-CWS-treated MSCs. Transmission electron microscopy and nanoparticle tracking analysis (NTA) confirmed the characteristic morphology and size of exosomes ( Figure 4 AD). Western blotting further verified the presence of exosome markers Alix, TSG101, and CD9 ( Figure 4 E). After 24 h of co-culture, macrophages showed significant uptake of the treated exosomes ( Figure 4 F). The particle size, morphology, and protein expression levels between untreated exosomes (Exos) and Nr-CWS-Exos were consistent, indicating that Nr-CWS treatment did not alter exosome secretion from hUVECs. These results confirmed the successful isolation of exosomes. Next, the polarization state of macrophages treated with low glucose (LG), high glucose (HG), Exos, and Nr-CWS-Exos was investigated. Compared with the HG and Exos treatment groups, the number of CD206-positive (M2) macrophages in the Nr-CWS-Exos group was significantly higher, while the number of CD86-positive (M1) macrophages showed an opposite trend ( Figure 4 GJ). In addition, the expression of iNOS protein associated with M2 macrophage function was significantly increased in the HG+Nr-CWS-Exos group, while the expression of Arg-1 associated with M1 macrophages showed the opposite pattern ( Figure 4K). We further evaluated the relative gene expression levels of anti-inflammatory and pro-inflammatory markers using qRT-PCR. Compared with the LG and HG groups, the expression of pro-inflammatory genes (iNOS, IL-1β, and TNF-α) in the Exos and Nr-CWS-Exos treatment groups was significantly reduced, among which the reduction in the Nr-CWS-Exos group was greater than that in the Exos group ( Figure 5 In contrast, the anti-inflammatory genes Arg-1 and IL-10 were upregulated in the Nr-CWS-Exos group ( Figure 4 L). In addition, secreted pro-inflammatory and anti-inflammatory cytokines were quantified using ELISA, and pro-inflammatory cytokines were significantly reduced in the Nr-CWS-Exos group compared with the other groups ( Figure 5 ). This suggests that Nr-CWS-treated hUMSC-derived exosomes can more effectively promote macrophage polarization toward the M2 phenotype than untreated hUMSC-derived exosomes.

[0103] In a specific embodiment, the present invention demonstrates that Nr-CWS-Exos increase the M1 to M2 polarization ratio and promote wound healing in vivo.

[0104] Specifically, to evaluate the anti-inflammatory effects of Nr-CWS-treated exosomes (Nr-CWS-Exos), we used the air pouch mouse model. On day 4 after injection of untreated exosomes (Exos) or Nr-CWS-Exos, inflammatory exudates ( Figure 5 A, B). Flow cytometric analysis of macrophage-specific markers showed an increase in CD206-positive (M2) macrophages and a decrease in CCR7-positive (M1) macrophages in the exudates of Exos-treated mice, an effect that was more pronounced in the Nr-CWS-Exos group ( Figure 5 CF). In addition, secreted anti-inflammatory and pro-inflammatory cytokines were quantified by ELISA ( Figure 5 G, H). The protein expression levels of iNOS (M1 marker) and Arg-1 (M2 marker) were examined. iNOS expression was significantly inhibited by Exos, even more significantly by Nr-CWS-Exos, while the opposite was true for Arg-1 ( Figure 5 I). To further evaluate the therapeutic effect of Nr-CWS-Exos, we established a diabetic mouse wound model ( Figure 5 K). The speed of wound healing was recorded over 14 days, and both wounds treated with Exos and Nr-CWS-Exos showed a significant reduction in wound size, with Nr-CWS-Exos having a superior effect than untreated Exos ( Figure 5 L). By day 14, the wounds treated with Nr-CWS-Exos healed significantly faster than those in the control group ( Figure 5J). Flow cytometry and immunofluorescence staining results confirmed that the proportion of CD206-positive (M2) macrophages increased, while the proportion of CD86-positive (M1) macrophages decreased in the Nr-CWS-Exos treatment group compared with the Exos and control groups ( Figure 5 M, N). Similarly, immunofluorescence staining of iNOS (M1) and CD163 (M2) also reflected this trend ( Figure 5 Q). The results of histological analysis of diabetic wounds showed that abundant granulation tissue was formed in the Nr-CWS-Exos group and the Exos group on days 7 and 14, and the granulation tissue layer was thicker and more organized. Collagen fiber deposition was also more obvious in the wounds treated with Nr-CWS-Exos compared with the control group ( Figure 5 O, P). In addition, the expression of angiogenic markers α-SMA and CD31 was significantly higher in the wounds of the Nr-CWS-Exos-treated group, further supporting the result that wound healing is enhanced by increasing vascularization. These results indicate that Nr-CWS-Exos significantly enhance M2 macrophage polarization and accelerate diabetic wound healing.

[0105] In a specific embodiment, the present invention demonstrates that CircGFRA3 is upregulated in Nr-CWS-Exos and regulates M1 to M2 macrophage polarization in vitro.

[0106] Specifically, circular RNA (circRNA) plays a key role in the biological function of endothelial cells during tissue injury. To investigate the mechanism by which Nr-CWS-Exos mediate macrophage polarization, we treated MSCs with Nr-CWS and isolated exosomes for analysis. Using RNA sequencing (RNA-Seq), we identified differentially expressed circRNAs in exosomes ( Figure 6 A). Hierarchical clustering plot of the top differentially expressed circRNAs highlights the significant differences between exosomes from normal, high glucose (HG), and Nr-CWS treated groups ( Figure 6 B). From this analysis, 41 circRNAs (fold change ≥ 2.0) were selected for qPCR validation, among which circGFRA3 (hsa_circ_0074097) showed the most significant expression change ( Figure 6 C). CircGFRA3 is derived from exon 4 of the GFRA3 gene and is 313 nucleotides long. Its corresponding sequence is shown in SEQ ID NO: 1. Its head-to-tail splicing was verified in MSCs by Sanger sequencing ( Figure 6 D, E). PCR analysis further confirmed that circGFRA3 could only be amplified using different primers from cDNA but not from genomic DNA ( Figure 6D). In addition, circGFRA3 was resistant to RNase R digestion, whereas linear GFRA3 mRNA was partially degraded by the enzyme ( Figure 6 F). The results of treatment with actinomycin D showed that circGFRA3 exhibited higher stability compared with GFRA3 mRNA ( Figure 6 G). Fluorescence in situ hybridization (FISH) analysis showed that circGFRA3 was mainly localized in the nucleus ( Figure 6 H, I), confirming that it is a genuine circRNA. Next, we investigated the role of circGFRA3 in macrophage polarization. Flow cytometry analysis showed that forced expression of circGFRA3 significantly suppressed CD86-positive (M1) macrophages, while the number of CD206-positive (M2) macrophages increased ( Figure 6 JM). Protein expression analysis further showed that in the circGFRA3 overexpression group, iNOS, a marker of M1 macrophages, was elevated, while Arg-1, a marker of M2 macrophages, showed an opposite trend ( Figure 6 N). Gene expression analysis by qRT-PCR showed that pro-inflammatory markers (iNOS, IL-1β, TNF-α) were significantly reduced, while anti-inflammatory markers (Arg-1, IL-10) were upregulated in the circGFRA3 overexpression group compared with HG and vector controls ( Figure 6 R). To further validate these findings, we performed ELISA to quantify secreted cytokines. In circGFRA3-transfected cells, the secretion of pro-inflammatory cytokines was significantly reduced, while the secretion of anti-inflammatory cytokines was increased ( Figure 6 To confirm the role of circGFRA3 in macrophage polarization, we used siRNA to inhibit circGFRA3 expression and observed the opposite trend in all the above assays ( Figure 6 PQ, O). These results collectively indicate that circGFRA3 promotes macrophage polarization toward M2 phenotype (promoting macrophage polarization from M1 phenotype to M2 phenotype, thereby promoting wound healing).

[0107] In a specific embodiment, the present invention demonstrates that CircGFRA3 interacts with NAT10 in THP-1 cells.

[0108] Specifically, to investigate whether circGFRA3 functions as a miRNA sponge in THP cells, we performed an RNA immunoprecipitation (RIP) assay. The results showed that while ciRS-7 (a circRNA known to bind to AGO2) was significantly enriched by the FLAG antibody, circGFRA3 was not ( Figure 7A), which suggests that circGFRA3 may not act as a miRNA sponge in THP cells. We then tested whether circGFRA3 interacted with proteins by performing RNA pull-down experiments. The circGFRA3 sense probe successfully enriched circGFRA3, and subsequent SDS-PAGE and mass spectrometry analysis of the pull-down samples identified approximately 452 potential interacting proteins ( Figure 7 B). By mass spectrometry analysis, we selected high-scoring proteins, among which NAT10 emerged as a prominent candidate ( Figure 7 C). We confirmed the interaction between circGFRA3 and NAT10 using RNA pull-down and RIP analysis ( Figure 7 D, E). RNA fluorescence in situ hybridization (FISH) and immunofluorescence analysis further confirmed the co-localization of circGFRA3 and NAT10 in the nucleus ( Figure 7 F). To identify the motifs required for NAT10 recruitment in circGFRA3, we used the catRAPID and MEME databases, and simultaneously used 3D RNAscore to predict circGFRA3 and build a circGFRA3 model. A 3D convolutional neural network (CNN) was used to process the NAT10 protein structure for high-precision pocket prediction ( Figure 7 I). Finally, pymol was used to simulate and screen the relevant docking sites. Through analysis, we explored that circGFRA3 binds to Lys-378 of NAT10 through C-113. Based on these predictions, we generated two NAT10 mutant plasmids and found that plasmid #2 had a more effective knockdown effect ( Figure 7 G). RNA-RIP experiments showed that there was no interaction between NAT10 mutants and circGFRA3 in relevant cells ( Figure 7 H). In addition, we explored the domains of NAT10 that interact with circGFRA3 and found that the helicase domain of NAT10 is essential for this interaction and mutations in this domain abolish binding ( Figure 7 H, I).

[0109] In a specific embodiment, 293T cells and hUCMSCs were infected with circGFRA3 KD, circGFRA3 OE vectors and lentivirus to stabilize the low or high expression of the circGFRA3 gene, and the vectors were designed by Heyuan Bio. Protein particles PRPF19, NAT10 and small interferors were transfected into cells using polyject (SignaGen) (the small interferors were designed and synthesized by conventional design and synthesis methods). PRPF19 and NAT10 tags were purchased from Ubao Bio.

[0110] In a specific embodiment, the present invention demonstrates that CircGRAF3 promotes NAT10 ubiquitination and degradation.

[0111] Specifically, given the interaction between circGFRA3 and NAT10, we next investigated whether circGFRA3 regulates NAT10 expression. circGFRA3 had no effect on NAT10 mRNA levels, but overexpression of circGFRA3 led to a significant decrease in NAT10 protein levels, whereas knockdown of circGFRA3 led to an increase in NAT10 protein expression ( Figure 8 A). In addition, mutation of circGFRA3 inhibited NAT10 protein degradation ( Figure 8 B), indicating that circGFRA3 disrupts NAT10 through protein-protein interactions. Treatment with the proteasome inhibitor MG132 restored NAT10 protein levels, indicating that circGFRA3 promotes proteasome-dependent NAT10 degradation ( Figure 8 C). Ubiquitination assay results showed that circGFRA3 overexpression significantly increased the ubiquitination level of NAT10, while circGFRA3 knockdown produced the opposite effect ( Figure 8 D, E). These results suggest that circGFRA3 reduces the stability of NAT10 by enhancing its ubiquitin / protease-dependent degradation.

[0112] In a specific embodiment, the present invention demonstrates that PRPF19 is an E3 ligase that mediates NAT10 ubiquitination via K48-linked ubiquitin chains.

[0113] Specifically, to identify the E3 ligase responsible for NAT10 ubiquitination, we performed mass spectrometry analysis on the Co-IP precipitates and identified several E3 ligases among 156 potential interacting proteins. PRPF19 interacts with circGFRA3 and was considered a possible candidate for NAT10 ubiquitination. Co-transfection of Flag-PRPF19 and His-NAT10 into THP1 and 293T cells confirmed the interaction between PRPF19 and NAT10 ( Figure 8 D, E). Further analysis showed that PRPF19 overexpression reduced NAT10 protein levels, while NAT10 overexpression did not change PRPF19 levels ( Figure 8 F, G). The results of treatment with protein synthesis inhibitor CHX (cyclohexyl imine) showed that PRPF19 accelerated the degradation of NAT10, while PRPF19 knockdown protected NAT10 from degradation ( Figure 8H, I), indicating that PRPF19 reduces the stability of NAT10 at the post-transcriptional level. In vivo ubiquitination analysis using different ubiquitin mutants confirmed that PRPF19 promotes NAT10 degradation via the protease pathway rather than the lysosomal pathway. Figure 8 J, K show the PRPF19-mediated K48-linked ubiquitination pathway of NAT10 protein. Overexpression of PRPF19 enhanced the K48-linked ubiquitination of NAT10 protein, while knockout of the Ring domain of PRPF19 inhibited the K48-linked ubiquitination of NAT10 protein ( Figure 8 K48-linked polyubiquitination is specifically mediated by PRPF19, as the HA-Ub-K48R mutant blocked polyubiquitination, whereas HA-Ub-K63R had no effect ( Figure 8 O, P).

[0114] In a specific embodiment, the present invention demonstrates that CircGFRA3 enhances the interaction between PRPF19 and NAT10.

[0115] Specifically, circRNAs are known to serve as scaffolds for efficient ubiquitination of their targets. Interestingly, the predicted binding sites of PRPF19 and NAT10 overlap with those of circGFRA3, suggesting that circGFRA3 may function as a scaffold for PRPF19 and NAT10. We confirmed the specific interaction between circGFRA3 and PRPF19 using RNA pull-down and RIP assays ( Fig. 9 A, B). RNAFISH analysis further demonstrated the co-localization of circGFRA3 and PRPF19 in the nucleus ( Fig. 9 C). To determine whether the ubiquitinase activity of PRPF19 on NAT10 is dependent on circGFRA3, we overexpressed and mutated circGFRA3 and found that the ubiquitination level of NAT10 was enhanced when overexpressed, while the ubiquitination level was significantly reduced after mutation ( Fig. 9 Treatment with RNase A (which degrades RNA but not RNase R) disrupts this interaction, confirming the role of circGFRA3 as a scaffold ( Fig. 9 F). Further experiments showed that knocking down CirCGFRA3-MUT and PRPF19 showed that circGFRA3 enhanced the binding of PRPF19 to NAT10, while overexpression of CirCGFRA3-MUT lost this effect. At the same time, overexpression of circGFRA3 and knocking down PRPF19 also lost this effect ( Fig. 9G, H). The above results show that circGFRA3 enhances the binding of PRPF19 to NAT10 and promotes the ubiquitination degradation of NAT10. At the same time, a 3D convolutional neural network (CNN) was used to predict the PRPF19 protein structure with high precision. Finally, pymol simulation was used to screen related docking sites. Through analysis, we explored that circGFRA3 binds to Lys-378 of NAT10 and ARG-190 of PRPF19 through C-113. Finally, the combined image of the three was predicted by pymol.

[0116] In a specific embodiment, the present invention demonstrates that NAT10 acts as a downstream mediator of circGRAF3 by regulating the mRNA stability of ac4C-modified HK1.

[0117] Specifically, NAT10 is the only known ac4C "writer" protein that plays a key role in regulating mRNA stability and translation. To explore the impact of NAT10-mediated ac4C modification on gene expression profiles, which is associated with M2 macrophage polarization, we integrated acRIP-seq, RNA-seq, and M2 polarization databases for analysis in cells overexpressing NAT10. acRIP-seq results showed widespread ac4C modifications in the transcriptome, mainly located in coding sequences (CDSs) ( Fig.10 A, B). Notably, upon NAT10 overexpression, ac4C modification of mRNAs increased significantly, consistent with the acetylation function of NAT10 ( Fig.10 C). A total of 810 highly acetylated enriched regions were identified after NAT10 overexpression ( Fig.10 D). A cytosine (C)-rich sequence pattern (CXX) was identified in these regions, which was disrupted after NAT10 knockdown ( Fig.10 E). Further analysis using GEO, NCBI, acRIP, and glycolysis data identified HK1 as the most relevant gene with a high enrichment score ( Fig.10 F, G). After NAT10 overexpression, multiple mRNAs including HK1 showed enhanced acetylation modification. NAT10 directly regulates ac4C modification of HK1 mRNA 5' untranslated region (UTR) ( Fig.10 H). Although NAT10 knockdown accelerated HK1 mRNA degradation, its pre-RNA level remained unchanged, indicating that ac4C modification by NAT10 mainly stabilizes HK1 mRNA. RIP experiments confirmed that HK1 mRNA was enriched by NAT10, while this interaction was abolished after NAT10 silencing ( Fig.10I). In addition, acRIP-qPCR experiments showed that ac4C modification of HK1 mRNA was significantly reduced after NAT10 silencing. NAT10 gene knockout ( Fig.10 I). Through sequence analysis, potential binding oligonucleotides were identified from the ac4C peak region of HK1 mRNA ( Fig.10 J). RNA affinity purification experiments confirmed that oligonucleotides 2-3 could effectively recruit NAT10 ( Fig.10 K). Mutation of specific cytosines in these oligonucleotides almost completely abolished their ability to recruit NAT10. Mutation of specific cytosines in these oligonucleotides almost completely abolished their interaction with NAT10 ( Fig.10 L). NAT10 knockdown reduced the luciferase activity in the ac4C peak region of HK1 mRNA, but had no effect in the cytosine mutation region ( Fig.10 M). To further verify the effect of NAT10 on mRNA stability, we demonstrated that NAT10 overexpression significantly increased HK1 mRNA levels, whereas NAT10 knockdown disrupted its stability ( Fig.10 O, P). These data suggest that NAT10 catalyzes ac4C modification of mRNA and enhances mRNA stability through direct interaction with the CXX sequence motif. NAT10 contains several key domains, including a DUF1726 domain at the N-terminus, followed by a helicase domain, a GNAT domain, and a tRNA binding domain. To determine which domain interacts with HK1, we constructed truncation mutants of all four domains ( Fig.10 Q, R). Truncation of the GNAT and helicase domains weakened the interaction between NAT10 and HK1 mRNA ( Fig.10 S). These findings suggest that NAT10 regulates mRNA stability through ac4C modification near the start codon and interacts with mRNA primarily through its helicase domain.

[0118] In a specific embodiment, the present invention demonstrates that CircGFRA3 regulates cellular glycolysis through the NAT10 / HK1 axis.

[0119] Specifically, HK1 is a key enzyme that catalyzes the first step of glycolysis and plays a vital role in glucose metabolism. Studies have shown that MSC-derived exosomes (MSCs-Exos) can regulate cell polarization by inhibiting cellular glycolysis. Given the crucial role of circGFRA3 in regulating HK1 mRNA stability through NAT10, we speculated that circGFRA3 may also regulate cellular glycolysis. We first evaluated whether circGFRA3 affects glycolysis in THP1 cells. Our results showed that overexpression of circGFRA3 significantly reduced the levels of four key glycolytic proteins: HK1, PKM2, GLUT1, and LDHA ( Fig.11 A). In addition, circGFRA3 overexpression reduced lactate production and ATP levels in THP1 cells ( Fig.11 B, C). To further evaluate glycolytic function, we measured glucose uptake, extracellular acidification rate (ECAR), and oxygen consumption rate (OCR) using the Seahorse XF Bioenergetics System. circGFRA3 overexpression resulted in decreased glucose uptake and glycolytic rate, while increasing internal respiratory capacity ( Fig.11 D, E). In contrast, knockdown of circGFRA3 showed the opposite effect ( Fig.11 FJ). In addition, in circGFRA3 knockdown THP1 cells, silencing NAT10 reversed the increases in glucose uptake, ECAR, and OCR induced by circGFRA3 knockdown ( Fig.11 Western blotting analysis confirmed that silencing NAT10 could rescue the expression of four key glycolytic proteins (HK1, PKM2, GLUT1, and LDHA) that were downregulated by circGFRA3 overexpression ( Fig.11 H).

[0120] In a specific embodiment, the present invention demonstrates that NAT10 is involved in M1 to M2 macrophage polarization regulated by circGRAF3 overexpression through HK1.

[0121] Specifically, to evaluate whether NAT10 plays a key role in circGFRA3-mediated M1 to M2 macrophage polarization under high glucose conditions, we overexpressed NAT10. The results showed that the expression of NAT10 and HK1 was increased in THP-1 cells overexpressing circGFRA3. Flow cytometry analysis showed that the increased expression of NAT10 and HK1 could alleviate the M2 polarization induced by circGFRA3 overexpression ( Fig.12AD). Specifically, the elevated iNOS expression in the circGFRA3 overexpression group could be significantly reduced by NAT10 overexpression and HK1 overexpression, while the protein expression level of Arg-1 was increased ( Fig.12 E). In addition, the relative expression of the pro-inflammatory gene (iNOS) induced by circGFRA3 overexpression was significantly decreased, while the expression of the anti-inflammatory gene (Arg-1) was enhanced after NAT10 and HK1 overexpression ( Fig.12 FG). Analysis of secreted cytokines by enzyme-linked immunosorbent assay further confirmed these findings, showing similar trends for pro-inflammatory and anti-inflammatory cytokines ( Fig.12 HK). These results suggest that NAT10 plays a key role in circGFRA3-induced M2 polarization of THP1 cells and contributes to the anti-inflammatory shift of macrophage phenotype.

[0122] In a specific embodiment, the present invention demonstrates that CircGFRA3 regulates the effect of Nr-CWS exosomes on wound healing in vivo through NAT10.

[0123] Specifically, we evaluated the role of circGFRA3-loaded exosomes (circGFRA3-Exo) in wound healing in a diabetic mouse model ( Fig.13 A). Wound healing curves and images of the mouse model showed that mice injected with exosomes overexpressing circGFRA3 showed improved wound healing at days 7 and 14, an effect that was inhibited by NAT10 overexpression ( Fig.13 B, C). On day 7, hematoxylin and eosin (HE) staining showed that the amount of granulation tissue in the circGFRA3 group was significantly higher than that in the control group. However, this effect was inhibited by overexpression of NAT10 ( Fig.13 D). By day 14, collagen deposition in the circGFRA3 group was denser and more organized, while overexpression of both circGFRA3 and NAT10 resulted in a disordered collagen structure. In addition, the measurements of dermal thickness were consistent with our findings, further supporting our conclusions ( Fig.13 E, F). Immunofluorescence staining results showed that the number of CD206-positive (M2) macrophages in the circGFRA3 group was significantly higher than that in the control group, while the number of CD86-positive (M1) macrophages showed the opposite trend. In the group overexpressing circGFRA3 and NAT10 at the same time, the number of CD206-positive macrophages decreased, while the number of CD86-positive macrophages increased ( Fig.13G). By day 14, most positive cells were concentrated in the superficial dermis, indicating that macrophages actively participate in wound healing. Immunofluorescence staining for α-SMA and CD31 showed that circGFRA3-Exo treatment enhanced angiogenesis compared with Exos treatment alone. In contrast, the group injected with AAV-NAT10 showed reduced angiogenesis. Notably, large blood vessels were clearly observed on day 14 in the circGFRA3-Exo-treated group. Exosomes from circGFRA3-overexpressing hUMSCs (circGFRA3-Exo) resulted in significantly reduced expression of proinflammatory factors IL-6, TNF-α, and IL-1β in wound tissues compared with control exosomes. Overall, these results suggest that topical application of circGFRA3-Exo can promote M2-like macrophage polarization and accelerate wound healing in diabetic mice through interaction with NAT10.

[0124] Figure 2 Schematic diagram of a screening system for screening drugs for promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10 provided in an embodiment of the present invention. Specifically, the screening system includes:

[0125] A data acquisition unit, which acquires circGFRA3 and PRPF19 protein data, or circGFRA3 and NAT10 protein data;

[0126] a site determination unit, which selects the spatial structure of the circGFRA3 and PRPF19 protein complex or the spatial structure of the circGFRA3 and NAT10 protein complex, and determines the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex as the binding site of the targeted drug;

[0127] The drug screening unit adopts a computer-assisted drug screening method to obtain a candidate drug targeting the binding site, wherein the computer-assisted drug screening method comprises:

[0128] Obtaining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex;

[0129] Based on the spatial structure of the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the spatial structure of the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex, screening small molecule compounds with similar structures in a molecular database;

[0130] The screened small molecule compounds are subjected to molecular docking with NAT10 protein to calculate the affinity or binding energy of the small molecule compounds targeting the receptor NAT10 protein to obtain the score of each small molecule compound, and the candidate drugs for promoting diabetic wound healing are obtained by ranking according to the score.

[0131] In some embodiments, the method for determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex comprises:

[0132] Construct n truncated expression mutants of PRPF19 or NAT10, where n is a natural number greater than or equal to 1;

[0133] Based on the n truncated expression mutants, RNA immunoprecipitation experiments were performed to obtain the key regions for the interaction between circGFRA3 and PRPF19 or NAT10;

[0134] The spatial structure of the key region of the interaction between circGFRA3 and PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex;

[0135] The spatial structure of the key region of the interaction between circGFRA3 and NAT10 is the binding site of circGFRA3 and NAT10 proteins in the circGFRA3 and NAT10 protein complex;

[0136] In some embodiments, the screening system further includes: a drug effectiveness verification unit, which obtains a diabetic wound animal model or a diabetic wound cell model; and uses the screened candidate drug for promoting diabetic wound healing to treat the diabetic wound animal model or the diabetic wound cell model to verify the effectiveness of the candidate drug for promoting diabetic wound healing.

[0137] Figure 3Schematic diagram of a computer device for screening drugs promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10 provided by an embodiment of the present invention. Specifically, the computer device includes:

[0138] A memory and a processor, wherein the memory is used to store program instructions; the processor is used to call the program instructions, and when the program instructions are executed, the computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10 as described above is implemented.

[0139] In some embodiments, the computer device may further include: an input device and an output device.

[0140] In some embodiments, the memory, processor, input device, and output device may be connected via a bus or other means. Figure 3 The bus connection is shown as an example; the memory is used to store program instructions; the processor is used to call the program instructions, and when the program instructions are executed, the above method is implemented. In some embodiments, the memory can be understood as any storage device for the program, and the processor can be understood as a device for using the program.

[0141] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10 as described above is implemented.

[0142] The present invention also provides any of the following products:

[0143] (1) A diabetic wound healing promoting drug, wherein the diabetic wound healing promoting drug is obtained by screening according to the computer-assisted drug screening method for screening diabetic wound healing promoting drugs based on PRPF19, circGFRA3 and NAT10 as described above;

[0144] (2) A pharmaceutical composition comprising circGFRA3 or a circGFRA3 promoter, wherein the sequence of circGFRA3 is shown in SEQ ID NO: 1.

[0145] The embodiments of the present invention also provide any of the following applications:

[0146] (1) Use of circGFRA3 or a circGFRA3 promoter in the preparation of a drug for promoting diabetic wound healing, wherein the sequence of circGFRA3 is shown in SEQ ID NO: 1;

[0147] (2) Use of PRPF19 or a PRPF19 promoter in the preparation of a drug for promoting diabetic wound healing;

[0148] (3) Use of NAT10 or a NAT10 inhibitor in the preparation of a medicament for promoting diabetic wound healing.

[0149] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0150] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0151] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0152] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units. The present invention has no particular limitation on the specific implementation form.

[0153] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. The above is a detailed introduction to a computer device provided by the present invention. For a person skilled in the art, according to the idea of ​​the embodiment of the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A computer-assisted drug screening method for promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10, characterized in that: The screening method comprises: Obtain circGFRA3 and PRPF19 protein data, or circGFRA3 and NAT10 protein data; Selecting the spatial structure of the circGFRA3 and PRPF19 protein complex, or the spatial structure of the circGFRA3 and NAT10 protein complex, and determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex as the binding site of the targeted drug; A computer-assisted drug screening method is used to obtain a candidate drug targeting the binding site, and the computer-assisted drug screening method comprises: Obtaining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex; Based on the spatial structure of the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the spatial structure of the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex, screening small molecule compounds with similar structures in a molecular database; The screened small molecule compounds are subjected to molecular docking with NAT10 protein to calculate the affinity or binding energy of the small molecule compounds targeting the receptor NAT10 protein to obtain the score of each small molecule compound, and the candidate drugs for promoting diabetic wound healing are obtained by ranking according to the score.

2. The computer-assisted drug screening method for promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10 according to claim 1, characterized in that: The method for determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex comprises: Construct n truncated expression mutants of PRPF19 or NAT10, where n is a natural number greater than or equal to 1; Based on the n truncated expression mutants, RNA immunoprecipitation experiments were performed to obtain the key regions for the interaction between circGFRA3 and PRPF19 or NAT10; The spatial structure of the key region of the interaction between circGFRA3 and PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex; The spatial structure of the key region of the interaction between circGFRA3 and NAT10 is the binding site of circGFRA3 and NAT10 proteins in the circGFRA3 and NAT10 protein complex.

3. The computer-assisted drug screening method for promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10 according to claim 2, characterized in that: The spatial conformation formed by the interaction between C-113 of circGFRA3 and Arg-190 of PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex; The spatial conformation formed by the interaction between C-113 of circGFRA3 and Lys-378 of NAT10 is the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex.

4. The computer-assisted drug screening method for promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10 according to claim 1, characterized in that: The screening method further comprises: Obtain diabetic wound animal model or diabetic wound cell model; The diabetic wound animal model or diabetic wound cell model is treated with the screened candidate drug for promoting diabetic wound healing to verify the effectiveness of the candidate drug for promoting diabetic wound healing.

5. A screening system for drugs promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10, characterized in that: The screening system comprises: A data acquisition unit, which acquires circGFRA3 and PRPF19 protein data, or circGFRA3 and NAT10 protein data; a site determination unit, which selects the spatial structure of the circGFRA3 and PRPF19 protein complex or the spatial structure of the circGFRA3 and NAT10 protein complex, and determines the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex as the binding site of the targeted drug; The drug screening unit adopts a computer-assisted drug screening method to obtain a candidate drug targeting the binding site, wherein the computer-assisted drug screening method comprises: Obtaining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex; Based on the spatial structure of the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the spatial structure of the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex, screening small molecule compounds with similar structures in a molecular database; The screened small molecule compounds are subjected to molecular docking with NAT10 protein to calculate the affinity or binding energy of the small molecule compounds targeting the receptor NAT10 protein to obtain the score of each small molecule compound, and the candidate drugs for promoting diabetic wound healing are obtained by ranking according to the score.

6. The screening system for promoting diabetic wound healing based on PRPF19, circGFRA3 and NAT10 according to claim 5, characterized in that: The method for determining the binding site of circGFRA3 and PRPF19 protein in the circGFRA3 and PRPF19 protein complex, or the binding site of circGFRA3 and NAT10 protein in the circGFRA3 and NAT10 protein complex comprises: Construct n truncated expression mutants of PRPF19 or NAT10, where n is a natural number greater than or equal to 1; Based on the n truncated expression mutants, RNA immunoprecipitation experiments were performed to obtain the key regions for the interaction between circGFRA3 and PRPF19 or NAT10; The spatial structure of the key region of the interaction between circGFRA3 and PRPF19 is the binding site of circGFRA3 and PRPF19 proteins in the circGFRA3 and PRPF19 protein complex; The spatial structure of the key region of the interaction between circGFRA3 and NAT10 is the binding site of circGFRA3 and NAT10 proteins in the circGFRA3 and NAT10 protein complex; Optionally, the screening system further comprises: a drug effectiveness verification unit for obtaining a diabetic wound animal model or a diabetic wound cell model; treating the diabetic wound animal model or the diabetic wound cell model with the screened candidate drug for promoting diabetic wound healing to verify the effectiveness of the candidate drug for promoting diabetic wound healing.

7. A computer device for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10, characterized in that: The computer device comprises: A memory and a processor, wherein the memory is used to store program instructions; the processor is used to call the program instructions, and when the program instructions are executed, the computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10 as described in any one of claims 1-4 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer-assisted drug screening method for screening drugs that promote diabetic wound healing based on PRPF19, circGFRA3 and NAT10 according to any one of claims 1 to 4 is implemented.

9. Any of the following products: (1) A drug for promoting diabetic wound healing, characterized in that: The diabetic wound healing promoting drug is a diabetic wound healing promoting drug screened by a computer-assisted drug screening method based on PRPF19, circGFRA3 and NAT10 according to any one of claims 1 to 4; (2) A pharmaceutical composition, characterized in that the pharmaceutical composition comprises circGFRA3 or a circGFRA3 promoter, and the sequence of the circGFRA3 is shown in SEQ ID NO:

1.

10. Any of the following applications: (1) Use of circGFRA3 or a circGFRA3 promoter in the preparation of a drug for promoting diabetic wound healing, characterized in that: The sequence of circGFRA3 is shown in SEQ ID NO: 1; (2) Use of PRPF19 or a PRPF19 promoter in the preparation of a drug for promoting diabetic wound healing; (3) Use of NAT10 or a NAT10 inhibitor in the preparation of a medicament for promoting diabetic wound healing.

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