Skin fibroblast marker protein targeting component and screening method

Abstract

The invention discloses a screening method of skin fibroblast marker protein targeting components. The screening method comprises the following steps: (1) constructing a human skin fibroblast cell membrane positioning marker protein data list; (2) obtaining a membrane localization marker protein targeting component; (3) predicting chemical similarity; and (4) molecular docking verification. Database mining, chemoinformatics and molecular docking technologies are comprehensively applied, the HSF membrane localization marker protein beneficial to targeted research is accurately locked, a targeted component set of the HSF membrane localization marker protein is obtained, and an accurate and effective scientific basis is provided for research and development of anti-aging cosmetics.

Description

Technical Field

[0001] The present invention relates to a skin fibroblast marker protein targeting component and a corresponding screening method, belonging to the field of cell biology. Background Art

[0002] Human Skin Fibroblasts (HSF) are the core cell type in the dermis of the skin and play a key role in maintaining the structural stability and functional integrity of the skin. These cells construct an elastic fiber, collagen fiber, and reticular fiber network by synthesizing matrix components such as elastin, collagen, and glycosaminoglycans, endowing the skin with elasticity and tension. In addition, HSF directly participates in the wound healing process by secreting signaling molecules such as growth factors and cytokines, initiating the injury repair mechanism, and restoring the physiological function of the skin.

[0003] Due to the core role of HSF in maintaining skin health, it has become a key research object in the cosmetics industry, especially in the research and development of anti-aging and wound care products. By analyzing the response mechanism of HSF to external stimuli, scientists can develop skin care formulations that delay aging and promote repair. However, no highly specific biomarker that can specifically label HSF has been found in current research. Many molecular markers that were traditionally considered to be specifically expressed in HSF also exist in other cell types, resulting in a technical bottleneck for accurately identifying HSF.

[0004] The limitations of the existing technology make it a difficult problem in the industry to accurately distinguish HSF from other cell types. To break through this bottleneck, the innovation of biomarker screening technology has become a research hotspot. By integrating multidisciplinary technical means such as database mining, chemoinformatics, and molecular docking, scientists are committed to developing active ingredients that can specifically target HSF membrane-localized marker proteins, providing a scientific basis for the research and development of anti-aging cosmetics and wound repair products, and at the same time promoting the development of skin cell biology research towards precision. Summary of the Invention

[0005] The primary technical problem to be solved by the present invention is to provide a screening method for a skin fibroblast marker protein targeting component.

[0006] Another technical problem to be solved by the present invention is to provide a skin fibroblast marker protein targeting component obtained by the above screening method.

[0007] Another technical problem to be solved by the present invention is to provide the use of the above skin fibroblast marker protein targeting component.

[0008] To achieve the above technical objectives, the present invention adopts the following technical solutions:

[0009] A screening method for skin fibroblast marker protein targeting components, comprising the following steps:

[0010] (1) Construct a data list of human skin fibroblast membrane localization marker proteins: Use the The Human SkinAtlas database to obtain a set of highly expressed and highly specific proteins, and construct a data list of highly expressed and highly specific proteins of human skin fibroblasts;

[0011] (2) Obtain membrane localization marker protein targeting components: Conduct target fishing to obtain the targeting components of HSF membrane localization marker proteins, and map the obtained targeting components with the INCI names and English names of cosmetic raw materials to screen the targeting components that are included in INCI, target human skin fibroblast membrane localization marker proteins, and can be applied to cosmetic formulations;

[0012] (3) Chemical similarity prediction: In order to expand the reserve of human skin fibroblast membrane localization marker protein targeting components, based on the targeting components obtained in step (2), conduct chemical similarity prediction, and the predicted components are screened using INCI to obtain chemical similarity prediction targeting components that can be applied to cosmetic formulations;

[0013] (4) Molecular docking verification: Use molecular docking to verify the binding activities between the targeting components described in step (2) and the predicted components described in step (3) and the corresponding human skin fibroblast membrane localization marker proteins to obtain the target targeting components.

[0014] Preferably, the step (1) includes the following sub-steps:

[0015] S11. Based on the The Human Skin Atlas database, compare the expression levels between different samples or different proteins using the iBAQ value;

[0016] S12. Use the abundance curve of endosialin as a reference to determine proteins with similar abundance patterns;

[0017] S13. Take the intersection of the proteins in S11 and S12 to obtain the data list of highly expressed and highly specific proteins of human skin fibroblasts;

[0018] S14. For the proteins in the data list obtained in S13, query the subcellular localization information of the proteins one by one, and obtain the membrane localization proteins from them to construct a data list of human skin fibroblast membrane localization marker proteins.

[0019] Preferably, the step (2) includes the following sub-steps:

[0020] S21. Conduct target fishing to construct a data list of target components for human skin fibroblast membrane localization marker proteins: Query one by one the target components that can bind to the marker proteins in the data list obtained in step (1) to construct a data list of target components for human skin fibroblast membrane localization marker proteins;

[0021] S22. Correlate the English names of the target components of human skin fibroblast membrane localization marker proteins in the data list in S21 with the INCI names and English names of cosmetic raw materials, and map to obtain target components that can target human skin fibroblast membrane localization marker proteins and can be applied to cosmetic formulations.

[0022] Preferably, in the above step (3), the method for chemical similarity prediction is: Obtain the SMILES structural formula of the component to be predicted from the PubChem database, and query and collect the comprehensive scores between drugs in the STITCH database; Divide the score by 1000 to ensure that the similarity value of chemical components is between 0 and 1, and obtain target components with strong chemical similarity to the component to be predicted according to the similarity value.

[0023] Preferably, in the above step (4), the screening criterion for binding activity is that the binding energy ≤ -5.0 kJ / mol.

[0024] Target components of skin fibroblast marker proteins, which are screened by the above method.

[0025] Preferably, the target components are copper, hyaluronic acid, glycolic acid, nicotinamide adenine dinucleotide phosphate, guanosine-5'-triphosphate, dermatan, calcium oxalate, lithium oxalate, and / or nicotinamide adenine dinucleotide.

[0026] Use of the above target components of skin fibroblast marker proteins in the preparation of cosmetic efficacy evaluation products.

[0027] Compared with the prior art, the present invention has the following technical effects:

[0028] (1) The present invention comprehensively applies database mining, chemoinformatics, and molecular docking technologies to accurately lock in HSF membrane localization marker proteins conducive to target research, and obtains a set of target components of HSF membrane localization marker proteins, providing an accurate and effective scientific basis for the research and development of anti-aging cosmetics.

[0029] (2) A total of 9 targeted components with strong binding to the corresponding HSF membrane localization marker proteins were accurately screened out in the present invention, namely Copper, Hyaluronic acid, Glycol ic acid, Nicotinamide adenine dinucleotide phosphate, Guanosine-5'-Triphosphate, dermatan, calcium oxalate, lithium oxalate, and Nicotinamide adenin e dinucleotide. Among them, Copper has the strongest binding to the ACTN1 protein. However, free copper ions are extremely difficult to enter the human body through the stratum corneum of the skin to take effect. The copper peptide (Copper Glycyl-histidine-tripeptide, GHK-Cu) mode can be considered. GHK is an active tripeptide. Under the transport of GHK, the GHK-Cu copper peptide can penetrate the stratum corneum of the skin and exert its effect. In addition, 2 components, Artenimol and Guanosine, also have a certain binding to the corresponding marker proteins, and they can also be considered for inclusion in the reserve library of targeted components of HSF membrane localization marker proteins. Description of the Drawings

[0030] Figure 1A 3D docking mode diagram of Copper and ACTN1 protein;

[0031] Figure 1B 2D docking mode diagram of Copper and ACTN1 protein;

[0032] Figure 1C 3D docking mode diagram of Hyaluronic acid and CD44 protein;

[0033] Figure 1D 2D docking mode diagram of Hyaluronic acid and CD44 protein;

[0034] Figure 1E 3D docking mode diagram of Healon and CD44 protein;

[0035] Figure 1F 2D docking mode diagram of Healon and CD44 protein;

[0036] Figure 1G 3D docking mode diagram of dermatan and CD44 protein;

[0037] Figure 1H It is a 2D docking pattern diagram of dermatan and CD44 protein;

[0038] Figure 1I It is a 3D docking pattern diagram of Glycolic acid and G6PD protein;

[0039] Figure 1J It is a 2D docking pattern diagram of Glycolic acid and G6PD protein;

[0040] Figure 1K It is a 3D docking pattern diagram of Calcium oxalate and G6PD protein;

[0041] Figure 1L It is a 2D docking pattern diagram of Calcium oxalate and G6PD protein;

[0042] Figure 1M It is a 3D docking pattern diagram of lithium oxalate and G6PD protein;

[0043] Figure 1N It is a 2D docking pattern diagram of lithium oxalate and G6PD protein;

[0044] Figure 1O It is a 3D docking pattern diagram of Artenimol and G6PD protein;

[0045] Figure 1P It is a 2D docking pattern diagram of Artenimol and G6PD protein;

[0046] Figure 1Q It is a 3D docking pattern diagram of Artemether and G6PD protein;

[0047] Figure 1R It is a 2D docking pattern diagram of Artemether and G6PD protein;

[0048] Figure 1S It is a 3D docking pattern diagram of Nicotinamide adenine dinucleotide and G6PD protein;

[0049] Figure 1T It is a 2D docking pattern diagram of Nicotinamide adenine dinucleotide and G6PD protein;

[0050] Figure 1U It is a 3D docking pattern diagram of Nicotinamide adenine dinucleotide phosphate and G6PD protein;

[0051] Figure 1V It is a 2D docking pattern diagram of Nicotinamide adenine dinucleotide phosphate and G6PD protein;

[0052] Figure 1W It is a 3D docking pattern diagram of Guanosine and RND3 protein;

[0053] Figure 1X It is a 2D docking pattern diagram of Guanosine and RND3 protein;

[0054] Figure 1Y It is a 3D docking pattern diagram of Guanosine-5'-Triphosphate and RND3 protein;

[0055] Figure 1Z It is a 2D docking pattern diagram of Guanosine-5'-Triphosphate and RND3 protein. Detailed implementation mode

[0056] The technical content of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0057] Example 1 Screening and verification of the skin fibroblast membrane localization marker protein targeting component of the present invention

[0058] I. Construction of a data list of human skin fibroblast membrane localization marker proteins:

[0059] The Human Skin Atlas database https: / / skin.science / , namely the human skin proteomics atlas resource database, is a research project aiming to advance translational skin research by providing a resource of mass spectrometry-based proteomic data from healthy and diseased skin. The Human Skin Atlas database quantitatively characterized the proteomic composition of healthy human skin, divided the skin into four layers and nine cell types using a combination of methods such as scraping, skin dissection, FACS sorting and primary cell culture, and successfully generated a proteomic map containing 10,701 proteins, which is the largest proteomic data set obtained from human skin so far.

[0060] The purpose of this step is to obtain the "skin fibroblast marker protein".

[0061] S11. Based on the MS-Intensity (iBAQ) of The Human Skin Atlas database, obtain the dataset of highly expressed protein profiles in human skin fibroblasts. iBAQ (intensity-based absolute quantification) is a quantitative index calculated based on the mass spectrometry intensity of each protein, reflecting the relative abundance of the protein in the sample. The higher the iBAQ value, the higher the relative abundance of the protein. Therefore, the iBAQ value can be used to compare the expression levels between different samples or different proteins;

[0062] S12. Endosialin (CD248 / TEM1) is a protein expressed in skin fibroblasts. The results of proteomic detection show that endosialin is located in the top one-third of the fibroblast proteome and is hardly detected in other types of cells. Therefore, use the abundance curve of endosialin as a reference to determine the TOP100 proteins with similar abundance patterns and construct the dataset of specifically expressed protein profiles in human skin fibroblasts;

[0063] S13. Take the intersection of S11 and S12 to obtain the set of highly expressed and highly specific proteins, and construct the "List of Highly Expressed and Highly Specific Data of Human Skin Fibroblasts".

[0064] Research results: ① A total of 10,088 proteins were detected in human skin fibroblasts, among which 5,066 were highly expressed proteins (iBAQ>0), and the dataset of highly expressed protein profiles in human skin fibroblasts was constructed; ② Using the abundance curve of endosialin CD248 / TEM1 as a reference, the top 100 proteins with similar abundance patterns were analyzed and the dataset of specifically expressed protein profiles in human skin fibroblasts was constructed; ③ Take the intersection of the former two, and finally 77 proteins were obtained, and the list of highly expressed and highly specific proteins in human skin fibroblasts was constructed. The results are shown in Table 1.

[0065] Table 1 List of Highly Expressed and Highly Specific Data of Human Skin Fibroblasts

[0066]

[0067]

[0068]

[0069]

[0070] S14. Membrane localization marker proteins of skin fibroblasts

[0071] Comprehensively utilize Uniprot (https: / / www.uniprot.org / ), PDB (https: / / www.rcsb.org / ), and The human protein atlas (https: / / www.proteinatlas.org / ) to query the expression localization-related information of highly expressed and highly specific proteins in human skin fibroblasts, and construct the "Data List of Membrane Localization Marker Proteins in Human Skin Fibroblasts".

[0072] Research results: For the 77 proteins in the highly expressed and highly specific data list of human skin fibroblasts, query the subcellular localization information of the cells one by one, and a total of 27 membrane localization proteins are obtained, constructing the data list of membrane localization marker proteins in human skin fibroblasts. The results are shown in Table 2.

[0073] Table 2 Data List of Membrane Localization Marker Proteins in Human Skin Fibroblasts

[0074]

[0075]

[0076]

[0077]

[0078] II. Obtaining Target Components of Membrane Localization Marker Proteins

[0079] S21. Comprehensively utilize DrugBank (https: / / www.drugbank.com / ), GeneCards (https: / / www.genecards.org / ), ChEMBL

[0080] (https: / / www.ebi.ac.uk / chembl / ) and IUPHAR / BPS Guide to PHARMACOLOGY (https: / / www.guidetopharmacology.org / ) to query the target components of highly expressed and highly specific membrane proteins (marker proteins) in human skin fibroblasts.

[0081] Research results: For the 27 highly expressed and highly specific membrane proteins in human skin fibroblasts shown in Table 2, query the target components that can bind to the marker proteins one by one. Among them, 23 corresponding target components are obtained for 12 marker proteins, constructing the data list of target components of membrane localization marker proteins in human skin fibroblasts. The results are shown in Table 3.

[0082] Table 3 Data list of targeting components of human skin fibroblast membrane localization marker proteins

[0083]

[0084]

[0085]

[0086] S22. Correspondence of targeting components in "International Cosmetic Ingredients"

[0087] The English names of the targeting components of human skin fibroblast membrane localization marker proteins are corresponded with the "INCI Name / English Name" in "International Cosmetic Ingredients" to map the targeting components that can target human skin fibroblast membrane localization marker proteins and can be applied to cosmetic formulations.

[0088] Research results: For 23 targeting components of human skin fibroblast membrane localization marker proteins, they were corresponded with the "INCI Name / English Name" in "International Cosmetic Ingredients" one by one, and 7 components were screened out: Copper, Hyaluronic acid, Glycolic acid, Nicotinamide adenine dinucleotide phosphate, Artenimol, Polyethylene glycol 400, Guanosine-5'-Triphosphate. The results are shown in Table 4.

[0089] Table 4 List of targeting components of human skin fibroblast membrane localization marker proteins included in INCI

[0090]

[0091] Note: There are multiple English names for the same compound. In the "International Nomenclature Cosmetic Ingredient (INCI) Directory", only one English name of the compound is randomly given, which may not correspond to the default English name downloaded from Pubchem. Therefore, all the English names (collected by Pubchem) corresponding to each compound need to be downloaded and compared one by one.

[0092] For example: niacinamide, "NIACINAMIDE" in the INCI catalog, and "Nicotinamide" is the default download from Pubchem; "COUMARIN" in the INCI catalog, and "Coumestrol" is the default download from Pubchem; α-ketoglutaric acid, "KETOGLUTARIC ACID" in the INCI catalog, and "alpha-Ketoglutarate" is the default download from Pubchem, etc.

[0093] III. Chemical Similarity Prediction

[0094] S31. The interaction pattern between drugs is important information for predicting drug responses. Text mining and chemical structure similarity are used to predict the relationships between chemical substances. STITCH (http: / / stitch.embl.de / ) is the abbreviation of "search tool for interactions of chemicals", and the drug-drug combination scores can be collected from the STITCH database. First, obtain the SMILES structural formula of the component to be predicted from the PubChem database, and query the STITCH database to collect the comprehensive scores between drugs. Since the chemical-chemical combination score range of STITCH is 1 - 1000, divide the score by 1000 to ensure that the similarity value (Tanimoto score) of the drug is between 0 and 1. The higher the Tanimoto score, the stronger the chemical similarity with the component to be predicted.

[0095] Research results: Chemical similarity prediction analysis was carried out for 7 components targeting human skin fibroblast membrane localization marker proteins included in the INCI of "International Cosmetic Ingredients": Copper, Hyaluronic acid, Glycolic acid, Nicotinamide adenine dinucleotide phosphate, Artenimol, Polyethylene glycol 400, Guanosine-5'-Triphosphate. In addition, although Human calcitonin is not included in the INCI table but is a possible component, it was also included in the chemical similarity prediction analysis (aiming to observe whether its similar components are included in the INCI). A total of 53 chemically similar components were predicted, and the results are shown in Table 5.

[0096] Table 5 List of Chemical Similarity Prediction Results for Targeting Components

[0097]

[0098]

[0099]

[0100]

[0101]

[0102] S32. Corresponding prediction of ingredients in "International Cosmetic Ingredients".

[0103] For the 53 chemically similar predicted ingredients obtained in the previous step, their English names are corresponded one by one with the "INCI Name / English Name" in "International Cosmetic Ingredients" to obtain the chemically similar predicted target ingredients applicable to cosmetic formulations.

[0104] Research results: Five ingredients, namely Healon (sodium hyaluronate), dermatan, calcium oxalate, lithium oxalate, and artemether, were screened out. The results are shown in Table 6.

[0105] Table 6 List of Chemically Similar Predicted Target Ingredients Included in INCI

[0106]

[0107] IV. Molecular Docking Verification

[0108] Molecular docking was performed using Discovery Studio software to verify the binding activities between the target ingredients and predicted ingredients included in INCI and the corresponding human skin fibroblast membrane localization marker proteins. Generally, the lower the energy when the conformation of the ligand-receptor binding is stable, the greater the possibility of interaction. In the present invention, the binding energy ≤ -5.0 kJ / mol was used as the screening criterion.

[0109] A total of 13 compounds were included in this invention for molecular docking verification. ① It included 6 kinds of target components of labeled proteins included in INCI: Copper, Hyaluronic acid, Glycolic acid, Nicotinamide adenine dinucleotide phosphate, Artenimol, Guanosine-5'-Triphosphate (Note: The exact chemical structure of Polyethyleneglycol 400 could not be found and molecular docking research could not be carried out, so it was excluded); ② It included 5 predicted target components obtained based on the chemical similarity prediction of the target components of labeled proteins included in INCI: Healon, dermatan, calcium oxalate, lithium oxalate, artemether; ③ In addition, since the predicted component Nicotinamide adenine dinucleotide phosphate was not directly included in the INCI list, its ester hydrolysis product Nicotinamide adenine dinucleotide was included in INCI, so Nicotinamide adenine dinucleotide was also included in the molecular docking research to observe the binding of the two components to the corresponding labeled proteins; ④ Similarly, the predicted component Guanosine-5'-Triphosphate was not directly included in the INCI list, and its ester hydrolysis product Guanosine was included in INCI, so Guanosine was also included in the molecular docking research to observe the binding of the two components to the corresponding labeled proteins.

[0110] Research results: The molecular docking results showed that 9 components, namely Copper, Hyaluronic acid, Glycolic acid, Nicotinamide adenine dinucleotide phosphate, Guanosine-5'-Triphosphate, dermatan, calcium oxalate, lithium oxalate, and Nicotinamide adeninedinucleotide, had strong binding with the corresponding marker proteins (BINDING ENERGY ≤ -5.0 kJ / mol); 2 components, Artenimol and Guanosine, had moderate binding with the corresponding marker proteins (BINDING ENERGY ≤ 0 kJ / mol); 2 components, Healon and artemether, had weak binding with the corresponding marker proteins. The molecular docking results are shown in Table 7; the molecular docking mode diagrams are shown in Figure 1A to Figure 1Z .

[0111] Table 7 List of Molecular Docking Results

[0112]

[0113]

Claims

1. A screening method for skin fibroblast marker protein targeting components, characterized in that It includes the following steps: (1) Construct a list of data on membrane localization marker proteins of human skin fibroblasts: Use the The Human Skin Atlas database to obtain a set of highly expressed and highly specific proteins, and construct a list of data on highly expressed and highly specific proteins of human skin fibroblasts; (2) Obtain the targeting components of membrane localization marker proteins: Conduct target fishing to obtain the targeting components of HSF membrane localization marker proteins, and map the obtained targeting components to the INCI names and English names of cosmetic raw materials, and screen the targeting components that are included in INCI and target human skin fibroblast membrane localization marker proteins and can be applied to cosmetic formulations; (3) Chemical similarity prediction: In order to expand the reserve of targeting components of human skin fibroblast membrane localization marker proteins, based on the targeting components obtained in step (2), conduct chemical similarity prediction, and screen the predicted components using INCI to obtain chemical similarity prediction targeting components that can be applied to cosmetic formulations; (4) Molecular docking verification: Use molecular docking to verify the binding activity between the targeting components described in step (2) and the predicted components described in step (3) and the corresponding human skin fibroblast membrane localization marker proteins, so as to obtain the target targeting components.

2. The screening method of the skin fibroblast marker protein targeting component according to claim 1, characterized in that The step (1) includes the following sub-steps: S11. Based on the The Human Skin Atlas database, compare the expression levels between different samples or different proteins using the iBAQ value; S12. Use the abundance curve of endosialin as a reference to determine proteins with similar abundance patterns; S13. Take the proteins in the intersection of S11 and S12 to obtain the list of data on highly expressed and highly specific proteins of human skin fibroblasts; S14. For the proteins in the data list obtained in S13, query the subcellular localization information of the proteins one by one, and obtain the membrane localization proteins from them, and construct a list of data on human skin fibroblast membrane localization marker proteins.

3. The screening method of the skin fibroblast marker protein targeting component according to claim 1, characterized in that The step (2) includes the following sub-steps: S21. Conduct target fishing to construct a list of data on targeting components of human skin fibroblast membrane localization marker proteins: Query one by one the targeting components that can bind to the marker proteins in the data list obtained in step (1), and construct a list of data on targeting components of human skin fibroblast membrane localization marker proteins; S22. Correlate the English names of the targeting components of human skin fibroblast membrane localization marker proteins in the data list in S21 with the INCI names and English names of cosmetic raw materials, and map to obtain the targeting components that can target human skin fibroblast membrane localization marker proteins and can be applied to cosmetic formulations.

4. The screening method of the skin fibroblast marker protein targeting component according to claim 1, wherein The method of chemical similarity prediction in the step (3) is as follows: Obtain the SMILES structural formula of the component to be predicted from the PubChem database, and query and collect the comprehensive scores between drugs in the STITCH database; Divide the score by 1000 to ensure that the similarity value of chemical components is between 0 and 1, and obtain the targeting components with strong chemical similarity to the component to be predicted according to the similarity value.

5. The screening method of the skin fibroblast marker protein targeting component according to claim 1, characterized in that In the step (4), the screening criterion for the binding activity is that the binding energy ≤ -5.0 kJ / mol.

6. A skin fibroblast marker protein targeting component, characterized in that: The targeting component is obtained by screening with the method according to any one of claims 1 to 5.

7. The skin fibroblast marker protein targeting component according to claim 6, characterized in that: The targeting component is copper, hyaluronic acid, glycolic acid, nicotinamide adenine dinucleotide phosphate, guanosine-5'-triphosphate, dermatan, calcium oxalate, lithium oxalate, and / or nicotinamide adenine dinucleotide.

8. Use of the skin fibroblast marker protein targeting component according to claim 6 or 7 in the preparation of a product for evaluating the efficacy of cosmetics.

Images