Method for screening active components of salvia miltiorrhiza and ligusticum chuanxiong as tissue factor inhibitors and use thereof

Abstract

The present application relates to a kind of methods for screening active ingredients of salvia miltiorrhiza and chuanxiong as tissue factor inhibitors and purposes, comprising: according to the requirement of pharmacophore model construction, obtain small molecule compounds with inhibiting TF coagulation activity as data set, data set is split into training set and test set, construct pharmacophore with activity prediction ability;With the pharmacophore with activity prediction ability constructed from multiple active ingredients of salvia miltiorrhiza and chuanxiong Virtual screening active molecule, multiple small molecule compounds with inhibiting TF coagulation activity are screened;Determine the macromolecular compound of TF related protein from PDB database;Using molecular docking software, small molecule compounds with inhibiting TF coagulation activity are screened, and docking is carried out with the macromolecular compound of TF protein, the docking result is combined to form complex, and the result is visualized using Schrodinger, the purpose is to find new small molecule inhibitors, obtain TF inhibitor with good bioavailability.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of medicine, and particularly relates to a method for screening active components of Salvia miltiorrhiza and Ligusticum chuanxiong as tissue factor inhibitors and uses thereof. BACKGROUND

[0002] Cardiovascular disease (CVD) has become a "modern epidemic" worldwide, and the trend of increasing incidence and mortality is increasingly evident. According to recent research reports, from 1990 to 2019, the number of cases of cardiovascular disease worldwide almost doubled, from 271 million to 523 million. In the ranking of the number of deaths from cardiovascular disease in countries around the world, China ranks first. Cardiovascular disease is the leading cause of death in urban and rural areas in China in the past 20 years. In 2018, the number of deaths from cardiovascular disease in China accounted for 43.8% and 46.7% of the total number of deaths in urban and rural areas of China, respectively, higher than other diseases (e.g., cancer, respiratory disease, etc.). If no action is taken, cardiovascular disease will cause huge economic losses to China.

[0003] Tissue factor (TF), also known as coagulation factor III (F3), is a single-chain transmembrane glycoprotein with a molecular weight of 47 kD, and is the only coagulation factor present in cells and tissues other than normal human plasma. Studies have shown that when the blood is exposed to the cell surface expressing TF after the blood vessel is damaged, TF forms a complex with its ligand FⅦ or FⅦa, which in turn activates coagulation factor IX and coagulation factor X, and simultaneously initiates the extrinsic and intrinsic coagulation pathways, further activates prothrombin (FII) and fibrinogen, and then forms a blood clot with activated platelets. Therefore, TF is the most important initiator of the coagulation process. Under physiological conditions, cells in direct contact with blood do not express TF, but under pathological conditions, inflammatory mediators and certain factors stimulate (e.g., interleukins, tumor necrosis factor, thrombin, bacterial endotoxin lipopolysaccharide, etc.) to induce the expression of TF in vascular endothelial cells and mononuclear cells in the blood, thereby participating in the formation of various pathological thrombosis and playing an important role in certain thromboembolic complications of diseases (e.g., thromboembolic complications of diabetes). Therefore, tissue factor (TF) is not only an important initiator of physiological hemostasis, but also a key factor in the formation of pathological thrombosis.

[0004] Studies have shown that inflammation and thrombosis are mutually influenced and promoted, and the key factor connecting the inflammation and thrombosis network is TF. Up-regulation of TF expression activates coagulation factors FVIIa, FXa, FIIa and fibrin in succession, and they all have pro-inflammatory activity, which can stimulate various cells to express TNF, interleukins, adhesion molecules and other inflammatory signal molecules, and these inflammatory signal molecules promote the formation of "thrombus" by up-regulating TF in a feedback manner. Therefore, TF links the inflammation factor network and the thrombus factor network, promotes the formation of the "coagulation-inflammation-thrombosis circuit", and thus participates in a wide range of pathophysiological processes, including atherosclerosis, cancer, diabetes, etc., and can be considered as one of the "key nodes" in the cardiovascular disease network.

[0005] Studies have also shown that inhibiting TF or TF / FVII(a) complex is an effective anti-thrombotic mechanism, which has the following advantages: TF inhibitors can effectively prevent coagulation and thrombosis, but reduce the risk of bleeding, and have little effect on normal physiological hemostasis. Therefore, TF will become an attractive new target for the discovery of anticoagulant and anti-thrombotic drugs, and inhibitors of TF or TF / FVII(a) complex are expected to become a new generation of anti-thrombotic drugs for the prevention and treatment of pathological thrombosis and cardiovascular diseases such as atherosclerosis. At present, TF has been targeted for the treatment of various thrombotic events internationally, and different treatment strategies are being developed to inhibit TF.

[0006] Meanwhile, with the deepening understanding of the role of TF, it is found that in addition to its role in the coagulation process, TF also assumes the functions of a signal receptor and other non-coagulation functions. This makes it play an important role in systemic inflammation, coagulation disorders, atherosclerosis, tumor angiogenesis and metastasis, diabetes and other diseases. The relationship between TF's non-coagulation functions and tumor growth, invasion and metastasis is particularly noteworthy. Its expression on the surface of malignant melanoma, pancreatic cancer, breast cancer, lung cancer, colon cancer and other tumor cells and tumor vascular endothelial cells is abnormally increased. In recent years, clinical observations and in vivo and in vitro experiments abroad have confirmed that FⅦa / TF complex has the effect of promoting tumor growth, invasion and metastasis. In addition, it has been reported that TF is expressed in human Langerhans islets, and TF is found in most islet endocrine cells ("islets produce TF"), which indicates that there is a certain relationship between the secretion of TF and the secretion of insulin. This TF is likely to be related to the high incidence of atherosclerosis and cardiovascular diseases in patients with type 2 diabetes or pre-diabetic patients. Therefore, inhibitors of TF activity or synthesis can also be used to prevent and treat tumor invasion and metastasis and thromboembolic complications of diabetes. SUMMARY

[0007] The present application mainly aims at the above problems, and provides a method and use for screening active components of Danshen and Chuanxiong as tissue factor inhibitors, so as to find new small molecule inhibitors and obtain TF inhibitors with good bioavailability.

[0008] To achieve the above-mentioned purpose, the present application provides a method for screening active components of Danshen and Chuanxiong as tissue factor inhibitors, comprising the following steps:

[0009] Step 1: According to the requirement of pharmacophore model construction, obtain small molecule compounds with TF coagulation activity inhibition as a data set, split the data set into a training set and a test set, generate a pharmacophore model according to the chemical characteristics of the small molecule compounds in the training set, verify the accuracy of the pharmacophore model for the activity value of molecules outside the training set by using the small molecule compounds in the test set with known activity values, and construct a pharmacophore with activity prediction ability;

[0010] Step 2: Virtually screen active molecules from a plurality of active components of Danshen and Chuanxiong by using the constructed pharmacophore with activity prediction ability, and screen a plurality of small molecule compounds with TF coagulation activity inhibition;

[0011] Step 3: Determine the macromolecular compounds of TF related proteins from the PDB database;

[0012] Step 4: Use molecular docking software to dock the plurality of small molecule compounds with TF coagulation activity inhibition screened in step 2 with the macromolecular compounds of TF proteins, combine the docking results to form a complex, and use Schrodinger to visualize the results.

[0013] Further, the specific steps of step 1 for obtaining small molecule compounds with TF coagulation activity inhibition as a data set according to the requirement of pharmacophore model construction include:

[0014] Obtaining and screening of active components of Danshen and Chuanxiong: screening according to the pharmacokinetic parameters (ADME parameters) of the chemical components of Danshen and Chuanxiong recorded in the TCMSP database (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform), and selecting representative active components of Danshen and Chuanxiong after literature research;

[0015] The plurality of small molecule compounds with TF coagulation activity inhibition are drawn by chemdraw14 to draw the two-dimensional structure of the compound, and are converted into a three-dimensional structure, a conformation model is generated by a fast method, the conformation model is minimized by CHARMm force field, and a data set of the plurality of small molecule compounds with TF coagulation activity inhibition is obtained.

[0016] Further, step 1 specifically includes the following steps:

[0017] Selecting half of the compounds with IC50 between 0.046-5660nm and activity spanning 4 orders of magnitude as the training set, recording the activity and activity uncertainty, generating a pharmacophore model according to the chemical characteristics of the active compounds in the training set;

[0018] Using the remaining data set as the test set, recording the related activity, and using the Fisher random verification method to verify the generated pharmacophore model, setting the confidence level to 95% during verification, and constructing a pharmacophore with activity prediction ability that meets the confidence level.

[0019] Further, step 3 specifically includes the following steps: obtaining the protein three-dimensional structure of the TF / FVIIa complex that meets the conditions from the database, preprocessing the protein by discovery studio software, deleting water molecules, hydrogen and charges, extracting the original ligand in the structure, and visualizing the preprocessed protein.

[0020] Further, in step 4, the docking of the small molecule compounds screened in step 2 with the TF protein macromolecule compound includes using AUTODUCK for molecular docking, wherein the specific docking steps include:

[0021] The site where trypsin directly interacts with coagulation factor TF / FVIIa is used as the active site for docking, the center of the active site is obtained, and the radius of the active site docking sphere is set;

[0022] The ligand of the TF protein macromolecule compound, the small molecule compounds of salvia miltiorrhiza and chuanxiong, and the autodock-vina software are placed in a folder;

[0023] The prepared 3D structure of the ligand compound structure of the small molecule compound is imported into raccoon software and converted into pdbqt format and stored;

[0024] Using Autodock tools, the prepared macromolecule compound is selected as the receptor and saved as pdbqt format;

[0025] Recording and saving the docking active site, receptor name and ligand name in notepad; running autodock-vina software docking from the command window.

[0026] Further, in step 4, the way of docking the small molecule compounds with inhibitory activity of TF coagulation activity screened in step 2 with the macromolecular compound of TF protein by using molecular docking software includes: performing molecular docking by using AUTODUCK, wherein the specific docking steps include:

[0027] The binding protein of TF and FⅦ is introduced into a macromolecular window, and the small molecule compounds of salvia miltiorrhiza and ligusticum wallichii are introduced into a small molecule window;

[0028] In the parameter browser, the binding protein of TF and FⅦ with PDB ID 4YLQ is selected as the receptor protein of computer molecular docking, the small molecule compounds of salvia miltiorrhiza and ligusticum wallichii are specified as ligands of computer molecular docking, and parameters are set;

[0029] Molecular docking is performed by using the CDOCKER module in the software Discovery Studio.

[0030] Further, the active ingredient of salvia miltiorrhiza is one of the following compounds: dihydrotanshinone, cryptotanshinone, tanshinone I, tanshinone IIA, danshensu, salvianic acid A, rosmarinic acid, baicalin, salvianolic acid B.

[0031] Further, the active ingredient of ligusticum wallichii is one of the following compounds: ethyl linoleate, myricetin, ligusticum wallichii indole, ligusticum wallichii coumarin, ligusticum wallichii naphthofuran, sitosterol, folic acid, ligusticum wallichii lactone, ferulic acid, ligusticum wallichii lactone A, ligusticum wallichii, ligusticum wallichii lactone, butenyl phthalide lactone, ligusticum wallichii lactone I, ligusticum wallichii lactone A, ligusticum wallichii lactone J, ligusticum wallichii lactone L, butyl phthalide lactone.

[0032] To achieve the above object, the present application provides a verification method of TF inhibitory activity, comprising the following steps:

[0033] 4) Subculture human umbilical vein endothelial cell fusion cells in the culture medium;

[0034] 5) repeatedly blow the subcultured human umbilical vein endothelial cell fusion cells into a cell suspension, and inoculate the cell suspension into the multi-well culture plate of the blank control group, the model group and the drug administration group, respectively, add 90 μL of 0.1% DMSO solution and the culture medium in the blank control group; add 90 μL of 0.1% DMSO solution and 10 μL of tumor necrosis factor in the model group, and add 90 μL of different concentrations of TF inhibitor and 10 μL of tumor necrosis factor in the drug administration group, and incubate for a certain period of time, wherein the TF inhibitor is a small molecule compound with inhibitory activity of TF coagulation activity obtained from the active ingredients of salvia miltiorrhiza or ligusticum wallichii;

[0035] And to each hole, add FXa chromogenic substrate solution, determine the absorbance value at 405 nm with microplate reader, and obtain whether cryptotanshinone, salvianolic acid B and ligustilide can inhibit the TF activity of TNF-α induced human umbilical vein endothelial cells in a concentration-dependent manner according to the absorbance value of the sample.

[0036] To achieve the above object, the application provides a use of a small molecule compound inhibitor obtained by screening active ingredients of Danshen and Chuanxiong as tissue factor inhibitors in treating and / or preventing pathological thrombus, wherein the small molecule compound inhibitor is selected from small molecule compounds of traditional Chinese medicine Danshen and Chuanxiong and combinations thereof.

[0037] The above technical scheme of the application has the following advantages: the binding ability and inhibitory activity of active ingredients of Danshen and Chuanxiong to the key target TF of cardiovascular diseases are studied by using molecular docking and computer virtual screening (3D-QSAR) technology, effective TF inhibitors are screened from the active ingredients of traditional Chinese medicine Danshen and Chuanxiong, and TF inhibitors with good bioavailability are obtained. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 An active ingredient group of Danshen is disclosed for the embodiments of the application.

[0039] Figure 2 An active ingredient group of Chuanxiong is disclosed for the embodiments of the application.

[0040] Figure 3 A degree of matching of a test set to 10 traditional pharmacophores is disclosed for the embodiments of the application.

[0041] Figure 4 A model diagram of the pharmacophore Hypogen1 is disclosed for the embodiments of the application.

[0042] Figure 5 A chart of inhibitory effects of cryptotanshinone, salvianolic acid B and ligustilide on TF activity of TNF-α induced human umbilical vein endothelial cells (EA.hy926) is disclosed for the embodiments of the application.

[0043] Figure 6 A screening chart of inhibitory activity of active ingredients of Chuanxiong on tissue factor is disclosed for the embodiments of the application.

[0044] Figure 7 A schematic diagram of TF / FVII protein structure is disclosed for the embodiments of the application.

[0045] Figure 8 A molecular docking scoring result table of candidate ingredients of Danshen and TF protein is disclosed for the embodiments of the application.

[0046] Figure 9 A molecular docking scoring result of an active ingredient of Chuanxiong and TF protein disclosed by an embodiment of the present application.

[0047] Figure 10 A structure diagram of a representative compound of Danshen and TF protein disclosed by an embodiment of the present application.

[0048] Figure 11 A structure diagram of a representative compound of Chuanxiong and TF / F7 protein disclosed by an embodiment of the present application. DETAILED DESCRIPTION

[0049] The specific embodiments of the present application will be further described in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application, but are not used to limit the scope of the present application.

[0050] In the description of the present application, it is to be understood that the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and therefore cannot be understood as indicating or implying that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second" are only used for description purposes and cannot be understood as indicating or implying relative importance.

[0051] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection" should be understood in a broad sense, for example, it can be a fixed connection, or a detachable connection, or an integral connection; it can be a mechanical connection, or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or the internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0052] In one aspect of the present application, a method for screening active ingredients of Salvia miltiorrhiza and Chuanxiong as tissue factor inhibitors is provided. The method uses tissue factor (TF) protein as a target, and utilizes molecular docking technology and computer virtual screening technology to screen effective TF inhibitors from active ingredients of Salvia miltiorrhiza and Chuanxiong. The TF inhibitors screened by the method for preparing TF inhibitors have good binding capacity and strong inhibitory effect, and can be used to prevent and treat human diseases affected by tissue factor. In the method of the present application, TF-related diseases refer to cardiovascular and cerebrovascular diseases, coagulation disorders, sepsis, tumor metastasis, and diabetes and related cardiovascular disease complications. The cardiovascular and cerebrovascular diseases are angina pectoris, atherosclerosis, stroke, pulmonary embolism, deep vein thrombosis, or other coronary artery diseases.

[0053] The TF inhibitors screened by the method of the present application have good bioavailability, and therefore can be widely promoted in a short period of time in China.

[0054] The present application provides a method for screening active ingredients of Salvia miltiorrhiza and Chuanxiong as tissue factor inhibitors, comprising the following steps:

[0055] Step 1: According to the requirement of pharmacophore model construction, obtain small molecule compounds with TF coagulation activity as a data set, split the data set into a training set and a test set, generate a pharmacophore model according to the chemical characteristics of the small molecule compounds in the training set, and verify the accuracy of the pharmacophore model for the activity values of molecules outside the training set using the small molecule compounds in the test set with known activity values, and construct a pharmacophore with activity prediction ability.

[0056] In this embodiment, the specific steps for constructing a pharmacophore (Hypogen) with activity prediction ability include: testing 33 small molecule compounds with TF coagulation activity in the early stage, removing 7 compounds without activity, then supplementing 13 compounds with TF coagulation activity by consulting literature, and arranging 39 active compounds.

[0057] Examples of the above-mentioned 33 small molecule compounds with TF coagulation activity include 12 flavonoids, 11 alkaloids, and 10 saponins.

[0058] The 39 active compounds are drawn into 2D chemical structure formula by chemdraw14, and then converted into 3D structure and saved as pdb format. Then they are imported into discovery studio2016 for energy minimization. Considering the structure and activity diversity, 24 active compounds (half maximal inhibitory concentration IC 50:0.046~5660nm, active span 4 quantity set) as a training set, named train, record the activity value (Active) and activity uncertainty.

[0059] In order to determine the accuracy of the constructed pharmacophore model in screening compounds, the remaining 15 compounds were used as a test set, named test, and their related activities and logactiv values were recorded. The training set was matched with five pharmacophore feature elements: hydrogen bond acceptor (HBA), hydrogen bond donor (HBD), positive charge center (PI), hydrophobic center (HY), and hydrogen bond aromatic ring center (HYDA), resulting in 10 hypothetical models as shown in Figure 3 The model was verified by Fisher random verification (confidence set to 95%).

[0060] The predicted activity of the Hypo1 model for the test set was similar to the experimental value. Using Ligand Profiler to match the test set with the pharmacophore (see Figure 3 ), it can be clearly seen that the matching degree of the pharmacophore Hypogen1 is the best, among which the correlation coefficient and total difference value of the Hypogen1 model are higher, and the root mean square error is lower. The matching degree for the high-activity compound Acetonylberberine (half-inhibitory concentration IC 50 : 0.046nM) is good (see Figure 4 -A), and the matching degree for the low-activity compound Luteolin (half-inhibitory concentration IC 50 : 1000000nM) is poor (see Figure 4 -B), so this model is selected for further evaluation.

[0061] Step 2: Use the constructed pharmacophore with activity prediction ability to virtually screen active molecules from multiple active components of Salvia miltiorrhiza and Chuanxiong.

[0062] As an example in this step 2, the above-mentioned Hypogen1 pharmacophore model with the best matching degree is used to predict the activity of Chinese medicine Chuanxiong active ingredients input into discovery studio 2016, and the half-inhibitory concentration IC 50 of Chuanxiong active ingredients inhibiting TF activity is obtained, see Figure 6 . As can be seen from Figure 6 , 18 active ingredients of Chuanxiong have good inhibitory activity on TF, among which 13 active ingredients have strong inhibitory activity on TF (their half-inhibitory concentration IC 50 value ≦ 1μM). It is further proved that the main active ingredients of Chuanxiong may play a role in treating related cardiovascular diseases by inhibiting the activity of TF.

[0063] It is worth noting that the TCMSP database includes 210 chemical components of Danshen, 45 of which meet the screening conditions (OB% ≥ 30 and DL ≥ 0.18, Caco-2 ≥ -0.4). After consulting the literature, 9 representative active components of Danshen were selected. The names of the active components and part of the ADME parameters and structural formulas are shown in Table 1. Figure 1 .

[0064] In the method of the present application, as shown in Figure 1 , the active components of Danshen are one of the following compounds: dihydrotanshinone, cryptotanshinone, tanshinone I, tanshinone IIA, danshensu, salvianic acid A, rosmarinic acid, baicalin, and salvianolic acid B.

[0065] The TCMSP database includes 189 chemical components of Chuanxiong, 7 of which meet the screening conditions (OB% ≥ 30% and DL ≥ 0.18). A total of 11 active components reported in the literature that are beneficial for treating thrombosis were integrated, and 18 chemical components were selected as the effective components of Chuanxiong. The names of the active components and ADME parameters and structural formulas are shown in Table 2. Figure 2 .

[0066] In the method of the present application, as shown in Figure 2 , the active components of Chuanxiong are one of the following compounds: ethyl linoleate, myricetin, chuanxiongindole, chuanxiong quinone, chuanxiong naphthofuranide, sitosterol, folic acid, ligustrazine, ferulic acid, chuanxiong lactone A, chuanxiong lactone, butenyl phthalide lactone, chuanxiong lactone I, angelica lactone A, chuanxiong lactone J, chuanxiong lactone L, and butyl phthalide lactone.

[0067] Step 3: Determine the macromolecular compounds of TF-related proteins from the PDB database.

[0068] In the step of the present embodiment, TF-related protein searching and preprocessing are included. Specifically, the three-dimensional structure of the TF-related protein is downloaded from the PDB database (https: / / www.rcsb.org / ), which includes the data of most of the reported biological macromolecular crystals, including the crystal complexes of biological macromolecules and active small molecules. The protein crystal structure of the TF / FVIIa complex is screened according to the following conditions: 1. The resolution of the protein is less than 3A; 2. The protein structure contains a crystal complex of small molecules; 3. The protein does not contain a mutated amino acid site.

[0069] Subsequently, the protein is preprocessed by the discovery studio software, the water molecules, hydrogen, and charges are deleted, the original ligand in the structure is extracted, and the visualization of the processed protein is performed by pymol.

[0070] Because the TF protein is prone to form crystal complexes with small molecules, after comparing the proteins related to TF in the RCSB database, the binding protein of TF and FVII with PDB ID 4YLQ is selected, and the specific crystal structure of the protein is as follows Figure 7 The PDB ID of the protein is: 4YLQ.

[0071] Step 4: Use molecular docking software to dock the small molecule compounds screened in step 2 with the macromolecular compound of the TF protein, combine the docking results to form a complex, and use Schrodinger to visualize the results.

[0072] Examples of the above at least one molecular docking software include using AUTODUCK for molecular docking, which includes the following steps:

[0073] Selection of active site: The binding of TF and FVIIa promotes the allosteric conformational change of the FVIIa protease domain, improves the catalytic performance of the FVIIa protease, and activates blood coagulation. The use of X-ray crystallography found that the trypsin loop is directly connected to the active site of FVIIa, which further stabilizes the 215-217 amino acids, resulting in increased activity. Therefore, the site where trypsin directly interacts with FVIIa is selected as the active site, and the center coordinates of the site are obtained, and then the radius of the docking sphere is set.

[0074] Autodock-vina molecular docking first places the prepared macromolecule (TF protein), ligand (small molecule compounds of Danshen and Chuanxiong), and vina (autodock-vina software) into a folder; secondly, the prepared ligand compound structure (3D structure of small molecule compounds) is imported into raccoon software to batch convert to pdbqt format and stored; use Autodock tools to select the prepared macromolecule as the receptor and save it as pdbqt format; use Notepad to record and save the docking active site, receptor name and ligand name; run vina docking from the command window; use pymol to combine the docking results to form a complex, and then use Schrodinger to visualize the results.

[0075] Examples of the above at least one molecular docking software include using CDOCKE for molecular docking, which includes the following steps:

[0076] Firstly, the prepared TF / FVIIa complex protein was introduced into a macromolecular window, and then all the prepared small molecule compounds of Salvia miltiorrhiza and Chuanxiong were introduced into a small molecule window. In the parameter browser, the TF and FⅦ binding protein with PDB ID 4YLQ was selected as the receptor protein for computer molecular docking, and the small molecule compounds of Salvia miltiorrhiza and Chuanxiong were selected as the ligand for computer molecular docking. The parameters were set, and the CDOCKER module in Discovery Studio software was used for molecular docking.

[0077] Both AUTODUCK-vina and the CDOCKER module in Discovery Studio are semi-flexible docking, and the score and interaction energy results are shown in Figure 8 and Figure 9 According to the literature, the docking score of AUTODUCK-vina less than -7.0 indicates that the target has strong binding ability with TF / FVIIa complex, and the score less than -5.0 greater than -7.0 indicates that the compound small molecule has good binding ability with the target, and the score between -5.0 and -4.25 indicates that the compound has certain binding ability with the macromolecular target.

[0078] The results of molecular docking show that the docking scores of 9 active components of Salvia miltiorrhiza with TF / FVIIa complex are almost less than -7, indicating that the main active components of Salvia miltiorrhiza have strong binding energy with TF protein. Among the 18 active components of Chuanxiong, 8 components have docking scores between -7 and -5 with TF / FVIIa complex, indicating that these 8 components have good binding ability with TF / FVIIa complex; 10 components such as myricetin, chuanxiong indole and angelica lactone A have docking scores less than -7 with TF / FVIIa complex, indicating that these components have strong binding ability with TF / FVIIa.

[0079] Figure 10- Figure 11 Several representative components with high scores were selected for analysis of the results of molecular docking.

[0080] It should be noted that, Figure 10 A is the binding of salvianolic acid B and 4YLQ; B is the force diagram of the interaction between salvianolic acid B and the amino acid residues on 4YLQ; C is the binding of tanshinone ⅡA and 4YLQ; D is the force diagram of the interaction between tanshinone ⅡA and the amino acid residues on 4YLQ; E is the binding of huangcensin and 4YLQ; F is the force diagram of the interaction between huangcensin and the amino acid residues on 4YLQ; G is the binding of cryptotanshinone and 4YLQ; H is the force diagram of the interaction between cryptotanshinone and the amino acid residues on 4YLQ.

[0081] It should be noted that, Figure 11A is the schematic diagram of the binding of 4YLQ and the force of the amino acid residues of ligustilide; B is the schematic diagram of the binding of 4YLQ and the force of the amino acid residues of folic acid; C is the schematic diagram of the binding of 4YLQ and the force of the amino acid residues of angelica lactone A; and D is the schematic diagram of the binding of 4YLQ and the force of the amino acid residues of senkyunolide I.

[0082] From Figure 10 , Figure 11 It is found that the cavities of the monomer compounds in the middle of the protein bind to the TF-related protein, and the amino acid residues that bind more are serine (SER) and leucine (LEU) residues, and the interactions of binding are hydrogen bonds, van der Waals forces, hydrophobic interactions, etc.

[0083] In the following examples, whether some representative compounds have inhibitory effect on the TF activity of human umbilical vein endothelial cell line (EA.hy926) is verified as an example.

[0084] As an example of the verification of the present embodiment, a verification method of TF inhibitory activity is provided, which comprises the following steps:

[0085] 1) Subculturing human umbilical vein endothelial cell fusion cells in the culture medium;

[0086] EA.hy926 is a human umbilical vein endothelial cell fusion cell line, which is cultured according to the Chinese Academy of Sciences typical culture instructions, and its complete culture medium is configured as follows: 90% DMEM / F12 (containing 2 mM L-glutamine) + 10% fetal bovine serum + 1% streptomycin / penicillin, and the culture environment is at 37°C, 5% CO2.

[0087] 2) Repeatedly blowing the subcultured human umbilical vein endothelial cell fusion cells EA.hy926 into a cell suspension, and inoculating 100 μL of the cell suspension in each well of a 96-well culture plate at a density of 1.5×105 cell / mL, and culturing at 37°C, 5% CO2 for 24 h to form a fusion state.

[0088] Before verification, the test is divided into three groups, the above-mentioned fusion state of cell suspension is inoculated in the blank control group, model group, drug group of multi-well culture plate, in the blank control group, 90 μL of 0.1% DMSO solution (solvent) and medium are added; in the model group, 90 μL of 0.1% DMSO solution (solvent) and 10 μL tumor necrosis factor (TNF-α, final concentration is 10 ng / mL) are added, and incubated for 4 hours to stimulate the expression of TF; in order to observe whether the TF inhibitor has inhibitory effect, in the drug group, 90 μL of different concentrations of TF inhibitor is added first, and then 10 μL of tumor necrosis factor TNF-α (10 ng / mL) is added, and incubated for 4 hours, wherein the TF inhibitor is a small molecule compound with inhibitory activity of TF coagulation obtained from the active ingredients of salvia miltiorrhiza or ligusticum wallichii.

[0089] As an example of the above-mentioned TF inhibitor, it can be ligustilide, salvianolic acid B, cryptotanshinone, etc., the TF inhibitor is first dissolved in pure DMSO solution (solvent), and a high concentration mother liquor with a concentration of 100 mmol / L is prepared, and then diluted to the required concentration with DMEM / F12 medium before use, and the final volume fraction of DMSO solution (solvent) is 0.1%.

[0090] Specifically, EA.hy926 cells (1.5×10 5 cell / mL) are incubated with cryptotanshinone (0.1, 1 and 10 μM), salvianolic acid B (0.1, 1 and 10 μM) and ligustilide (1, 3 and 10 μM) for 1 hour, and then stimulated with tumor necrosis factor TNF-α (10 ng / mL) for 4 hours to induce TF expression.

[0091] 3) and add FXa chromogenic substrate solution to each well, and measure the absorbance value at 405 nm with an enzyme marker, and according to the absorbance value of the sample, it can be determined whether cryptotanshinone, salvianolic acid B and ligustilide can inhibit the TF activity of TNF-α induced human umbilical vein endothelial cells in a concentration-dependent manner within a certain concentration range.

[0092] In step 3) of the present application, the activated Xa of TF-Ⅶa complex can decompose the chromogenic substrate into polypeptide and p-nitroaniline (PNA), and the latter has an absorption peak at 405 nm. The absorbance (OD) value at 405 nm is measured by enzyme marker, and the change of absorbance of PNA at 405 nm is proportional to the activity of TF enzyme, and the value can reflect the activity level of TF.

[0093] The specific operation steps of the method (refer to TF activity detection kit Assaypro, St. Charles, MO, USA) are as follows:

[0094] After the TF inhibitor is incubated with tumor necrosis factor TNF-α for 4 hours, the culture medium in the cell plate is removed, 25 μL of lysis solution (15 mM n-octyl-β-D-glucopyranoside) is added to each well, and the sample is collected in a centrifuge tube after lysis for 15 minutes. 70 μL of assay diluent (Human Factor VII: Human Factor X = 5:1:1) is added to each well of the detection plate, the plate is gently tapped to ensure that the microwells are completely covered. 10 μL of sample is added to each well. Gently tap to ensure thorough mixing and eliminate air bubbles. Cover the microwells with sealing tape, and incubate in a humidity incubator at 37°C for 30 minutes. Then, prepare the FXa chromogenic substrate solution according to the instructions, and add 20 μL of the FXa chromogenic substrate solution to each well, gently tap the plate to ensure thorough mixing and eliminate air bubbles, and read the absorbance value at 405 nm. After each reading, incubate at 37°C, and read the absorbance at 405 nm every 5 minutes for 35 minutes.

[0095] All data are expressed as mean ± standard deviation, and analysis of variance and t-test are used for comparison between groups. P<0.05 is considered statistically significant.

[0096] The above examples select three representative compounds for in vitro activity experiment verification. The three representative compounds are: cryptotanshinone, salvianolic acid B and ligustilide. In vitro activity experiments are used to investigate whether they can inhibit the TF activity of EA.hy926 endothelial cells induced by tumor necrosis factor TNF-α. The experimental results show that after the human umbilical vein endothelial cell line EA.hy926 is acted on by tumor necrosis factor TNF-α (the final concentration is 10 ng / mL), the TF activity can be significantly increased; and cryptotanshinone, salvianolic acid B and ligustilide can all inhibit the TF activity of EA.hy926 endothelial cells induced by tumor necrosis factor TNF-α in a concentration-dependent manner within a certain concentration range, which is consistent with the result of computer virtual screening, and the result is shown in Table 1. Figure 5 In Table 1, # indicates p<0.01 compared with the normal group; and ** indicates p<0.01 compared with the TNF-α-induced model group. Figure 5

[0097] In the present application, another important finding is that TF is likely to be related to the high incidence of atherosclerosis and cardiovascular diseases in patients with type II diabetes or pre-diabetic patients. Therefore, the small molecule compound inhibitor obtained by the method for screening active ingredients of Danshen and Chuanxiong as tissue factor inhibitors in the present example has the use for treating and / or preventing pathological thrombosis, wherein the small molecule compound inhibitor is selected from: small molecule compounds of traditional Chinese medicines Danshen and Chuanxiong and combinations thereof.

[0098] ​It should be noted that the various embodiments described in the present application and / or technical features in various embodiments can be combined with each other in any manner without conflict, and the technical scheme obtained after combination shall also fall within the protection scope of the present application. It should be understood that in various embodiments of the present application, the size of the serial number of the above processes does not mean the order of execution, and the execution order of the processes shall be determined according to its function and inherent logic, and shall not constitute any limitation on the implementation process of the embodiments of the present application.

[0099] The above only describes the preferred embodiments of the present application, and it should be noted that for ordinary skilled persons in the art, several improvements and modifications can be made without departing from the technical principles of the present application, and these improvements and modifications shall also be regarded as the protection scope of the present application.

Claims

1. A method for screening active components of Danshen and Chuanxiong as tissue factor inhibitors, characterized in that, Includes the following steps: Step 1: Based on the requirements for pharmacophore model construction, obtain small molecule compounds with TF coagulation activity as a dataset, split the dataset into a training set and a test set, generate a pharmacophore model based on the chemical characteristics of the small molecule compounds in the training set, and use the small molecule compounds in the test set with known activity values ​​to verify the accuracy of the pharmacophore model for molecular activity values ​​outside the training set, thus constructing a pharmacophore model with activity prediction capabilities. Step 2: Using a constructed pharmacophore with activity prediction capabilities, active molecules were virtually screened from multiple active components of Danshen and Chuanxiong, and several small molecule compounds with inhibitory TF coagulation activity were obtained. Step 3: Identify the macromolecular compounds of TF-related proteins from the PDB database; Step 4: Use molecular docking software to dock multiple small molecule compounds with TF coagulation inhibitory activity obtained in Step 2 with macromolecular compounds of TF protein, combine the docking results to form complexes, and use Schrödinger to visualize the results; Step 1, based on the requirements for constructing the pharmacophore model, involves obtaining small molecule compounds with inhibitory TF coagulation activity as the dataset. The specific steps include: Acquisition and screening of active ingredients of Danshen and Chuanxiong: The pharmacokinetic parameters of chemical components of Danshen and Chuanxiong included in the TCMSP database were screened, and representative active ingredients of Danshen and Chuanxiong were selected after literature review. The two-dimensional structures of several small molecule compounds with TF-inhibiting coagulation activity were drawn using ChemDraw 14 and transformed into three-dimensional structures. A conformational model was generated using a fast method, and the conformational model was minimized using the CHARMm force field to obtain a dataset of several small molecule compounds with TF-inhibiting coagulation activity. Step 1 specifically includes the following steps: Active compounds with half-maximal inhibitory concentrations between 0.046 and 5660 nm and activities spanning four order of magnitudes were selected from the dataset as a training set. Activity values ​​and activity uncertainties were recorded, and pharmacophore models were generated based on the chemical characteristics of the active compounds in the training set. The active compounds in the remaining dataset were used as the test set. The relevant activities were recorded, and the generated pharmacophore model was validated using Fisher random validation. The confidence level was set to 95% during validation. A pharmacophore model with activity prediction capability that meets the confidence level condition was constructed.

2. The method for screening active components of Danshen and Chuanxiong as tissue factor inhibitors as described in claim 1, characterized in that, Step 3 specifically includes the following steps: obtaining the three-dimensional structures of relevant proteins of the TF / FVIIa complex that meet the conditions from the database, preprocessing the proteins using Discovery Studio software to remove water molecules, hydrogen atoms, and charges, extracting the proligands from the structures, and visualizing the preprocessed proteins.

3. The method for screening active components of Danshen and Chuanxiong as tissue factor inhibitors as described in claim 1, characterized in that, In step 4, the method of docking the multiple small molecule compounds with inhibitory TF coagulation activity obtained in step 2 with the large molecule compounds of TF protein using molecular docking software includes: molecular docking using AutoDuck, wherein the specific docking steps include: The site where trypsin directly interacts with coagulation factor TF / FVIIa is used as the docking active site to obtain the center of the active site, and the radius of the docking sphere of the active site is set. Place the macromolecular compounds of TF protein, the ligands of the small molecule compounds of Danshen and Chuanxiong, and the autodock-vina software into a folder; Import the prepared 3D structures of small molecule compounds and their ligand compound structures into the RACCOON software for batch conversion into pdbqt format and save. Use Autodock tools to select the prepared macromolecular compound as the receptor and save it in pdbqt format; Record and save the docking active site, receptor name, and ligand name using Notepad; run the autodock-vina software from the command window to dock.

4. The method for screening active components of Danshen and Chuanxiong as tissue factor inhibitors as described in claim 1, characterized in that, In step 4, the method of docking the multiple small molecule compounds with TF-inhibiting coagulation activity screened in step 2 with the large molecule compounds of TF protein using molecular docking software includes: molecular docking using CDOCKER, wherein the specific docking steps include: The binding protein of TF and FⅦ was introduced into a macromolecular window, and the small molecule compounds of Danshen and Chuanxiong were introduced into a small molecule window; In the parameter browser, select the TF-FⅦ binding protein with PDB ID 4YLQ as the acceptor protein for computer molecular docking, specify the small molecule compounds of Danshen and Chuanxiong as the ligands for computer molecular docking, and set the parameters. Molecular docking was performed using the CDOCKER module in Discovery Studio software.

5. The method for screening active components of Danshen and Chuanxiong as tissue factor inhibitors as described in claim 1, characterized in that, The active ingredient of tanshinone is one of the following compounds: dihydrotanshinone, cryptotanshinone, tanshinone I, tanshinone IIA, tanshinone neoketone, tanshinone, rosmarinic acid, baicalin, and salvianolic acid B.

6. The method for screening active components of Danshen and Chuanxiong as tissue factor inhibitors as described in claim 1, characterized in that, The active ingredient of Ligusticum chuanxiong is one of the following compounds: ethyl linoleate, myricetin, ligustodole, ligustoquinone, ligustodole-naphthol lactone, sitosterol, folic acid, ligustilide, ferulic acid, ligustodole-lactone A, ligustrazine, ligustodole, butylphthalide, ligustodole-lactone I, angelica lactone A, ligustodole-lactone J, ligustodole-lactone L, and butylphthalide.

7. A method for verifying TF inhibitory activity using an inhibitor obtained based on the method described in claims 1-6, characterized in that, Includes the following steps: 1) Passage and culture human umbilical vein endothelial cell fusion cells in culture medium; 2) Human umbilical vein endothelial cell fusion cells were repeatedly pipetted into a cell suspension. The cell suspension was then seeded into multi-well culture plates of the blank control group, model group, and drug treatment group, respectively. 90 μL of 0.1% DMSO solution and culture medium were added to the blank control group; 90 μL of 0.1% DMSO solution and 10 μL of tumor necrosis factor were added to the model group; and 90 μL of different concentrations of TF inhibitors and 10 μL of tumor necrosis factor were added to the drug treatment group. The cells were incubated together for a certain period of time. The TF inhibitors were small molecule compounds with TF-inhibiting coagulation activity obtained from the active components of Danshen or Chuanxiong. 3) Add FXa chromogenic substrate solution to each well and measure the absorbance at 405 nm using an enzyme-linked immunosorbent assay (ELISA) reader. Based on the absorbance of the sample, determine whether cryptotanshinone, salvianolic acid B, and ligustilide can inhibit TNF-α-induced TF activity in human umbilical vein endothelial cells in a concentration-dependent manner within a certain concentration range.

Images