Novel antifungal compound targeting glycosyl phosphatidylinositol acylation mechanism

Abstract

The invention provides a compound for targeted inhibition of a fungal glycosyl phosphatidylinositol acetylation process. The compound can be used for treating fungal infection. The compound is competitively combined with acetyl coenzyme A or a derivative thereof in an active pocket of fungal glycosyl phosphatidylinositol anchoring protein Gwt1, so that the acetylation process of fungal glycosyl phosphatidylinositol is inhibited, and abnormal synthesis of fungal cell walls is caused. Compared with the existing antifungal drugs, the compound provided by the invention has higher antifungal activity and broad spectrum.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine, and more particularly to a compound for targeting and inhibiting the glycosylphosphatidylinositol acylation process for the treatment of fungal infections. Background Art

[0002] Invasive fungal infection is one of the most common nosocomial bloodstream infections, with an incidence rate of approximately six per 100,000 and an average mortality rate of 27.6%. With factors such as the long-term application of organ transplantation, tumor chemotherapy, cell therapy, and high-dose broad-spectrum antibacterial drugs, as well as the widespread use of glucocorticoids and immunosuppressants, the incidence and mortality of invasive fungal infections show a significant increasing trend year by year. The main pathogens causing invasive fungal infections include Candida and Aspergillus. In China, the incidence and mortality of Candida are 0.32% and 36.6 - 60% respectively, while the incidence and mortality of Aspergillus are 0.29 - 14% and 62 - 100% respectively.

[0003] Currently, the antifungal treatment in China mainly relies on azole drugs, including fluconazole, itraconazole, voriconazole, and amphotericin B, etc. However, these drugs have certain limitations. For example, fluconazole is naturally resistant to Candida krusei and has no inhibitory activity against filamentous fungi; itraconazole and voriconazole are ineffective against zygomycetes; amphotericin B has poor inhibitory effects on Candida lusitaniae and Aspergillus terreus; caspofungin is also ineffective against Cryptococcus, Fusarium, and zygomycetes. The continuous emergence of drug-resistant strains has made the treatment of invasive fungal infections more and more complicated. For example, Candida guiliermondii shows significant resistance to fluconazole and voriconazole (Pfaller MA, et al. J. Clin. Microbiol. 2010, 48, 1366 - 1377). In addition, Candida auris is a multi-drug resistant Candida, and in addition to fluconazole and voriconazole, it also shows strong resistance to other azole drugs (such as amphotericin B and echinocandins) (Chowdhary A, et al. PLoS Pathog. 2017, 13, e1006290). Investigations show that only 0.6% of Candida albicans in China is sensitive to voriconazole, while more than 96% of Candida glabrata is resistant to voriconazole (Guo F, et al. Antimicrob. Chemother. 2013, 68, 1660 - 1668).

[0004] The widespread use of azole compounds as fungal fungicides in agriculture has led to the emergence of azole-resistant strains of Aspergillus, such as Aspergillus fumigatus (Lockhart SR, et al. Antimicrob. Agents Chemother. 2011, 55, 4465-4468). Given the limited availability of current antifungal drugs and their significant side effects, coupled with the increasing problem of drug resistance, there is an urgent need to develop a new generation of highly effective, broad-spectrum, and safe antifungal drugs.

[0005] The fungal cell wall is a complex polysaccharide structure, and its integrity is crucial for the survival of fungi. The absence of the cell wall leads to the rupture of the fungal plasma membrane and cell lysis. In addition, the fungal cell wall is not only closely related to the survival and differentiation of fungi but also involved in important functions such as stress adaptation and immune escape. Therefore, the fungal cell wall is regarded as an ideal target for the development of antifungal drugs. Currently, drugs targeting the fungal cell wall mainly include echinocandins targeting β-1,3-glucan synthase (such as caspofungin) and nikkomycin targeting chitin synthase. However, the short half-life of these drugs and the continuous emergence of drug-resistant strains limit their clinical applications.

[0006] The proteins on the outer layer of the fungal cell wall are mainly linked to the more flexible β-1,6-glucan part in the glucan layer through the mannose residues of glycosylphosphatidylinositol (GPI), thus being anchored to the glucan layer of the fungal cell wall. Therefore, these proteins are called glycosylphosphatidylinositol-anchored proteins (GPI-anchored proteins). GPI-anchored proteins are not only important components of the fungal cell wall, responsible for maintaining physiological functions such as the morphology of fungi, the stability and regeneration of the cell wall, but also play key roles in multiple aspects of fungal infection, such as adhesion, hyphal growth, biofilm formation, and the perception of external stress (Kinoshita T, et al. J. Lipid Res. 2016, 57, 6-24). There are a large number of GPI-anchored proteins in the fungal cell wall, with more than a hundred species. However, the specific functions of the vast majority of GPI-anchored proteins are not yet clear. Therefore, the inhibition of one or a few GPI-anchored proteins has limited effects on the fungal cell wall. Then, the inhibition of GPI anchor synthesis is regarded as a novel strategy for the development of antifungal drugs.

[0007] The earliest research on inhibitors of glycosylphosphatidylinositol (GPI) anchor synthesis was conducted by scientists from Eisai Co., Ltd. and the National Institute of Advanced Industrial Science and Technology (AIST) in Japan. Through phenotypic screening of GPI-anchored proteins in the cell wall of Saccharomyces cerevisiae, they found that 1-(4-butylphenyl)isoquinoline could effectively inhibit the synthesis of GPI anchors (Tsukahara K, et al. Microbiol. 2003, 48, 1029-1042). Based on this, Eisai Co., Ltd. optimized the structure of 1-(4-butylphenyl)isoquinoline using techniques such as compound library screening and successfully obtained a series of aminopyridine compounds that showed excellent inhibitory activity against Candida albicans and Aspergillus fumigatus (WO2005 / 033079, US 7691882). After further structure optimization, the company developed the heterocyclic-substituted aminopyridine compound E1210 (Watanabe NK, et al. Antimicrob. Agents Chemother. 2012, 56, 960-971), which was then transferred to Amplys Pharmaceuticals and renamed APX001A (WO 2019 / 113542, WO 2020 / 247804). In addition, scientists from the Whitehead Institute for Biomedical Research in the United States found through high-throughput screening that Gepinacin could effectively inhibit the synthesis of GPI anchors (McLellan CA, et al. ACS Chem. Biol. 2012, 7, 1520-1528). In 2014, the Second Military Medical University of the Chinese People's Liberation Army also reported a class of aminopyridine compounds that showed relatively broad antifungal activity in in vitro experiments (CN103980264). Summary of the Invention

[0008] To solve the above problems, the present invention provides a compound that can be used to treat fungal infections.

[0009] The present invention provides a compound or its stereoisomer, tautomer, solvate, hydrate, prodrug, stable isotope derivative, and pharmaceutically acceptable salt, wherein the compound is any one of the following: 、 。

[0010] On the other hand, the present invention provides a pharmaceutical composition comprising the aforementioned compound or its stereoisomer, tautomer, solvate, hydrate, prodrug, stable isotope derivative, and pharmaceutically acceptable salt.

[0011] In certain embodiments, the unit dose of the pharmaceutical composition is 0.001 mg - 1000 mg.

[0012] In certain embodiments, based on the total weight of the composition, the pharmaceutical composition contains 0.01% - 99.99% of the aforementioned compound. In certain embodiments, the pharmaceutical composition contains 0.1% - 99.9% of the aforementioned compound. In certain embodiments, the pharmaceutical composition contains 0.5% - 99.5% of the aforementioned compound. In certain embodiments, the pharmaceutical composition contains 1% - 99% of the aforementioned compound. In certain embodiments, the pharmaceutical composition contains 2% - 98% of the aforementioned compound.

[0013] In certain embodiments, based on the total weight of the composition, the pharmaceutical composition contains 0.01% - 99.99% of a pharmaceutically acceptable carrier, diluent, or excipient. In certain embodiments, the pharmaceutical composition contains 0.1% - 99.9% of a pharmaceutically acceptable carrier, diluent, or excipient. In certain embodiments, the pharmaceutical composition contains 0.5% - 99.5% of a pharmaceutically acceptable carrier, diluent, or excipient. In certain embodiments, the pharmaceutical composition contains 1% - 99% of a pharmaceutically acceptable carrier, diluent, or excipient. In certain embodiments, the pharmaceutical composition contains 2% - 98% of a pharmaceutically acceptable carrier, diluent, or excipient.

[0014] All compounds involved in the present invention and mixtures, compositions, etc. containing the compounds of the present invention can be administered into a living body via any administration route. The administration route can be oral administration, intravenous injection, intramuscular injection, subcutaneous injection, rectal administration, vaginal administration, sublingual administration, nasal inhalation, oral inhalation, eye drops, or topical or systemic transdermal administration.

[0015] All compounds involved in the present invention, as well as mixtures, compositions, etc. containing the compounds of the present invention, can be formulated into single doses, which contain the active compounds of the present invention as well as carriers, excipients, etc. The dosage forms for administration can be tablets, capsules, injections, granules, powders, suppositories, pills, creams, pastes, gels, powders, oral solutions, inhalants, suspensions, dry suspensions, patches, lotions, etc. These dosage forms can contain components commonly used in pharmaceutical preparations, such as diluents, absorbents, wetting agents, binders, disintegrants, coloring agents, pH regulators, antioxidants, bacteriostatic agents, isotonicity regulators, anti-adhesion agents, etc.

[0016] Suitable formulations for the above-mentioned various dosage forms can be obtained from public sources, such as Remington: The Science and Practice of Pharmacy, 21st Edition, published by Lippincott Williams & Wilkins in 2006 and Rowe, Raymond C. Handbook of Pharmaceutical Excipients, Chicago, Pharmaceutical Press in 2005. Therefore, those skilled in the art can easily prepare them.

[0017] According to factors such as the nature and intensity of the diseases suffered by different individuals, the age, gender, and weight of the patients, and the route of administration, different dosages can be selected. The dosage of the compounds of the present invention can be 0.01 to 500 mg / kg per day, preferably the daily dosage is 1 - 100 mg / kg, and it can be administered once or multiple times.

[0018] The present invention also provides the compounds of the present invention or their stereoisomers, tautomers, solvates, hydrates, prodrugs, stable isotope derivatives, and pharmaceutically acceptable salts, or the aforementioned pharmaceutical compositions, which are used for treating fungal infections.

[0019] In certain embodiments, the fungal infections are caused by fungal species selected from the following group: Candida, Cryptococcus, Aspergillus, Rhizopus, Blastomyces, Histoplasma, and Sporothrix; preferably from Candida, Cryptococcus, and Aspergillus.

[0020] The present invention also provides the compounds of the present invention or their stereoisomers, tautomers, solvates, hydrates, prodrugs, stable isotope derivatives, and pharmaceutically acceptable salts, or the aforementioned pharmaceutical compositions, which are used for treating diseases related to fungal infections.

[0021] In certain embodiments, the fungal infection-related diseases are selected from aspergillosis, blastomycosis, candidiasis, coccidioidomycosis, cryptococcosis, fungal eye infections, histoplasmosis, mucormycosis, pneumocystis pneumonia, sporotrichosis, and talaromycosis; preferably selected from candidiasis, cryptococcosis, and aspergillosis.

[0022] Term Explanation: Unless otherwise stated, the terms used in the specification and claims have the following meanings.

[0023] The term "stereoisomer" refers to compounds having the same chemical structure but different spatial arrangements of atoms or groups. Stereoisomers include enantiomers, conformational isomers (rotational isomers), geometric (cis / trans) isomers, atropisomers, etc.

[0024] The term "tautomer" refers to structural isomers of different energies that can interconvert via a low energy barrier. For example, proton tautomers (also known as proton-transfer tautomers) include interconversions via proton migration, such as keto-enol and imine-enamine, lactam-lactim isomerization, pyrazolyl isomerization, etc.

[0025] The term "isotope derivative" refers to a compound that differs in structure only by the presence of one or more isotopically enriched atoms. For example, replacing hydrogen with "deuterium" or "tritium", or 18 F-fluorine labeling ( 18 F isotope) instead of fluorine, or using 11 C-, 13 C-, or 14 C-enriched carbon ( 11 C-, 13 C-, or 14 C-carbon labeling; 11 C-, 13 C-, or 14 C-isotope) instead of a carbon atom in a compound.

[0026] The term "pharmaceutical composition" refers to a mixture containing one or more of the compounds described herein or their physiologically / pharmaceutically acceptable salts or prodrugs, along with other chemical components, as well as other components such as physiologically / pharmaceutically acceptable carriers and excipients. The purpose of the pharmaceutical composition is to facilitate administration to an organism, promote absorption of the active ingredient, and thereby exert its biological activity.

[0027] The term "pharmaceutically acceptable salt" refers to salts of the compounds of the present invention that are safe and effective when used in mammals and have the appropriate biological activity. The salts can be prepared separately during the final isolation and purification of the compounds or by reacting suitable groups with suitable acids or bases. Bases commonly used to form pharmaceutically acceptable salts include inorganic bases and organic bases. Acids commonly used to form pharmaceutically acceptable salts include inorganic acids and organic acids.

[0028] The term "solvate" refers to the physical association of a compound of the present invention with one or more, preferably 1-3, solvent molecules, whether organic or inorganic. This physical association includes hydrogen bonding. In some cases, for example, when one or more, preferably 1-3, solvent molecules are incorporated into the crystal lattice of a crystalline solid, the solvate will be isolated. Exemplary solvates include, but are not limited to, hydrates, ethanolates, methanolates, and isopropanolates. Solvation methods are well known in the art.

[0029] The term "prodrug" refers to a compound that can be converted in vivo under physiological conditions, for example, by hydrolysis in the blood, to produce the active parent drug compound.

[0030] The term "pharmaceutically acceptable" means that these compounds, materials, compositions, and / or dosage forms are suitable, within the scope of reasonable medical judgment, for contact with the tissues of a patient without excessive toxicity, irritation, allergic response, or other problems or complications, have a reasonable benefit / risk ratio, and are effective for their intended use.

[0031] As used herein, the singular forms "a", "an", and "the" include plural references, and vice versa, unless the context clearly indicates otherwise.

[0032] The above terms related to the present invention are defined, and those skilled in the art can also understand the above terms in combination with the prior art. The following further describes based on the content of the present invention and the definitions of the terms. Description of the Drawings

[0033] Figure 1 : Exemplary results describing the binding mode of acetyl-CoA in the glycosylphosphatidylinositol-anchored protein Gwt1.

[0034] Figure 2 : Exemplary results describing the acetylation ratio of glycosylphosphatidylinositol in six Gwt1 mutants. Detailed Description of the Invention

[0035] The following examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. The experimental methods without specific conditions in the following examples are generally carried out under conventional conditions or according to the conditions recommended by the manufacturers.

[0036] Example 1: Identification of the Acetyl-Coenzyme Binding Site of the Fungal Glycosylphosphatidylinositol Anchored Protein Gwt1 and Construction of the Binding Model

[0037] Step 1: Construction of the Training Set and the Test Set

[0038] The binding information database of acetyl-CoA and its derivatives was selected from the BioLiP database (Yang J. et al., Nucleic Acids Res. 2013, 41, D1096-1103). A total of 776 protein structures and the binding information of 63 acetyl-CoA and its derivatives were collected from the BioLiP database. After removing redundancy, a total of 219 protein sequences and 4024 acetyl-CoA binding site amino acids were recorded. Two-thirds of them were randomly selected as the training set, and the remaining one-third was used as the test set.

[0039] Step 2: Construction of the Deep Network Learning Model

[0040] In this example, a deep learning model based on the attention mechanism was used to identify the binding site of acetyl-CoA. The deep learning model based on the attention mechanism consists of a convolutional layer, a multi-head attention layer, a fully connected layer, and an output layer.

[0041] In the deep learning model based on the attention mechanism, the convolutional layer has at least one convolutional kernel with a size of 3×3 or 5×5, and performs convolutional operations and normalization operations on the input protein sequence features, acetyl-CoA derivative structure features, and the physicochemical property features of the binding site amino acids to obtain the corresponding eigenvalue.

[0042] In the deep learning model based on the attention mechanism, the multi-head attention layer multiplies the eigenvalues output by the convolutional layer with multiple sets of trainable parameter matrices respectively to obtain multiple sets of query matrices, key matrices, and value matrices corresponding to the parameter matrices one by one, and performs a concatenation operation and a vector dot product operation on the above multiple sets of query matrices to obtain the attention matrix, which is then passed to the fully connected layer through ReLU activation.

[0043] In the deep learning model based on the attention mechanism, the fully connected layer processes the output of the multi-head attention layer through the activation of the ReLU function and the dropout operation to obtain the output result and passes it to the output layer.

[0044] In the deep learning model based on the attention mechanism, the output layer uses the Sigmoid activation function to map the output result of the fully connected layer to (0,1) to obtain the output probability.

[0045] Step 3: Prediction Effect Evaluation

[0046] In this embodiment, the prediction performance of the deep learning model and various other acetyl-CoA binding site prediction algorithms, such as COFACTOR (Zheng C, et al., Nucleic Acids Res. 2017, 45, W291-W299), COACH (Yang J, et al., Bioinformatics 2013, 29, 2588-2595), and CoABind (Meng Q, et al., Bioinformatics 2018, 34, 3598-2604), is evaluated by the following four metrics:

[0047] 1) Matthews correlation coefficient (MCC), and the specific calculation formula is as follows:

[0048] 2) Precision, and the specific calculation formula is as follows:

[0049] 3) Recall, and the specific calculation formula is as follows:

[0050] 4) Area Under the Curve (AUC), which is specifically defined as the area under the Receiver Operating Characteristic (ROC) curve.

[0051] Among them, TP represents the number of correctly predicted acetyl-CoA binding sites, TN represents the number of correctly predicted non-acetyl-CoA binding sites, FP represents the number of non-acetyl-CoA binding sites predicted as acetyl-CoA binding sites, and FN represents the number of non-acetyl-CoA binding sites predicted as non-acetyl-CoA binding sites.

[0052] Step 4: Construction of the Gwt1-acetyl-CoA binding model

[0053] Using the predicted AlphaFold structure (AF-P47026-F1-v4) of the glycosylphosphatidylinositol-anchored protein Gwt1 from Saccharomyces cerevisiae as the initial structure, the above deep learning model was applied to identify its acetyl-CoA binding site, and then AutoDock Vina was used to perform molecular docking at this predicted binding site. The best conformation was selected as the initial binding model of Gwt1-acetyl-CoA, and then the initial binding model was optimized by molecular dynamics in a phospholipid membrane environment to finally obtain the binding model of Gwt1-acetyl-CoA.

[0054] Table 1. Comparative analysis of the prediction effects of various prediction tools on the acetyl-CoA binding site Prediction method MCC Accuracy rate Recall rate AUC COFACTOR 0.475 0.509 0.536 0.811 COACH 0.411 0.398 0.490 0.778 CoABind 0.505 0.553 0.612 0.878 The present invention 0.635 0.699 0.703 0.903

[0055] As shown in Table 1, compared with COFACTOR, COACH, and CoABind, the algorithm of the embodiment of the present invention has obvious advantages in terms of MCC, accuracy, recall rate, and AUC.

[0056] Using the above deep learning model and molecular simulation method, we obtained the binding model of Gwt1-acetyl-CoA and found that there are 3 acetyl-CoA specific recognition regions in the Gwt1 protein structure, as Figure 1 shown:

[0057] 1) The purine structure recognition region of the acetyl-CoA head with Glu157 and His228 as the core, which is located in the endoplasmic reticulum lumen; where His228 recognizes and fixes the purine conjugated heterocyclic system in acetyl-CoA through pi-pi interaction, and Glu157 recognizes the purine amino group in acetyl-CoA through a salt bridge;

[0058] 2) The positively charged region with Arg216 as the core, which can recognize the phosphate group of acetyl-CoA through electrostatic interaction;

[0059] 3) The protein central pocket with Thr137, Leu163, and Ser170 as the core, which can recognize the tail acetamide and thiol structures of acetyl-CoA.

[0060] Example 2: In vitro detection of acetylated phosphatidylinositol

[0061] The first step: Preparation of standards

[0062] The stable isotope-labeled standards of phosphatidylinositol and acetylated phosphatidylinositol (SPLASH TM Lipidomix TM, Avanti Research) prepared nine standards with different concentrations ranging from 1.0 to 500 ng / mL for drawing a standard curve for quantification.

[0063] Step 2: Preparation of samples to be tested

[0064] Pipette 10 mL of bacterial solution, centrifuge, add 8 mL of buffer (50 mM Tris-HCl, pH 8.5-9.0, 2 mMEDTA, 100 mM NaCl, 0.5% TritonX-100, 1 mg / mL lysozyme), suspend, place on ice for 30 minutes, sonicate for 90 minutes (750 W, 5 seconds sonication, 9 seconds interval), precipitate protein with isopropanol, vortex mix for 1 minute, and place at -20 °C for 10 minutes. After vortex mixing for 1 minute, warm to 4 °C and place for 2 hours to ensure complete protein precipitation. Centrifuge the sample at 4 °C (3000 rmp, 10 min), and reserve the supernatant for later use.

[0065] Step 3: LC-MS / MS detection

[0066] The supernatant obtained in the previous step was analyzed by LC-MS / MS, and the experimental conditions are shown in Table 2. TargetLynx software was used to process the experimental data.

[0067] Table 2. LC-MS / MS experimental conditions

[0068] We detected the acetylation ratio of glycosylphosphatidylinositol in cells of six mutants of Saccharomyces cerevisiae Gwt1 (T137A, E157A, L163A, S170A, R216A, and H228A). Figure 2 As shown in the figure, acetylated glycosylphosphatidylinositol was almost undetectable in mutants R216A and H228A, indicating that these two mutants can completely inactivate Gwt1; T137A and E157A can inhibit the acetylation process of glycosylphosphatidylinositol, reducing it to 35% and 10% of the wild type; L163A and S170A can reduce the acetylation process of glycosylphosphatidylinositol, which is 67% and 85% of the wild type, respectively. The above in vitro test results confirm the influence of key amino acids in the Gwt1-acetyl CoA binding model on the acetylation of glycosylphosphatidylinositol.

[0069] Example 3: Virtual screening based on the Gwt1-acetyl-CoA binding model

[0070] Step 1: Protein PDB file processing

[0071] Use AutoDockTools to remove the redundant water molecules, hydrogen atoms, and acetyl coenzyme molecules in the Gwt1-acetyl coenzyme binding model, then add polar hydrogen atoms, and export it as a receptor.pdbqt file.

[0072] Step 2: Selection of the binding pocket

[0073] According to the binding model of Gwt1-acetyl coenzyme, select a range of 5 Å around the acetyl coenzyme as the binding pocket, and then use AutoDockTools to generate the binding pocket configuration file config.txt.

[0074] Step 3: Preparation of the compound library

[0075] In the ZINC20 database, select commercially available drug molecules that are natural product molecules and FDA-approved (about 9390 compounds), download their mol2 files, and use MGLTools to convert them into ligand.pdbqt files.

[0076] Step 4: Virtual screening

[0077] Use AutoDock Vina 1.1.2 and perform molecular docking using the above receptor.pdbqt, ligand.pdbqt, and config.txt as input files.

[0078] Table 3. Virtual screening results based on the Gwt1-acetyl coenzyme A binding model Ranking ZINC id Compound name dG (kcal / mol) 1 1489430 Tivozanib -7.64 2 968328 Rosiglitazone -7.40 3 169347624 - -7.25 4 65320291 - -7.12 5 37556079 - -7.07

[0079] The results are shown in Table 3. Using the above binding model of Gwt1-acetyl coenzyme A as the initial structure and the 3 recognition regions of acetyl coenzyme A as restrictive conditions, natural product molecules and FDA-approved drug molecules in the ZINC database are used as the screening compound library, and virtual screening is performed using AutoDock Vina. The results are shown in Table 3. Among the top five compounds ranked by scoring, there are two known FDA-approved marketed drugs (tivozanib and rosiglitazone). Tivozanib is a vascular endothelial growth factor tyrosine kinase inhibitor and was approved by the US FDA in March 2023 for the treatment of relapsed / refractory advanced renal cell carcinoma. Rosiglitazone is a thiazolidinedione diabetes drug that effectively controls blood sugar by providing insulin sensitivity.

[0080] Example 4: In vitro antifungal activity test of compounds

[0081] Step 1: Preparation of the test compounds

[0082] Prepare stock solutions of the test compounds, namely, tivozanib (TargetMol, Cat#T2456), rosiglitazone (TargetMol, Cat#T0334), voriconazole (TargetMol, Cat#T0120), posaconazole (TargetMol, Cat#T6211), and amphotericin B (TargetMol, Cat#T1067), at a concentration of 2 mg / mL in DMSO for later use.

[0083] Step 2: Activate the test strains

[0084] Take out the cryopreserved strains, namely, Candida albicans (ATCC-MYA-574, WuXi AppTec), Cryptococcus neoformans (ATCC208821, WuXi AppTec), Aspergillus fumigatus (ATCC-MYA-4609, WuXi AppTec), and Aspergillus niger (ATCC 16404, WuXi AppTec). Pipette 10 mL of the bacterial solution into a test tube containing 1 mL of YEPD culture medium (10 g yeast extract; 20 g D-glucose; 20 g peptone; 800 mL ultrapure water), and place it in a constant temperature incubator at 30 °C. Shake the culture at 200 rpm / min for 24 hours. Then, pipette 10 mL from the YEPD bacterial suspension into a new 1 mL of YEPD culture medium and continue to shake the culture at 30 °C for 16 hours to complete the activation.

[0085] Step 3: Prepare the bacterial suspension

[0086] Transfer the test strains at the end of the exponential growth phase into a centrifuge tube, centrifuge (3000 rpm, 1 min), discard the supernatant, wash the strains with 1 mL of PBS buffer (8 g NaCl; 3.57 g Na2HPO4·12H2O; 0.20 g KCl; 0.24 g KH2PO4; made up to 1000 mL with ultrapure water), then centrifuge (300 rpm, 1 min), discard the supernatant, and repeat the washing process 3 times. Dilute 10 mL of the fungal stock solution 100-fold, and then use a hemocytometer (Shanghai Titan Technology Co., Ltd., product number: TS002-149) to count under a biological microscope (Beijing Ceiwei Optoelectronic Technology Co., Ltd., model: LW100T) and calculate the bacterial concentration of the fungal stock solution. Then, dilute it to 1×10 3 CFU / mL with RPMI 1640 culture medium (10 g RPMI 1640; 2 g NaHCO3; 34.5 g 3-morpholinopropanesulfonic acid; 2.7 g NaOH; made up to 1000 mL with ultrapure water).

[0087] Step 4: Determine the minimum inhibitory concentration MIC90

[0088] After vortexing the prepared bacterial suspension evenly, transfer it to a 96-well cell culture plate. Add 200 μL to each well in the first column and 100 μL to the remaining wells. Add the prepared test compound solution to three consecutive wells in the first column of the above 96-well cell culture plate to make three replicates. Add 6.4 μL of the test compound to each well to make the final concentration 64 mg / mL. Perform serial two-fold dilutions column by column from left to right so that the final concentrations of the compounds in the first column to the tenth column are 64 - 0.125 mg / mL. In each well of the eleventh column, add the bacterial suspension without any compound as the negative control group; in each well of the twelfth column, add blank RPMI 1640 culture medium as the blank control group. Place the 96-well plate in a constant temperature incubator at 30 °C. After culturing for 48 - 72 hours, use an enzyme-linked immunosorbent assay (Thermo Fisher, model: Thermo Multiskan FC) to measure the optical density value (OD value) of each well of fungi at 630 nm. Calculate the inhibition rate (%) of each well corresponding to different compound concentrations according to the following formula. The minimum concentration corresponding to an inhibition rate (%) ≥ 90% is the minimum inhibitory concentration MIC90 value of the compound:

[0089] To verify the results of virtual screening, we selected 4 clinical strains, namely Candida albicans (ATCC-MYA-574), Cryptococcus neoformans (ATCC208821), Aspergillus fumigatus (ATCC-MYA-4609), and Aspergillus niger (ATCC 16404), and detected the minimum inhibitory concentration MIC90 values of tivozanib and rosiglitazone against the above 5 clinical strains. The results are shown in Table 4. The minimum inhibitory concentration MIC90 of tivozanib against Aspergillus fumigatus and Aspergillus niger is significantly better than that of voriconazole, posaconazole, and amphotericin B. Its minimum inhibitory concentration MIC90 against Candida albicans is comparable to that of voriconazole, but significantly better than that of posaconazole and amphotericin B.

[0090] Table 4. Minimum inhibitory concentration MIC90 of the compounds

[0091] In summary, tivozanib has excellent inhibitory activity against Candida albicans, Cryptococcus neoformans, Aspergillus fumigatus, and Aspergillus niger, and its inhibitory activity is better than that of existing antifungal drugs in various clinical strains.

Claims

1. A compound having antifungal activity or its stereoisomers, tautomers, solvates, hydrates, prodrugs, stable isotope derivatives and pharmaceutically acceptable salts, characterized in that: The compound is selected from any one of the following:

2. The compound according to claim 1 or its stereoisomers, tautomers, solvates, hydrates, prodrugs, stable isotope derivatives and pharmaceutically acceptable salts thereof, for use in treating diseases related to fungal infections.

3. A pharmaceutical combination comprising a compound according to any one of claims 1 to 2 or a stereoisomer, tautomer, solvate, hydrate, prodrug, stable isotope derivative and a pharmaceutically acceptable salt thereof, and at least one pharmaceutically acceptable carrier, diluent or excipient, characterized in that Used for the treatment of diseases related to fungal infections.

4. A method for treating fungal infection-related diseases, comprising administering to a patient an effective therapeutic dose of any one of the compounds of claims 1-2 or any one of the pharmaceutical combinations of claim 3.

5. The method according to claim 4, wherein the fungal infection is caused by a fungal species from the following group: Candida, Cryptococcus, Aspergillus, Trichoderma, Blastomyces, Cytoplasma and Sporozoites.

6. The method according to claim 4, wherein the fungal infection-related disease is selected from aspergillosis, blastomycosis, candidiasis, coccidioidomycosis, cryptococcosis, fungal eye infection, histoplasmosis, mucormycosis, pneumocystis pneumonia, sporotrichosis and talaromycosis; preferably from candidiasis, cryptococcosis and aspergillosis.

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