Virtual screening method based on Kv1.3 inhibitor, drug lead compound and application

Abstract

The invention discloses a virtual screening method based on a Kv1.3 inhibitor, a drug lead compound and application, and relates to the field of pharmaceutical chemistry. The virtual screening method comprises the following steps: selection and pretreatment of a Kv1.3 protein crystal structure: obtaining a Kv1.3 protein-small molecule compound crystal structure from a Protein Data Bank database, and carrying out pretreatment on the Kv1.3 protein-small molecule compound crystal structure; determining a butt-joint active pocket; selecting a binding site; selecting and downloading a to-be-screened compound library; and virtual screening of the compounds: performing molecular docking by using virtual screening software to obtain the compounds of which the binding free energy (delta G) is negative and the absolute values are ranked from large to small. The compound Z239529546 has the beneficial effects that the compound Z239529546 screened by the method can reduce the expression of related inflammatory factors such as IL-6, IL-1beta, TNF-alpha and the like in cells and Kv1.3 protein in cell experiments, and has a certain effect of treating and / or preventing inflammation.

Description

Technical Field

[0001] The present invention relates to the field of medicinal chemistry, and particularly to a virtual screening method, a drug lead compound and an application of a Kv1.3 inhibitor with anti-inflammatory activity. Background Art

[0002] As a member of the voltage-dependent potassium ion channel family, Kv1.3 (KCNA3) is a crucial ion channel regulatory protein in the immune system response. It was initially discovered in T lymphocytes and is the starting factor for regulating T cell activity and differentiation. Its function is closely related to immune regulation. Blocking Kv1.3 can inhibit Ca 2+ signal transduction, T cell proliferation and IL-2 secretion. A number of studies have confirmed that Kv1.3 is highly expressed in macrophages, microglia and TEM cells, indicating that Kv1.3 plays a key role in the inflammatory response and has been regarded as an important target for immunosuppression, tumors and neurological diseases. Although more and more clinical trials have confirmed the superiority of Kv1.3 targeted therapy, very few Kv1.3 inhibitors have entered clinical research. Currently, two types of inhibitors targeting the Kv1.3 channel have been developed: organic small molecules and toxin-derived peptides. However, due to the high homology among the subtypes of the Kv1 family, the selectivity of small molecule compounds faces challenges. Even if some compounds have high selectivity for Kv1.3, they may still have off-target effects on other ion channels. Larger molecules such as peptides and antibodies are effective alternatives, but they may face problems such as membrane permeability or adverse immune reactions. Therefore, developing novel Kv1.3 inhibitors with better activity and higher specificity for anti-inflammatory has important scientific significance, clinical significance and social benefits.

[0003] Virtual screening is to perform drug screening on a computer. By using molecular docking technology, it analyzes the interaction between the target and the candidate compound, calculates the affinity between the two, and selects potential lead compounds from a large number of organic compounds to avoid blind screening, thus greatly reducing the time and money costs. Molecular docking research is a method that combines applied mathematics, biology and computer models to predict the affinity of small molecules for receptors and plays a key role in the virtual screening of drugs. Compared with traditional drug screening methods, virtual screening can not only shorten the drug development cycle but also reduce the drug development cost. There has been no report on how to quickly and efficiently screen out a method for an anti-inflammatory drug targeting Kv1.3 to discover more potential Kv1.3 inhibitors. Summary of the Invention

[0004] The technical problem to be solved by the present invention is how to provide a virtual screening method and application of a Kv1.3 inhibitor with anti-inflammatory activity.

[0005] The present invention solves the above technical problems through the following technical means:

[0006] The first aspect of the present invention provides a virtual screening method for Kv1.3 inhibitors with anti-inflammatory efficacy, comprising the steps of:

[0007] (1) Selection and preprocessing of Kv1.3 protein crystal structure: The crystal structure of Kv1.3 protein-small molecule complex was obtained from the Protein Data Bank database, and the crystal structure of Kv1.3 protein-small molecule complex was preprocessed using virtual screening software;

[0008] (2) Determination of docking active pocket: selection of binding site;

[0009] (3) Select and download the compound library to be screened;

[0010] (4) Virtual screening of compounds: Use virtual screening software to perform molecular docking and calculation and ranking to obtain compounds with high binding free energy (ΔG) scores, that is, to obtain Kv1.3 inhibitors with anti-inflammatory efficacy; the high binding free energy (ΔG) score means that the binding free energy (ΔG) is negative and the absolute value is ranked high from large to small.

[0011] Preferably, in step (1), the Kv1.3 protein-small molecule complex crystal structure is a complex crystal structure of human Kv1.3 protein and small molecule Dalazatide.

[0012] Preferably, in step (1), the Kv1.3 protein-small molecule complex crystal structure is preprocessed using the QuickPrep module in the virtual screening software MOE.

[0013] Preferably, in step (1), the pretreatment includes one or more of deleting solvent molecules, hydrogenation, repairing missing residues and side chains, protonating protein residues, optimizing hydrogen bond networks, minimizing energy, and repairing erroneous atom types.

[0014] Preferably, in step (2), the binding site is selected from the two amino acids G448 and H451 that interact with the outer pore of Kv1.3 of the inhibitor Dalazatide. Specifically, Dalazatide is a discovered highly active inhibitor of Kv1.3 channels that can bind to any of the four subunits of Kv1.3. Therefore, the two amino acids G448 and H451 in the four subunits are defined as the amino acid residues of the binding site.

[0015] Preferably, in step (3), two databases, Ion Channel and Macrocycle, from Enamine are selected as compound libraries for virtual screening, which contain a total of 38,752 small molecule compounds.

[0016] Preferably, in step (4), the General Dock module in the virtual screening software MOE is used for molecular docking; according to the docking results, the conformation with the best docking effect is obtained, the binding information of multiple small molecule compounds with the best interaction binding energy between Kv1.3 and the small molecules is calculated, and the molecules ranked at the top are screened as potential active compounds.

[0017] The second aspect of the present invention provides a drug lead compound with Kv1.3 inhibitory activity, which is obtained by the above virtual screening method, and the drug lead compound is a compound with the structure shown in formula I or a pharmaceutically acceptable salt thereof:

[0018]

[0019] The third aspect of the present invention provides any one of the following applications of the above drug lead compound:

[0020] (a) Application in the preparation of Kv1.3 inhibitors;

[0021] (b) Application in the preparation of drugs for treating and / or preventing inflammatory diseases related to abnormal Kv1.3.

[0022] Preferably, the inflammatory diseases include, but are not limited to, one or more of psoriasis, inflammatory bowel disease, and neuroinflammatory diseases.

[0023] The beneficial effects of the present invention are as follows:

[0024] 1. The screening implementation scheme of the anti-inflammatory drug targeting Kv1.3 involved in the present invention is simple, rapid, and efficient, and the probability of screening positive compounds is relatively high. The screened compounds have significant anti-inflammatory and Kv1.3 inhibitory effects.

[0025] 2. The present invention has obtained a novel Kv1.3 inhibitor with significant anti-inflammatory effects and Kv1.3 inhibitory effects through this screening process. The present invention can provide a reference for the screening of Kv1.3 inhibitors with anti-inflammatory effects.

[0026] 3. The compound Z239529546 screened in the present invention has obvious anti-inflammatory effects and Kv1.3 inhibitory effects, and can be used to develop drugs for treating anti-inflammatory or Kv1.3 inhibition-related diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the molecular docking of the compound Z239529546 and Kv1.3 in Example 1 of the present invention.

[0028] Figure 2This is the experimental result graph of cell viability in Example 2 of the present invention.

[0029] Figure 3 This is the analysis result graph of the anti-inflammatory activity of compound Z239529546 in Example 3 of the present invention.

[0030] Figure 4 This is the analysis result graph of the Kv1.3 inhibitory effect of compound Z239529546 in Example 4 of the present invention. Detailed implementation manners

[0031] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0032] The test materials and reagents used in the following embodiments can be obtained from commercial channels without special instructions.

[0033] For those not specifying specific techniques or conditions in the embodiments, they can all be carried out according to the techniques or conditions described in the literature in this field or according to the product specifications. Without special instructions, the quantitative tests in the following embodiments are all set with more than three repeated experiments, and the results are averaged.

[0034] Example 1:

[0035] Virtual screening process of Kv1.3 inhibitors

[0036] (1) Selection and pretreatment of the Kv1.3 protein crystal structure: Obtain the crystal structure of the Kv1.3 protein-small molecule complex from the Protein Data Bank database. This structure is the crystal structure of the human Kv1.3 protein and the small molecule Dalazatide (PDB: 7WF4). Use the QuickPrep module in the virtual screening software MOE to preprocess the crystal structure of the Kv1.3 protein-small molecule complex;

[0037] (2) Determination of the docking active pocket: The crystal structure (PDB: 7WF4) shows the interaction between Dalazatide and G448 and H451 in the outer pore of Kv1.3. However, due to symmetry mismatch, a model of Dalazatide itself could not be established. The Dalazatide peptide can bind to any one of the four subunits of Kv1.3, resulting in the averaging of its density during particle classification. Therefore, the two amino acids G448 and H451 in the four subunits were defined as the amino acid residues of the binding site, and virtual screening based on molecular docking was carried out.

[0038] (3) Selection and download of the compound library to be screened: Two databases, Ion Channel and Macrocycle from Enamine, were selected as the compound libraries for virtual screening, containing a total of 38,752 small molecule compounds.

[0039] (4) Virtual screening of compounds: The General Dock module in MOE was used for molecular docking. The method used for molecular docking was Triangle Matcher as the search engine for docking, with a maximum of 1000 searches; the scoring function for each docking was evaluated using London dG to assess the docking quality, and 30 best conformations were retained for optimization using the Rigid Receptor method. The optimization results were evaluated using GBVI / WAS dG, and finally 1 best docking mode was retained. The binding information of the top 100 small molecule compounds with the best interaction binding energy between Kv1.3 and small molecules was calculated, including the 3D pharmacodynamic information of the small molecules, Enamine ID, small molecule druggability attribute information, and the binding energy of the molecule to Kv1.3. When the output ligand file and its corresponding Kv1.3 target structure information are opened simultaneously, the complex structure information of the target - small molecule can be viewed. The top - ranked molecules were purchased and their activities were verified by experiments. Finally, 8 compounds a1, a2, a3, a4, b1, b2, b3, b4 (EnamineID: a1:Z29616838, a2:Z1000661256, a3:Z299576254, a4:Z88236610, b1:Z239529546, b2:Z27454483, b3:Z109771472, b4:Z27425793) with the following structures were successfully purchased for activity verification:

[0040]

[0041] Example 2:

[0042] CCK - 8 experiment for cytotoxicity assay

[0043] RAW264.7 cells (mouse peritoneal macrophages) in the logarithmic growth phase were prepared into cell suspensions and inoculated into 96-well plates at 100 μL / well (about 3000 cells), with 3 parallel replicates, and cultured in an incubator at 37 °C containing 5% CO 2 for 24 h. The test compound was dissolved in DMSO to prepare a stock solution with a concentration of 5 mM, and the stock solution was diluted with cell culture medium. After taking out the culture plate, different concentrations of the test samples were added to each well, with 3 parallel replicates, and then placed in a CO 2 incubator and continued to culture for 24 h. The culture plate was taken out, 10 μL of CCK8 solution was added to each well, and incubated in an incubator at 37 °C containing 5% CO 2 for 1 - 2 h. The absorbance (OD value) at 450 nm of each well was measured using a microplate reader. The blank group was the medium without cells, and the control group was the cells without the drug.

[0044] The inhibition rate of the drug on cell proliferation was calculated based on the OD value, and the formula was as follows:

[0045] Cell survival rate (%) = (OD sample - OD blank ) / (OD control - ODblank) × 100%;

[0046] Cell inhibition rate (%) = (OD control - OD sample ) / (OD control - OD blank ) × 100%;

[0047] OD sample : OD value of the experimental well;

[0048] OD control : OD value of the control well;

[0049] OD blank : OD value of the blank well.

[0050] The half-maximal inhibitory concentration IC 50 value was obtained by fitting the inhibition rates at each concentration.

[0051] Figure 2 The toxicity of eight compounds against RAW264.7 cells at concentrations of 0.001, 0.01, 0.1, 1, and 10 μM is shown. It can be seen that only a1 and a3 have obvious cytotoxicity. The other compounds have no obvious cytotoxicity below 1 μM. The other compounds were further selected for further experiments.

[0052] Example 3:

[0053] Determination of the anti-inflammatory activity of the compound

[0054] Six small molecule compounds screened in Example 2 were selected for the determination of anti-inflammatory activity. Interleukin 6 (IL-6) and interleukin-1β (IL-1β) are both pro-inflammatory factors and play important roles in inflammatory immunity. Tumor necrosis factor-α (TNF-α) can promote inflammatory responses and is one of the important mediators of acute inflammation. An increase in TNF-α, IL-6, and IL-1β indicates an exacerbation of the degree of inflammation, and vice versa indicates a reduction in inflammation.

[0055] The results of real-time fluorescence quantitative PCR are as Figure 3 shown. It can be seen that in the LPS-induced RAW264.7 cell inflammation model, the expression of cell inflammation-related factors induced by LPS was significantly higher than that of the normal control group, while the compound Z239529546 (i.e., compound b1) administration group significantly reduced the expression levels of cell IL-6, IL-1β, and TNF-α at concentrations of 90 nM, 30 nM, and 10 nM, suggesting that this compound has certain anti-inflammatory activity.

[0056] Example 4:

[0057] Western Blot (WB) experiment was used to detect the ability of compound Z239529546 (i.e., compound b1) to inhibit Kv1.3

[0058] RAW264.7 cells were seeded in 6-well plates. After the cell density reached 70%-80%, the cells were treated with a medium containing 100 ng / ml LPS and the specified concentration of compound Z239529546 for 24 h. Untreated RAW264.7 cells were used as a control. Proteins in each group of cells were extracted with RIPA lysis buffer containing 1% PMSF, ultracentrifuged at 12,000 g at 4 °C for 30 min, the supernatant was extracted, and after adding protein loading buffer, it was denatured at 100 °C for 10 min to obtain protein samples. The ability of compound Z239529546 to inhibit Kv1.3 was analyzed by Western Blot, and the results are as Figure 4 shown.

[0059] It can be seen that compared with the normal group, the expression of Kv1.3 protein in the model group cells increased, while in the cells treated with compound Z239529546 (90 nM, 30 nM, 10 nM), the content of Kv1.3 decreased significantly compared with the model group cells.

[0060] In summary, the present invention provides a rapid screening implementation scheme for anti-inflammatory drugs targeting Kv1.3, and the screened compounds have obvious anti-inflammatory effects and Kv1.3 inhibitory effects. The compound Z239529546 (i.e., compound b1) obtained in the present invention can be used as a lead compound for further optimization and development of drugs for the treatment of Kv1.3-related inflammatory diseases.

[0061] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A virtual screening method for Kv1.3 inhibitors with anti-inflammatory efficacy, characterized in that: Includes steps: (1) Obtain the crystal structure of the Kv1.3 protein-small molecule complex from the Protein Data Bank database and pre-process the crystal structure of the Kv1.3 protein-small molecule complex using virtual screening software; (2) Determination of docking active pocket: selection of binding site; (3) Select and download the compound library to be screened; (4) Using virtual screening software to perform molecular docking and calculation ranking to obtain compounds with high binding free energy (ΔG) scores, that is, obtaining Kv1.3 inhibitors with anti-inflammatory efficacy; the high binding free energy (ΔG) score means that the binding free energy (ΔG) is negative and the absolute value is ranked high from large to small.

2. The virtual screening method according to claim 1, characterized in that In step (1), the Kv1.3 protein-small molecule complex crystal structure is a complex crystal structure of human Kv1.3 protein and small molecule Dalazatide.

3. The virtual screening method according to claim 1, characterized in that In step (1), the Kv1.3 protein-small molecule complex crystal structure was preprocessed using the QuickPrep module in the virtual screening software MOE.

4. The virtual screening method according to claim 1, characterized in that In step (1), the pretreatment includes one or more of deleting solvent molecules, hydrogenation, repairing missing residues and side chains, protonating protein residues, optimizing hydrogen bond networks, minimizing energy, and repairing erroneous atom types.

5. The virtual screening method according to claim 1, characterized in that In step (2), the binding site is selected from the two amino acids G448 and H451 that interact with the Kv1.3 outer pore of the inhibitor Dalazatide.

6. The virtual screening method according to claim 1, wherein: In step (3), the IonChannel and Macrocycle databases from Enamine were selected as compound libraries for virtual screening.

7. The virtual screening method according to claim 1, characterized in that The GeneralDock module in the virtual screening software MOE was used for molecular docking. The conformation with the best docking effect was obtained based on the docking results. The binding information of multiple small molecule compounds with the best interaction energy between Kv1.3 and small molecules was calculated, and the top-ranked molecules were screened as compounds with potential activity.

8. A drug lead compound having Kv1.3 inhibitory activity, characterized in that: The drug lead compound obtained by the virtual screening method according to any one of claims 1 to 7 is a compound having a structure shown in Formula I or a pharmaceutically acceptable salt thereof:

9. The use of the drug lead compound according to claim 8 in any of the following: (a) Use in the preparation of Kv1.3 inhibitors; (b) Use in the preparation of a medicament for treating and / or preventing inflammatory diseases associated with Kv1.3 abnormalities.

10. The use according to claim 9, characterized in that The inflammatory disease is one or more of psoriasis, inflammatory bowel disease, and neuroinflammatory disease.

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