MGluR5 micromolecule allosteric modulator and application thereof in inhibition of neuroinflammation

Abstract

The invention discloses an mGluR5 small-molecule allosteric modulator and application thereof in inhibition of neuroinflammation, and belongs to the technical field of neuropharmacology and anti-inflammatory drug research, two mGluR5 small-molecule allosteric modulators are obtained by virtual screening through an allosteric pocket targeting mGluR5, the structural formulas of the two mGluR5 small-molecule allosteric modulators are shown in the specification, and the structural formula of the mGluR5 small-molecule allosteric modulators is shown in the specification. The mGluR5 micromolecule allosteric modulator can be used for inhibiting microglial cell inflammation, and can effectively relieve LPS-induced microglial cell NO release.

Description

Technical Field

[0001] This invention belongs to the field of neuropharmacology and anti-inflammatory drug research technology, specifically involving mGluR5 small molecule allosteric modulators and their application in inhibiting neuroinflammation. Background Technology

[0002] Parkinson's disease is a neurodegenerative disease that primarily affects middle-aged and elderly people. Since its first description in 1817, it has become the most common movement disorder, second only to Alzheimer's disease in prevalence among neurodegenerative diseases. The prevalence of Parkinson's disease has increased significantly over the past three decades, making the exploration of new prevention and treatment strategies imperative.

[0003] The pathological features of Parkinson's disease include the abnormal accumulation of α-synuclein in Lewy bodies and Lewy neurites. This accumulation can trigger innate and adaptive immune responses in the central nervous system, thereby exacerbating the neuroinflammatory process. Abnormal activation of microglia is considered a key element in the mechanism of neuroinflammatory development. As the main innate immune cells in the central nervous system, microglia possess a continuous dynamic phenotypic profile at rest and can undergo phenotypic shifts with changes in the microenvironment. When stimulated pathologically, microglia are rapidly activated, releasing various inflammatory cytokines. These cytokines not only directly cause neuronal damage but also further promote α-synuclein expression, forming a positive pathological feedback loop that exacerbates disease progression. Neuroinflammatory features have been consistently detected in both clinical observations and experimental models of Parkinson's disease, indicating that the inflammatory response is closely related to the pathogenesis of the disease.

[0004] Therefore, the aggregation and diffusion of α-synuclein, and the accompanying neuroinflammatory response, play a central role in the development and progression of Parkinson's disease. Although regulating these processes has become an important direction in therapeutic strategy research in this field, a controllable technical solution is still lacking.

[0005] Metabolic glutamate receptors (mGluR) belong to the G protein-coupled receptor family and hold significant potential in the regulation of neuroinflammation. Related studies have shown that mGluR5 not only participates in regulating physiological processes such as synaptic plasticity but also plays a crucial role in neuroinflammation pathways. Of particular note is the possibility that the susceptibility of hippocampal neurons to α-synuclein toxicity may be mediated by mGluR5, and that activation of mGluR5 can inhibit α-synuclein-induced inflammatory responses. These findings confirm the crucial role of mGluR5 in α-synuclein-induced neuroinflammation and neurotoxicity, suggesting its potential as a therapeutic target for Parkinson's disease.

[0006] Structurally, mGluR5 possesses three domains: a Venus flytrap domain with an ortho-binding site, a cysteine-rich domain, and a seven-transmembrane domain containing an allosteric site. However, the ortho-binding site of mGluR5 is highly conserved throughout evolution, making it difficult to develop ortho-ligands with high selectivity for specific subtypes. In contrast, allosteric modulators, by binding to the cavity of the less conserved seven-transmembrane domain, exhibit higher bioavailability and superior pharmacokinetic properties.

[0007] Despite the large number of reported allosteric modulators, most compounds still suffer from insufficient selectivity, poor blood-brain barrier penetration, or significant toxic side effects. With advancements in computational technology, computer-aided drug design has become a key tool for achieving breakthroughs in rational drug development. Within computer-aided drug design, virtual screening is an important tool for rapid compound screening based on the three-dimensional structure of biological macromolecules. Depending on the availability of protein target structures, virtual screening can be divided into structure-based virtual screening and ligand-based virtual screening. Summary of the Invention

[0008] In view of the above, the purpose of this invention is to provide a small molecule allosteric regulator of mGluR5 and its application in inhibiting neuroinflammation. This small molecule targets mGluR5, activates mGluR5, and thereby inhibits microglial cell inflammation, providing a reference for further development of small molecule drugs for the treatment of Parkinson's disease.

[0009] This invention provides the following technical solution: mGluR5 small molecule allosteric modulators were obtained through a virtual screening method, which specifically includes the following steps: 1. Virtual Filtering PDB files of the resolved mGluR5 dimer were extracted from the Protein Data Bank database and preprocessed. Small molecules bound to allosteric sites in the PDB structure were then extracted, preprocessed, and re-coupled to the allosteric sites of mGluR5 to evaluate whether this docking method could reproduce the experimentally determined binding conformation. Decoy molecules were then generated using the DUDE-E website, and active, positively allosteric small molecules targeting mGluR5 were collected from literature and the IUPHAR / BPS website. All decoy and active molecules were preprocessed and then docked to the preprocessed PDB files. Based on the docking scores, receiver operating characteristic (ROC), area under the curve (AUC), and enrichment factor (EF) were calculated to evaluate the computational model's ability to distinguish between active and inactive compounds. The evaluated PDB files were processed using Maestro software to generate corresponding docking pocket files for later use. We obtained an internal virtual screening library of small molecules from TSBiochem and filtered the compounds in this database using QikProp and the five principles of drug-likeness in the vsSW program of Maestro software. The remaining small molecule compound library was first initially screened using the High-Throughput Virtual Screening (HTVS) scoring function in Glide, retaining the top 10% of compounds. Subsequently, these compounds were re-interlocked using the Standard Precision (SP) method, and the top 10% of candidate compounds were selected again. Finally, the ultra-fine precision (XP) scoring function was used for further optimization screening. Next, the top 10% of candidate compounds from the XP screening were screened for blood-brain barrier (BBB) ​​permeability using an internal toxicity prediction model. To ensure the structural novelty and chemical diversity of the final matched compounds, cluster analysis based on molecular similarity was performed using the Canvas similarity and clustering module of Schrödinger. From each cluster, 100 representative compounds were selected based on their interlocking scores. The binding conformations of these selected compounds were then visually examined to assess their specific interactions with the target. To further screen for potential small molecules that possess both strong target binding affinity and structural diversity, the remaining compounds underwent in-depth analysis using the Tanimoto coefficient (Tc). This coefficient, based on molecular fingerprinting, quantifies the structural similarity between molecules to aid in the selection of the best among the best, ultimately identifying 17 drug small molecules.

[0010] 2. Cell Culture and Nitric Oxide (NO) Measurement BV-2 microglia were cultured in a humidified incubator at 37°C using high-glucose DMEM medium supplemented with 10% fetal bovine serum. Subsequently, BV-2 microglia were cultured at 2.0 × 10⁶ cells per well. 4Cells were seeded at a density of [number] cells per well in 96-well plates. After 24 hours of lipopolysaccharide stimulation, 50 μl of cell culture supernatant was transferred to a new 96-well plate and mixed with 50 μl of Griess reagent. The absorbance was measured at 540 nm using a microplate reader, and NO production was calculated accordingly.

[0011] 3. Cell viability assay Cell viability was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. The simplified procedure was as follows: After appropriate treatment, 10 μl of MTT reagent was added to each well and incubated at 37°C for 1 hour. Subsequently, 100 μl of dimethyl sulfoxide (DMSO) was added to each well to dissolve the formazan crystals, and the absorbance was measured at 490 nm using a microplate reader to calculate cell viability.

[0012] 4. RNA extraction and real-time quantitative PCR Total RNA was extracted from microglia using TRNzol universal reagent, and cDNA was synthesized using the HiScript III RT SuperMix for qPCR kit. Real-time quantitative PCR was performed on an Applied Biosystems 7500 system using ChamQ Pro Universal SYBR qPCR premix, with GAPDH as an internal control gene. The relative expression level of the target gene was calculated using the 2−ΔΔCT method.

[0013] 5. Western blot for protein immunoblotting After appropriate treatment, BV-2 microglia were lysed on ice for 30 minutes using RIPA lysis buffer containing 1% protease inhibitor, 1 mM NaF, 1 mM Na3VO4, and 1 mM PMSF. The lysis buffer was centrifuged at 12000 × g for 15 minutes at 4°C, and the supernatant was mixed with 5× SDS loading buffer for SDS-PAGE gel electrophoresis. Proteins were then transferred to nitrocellulose membranes, blocked with 5% skim milk at room temperature for 2 hours, incubated overnight at 4°C with primary antibody, and then incubated with HRP-labeled secondary antibody at room temperature for 1 hour. Finally, enhanced chemiluminescence was used to detect protein bands, and imaging analysis was performed using a fully automated chemiluminescence image analysis system (Shanghai Tianneng Technology Co., Ltd., Shanghai, China).

[0014] 6. Statistical Analysis Data are expressed as mean ± standard error of three independent experiments. Statistical analysis was performed using GraphPad Prism software. Student's t-test was used for comparisons between two groups, and one-way ANOVA combined with Dunnett's multiple comparison test was used for comparisons among multiple groups. Statistical significance was defined as *P < 0.05.

[0015] The compound described in this invention has the following technical advantages: (1) This invention is a novel compound among the reported clinical phase I to IV compounds of mGluR5; (2) These two compounds can effectively inhibit LPS-induced inflammatory factors in microglia; (3) Compared with the known mGluR5 allosteric regulator VU0360172 in inhibiting neuroinflammation, compounds A6 and A11 of the present invention, in the LPS-induced BV-2 microglia model, not only inhibit NO release activity (IC50) 50 It improved by 1.6-2.0 times and significantly increased cell survival rate from 37.25% to 64.26%-68.51%, achieving synergistic optimization of anti-inflammatory efficacy and cell safety, and demonstrating better therapeutic potential. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0017] Figure 1 These are the docking results of 17 small drug molecules obtained through virtual screening.

[0018] Figure 2 This is a heatmap of the Tanimoto coefficient.

[0019] Figure 3 Compounds A6 and A11 inhibit the mRNA levels of pro-inflammatory factors in LPS-induced BV-2 microglia.

[0020] Figure 4 Compounds A6 and A11 inhibited LPS-induced protein expression levels of iNOS and COX-2 in BV-2 microglia. Detailed Implementation

[0021] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] Example 1

[0023] The parsed mGluR5 dimer PDB file was obtained from the Protein Data Bank database, and the protein structure was preprocessed using Schrödinger's Maestro software. Given that mGluR5 is a homodimer and both monomers' transmembrane domains can bind allosteric small molecules, the dimer was split into two independent monomers. Small molecules bound to the allosteric sites were extracted from the original PDB structure, preprocessed, and then re-attached to the allosteric pockets of mGluR5. To evaluate whether the selected crystal and docking method could accurately reproduce the actual binding mode of the co-crystallized ligand in the experiment, the root mean square deviation (RMSD) between the docked ligand conformation and the native PAM conformation in the crystal structure was calculated. Generally, an RMSD threshold less than 2.0 Å is considered a successful docking. As shown in Table 1, the Glide docking method using the SP scoring function successfully reproduced near-native ligand binding postures in all seven binding pockets of the cryo-electron microscopy structure.

[0024] Table 1. RMSD (Å) of docking conformation relative to experimental crystal structure conformation

[0025] Example 2 Compared to evaluating binding conformations, the model's ability to reliably distinguish between active and inactive compounds is another key performance indicator for evaluating the effectiveness of the virtual screening process. Therefore, we further utilized each structural model to test its ability to identify real PAMs from inactive bait molecules. Known active mGluR5 allosteric modulators were collected by reviewing literature and accessing the IUPHAR / BPS website; simultaneously, corresponding bait molecules were generated using the DUDE-E website. After pretreatment of all molecules, they were docked into pretreated mGluR5 monomer allosteric pockets. The screening ability of each protein conformation was quantified by calculating the area under the ROC curve (AUC) constructed from the docking scores of known PAMs and bait molecules. The results showed that all structures had high AUC values, indicating strong discriminative ability (Table 2).

[0026] Table 2. AUC of two binding pockets in different PDB structures

[0027] Example 3 While effective ligand enrichment does not guarantee success in future virtual screening, such benchmark assessments remain valuable for optimizing docking parameters and procedures. Therefore, the EF values ​​of the top 0.5%, 1%, and 2% were further evaluated. According to Table 3, all structures except 8X0F (PDB IDs: 8X0B, 8X0C, 8X0D) performed well. Structure 8X0F had EF values ​​of 0.0 at EF0.5% and EF1%, and even at EF2% (3.08), the value was still relatively low. Based on the comprehensive evaluation (docking reproducibility, AUC discrimination, and EF enrichment capability), three high-performing structural models (PDB IDs: 8X0B, 8X0C, and 8X0D) were ultimately selected for subsequent large-scale virtual screening to discover novel mGluR5 receptor PAM candidate compounds.

[0028] Table 3. EF0.5%, EF1%, and EF2% for the two binding pockets in different PDB structures.

[0029] Example 4 After screening and validating the structural models, a systematic virtual screening of an internal ligand library was performed on the six selected allosteric pockets. First, a total of 1,741,694 compounds were prepared using the LigPrep module, and then filtered according to Lipinski's five rules, retaining 1,241,509 molecules for subsequent docking.

[0030] Example 5

[0031] The 1,241,509 retained molecules were sequentially docked to the three evaluated models using a hierarchical docking strategy. First, high-throughput virtual screening narrowed the candidate pool to 124,150 high-resolution molecules, then standard precision docking further refined the pool to 12,415 compounds, and finally additional precision docking identified 1,241 potential ligands with high affinity.

[0032] Example 6

[0033] Next, the blood-brain barrier permeability potential and drug-likeness of these 1241 molecules were evaluated. To ensure the chemical diversity of the screening results, the remaining compounds were clustered, and based on a combination of molecular structure and scoring, 100 representative molecules were selected for detailed visual examination, ultimately identifying 17 candidate molecules with distinct structures. Figure 1 ).

[0034] Example 7

[0035] To ensure good structural diversity among the selected molecules, similarity coefficients were calculated between them. Based on... Figure 2 The results showed that the Tc values ​​among the 17 molecules were all less than 0.5, indicating good structural diversity among the 17 molecules. Figure 2 The color scale indicates the degree of similarity, ranging from 0 to 1. The elements on the diagonal represent comparisons of the molecules themselves, with a similarity coefficient of 1. These 17 compounds were purchased from TargetMol Biochemicals for subsequent experimental verification.

[0036] Example 8

[0037] Nitric oxide (NO) production rate assay: To examine the effects of 17 compounds on LPS-induced microglial inflammatory responses, this study measured the concentration of nitric oxide (NO) in the culture supernatant of BV-2 microglia after LPS stimulation. BV2 cells (mouse microglia) were seeded into 96-well culture plates using DMEM medium and cultured in a 37°C incubator containing 5% CO2. Subsequently, BV2 cells were sputtered at 2.0 × 10⁻⁶ cells / well. 4 Cells were seeded at a density of 100 cells / well in 96-well plates. Cells were divided into three groups: a drug-treated group, a positive control group, and an LPS model group. After 24 hours of LPS stimulation, 50 μl of cell culture supernatant was transferred to a new 96-well plate, and 50 μl of Griess reagent was added and mixed. The absorbance was measured at 540 nm using a BioTe microplate reader. The NO production rate in the LPS model group was set as 100% (n=3), and the NO production rates in the other groups were calculated accordingly.

[0038] Cell viability assay: Cell viability was assessed using the MTT assay. BV2 cells were seeded in 96-well plates using DMEM medium and cultured at 37°C in a 5% CO2 incubator. Cells were divided into a drug-treated group and an LPS model group. 10 μl of MTT reagent was added to each well of BV2 cells, and the cells were incubated at 37°C for 1 hour. Subsequently, 100 μl of dimethyl sulfoxide (DMSO) was added to each well to dissolve the generated formazan crystals, and the OD value was measured at 490 nm using a microplate reader. The cell viability of the LPS model group (n=3) was set as 100%, and the cell viability of the other groups was calculated accordingly.

[0039] Results: As shown in Table 4, the mGluR5 receptor selective positive allosteric regulator VU0360172, used as a positive control, showed an IC50 value of 9.96±2.57 μM for NO inhibition and 37.25±0.47 μM for BV2 cell viability. Among the 17 tested compounds, A6 and A11 exhibited the best anti-inflammatory activity, with IC50 values ​​of 6.21±0.40 μM and 4.99±0.51 μM for inhibiting NO production, respectively. The IC50 values ​​of compounds A6 and A11 for inhibiting cell viability were 64.26±9.56 μM and 68.51±3.96 μM, respectively. These results indicate that, compared with VU0360172, compounds A6 and A11 have superior anti-inflammatory effects on microglial inflammation and lower cytotoxicity.

[0040] Table 4. Anti-inflammatory activity of the compounds in LPS-induced BV-2 microglia.

[0041] Example 9 RNA Extraction and Real-Time Quantitative PCR Analysis: To further evaluate the regulatory effects of compounds A6 and A11 on microglial inflammation, real-time quantitative PCR (Table 5) was used to detect the transcriptional levels of pro-inflammatory mediators interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), and NOD-like receptor family pyrin domain protein 3 (NLRP3). BV-2 microglia were pretreated with compounds A6 and A11 (5 μM and 10 μM) for 2 hours, followed by stimulation with LPS (100 ng / mL) for 6 hours. Total RNA was extracted from microglia using TRNzol Universal Reagent. cDNA synthesis was performed using the HiScript III RT SuperMix for qPCR kit. Real-time quantitative PCR was performed on Applied Biosystems 7500 cells using the ChamQ Pro Universal SYBR qPCR Master Mix. Using GAPDH as an internal reference gene, 2 −ΔΔCT The method calculates the relative gene expression level.

[0042] Table 5. Primers used for real-time quantitative PCR

[0043] Test results: The results show ( Figure 3 , Figure 3In the diagram, A represents IL-1β, B represents IL-6, C represents TNF-α, D represents iNOS, E represents COX-2, and F represents NLRP3. LPS stimulation significantly upregulated the mRNA expression of IL-1β, IL-6, TNF-α, iNOS, COX-2, and NLRP3 in BV-2 microglia. Treatment with compound A6 resulted in a dose-dependent decrease in the transcriptional levels of IL-1β, TNF-α, iNOS, and COX-2. Furthermore, treatment with compound A11 significantly inhibited the mRNA expression of IL-1β, IL-6, TNF-α, iNOS, COX-2, and NLRP3.

[0044] Example 10

[0045] Western blotting: To further investigate the regulatory effects of compounds on microglia activation, the protein expression levels of key inflammatory enzymes iNOS and COX-2 were assessed using Western blotting. After appropriate treatment, BV-2 microglia were lysed in RIPA lysis buffer containing 1% protease inhibitor, 1 mM NaF, 1 mM Na3VO4, and 1 mM PMSF for 30 minutes on ice. The lysate was centrifuged at 12,000 × g for 15 minutes at 4°C, mixed with 5× SDS loading buffer, and separated by SDS-PAGE electrophoresis. The proteins were then transferred to a nitrocellulose membrane, blocked with 5% skim milk at room temperature for 2 hours, and incubated overnight at 4°C with primary antibody. Following this, the membrane was incubated with HRP-labeled secondary antibody for 1 hour at room temperature. Finally, protein bands were detected by enhanced chemiluminescence immunoassay and analyzed using a fully automated chemiluminescence imaging system.

[0046] Test results: The results show ( Figure 4 , Figure 4 In the diagram, A represents the Western blot (WB) plot of iNOS and COX-2 protein expression levels, and B and C represent the relative expression levels of iNOS and COX-2, respectively. LPS stimulation significantly upregulated the expression of iNOS and COX-2 in BV-2 microglia. Compounds A6 and A11 both inhibited LPS-induced iNOS and COX-2 protein expression in a dose-dependent manner. These results indicate that A6 and A11 can significantly reduce the protein expression levels of the inflammation-related enzymes iNOS and COX-2.

[0047] This study employed a multi-conformation structure virtual screening approach to discover novel mGluR5 positive allosteric modulators. By integrating multiple crystal structures from the receptor's allosteric pocket, a reliable docking and screening process was established, effectively distinguishing known active molecules from decoy molecules. Based on this computational strategy, 17 candidate compounds with good drug-like properties and structural diversity were screened. Subsequent biological validation revealed that two highly potent compounds, A6 and A11, significantly inhibited the inflammatory response in an LPS-activated BV-2 microglia model. These two compounds dose-dependently reduced NO production and inhibited the expression of key pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, iNOS, COX-2, and NLRP3) and inflammatory enzymes (iNOS, COX-2), while exhibiting good cellular safety.

[0048] The above embodiments describe the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are only illustrative of the principles of the present invention. Various changes and modifications can be made to the present invention without departing from the scope of the principles of the present invention, and all such changes and modifications fall within the protection scope of the present invention.

Claims

1. A class of mGluR5 small molecule allosteric modifiers, characterized in that, The mGluR5 small molecule allosteric modifier is compound A6 or compound A11. The molecular structure of compound A6 is shown in formula (I), and the molecular structure of compound A11 is shown in formula (II). 。 2. The mGluR5 small molecule allosteric modifier as described in claim 1, characterized in that, mGluR5 small molecule allosteric modulators were obtained through a virtual screening method, which included the following steps: 1) Obtain the dimeric crystal structure of mGluR5 from a protein database; 2) Preprocess the crystal structure and verify the reliability of the docking method; 3) Use a hierarchical docking strategy to screen the compound library, including high-throughput virtual screening, standard precision docking, and ultra-fine precision docking; 4) Compound optimization is performed based on docking scores, blood-brain barrier permeability, and drug-like properties.

3. The application of the mGluR5 small molecule allosteric modulator as described in claim 1 in the preparation of a drug, characterized in that, The drug is used to suppress microglial cell inflammation.

4. The application of the mGluR5 small molecule allosteric modulator as described in claim 3 in the preparation of a drug, characterized in that, IC50 of the anti-inflammatory activity of compounds A6 and A11 50 The values ​​were 6.21±0.40 μM and 4.99±0.51 μM, respectively.

5. The application of the mGluR5 small molecule allosteric modulator as described in claim 3 in the preparation of a drug, characterized in that, Suppressing microglial inflammation includes reducing nitric oxide production.

6. The application of the mGluR5 small molecule allosteric modulator as described in claim 3 in the preparation of a drug, characterized in that, Inhibiting microglial inflammation includes suppressing the mRNA expression of pro-inflammatory factors, which are selected from the group consisting of interleukin-1β, interleukin-6, tumor necrosis factor-α, inducible nitric oxide synthase, cyclooxygenase-2, and NOD-like receptor family pyrin domain protein 3.

7. The application of the mGluR5 small molecule allosteric modulator as described in claim 3 in the preparation of a drug, characterized in that, Inhibiting microglial inflammation includes suppressing the protein expression of iNOS and COX-2.

8. The application of the mGluR5 small molecule allosteric modulator as described in claim 3 in the preparation of a drug, characterized in that, Microglial inflammation is induced by lipopolysaccharide.

9. The application of the mGluR5 small molecule allosteric modulator as described in claim 3 in the preparation of a drug, characterized in that, Drugs are used to treat or prevent neurodegenerative diseases.

10. The application of the mGluR5 small molecule allosteric modulator as described in claim 3 in the preparation of a drug, characterized in that, The drug contains a pharmaceutically acceptable carrier or excipient.

Images