Novel small molecule drug virtual screening method for regulating brown adipose tissue and application
Through the molecular similarity screening of PPARγ binding pocket screening and the traditional Chinese medicine database, the problems of low side effects and safety of existing obesity treatment drugs were solved, and compounds with selective PPARγ regulation were screened, achieving efficient screening of obesity treatment drugs and Improved safety.
Patent Information
- Application Number
- CN202310813681.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-07-04
- Publication Date
- 2025-01-07
AI Technical Summary
Existing obesity treatment drugs have problems with side effects and low safety, and existing PPARγ agonists may cause cardiovascular risks during long-term use, making it difficult to effectively induce brown fat production.
Using computer-assisted drug design and molecular similarity screening methods, PPARγ selective regulators were screened through screening and molecular docking of PPARγ binding pockets, natural compounds were screened in combination with traditional Chinese medicine databases, and 2D and 3D molecular similarity screening were performed to screen them for promotion. Fat browned compounds.
The screening efficiency and safety of obesity treatment drugs were improved, and leading compounds with selective PPARγ regulation were found, such as NJT-2, which can effectively induce brown adipogenesis, reduce the number and cost of compounds, and improve screening efficiency.
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Abstract
Description
Technical Field
[0001] The present invention relates to the field of drug screening, and in particular to a novel virtual screening method for small molecule drugs for regulating brown adipose tissue and its application. Background Art
[0002] Obesity is a systemic metabolic disease characterized by excessive accumulation of adipose tissue, which can further cause type II diabetes, cardiovascular disease, heart disease and cancer. At present, obesity is widely prevalent in the world. In 2020, the number of obese people in the world reached 1.211 billion, a year-on-year increase of 5.04%. The strategies for treating obesity mainly include drug therapy, dieting, exercise and surgery, with drug therapy as the main intervention method. The drugs for treating obesity mainly include pancreatic lipase inhibitors and appetite suppressants of the central nervous system. However, due to the side effects of these drugs (liver damage, adverse reactions of the nervous system, and low safety), their clinical application is further limited. Therefore, it is urgent to develop new drugs for the treatment of obesity.
[0003] The adipose tissue of mammals includes white fat, brown fat and beige fat. White fat mainly stores lipids, while brown fat highly expresses (uncoupling protein-1) UCP-1 and is an important tissue for body heat production. Therefore, inducing brown fat production or browning of white fat is an ideal strategy for obesity treatment.
[0004] Peroxisome proliferator-activated receptor γ (PPARγ) is an important ligand-dependent nuclear transcription factor that controls cell life activities and is also an important energy regulator of the body. PPARγ is highly expressed in adipocytes and plays a decisive role in adipose differentiation. It is involved in regulating fat metabolism, brown fat production, and the formation of inflammation. Targeted regulation of adipose PPARγ is one of the important research directions for obesity treatment.
[0005] Thiazolidinediones (TZDs), as classic PPARγ full agonists, such as rosiglitazone, pioglitazone, and troglitazone, are considered to be the best insulin sensitizers in clinical practice, and have a significant improvement effect on the treatment of type II diabetes. Although the above three TZDs are already on the market, with their widespread clinical use, their adverse reactions have been reported one after another, such as weight gain, water and sodium retention, osteoporosis, tumors, and cardiovascular risks, especially long-term medication-induced cardiovascular risks. In order to retain the insulin sensitizing effect mediated by PPARγ to the greatest extent and minimize the occurrence of related adverse reactions, the concept of selective PPARγ modulators (SPPARγMs) has been proposed and developed, and has guided the practice of new drug research and development.
[0006] The advantage of Chinese medicine in treating obesity is that it regulates the balance of the spleen and stomach system and restores the overall function. For example, there are Qi-invigorating and spleen-strengthening drugs with Atractylodes macrocephala, Astragalus membranaceus, Licorice root and Tangerine peel as the core, dampness-removing drugs with Poria cocos and Alisma orientalis as the core, and bowel-clearing, digestive and digestive drugs with Rhubarb, Hawthorn, Lotus leaf and Cassia seed as the main drugs. Chinese medicine has been used clinically for hundreds of years, and its clinical safety has been effectively guaranteed. Chinese medicine has obvious effects and no obvious side effects, and has played an increasingly important role in the treatment of obesity in recent years.
[0007] Chinese medicine chemistry has become complex and diverse, and some compounds have been reported to be selective regulators of PPARγ and have the ability to induce browning, such as genistein, soybean flavonoids, honokiol, osthole and quercetin. A compound database was established based on Chinese medicines that regulate the spleen and stomach, and partial agonists of PPARγ were screened from them, which greatly improved the screening efficiency and obtained more effective compounds.
[0008] CDDO is a PPARγ selective modulator with a strong fat browning function, but its toxic side effects limit its further development and utilization. Molecular similarity includes 2D and 3D molecular fingerprints. 2D similarity screening is fast and accurate, and can reflect the structural fragments of the compound, but the skeleton transition ability is weak. 3D similarity greatly improves the ability of skeleton transition, but the accuracy is relatively low. Combining 2D and 3D molecular fingerprints, CDDO is screened for molecular similarity to improve screening efficiency and hit rate.
[0009] Therefore, we used computer-aided drug design to target PPARγ and analyze its new binding pocket. We used our own local database of small molecules and virtual screening methods based on molecular similarity and molecular docking to screen PPARγ selective regulators and explore their role in promoting fat browning, thereby discovering lead compounds for the treatment of obesity. Summary of the invention
[0010] Based on the above problems, the present invention provides a novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue, which can reduce the number of compounds, save costs, improve screening efficiency, and can be used for further development and utilization of lead compounds for the treatment of obesity.
[0011] A novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue, comprising the following steps:
[0012] S1: Screening of the PPARγ binding pocket
[0013] Hydrogen-deuterium exchange mass spectrometry was used to obtain peptides with different hydrogen-tritium atomic exchange rates of the CDDO-PPARγ complex. The binding pocket of PPARγ was predicted using Sitemap software, and CDDO was further molecularly docked with the predicted binding pocket to finally obtain key amino acid information. The protein sequences of the above two were intersected to obtain the key amino acid residues of Ser342, Gln273 and Gln444.
[0014] S2: Identification of the PPARγ binding pocket
[0015] The corresponding mutants (S342A, Q273A and Q444A) were constructed in vitro and the dual luciferase transcription activity was determined. The stability of the complex was further investigated using molecular dynamics simulation technology.
[0016] S3: Establishment of natural product database
[0017] The traditional Chinese medicine compound prescriptions that can regulate fat metabolism were screened from the traditional Chinese medicine classics "Treatise on the Piwei", "Golden Chamber" and "Treatise on Febrile Diseases". The compounds in the compound prescriptions were annotated based on the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), the Traditional Chinese Medicine Integrated Database TCMID and the Chinese Academy of Sciences Chemistry Database (CSDB), and finally 4097 natural compounds were obtained.
[0018] S4: 2D and 3D molecular similarity screening
[0019] Similarity screening was performed based on the 2D and 3D molecular fingerprints of CDDO, and further screening was performed using ADME characteristics (LogP < 5.0) and cluster analysis, and ultimately 10 potential compounds were obtained.
[0020] S5: Molecular docking and binding free energy analysis based on the novel binding pocket
[0021] Based on the binding pocket information obtained in step S2 and the 10 compounds obtained in step S4, molecular docking and binding free energy analysis were performed. Based on the interaction information with key amino acids, 2 compounds were finally obtained.
[0022] S6: In vitro activity assessment
[0023] The compound obtained in step S5 is purchased and subjected to in vitro activity evaluation, specifically including transcription activity assay and browning induction ability evaluation.
[0024] S7: In vivo effect evaluation
[0025] The excellent compounds obtained in the screening step S6 were evaluated in the high-fat induced C57BL / 6J mouse model, including body weight changes, white fat browning ability, white fat fatty acid β-oxidation level and UCP-1 expression.
[0026] Compared with the existing virtual technology, the advantages of the present invention are: for the first time, the binding pocket of PPARγ was identified, providing screening information for the efficient screening of PPARγ selective modulators; for the first time, a database of compounds for regulating the spleen and stomach was established, providing a compound library for screening PPARγ partial agonists, saving time and cost and improving screening efficiency; through this virtual screening method, selective modulators that efficiently target PPARγ can be obtained, which can be used to further develop new drugs for the treatment of obesity. BRIEF DESCRIPTION OF THE DRAWINGS
[0027] Figure 1 This is an information diagram of the new binding pocket of PPARγ obtained in the present invention.
[0028] Figure 2 is the transcriptional activity of PPARγ mutants.
[0029] Figure 3 These are the structural diagrams of 10 compounds obtained through virtual screening of the present invention.
[0030] Figure 4 Binding free energy analysis of 8 compounds.
[0031] Figure 5 In vitro activity evaluation of compound NJT-2 and compound NJT-5.
[0032] Figure 6 To evaluate the in vivo efficacy of compound NJT-2. DETAILED DESCRIPTION The principles and features of the present invention are described below in conjunction with examples. The examples are only used to explain the present invention and are not used to limit the scope of the present invention.
[0033] Example:
[0034] A novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue, comprising the following steps:
[0035] S1: Screening of the PPARγ binding pocket
[0036] Using hydrogen-deuterium exchange mass spectrometry, peptides with different hydrogen-tritium atomic exchange rates of the CDDO-PPARγ complex were obtained. The binding pocket of PPARγ was predicted using Sitemap software, and 5 pocket models with high scores were generated. The small molecule CDDO was further docked with the predicted binding pocket, and finally the key amino acid information of the interaction between CDDO and PPARγ was obtained. The protein sequences of the above two were intersected to obtain the key amino acid residues of Ser342, Gln273 and Gln444.
[0037] S2: Identification of the PPARγ binding pocket
[0038] The corresponding mutants (S342A, Q273A and Q444A) were constructed in vitro and the dual luciferase transcriptional activity was determined. The transcriptional activity of the S342A mutant was significantly reduced. The molecular dynamics simulation technology was further used to simulate the dynamics of the CDDO-PPARγ (S342 binding site) complex. The results showed that the RMSD value of the complex fluctuated around 0.6 angstroms, indicating that the energy system of the protein complex tended to be stable in the binding mode.
[0039] S3: Establishment of natural product database
[0040] According to TCM theory and clinical practice, Chinese herbal compound prescriptions that can regulate fat metabolism were screened from Treatise on the Spleen and Stomach, Synopsis of the Golden Chamber, and Treatise on Febrile Diseases, including Liujunzi Decoction, Shenling Baizhu Powder, Lizhong Decoction, Xiaojianzhong Decoction, Dachengqi Decoction, Sijunzi Decoction, Chaihu Shugan Powder, Xiaoyao Powder, Xiaochengqi Decoction, Banxia Xiexin Decoction, and Yinchenhao Decoction. Single herbs with a frequency of use ≥ 2 were further screened, and finally 32 herbs were screened from Treatise on Febrile Diseases, 43 herbs were screened from Synopsis of the Golden Chamber, and 62 herbs were screened from Treatise on the Spleen and Stomach. The compounds in the compound prescriptions were annotated based on the Chinese Medicine Systems Pharmacology Database (TCMSP), the Chinese Medicine Integrated Database TCMID, and the Chinese Academy of Sciences Chemical Database (CSDB). 3056 compounds were annotated from TCMSP, 2275 compounds were annotated from TCMID, and 2032 compounds were annotated from CSDB. After removing duplicates, 4097 natural compounds were finally obtained.
[0041] S4: 2D and 3D molecular similarity screening
[0042] According to the 4097 compounds obtained in step S3, the 2D and 3D molecular fingerprints of CDDO were used for similarity screening. The 2D molecular fingerprints include MACCS, ECFP and Topological, and the top 20 compounds of each score were taken to obtain 51 compounds. The 3D molecular fingerprints include Screen-pha and Screen-ato, and the top 20 compounds of each score were taken to obtain 38 compounds. After removing the repeated compounds in 2D and 3D, 80 compounds were finally obtained. These 80 compounds were screened by ADME feature filtering (LogP < 5.0) and cluster analysis, and finally 10 potential compounds were obtained. The compound information is shown in Table 1.
[0043] Table 1 Information of 10 compounds screened based on molecular similarity
[0044] S5: Molecular docking and binding free energy analysis based on the novel binding pocket
[0045] Based on the binding pocket information obtained in step S2 and the 10 compounds obtained in step S4, molecular docking and binding free energy analysis were performed under the OPLS-2005 standpoint. The molecular docking scores and binding free energy are shown in Table 2. Based on the interaction information with the key amino acid (Ser342), two compounds were finally obtained.
[0046] Table 2 Compound molecular docking scores and binding free energy table
[0047] S6: In vitro activity assessment
[0048] The compounds NJT-2 and NJT-5 obtained in step S5 were purchased and compared with the classical agonist rosiglitazone (RSG) and the partial agonist (CDDO) for in vitro activity evaluation, including transcriptional activity determination and browning induction ability evaluation, and the final concentration of the compound test was 100nM. The results showed that NJT-2 has a strong PPARγ agonist ability, which is about 30% of the full agonist RSG, and belongs to the category of selective regulators (agonist activity is 20%-60% of RSG). In addition, compound NJT-2 can significantly increase the expression of brown genes (UCP-1, PRDM16, COX8B, DIO2, ATGL and Acotl1).
[0049] S7: In vivo effect evaluation
[0050] The compound NJT-2 with excellent activity obtained in step S6 was screened, and the compound was evaluated in high-fat induced C57BL / 6J mice (10 mg / kg), and the drug was continuously administered by gavage for 2 weeks. The changes in body weight, the ability of white fat to brown, the level of white fat fatty acid β-oxidation, and UCP-1 expression were investigated. The results showed that compound NJT-2 can effectively improve white fat content, weight gain, insulin resistance, free fatty acids, low-density lipoprotein, and total cholesterol. Compound NJT-2 can increase brown fat content, induce UCP-1 expression, and promote fatty acid β-oxidation.
[0051] The above is an embodiment of the present invention. The above embodiments and the specific parameters in the embodiments are only for the purpose of clearly describing the invention verification process, and are not intended to limit the patent protection scope of the present invention. The patent protection scope of the present invention is still subject to its claims, and any equivalent structural changes made using the contents of the specification of the present invention should be included in the protection scope of the present invention.
Claims
1. A novel virtual screening method for small molecule drugs for regulating brown adipose tissue and its application, characterized in that: The following steps are involved: S1: Screening of the PPARγ binding pocket Using hydrogen-deuterium exchange mass spectrometry, peptides with different hydrogen-tritium atomic exchange rates of the CDDO-PPARγ complex were obtained. The binding pocket of PPARγ was predicted using Sitemap software, and the small molecule CDDO was further docked with the predicted binding pocket to obtain key amino acid information. The protein sequences of the two proteins were intersected to obtain key amino acid residues. S2: Identification of the PPARγ binding pocket The corresponding mutants were constructed in vitro and the dual luciferase transcriptional activity was determined. Molecular dynamics simulation technology was further used to investigate the stability of the CDDO-PPARγ complex. S3: Establishment of natural product database The recurrence of traditional Chinese medicine that can regulate fat metabolism was screened from traditional Chinese medicine classics, and the compound information in the compound was screened in the compound database. S4: 2D and 3D molecular similarity screening Similarity screening was performed based on the 2D and 3D molecular fingerprints of CDDO, and further screening was performed using ADME characteristics and cluster analysis. S5: Molecular docking and binding free energy analysis based on the novel binding pocket According to the methods described in claims S2 and S4, the obtained binding pockets and compounds are further subjected to molecular docking and binding free energy analysis. S6: In vitro activity assessment According to the method of claim S5, the compound is further subjected to in vitro activity evaluation, specifically including transcription activity determination, browning induction ability and fatty acid oxidation ability evaluation. S6: In vivo effect evaluation According to the method described in claim S6, the screened compounds are evaluated in high-fat induced C57BL / 6J mice, specifically including body weight changes, white fat browning ability, white fat fatty acid β-oxidation level and UCP-1 expression.
2. A novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue according to claim 1, characterized in that: The key amino acids in step S1 are Ser342, Gln273 and Gln444.
3. A novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue according to claim 1, characterized in that: The novel binding pocket identified in step S2 is a binding mode formed by the key amino acid Ser342.
4. A novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue according to claim 1, characterized in that: The Chinese medicine classics described in step S4 are "Treatise on the Piwei", "Golden Chamber Synopsis" and "Treatise on Febrile Diseases", and the small molecule annotation databases are the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), the Traditional Chinese Medicine Integrated Database TCMID and the Chinese Academy of Sciences Chemistry Database (CSDB).
5. A novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue according to claim 1, characterized in that: The 2D molecular fingerprints in step S4 are MACCS, ECFP and Topological, and the 3D molecular fingerprints are Shape-pha and Shape-ato, and the top 20 are selected for subsequent analysis. The ADME screening parameter is Log P < 5.
0.
6. A novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue according to claim 1, characterized in that: The compound described in step S5 is Saikosaponin D, Saikosaponin A, Licorice-saponin F3, Saikosaponin B3, Ginsenoside Rg3, Longispinogenin 3-O-beta-D-glucuronopyranoside, Uralsaponin B, 26-Deoxyactein, Arjungenin, Hederagenin 3-O-arabinoside.
7. A novel virtual screening method and application of small molecule drugs for regulating brown adipose tissue according to claim 1, characterized in that: The compounds described in step S6 are Saikosaponin A and Ginsenoside Rg3.
8. Use of the method according to claim 1 as a method for screening small molecule natural products for regulating brown fat activity.
9. Use of the method according to claim 1 for screening obesity drugs.