{"title":"综合网络药理学、分子对接和实验验证,探索西诺明治疗骨关节炎的潜在机制","authors":"Shaojun Wang, Fanglin Lai, Ting Xiang, Yan Xu","doi":"10.1177/1934578x241262909","DOIUrl":null,"url":null,"abstract":"ObjectiveTo systematically explore the targets and signaling pathways of sinomenine (SIN) in the treatment of osteoarthritis (OA) using integrated network pharmacology, molecular docking, and experimental validation.MethodsThe TCMSP, SwissADME, and Pharmmapper databases were used to predict SIN targets, while the databases of GeneCards, DisGeNET, OMIM, and DrugBank were selected to acquire OA targets. Subsequently, the intersection targets of SIN and OA disease were collected using the Veeny platform. Then, the protein-protein interaction (PPI) network map of “SIN-targets-OA” was established using String database and Cytoscape software. Additionally, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed through the Database for Annotation, Visualization and Integrated Discovery (DAVID). Additionally, the potential proteins of SIN against OA were validated via molecular docking technique. Finally, the experimental validation was performed in SW1353 cells induced by interleukin (IL)-1β.ResultsA total of 315 potential targets of SIN and 4300 OA-associated targets were collected from public databases, and 42 intersecting potential targets of SIN and OA disease acquired. Then, the PPI network diagram of “SIN-targets-OA” was acquired that comprised a total of 43 nodes and 82 edges. Moreover, 173 GO and 21 KEGG pathway entries were screened with a P-value <.05. Among them, peroxisome proliferator-activated receptor (PPAR) and IL-17 are the core signaling pathways. Molecular docking technique indicated strong binding energies of SIN with PPAR (−6.1 kcal/mol) and IL-17 (−6.3 kcal/mol). Lastly, SIN at the concentration of 50 μmol/L has a significant effect on IL-1β-induced SW1353 cells by the inhibition of PPAR-γ and IL-17A proteins without cytotoxicity.ConclusionThis work revealed the underlying targets and signaling pathways of SIN against OA using integrated network pharmacology molecular docking, and experimental validation. These findings provide scientific evidence for the clinical application of SIN for OA treatment.","PeriodicalId":19019,"journal":{"name":"Natural Product Communications","volume":"11 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated Network Pharmacology, Molecular Docking, and Experimental Validation to Explore Potential Mechanisms of Sinomenine in the Treatment of Osteoarthritis\",\"authors\":\"Shaojun Wang, Fanglin Lai, Ting Xiang, Yan Xu\",\"doi\":\"10.1177/1934578x241262909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ObjectiveTo systematically explore the targets and signaling pathways of sinomenine (SIN) in the treatment of osteoarthritis (OA) using integrated network pharmacology, molecular docking, and experimental validation.MethodsThe TCMSP, SwissADME, and Pharmmapper databases were used to predict SIN targets, while the databases of GeneCards, DisGeNET, OMIM, and DrugBank were selected to acquire OA targets. Subsequently, the intersection targets of SIN and OA disease were collected using the Veeny platform. Then, the protein-protein interaction (PPI) network map of “SIN-targets-OA” was established using String database and Cytoscape software. Additionally, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed through the Database for Annotation, Visualization and Integrated Discovery (DAVID). Additionally, the potential proteins of SIN against OA were validated via molecular docking technique. Finally, the experimental validation was performed in SW1353 cells induced by interleukin (IL)-1β.ResultsA total of 315 potential targets of SIN and 4300 OA-associated targets were collected from public databases, and 42 intersecting potential targets of SIN and OA disease acquired. Then, the PPI network diagram of “SIN-targets-OA” was acquired that comprised a total of 43 nodes and 82 edges. Moreover, 173 GO and 21 KEGG pathway entries were screened with a P-value <.05. Among them, peroxisome proliferator-activated receptor (PPAR) and IL-17 are the core signaling pathways. Molecular docking technique indicated strong binding energies of SIN with PPAR (−6.1 kcal/mol) and IL-17 (−6.3 kcal/mol). Lastly, SIN at the concentration of 50 μmol/L has a significant effect on IL-1β-induced SW1353 cells by the inhibition of PPAR-γ and IL-17A proteins without cytotoxicity.ConclusionThis work revealed the underlying targets and signaling pathways of SIN against OA using integrated network pharmacology molecular docking, and experimental validation. These findings provide scientific evidence for the clinical application of SIN for OA treatment.\",\"PeriodicalId\":19019,\"journal\":{\"name\":\"Natural Product Communications\",\"volume\":\"11 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Natural Product Communications\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/1934578x241262909\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Natural Product Communications","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/1934578x241262909","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0
摘要
方法 利用 TCMSP、SwissADME 和 Pharmmapper 数据库预测 SIN 靶点,同时选择 GeneCards、DisGeNET、OMIM 和 DrugBank 数据库获取 OA 靶点。随后,利用 Veeny 平台收集了 SIN 和 OA 疾病的交叉靶点。然后,利用 String 数据库和 Cytoscape 软件建立了 "SIN-靶点-OA "的蛋白-蛋白相互作用(PPI)网络图。此外,还通过注释、可视化和综合发现数据库(DAVID)进行了基因本体(GO)和京都基因组百科全书(KEGG)通路富集分析。此外,还通过分子对接技术验证了 SIN 针对 OA 的潜在蛋白。最后,在白细胞介素(IL)-1β诱导的SW1353细胞中进行了实验验证。结果从公共数据库中共收集到315个SIN潜在靶点和4300个OA相关靶点,并获得了42个SIN和OA疾病的交叉潜在靶点。然后,得到了 "SIN-靶点-OA "PPI 网络图,该网络图由 43 个节点和 82 条边组成。此外,还筛选出 173 个 P 值为 0.05 的 GO 和 21 个 KEGG 通路条目。其中,过氧化物酶体增殖激活受体(PPAR)和 IL-17 是核心信号通路。分子对接技术表明,SIN 与 PPAR(-6.1 kcal/mol)和 IL-17 (-6.3 kcal/mol)的结合能很强。最后,浓度为 50 μmol/L 的 SIN 通过抑制 PPAR-γ 和 IL-17A 蛋白,对 IL-1β 诱导的 SW1353 细胞有显著效果,且无细胞毒性。这些发现为 SIN 治疗 OA 的临床应用提供了科学依据。
Integrated Network Pharmacology, Molecular Docking, and Experimental Validation to Explore Potential Mechanisms of Sinomenine in the Treatment of Osteoarthritis
ObjectiveTo systematically explore the targets and signaling pathways of sinomenine (SIN) in the treatment of osteoarthritis (OA) using integrated network pharmacology, molecular docking, and experimental validation.MethodsThe TCMSP, SwissADME, and Pharmmapper databases were used to predict SIN targets, while the databases of GeneCards, DisGeNET, OMIM, and DrugBank were selected to acquire OA targets. Subsequently, the intersection targets of SIN and OA disease were collected using the Veeny platform. Then, the protein-protein interaction (PPI) network map of “SIN-targets-OA” was established using String database and Cytoscape software. Additionally, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed through the Database for Annotation, Visualization and Integrated Discovery (DAVID). Additionally, the potential proteins of SIN against OA were validated via molecular docking technique. Finally, the experimental validation was performed in SW1353 cells induced by interleukin (IL)-1β.ResultsA total of 315 potential targets of SIN and 4300 OA-associated targets were collected from public databases, and 42 intersecting potential targets of SIN and OA disease acquired. Then, the PPI network diagram of “SIN-targets-OA” was acquired that comprised a total of 43 nodes and 82 edges. Moreover, 173 GO and 21 KEGG pathway entries were screened with a P-value <.05. Among them, peroxisome proliferator-activated receptor (PPAR) and IL-17 are the core signaling pathways. Molecular docking technique indicated strong binding energies of SIN with PPAR (−6.1 kcal/mol) and IL-17 (−6.3 kcal/mol). Lastly, SIN at the concentration of 50 μmol/L has a significant effect on IL-1β-induced SW1353 cells by the inhibition of PPAR-γ and IL-17A proteins without cytotoxicity.ConclusionThis work revealed the underlying targets and signaling pathways of SIN against OA using integrated network pharmacology molecular docking, and experimental validation. These findings provide scientific evidence for the clinical application of SIN for OA treatment.
期刊介绍:
Natural Product Communications is a peer reviewed, open access journal studying all aspects of natural products, including isolation, characterization, spectroscopic properties, biological activities, synthesis, structure-activity, biotransformation, biosynthesis, tissue culture and fermentation. It covers the full breadth of chemistry, biochemistry, biotechnology, pharmacology, and chemical ecology of natural products.
Natural Product Communications is a peer reviewed, open access journal studying all aspects of natural products, including isolation, characterization, spectroscopic properties, biological activities, synthesis, structure-activity, biotransformation, biosynthesis, tissue culture and fermentation. It covers the full breadth of chemistry, biochemistry, biotechnology, pharmacology, and chemical ecology of natural products.
Natural Product Communications is a peer reviewed, open access journal studying all aspects of natural products, including isolation, characterization, spectroscopic properties, biological activities, synthesis, structure-activity, biotransformation, biosynthesis, tissue culture and fermentation. It covers the full breadth of chemistry, biochemistry, biotechnology, pharmacology, and chemical ecology of natural products.