关于 Dispel-Scar 软膏治疗疤痕的分子靶点和机制的网络药理学、分子对接分析和实验验证。

IF 1.6 4区医学 Q4 BIOCHEMICAL RESEARCH METHODS

Combinatorial chemistry & high throughput screening Pub Date : 2024-08-21 DOI:10.2174/0113862073335953240820075044

Zhaoyi Li, Yi Cao, Hui Li, Sihua Le, Libo Yin

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引用次数: 0

摘要

民族药理学意义：祛疤膏在中医中被用于治疗瘢痕组织，越来越多的证据表明祛疤膏具有强大的治疗作用；然而，其确切机制仍有待探索：研究目的：本研究采用网络药理学、分子对接和实验验证等方法探讨了DSO对瘢痕的分子作用机制：材料：研究人员利用公共数据库预测了DSO抗疤痕的生物活性成分和假定靶点。使用 Cytoscape 软件构建了化合物-靶点网络。利用ClueGo和FunRich进行了富集分析，以明确枢纽靶点的生物功能和相关途径。分子对接用于验证主要活性成分与中心靶标之间的相关性，并使用 PyMol 2.3 进行可视化。实验验证采用 CCK-8、伤口划痕、细胞活性氧和 Western 印迹检测法阐明了 DSO 对瘢痕疙瘩成纤维细胞的影响。结果：DSO治疗瘢痕的网络药理学分析确定了146种成分和1078个基因靶点。主要靶点包括前列腺素内过氧化物合成酶 2、基质金属肽酶和一氧化氮合成酶 2。ClueGo 分析发现了 29 个通路（p&amp;lt;0.05）和 FunRich 345 个通路（p&amp;lt;0.05），主要是类收费受体、TGF-β、白细胞介素-4/13、glypican 和肿瘤坏死因子相关凋亡诱导配体通路。分子对接显示，MMP2-黄酮黄素、MMP9-木犀草素和MMP-9-山奈酚与DSO结合得最好。DSO可抑制瘢痕成纤维细胞的增殖和迁移，并以浓度依赖的方式促进其凋亡。DSO 还能降低 TGF-β1、-βR2、pSMAD2、pSMAD3、SMAD4、CoL1a1 和 MMP2 的表达：网络药理学、分子对接和实验验证表明，DSO&#039;具有治疗疤痕的潜力。它可能通过 TGF-β1/SMADs/MMPs 信号通路抑制疤痕，为 DSO&#039 的疤痕治疗应用提供了依据。

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Network Pharmacology, Molecular Docking Analysis and Experiment Validations on Molecular Targets and Mechanisms of the Dispel-Scar Ointment in Scar Treatment.

Ethnopharmacological relevance: Dispel-Scar Ointment is used in Traditional Chinese Medicine to treat scarred tissue and increasing evidence has shown that DSO has potent therapeutic; however, its exact mechanism remains unexplored.

Aim of the study: This study explored the molecular mechanisms of action of DSO in scarring using network pharmacology, molecular docking, and experimental validation.

Materials and methods: Public databases were used to predict the bioactive ingredients and putative targets of DSO against scars. A compounds-targets network was constructed using the Cytoscape software. Enrichment analysis was performed using ClueGo and FunRich to specify the biological functions and associated pathways of hub targets. Molecular docking was used to verify the correlation between the major active components and hub targets, visualised using PyMol 2.3. Experimental validations were conducted to elucidate the influence of DSO on keloid fibroblast cells using the CCK-8, wound-scratch, cell reactive oxygen species, and western blot assays. Results：Network pharmacological analysis of DSO for scar treatment identified 146 ingredients and 1078 gene targets. Major targets included, prostaglandin-endoperoxide synthase 2 matrix metallopeptidases, and nitric oxide synthase 2. ClueGo analysis revealed 29 pathways (p&amp;lt;0.05) and FunRich 345 pathways (p&amp;lt;0.05), mainly toll-like receptor, TGF-β, interleukin-4/13, glypican, and tumour necrosis factor-related apoptosis-inducing ligand pathways. Molecular docking showed MMP2-flavoxanthin, MMP9-luteolin and MMP-9-kaempferol bound best to DSO. DSO could inhibit the proliferation and migration of scar fibroblasts and promote their apoptosis in a concentration-dependent manner. DSO also decreased TGF-β1, -βR2, pSMAD2, pSMAD3, SMAD4, CoL1a1, and MMP2 expression.

Conclusions: Network pharmacology, molecular docking, and experimental validation showed DSO&#039;s potential in treating scars. It may inhibit scars via the TGF-β1/SMADs/MMPs signalling pathway, providing a basis for DSO&#039;s scar treatment application.

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来源期刊

Combinatorial chemistry & high throughput screening 化学-生化研究方法

CiteScore

3.10

自引率

5.60%

发文量

327

审稿时长

7.5 months

期刊介绍： Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.