Exploring You-gui Pill for the Treatment of Diabetic Erectile Dysfunction: Data Mining Analysis, Network Pharmacology and Experiments In Vitro.

IF 1.6 4区 医学 Q4 BIOCHEMICAL RESEARCH METHODS Combinatorial chemistry & high throughput screening Pub Date : 2024-10-22 DOI:10.2174/0113862073329189241014102457
Jiaqi Chen, Yanan Gao, Yanqiu Zhang, Yue Sun, Yue Jiang, Yong Yang, Mingxing Wang
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Abstract

Introduction: The You-gui pill (YGP) is a classical compound used for treating antidiabetic erectile dysfunction (DMED). However, the specific active ingredients responsible for its effects on DMED and their mechanisms remain unclear.

Methods: In this paper, we used data mining techniques to analyze high-frequency herbs and herb combinations used in Chinese medicine for the treatment of DMED based on existing literature. Using network pharmacology to study the active components and mechanism of action of YGP against DMED, molecular docking was used to analyze the interactions of the active components with major structural proteins, nonstructural proteins, and mutants. Also, the therapeutic effect of YGP on hyperglycemic modelling and its underlying mechanisms were experimentally validated in CCEC cells by analyzing the expression of its relevant target mRNAs.

Results: Network pharmacological analysis identified the three core components of YGP as quercetin, kaempferol, and β-sitosterol, and constructed a PPI network map of common targets of YGP and DMED, which included HIF-1α, ALB, Bcl-2, INS, IL-1β, IL-6, TNF-α, CASP3, and TP53. Combined with molecular docking results, these targets had a strong binding affinity between them and the active ingredient compounds, with the highest affinity for HIF-1α and TNF-α. During the in vitro cellular assay validation, the HIF-1α, ALB, Bcl-2, TNF-α, and IL-6 mRNA in CCECs cells showed positive regulation after YGP intervention.

Conclusion: The combination of "data mining - network pharmacology - molecular docking - experimental validation" provides a powerful methodological basis for the study of the main active components and mechanism of action of YGP against DMED, as well as the development and application of the drug.

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探索治疗糖尿病勃起功能障碍的 "友桂丸":数据挖掘分析、网络药理学和体外实验。
简介右归丸(YGP)是一种用于治疗抗糖尿病勃起功能障碍(DMED)的经典复方制剂。然而,该药对勃起功能障碍的具体有效成分及其作用机制仍不清楚:本文在现有文献的基础上,利用数据挖掘技术分析了中医治疗 DMED 的高频中草药和中草药组合。利用网络药理学研究YGP对DMED的活性成分和作用机制,利用分子对接分析活性成分与主要结构蛋白、非结构蛋白和突变体的相互作用。此外,还通过分析 YGP 相关靶 mRNA 的表达,在 CCEC 细胞中实验验证了 YGP 对高血糖模型的治疗效果及其内在机制:网络药理学分析确定了YGP的三种核心成分为槲皮素、山奈酚和β-谷甾醇,并构建了YGP和DMED共同靶点的PPI网络图,包括HIF-1α、ALB、Bcl-2、INS、IL-1β、IL-6、TNF-α、CASP3和TP53。结合分子对接结果,这些靶点与活性成分化合物之间具有很强的结合亲和力,其中与 HIF-1α 和 TNF-α 的亲和力最高。在体外细胞检测验证中,YGP干预后,CCECs细胞中的HIF-1α、ALB、Bcl-2、TNF-α和IL-6 mRNA均呈现正向调节:结论:"数据挖掘-网络药理学-分子对接-实验验证 "相结合的方法为研究YGP抗DMED的主要活性成分和作用机制以及该药物的开发和应用提供了强有力的方法学基础。
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来源期刊
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.
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