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基于生物信息学分析的多囊卵巢综合征发病机制新药物候选物再利用和关键分子鉴定。

Repurposing new drug candidates and identifying crucial molecules underlying PCOS Pathogenesis Based On Bioinformatics Analysis.

机构信息

Student Research Committee, Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Cellular & Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

出版信息

Daru. 2021 Dec;29(2):353-366. doi: 10.1007/s40199-021-00413-9. Epub 2021 Sep 4.

Abstract

BACKGROUNDS

Polycystic ovary syndrome affects 7% of women of reproductive ages. Poor-quality oocytes, along with lower cleavage and implantation rates, reduce fertilization.

OBJECTIVE

This study aimed to determine crucial molecular mechanisms behind PCOS pathogenesis and repurpose new drug candidates interacting with them. To predict a more in-depth insight, we applied a novel bioinformatics approach to analyze interactions between the drug-related and PCOS proteins in PCOS patients.

METHODS

The newest proteomics data was retrieved from 16 proteomics datasets and was used to construct the PCOS PPI network using Cytoscape. The topological network analysis determined hubs and bottlenecks. The MCODE Plugin was used to identify highly connected regions, and the associations between PCOS clusters and drug-related proteins were evaluated using the Chi-squared/Fisher's exact test. The crucial PPI hub-bottlenecks and the shared molecules (between the PCOS clusters and drug-related proteins) were then investigated for their drug-protein interactions with previously US FDA-approved drugs to predict new drug candidates.

RESULTS

The PI3K/AKT pathway was significantly related to one PCOS subnetwork and most drugs (metformin, letrozole, pioglitazone, and spironolactone); moreover, VEGF, EGF, TGFB1, AGT, AMBP, and RBP4 were identified as the shared proteins between the PCOS subnetwork and the drugs. The shared top biochemical pathways between another PCOS subnetwork and rosiglitazone included metabolic pathways, carbon metabolism, and citrate cycle, while the shared proteins included HSPB1, HSPD1, ACO2, TALDO1, VDAC1, and MDH2. We proposed some new candidate medicines for further PCOS treatment investigations, such as copper and zinc compounds, reteplase, alteplase, gliclazide, Etc.

CONCLUSION

Some of the crucial molecules suggested by our model have already been experimentally reported as critical molecules in PCOS pathogenesis. Moreover, some repurposed medications have already shown beneficial effects on infertility treatment. These previous experimental reports confirm our suggestion for investigating our other repurposed drugs (in vitro and in vivo).

摘要

背景

多囊卵巢综合征影响着 7%的育龄妇女。卵子质量差,以及更低的卵裂和着床率,降低了受精率。

目的

本研究旨在确定多囊卵巢综合征发病机制背后的关键分子机制,并重新利用与这些机制相互作用的新药候选物。为了更深入地预测,我们应用了一种新的生物信息学方法来分析多囊卵巢综合征患者中与药物相关的蛋白质和多囊卵巢综合征蛋白质之间的相互作用。

方法

从 16 个蛋白质组学数据集检索最新的蛋白质组学数据,并使用 Cytoscape 构建多囊卵巢综合征 PPI 网络。拓扑网络分析确定了枢纽和瓶颈。使用 MCODE 插件识别高度连接的区域,并使用卡方/ Fisher 精确检验评估多囊卵巢综合征簇与与药物相关的蛋白质之间的关联。然后,研究了关键的 PPI 枢纽-瓶颈以及与多囊卵巢综合征簇和与药物相关的蛋白质共享的分子(之间),以研究它们与以前美国 FDA 批准的药物的药物-蛋白质相互作用,从而预测新的药物候选物。

结果

PI3K/AKT 途径与一个多囊卵巢综合征子网络和大多数药物(二甲双胍、来曲唑、吡格列酮和螺内酯)显著相关;此外,VEGF、EGF、TGFB1、AGT、AMBP 和 RBP4 被鉴定为多囊卵巢综合征子网络与药物之间共享的蛋白质。另一个多囊卵巢综合征子网络与罗格列酮共享的顶级生化途径包括代谢途径、碳代谢和柠檬酸循环,而共享的蛋白质包括 HSPB1、HSPD1、ACO2、TALDO1、VDAC1 和 MDH2。我们提出了一些新的候选药物,用于进一步研究多囊卵巢综合征的治疗,如铜和锌化合物、瑞替普酶、阿替普酶、格列齐特等。

结论

我们的模型提出的一些关键分子已经被实验报道为多囊卵巢综合征发病机制中的关键分子。此外,一些重新利用的药物已经显示出对不孕治疗有益的效果。这些先前的实验报道证实了我们对其他重新利用药物(体外和体内)进行研究的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1764/8602600/0e7e6ef7e948/40199_2021_413_Fig1_HTML.jpg

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