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

Zeinab Dehghan, Samira Mohammadi-Yeganeh, Marzieh Sameni, Seyed Amir Mirmotalebisohi, Hakimeh Zali, Mohammad Salehi
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引用次数: 9

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).

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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的新候选药物再利用和关键分子鉴定。
背景:7%的育龄妇女患有多囊卵巢综合征。卵母细胞质量差,再加上卵裂率和植入率低,会减少受精。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,并重新利用与之相互作用的候选新药。为了预测更深入的见解,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药物相关蛋白和多囊卵巢综合症蛋白之间的相互作用。方法:从16个蛋白质组学数据集中检索最新的蛋白质组学信息,并使用Cytoscape构建PCOS PPI网络。拓扑网络分析确定了枢纽和瓶颈。MCODE插件用于识别高度连接的区域,并使用卡方/费雪精确检验评估PCOS簇和药物相关蛋白之间的关联。然后,研究了关键的PPI中枢瓶颈和共享分子(PCOS簇和药物相关蛋白质之间)与先前美国FDA批准的药物的药物-蛋白质相互作用,以预测新的候选药物。结果:PI3K/AKT通路与一个PCOS亚网络和大多数药物(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PCOS子网络与药物之间的共享蛋白。另一个PCOS子网络和罗格列酮之间共享的顶级生化途径包括代谢途径、碳代谢和柠檬酸盐循环,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,如铜和锌化合物、雷普酶、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PCOS发病机制中的关键分子。此外,一些重新调整用途的药物已经显示出对不孕不育治疗的有益效果。这些先前的实验报告证实了我们对研究其他再利用药物(体外和体内)的建议。
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