Tian Junhua, Liu Xiaochun
Department of Gynecology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China.
Iran J Pharm Res. 2024 Apr 6;23(1):e144266. doi: 10.5812/ijpr-144266. eCollection 2024 Jan-Dec.
Endometriosis is a chronic gynecological disorder characterized by the ectopic growth of endometrial tissue outside the uterus, leading to debilitating pain and infertility in affected women. Despite its prevalence and clinical significance, the molecular mechanisms underlying the progression of endometriosis remain poorly understood. This study employs bioinformatics tools and molecular docking simulations to unravel the intricate genetic and molecular networks associated with endometriosis progression.
The primary objectives of this research are to identify differentially expressed genes (DEGs) linked to endometriosis, elucidate associated biological pathways using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), construct a Protein-Protein Interaction (PPI) network to identify hub genes, and perform molecular docking simulations to explore potential ligand-protein interactions associated with endometriosis.
Microarray data from Homo sapiens, specifically Accession: GDS3092 Series = GSE5108 (Platform: GPL2895), were retrieved from the NCBI Gene Expression Omnibus (GEO). The data underwent rigorous preprocessing and DEG analysis using NCBI GEO2. Database for Annotation, Visualization, and Integrated Discovery analysis was employed for functional annotation, and a PPI network was constructed using the STITCH database and Cytoscape 3.8.2. Molecular docking simulations against target proteins associated with endometriosis were conducted using MVD 7.0.
A total of 1 911 unique elements were identified as DEGs associated with endometriosis from the microarray data. Database for Annotation, Visualization, and Integrated Discovery analysis revealed pathways and biological characteristics positively and negatively correlated with endometriosis. Hub genes, including BCL2, CCNA2, CDK7, EGF, GAS6, MAP3K7, and TAB2, were identified through PPI network analysis. Molecular docking simulations highlighted potential ligands, such as Quercetin-3-o-galactopyranoside and Kushenol E, exhibiting favorable interactions with target proteins associated with endometriosis.
This study provides insights into the molecular signatures, pathways, and hub genes associated with endometriosis. Utilizing DAVID in this study clarifies biological pathways associated with endometriosis, revealing insights into intricate genetic networks. Molecular docking simulations identified ligands for further exploration in therapeutic interventions. The consistent efficacy of these ligands across diverse targets suggests broad-spectrum effectiveness, encouraging further exploration for potential therapeutic interventions. The study contributes to a deeper understanding of endometriosis pathogenesis, paving the way for targeted therapies and precision medicine approaches to improve patient outcomes. These findings advance our understanding of the molecular mechanisms in endometriosis (EMS), offering promising avenues for future research and therapeutic development in addressing this complex condition.
子宫内膜异位症是一种慢性妇科疾病，其特征是子宫内膜组织在子宫外异位生长，导致受影响女性出现使人衰弱的疼痛和不孕。尽管其发病率和临床意义重大，但子宫内膜异位症进展的分子机制仍知之甚少。本研究采用生物信息学工具和分子对接模拟来揭示与子宫内膜异位症进展相关的复杂遗传和分子网络。
本研究的主要目的是识别与子宫内膜异位症相关的差异表达基因（DEG），使用注释、可视化和综合发现数据库（DAVID）阐明相关的生物学途径，构建蛋白质-蛋白质相互作用（PPI）网络以识别枢纽基因，并进行分子对接模拟以探索与子宫内膜异位症相关的潜在配体-蛋白质相互作用。
从NCBI基因表达综合数据库（GEO）中检索来自智人的微阵列数据，具体登录号为：GDS3092系列=GSE5108（平台：GPL2895）。使用NCBI GEO2对数据进行严格的预处理和DEG分析。采用注释、可视化和综合发现数据库分析进行功能注释，并使用STITCH数据库和Cytoscape 3.8.2构建PPI网络。使用MVD 7.0对与子宫内膜异位症相关的靶蛋白进行分子对接模拟。
从微阵列数据中总共鉴定出1911个独特元件作为与子宫内膜异位症相关的DEG。注释、可视化和综合发现数据库分析揭示了与子宫内膜异位症呈正相关和负相关的途径及生物学特征。通过PPI网络分析鉴定出枢纽基因，包括BCL2、CCNA2、CDK7、EGF、GAS6、MAP3K7和TAB2。分子对接模拟突出了潜在配体，如槲皮素-3-O-吡喃半乳糖苷和苦参醇E，它们与子宫内膜异位症相关靶蛋白表现出良好的相互作用。
本研究深入了解了与子宫内膜异位症相关的分子特征、途径和枢纽基因。在本研究中使用DAVID阐明了与子宫内膜异位症相关的生物学途径，揭示了对复杂遗传网络的见解。分子对接模拟鉴定出了可在治疗干预中进一步探索的配体。这些配体在不同靶点上的一致疗效表明其具有广谱有效性，鼓励进一步探索潜在的治疗干预措施。该研究有助于更深入地理解子宫内膜异位症的发病机制，为改善患者预后的靶向治疗和精准医学方法铺平了道路。这些发现推进了我们对子宫内膜异位症（EMS）分子机制的理解，为解决这一复杂病症的未来研究和治疗开发提供了有希望的途径。
