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使用生物信息学和基于网络的查方法全面识别潜在的分子标和黑色素瘤癌症的小药物候选者

Dhrubo Ahmed Khan¹, Tonmoy Adhikary², Mst Tania Sultana²

¹Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, Bangladesh.

Journal of biomolecular structure & dynamics

|August 3, 2023

概括

这项研究确定了关键基因和潜在的黑色素瘤候选药物. 生物信息学和网络分析确定了改善黑色素瘤诊断和治疗策略的关键分子标.

科学领域:

在瘤学瘤学.
生物信息学是一种生物信息学.
基因组学就是基因组学.

背景情况:

黑色素瘤的发病率和死亡率正在上升,这是由于它的转移潜力.
确定可靠的分子点对于有效的黑色素瘤诊断,预后和治疗至关重要.

研究的目的:

通过综合生物信息学和网络分析,识别黑色素瘤的关键分子标和潜在的小分子药物.
阐明导致黑色素瘤发展的病原遗传机制.

主要方法:

使用LIMMA方法对两个微阵列数据集 (GSE130244,GSE15605) 的差异基因表达分析.
蛋白质与蛋白质相互作用网络分析以确定关键基因 (KG).
监管网络分析,分子对接,动态建模和连接地图 (CMap) 数据库分析用于药物发现.

主要成果:

确定了246个常见差异表达基因 (cDEGs) 和15个关键基因 (KGs),这些基因对黑色素瘤发育至关重要.
发现了10个转录因子和3个miRNAs作为黑色素瘤基因的重要调节者.
通过分子动力学模拟验证了四种潜在的黑色素瘤药物 (Fisetin,Epicatechin Gallate,1237586-97-8,PF 431396).

结论:

这项研究提供了针对黑色素瘤的分子标和候选药物的全面列表.
这些发现为在黑色素瘤诊断,预后和治疗开发中进行湿实验室验证提供了宝贵的资源.

关键词:

生物标志物生物标志物计算机辅助药物设计基因表达的基因表达方式核心基因的基因中心.综合强大的统计统计.黑色素瘤是一种癌症.

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