网络社区作为癌症治疗的药物重新定位方法
1The Graduate School of Natural and Applied Sciences, Dokuz Eylül University, Izmir, Turkiye.
PeerJ
|July 17, 2023
概括
这项研究引入了一种新的基于网络的药物重新定位方法,通过分析基因和药物相互作用来确定现有药物的潜在新用途. 该方法成功预测了癌症候选药物,其中一些药物通过临床试验得到了验证.
科学领域:
- 计算生物学是一种计算生物学.
- 系统生物学 系统生物学
- 药理学 药理学是指药理学的学科.
背景情况:
- 传统药物开发是昂贵和耗时的.
- 计算药物重新定位提供了一个具有成本效益的替代方案.
- 整合系统生物学方法可以增强药物发现.
研究的目的:
- 提出一种新的基于网络的药物重新定位方法.
- 通过计算致病基因和受药物影响的基因之间的相似性来识别候选药物.
- 通过整合功能基因信息和药物转录组效应来改善治疗选择.
主要方法:
- 利用蛋白质-蛋白质相互作用网络绘制致病基因图.
- 来自LINCS项目的候选药物的综合转录组资料.
- 使用Adamic-Adar,PageRank和社区评分指标计算了网络相似性.
- 在黑色素瘤,结肠直肠癌和前列腺癌数据集上进行实验.
主要成果:
- 确定了具有显著相似度评分 (AUC > 0.6) 的候选药物.
- 成功预测了对已测试的癌症的潜在候选药物.
- 通过临床试验和体内研究的文献审查验证了一些预测.
结论:
- 拟议的基于网络的方法有效地识别了有希望的药物候选人,以便重新定位.
- 这种方法整合了系统生物学和基因药物相互作用数据,以加强药物发现.
- 这种方法为发现各种疾病更好的治疗选择提供了有价值的工具.
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