基于网络的药物重定向用于精神分裂症
Trang T T Truong1, Zoe S J Liu1, Bruna Panizzutti1
1Deakin University, IMPACT, The Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Geelong, Australia.
概括
通过分析基因调节网络,计算药物重定向通过分析基因调节网络,确定了18种潜在的精神分裂症治疗方法. 针对的关键途径包括能量代谢和免疫反应,像里莫纳班特这样的候选药物显示出承诺.
科学领域:
- 计算神经科学是一种计算神经科学.
- 基因组学就是基因组学.
- 药理学 药理学是指药理学的学科.
背景情况:
- 精神分裂症药物发现面临着持续的挑战.
- 计算药物重新定位通过利用广泛的生物医学数据库提供了一个有希望的途径.
- 基因调节网络 (GRNs) 对于理解转录因子 (TF) 调节效应至关重要.
研究的目的:
- 确定精神分裂症患者和健康对照者之间的TF基因调节网络的拓差异.
- 为了利用这些差异进行计算药物重新定位,找到新的精神分裂症治疗方法.
主要方法:
- 利用PANDA算法从RNA-seq数据 (CommonMind项目,532个样本) 中构建和分析TF基因调节网络.
- 集成的结合基因,蛋白相互作用和基因共同表达数据.
- 采用差异网络分析 (CLUEreg工具) 来识别针对疾病相关基因特征的候选药物.
主要成果:
- 在精神分裂症病例和对照中为15831个基因和413个TF构建了GRNs.
- 确定了18个有前途的药物重用候选人用于精神分裂症.
- 与精神分裂症相关的TF主要调节能量代谢,免疫反应,细胞粘附和甲状腺激素信号传递的途径.
结论:
- 药物重用候选人可能会准已识别的TF调节路径.
- 里莫纳班特和凯姆菲罗尔被强调为候选药物,需要进一步研究.
- 这种基于网络的方法为识别精神分裂症的新疗法目标提供了一个强大的策略.
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