整合人口层面和基于细胞的签名,用于药物重新定位
bioRxiv : the preprint server for biology
|November 14, 2023
概括
我们开发了TReD,这是一种用于药物重新定位的新框架,它集成了遗传疾病特征和药物诱导的基因表达特征. 这种方法可以识别潜在的COVID-19治疗方法,包括巴里西提尼布和新型候选药物,如酶氨酸,加速药物发现.
科学领域:
- 计算生物学和生物信息学
- 基因组学和转录基因组学
- 药理学和药物发现
背景情况:
- 药物重新定位为扩大治疗选择提供了一个具有成本效益的策略.
- 基因支持药物显示出更高的临床试验成功率.
- 现有的多基因药物重新定位方法通常依赖于差异基因表达 (DGE),这与因果推理和识别疾病后果而不是原因而斗争.
研究的目的:
- 引入TReD (转录基因知情逆转距离),这是一个用于基于多基因的药物重新定位的新框架.
- 整合基于细胞的药物诱导的转录组概况,以强大地逆转因果关系的种群级遗传疾病签名.
- 使用TReD框架识别使用COVID-19治疗的潜在药物候选者.
主要方法:
- 开发了TReD框架,将疾病特征和药物概况嵌入高维规范空间.
- 使用基于细胞的试验量化药物逆转潜力,通过额外的查评估来确保稳定性.
- 应用的TReD使用转录组广泛关联研究 (TWAS) 和DGE从COVID-19相关组织的结果.
主要成果:
- 确定了37种药物,它们可能对抗COVID-19的签名发挥逆转作用.
- 超过70%的已识别的药物 (27/37) 之前与COVID-19有联系,其中八种药物得到了临床试验的支持.
- TReD成功地确定了巴里西提尼布和新型候选药物,如酶氨酸,证明了其在药物发现中的有效性.
结论:
- 该TReD框架为药物重新定位提供了一个全面的,基因固的方法.
- 整合人口级别的签名和基于细胞的屏幕加速了新型治疗策略的识别.
- 通过利用分子签名和遗传证据,TReD提高了药物发现效率.
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