在新药药理学协同作用的体内识别:Trabectedin案例
Laura Mannarino1,2, Nicholas Ravasio3, Maurizio D'Incalci1,2
1Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20072 Milan, Italy.
International journal of molecular sciences
|February 24, 2024
概括
这项研究引入了用于药物重新定位的in-silico方法,识别了潜在的药物组合. 该方法揭示了trabectedin与其他药物共享途径调节,这表明癌症治疗的新治疗协同作用.
科学领域:
- 在瘤学瘤学.
- 药理学 药理学是指药理学的学科.
- 生物信息学是一种生物信息学.
背景情况:
- 药物重新定位通过确定现有药物的新用途来加速药物发现.
- 特拉贝克德丁和伊利诺特干 (一种拓酶I抑制剂) 呈现相关的表达变化,表明潜在的治疗联系.
- 转录数据分析为探索药物相互作用和协同作用提供了一个强大的工具.
研究的目的:
- 开发和验证一种一般的in-silico药物重新定位方法,用于识别新药协同作用.
- 为了研究涉及抗癌剂trabectedin的潜在协同相互作用.
- 建立一种工作流程,用于识别药物选择性调节的基因,并预测新型药物相互作用.
主要方法:
- 使用一种利用转录性癌症数据集 (trabectedin,lurbinectedin,对照) 的in-silico策略.
- 从数据集中的基因表达签名与连接地图数据库 (476,251个签名) 的基因表达签名进行比较.
- 分析了连贯调节的基因,以确定共享的途径和潜在的药物协同作用.
主要成果:
- 鉴定出了特拉贝克丁和米托米辛-c,拓酶II抑制剂,PKC抑制剂,Chk1抑制剂,抗真菌剂和谷氨酸受体对抗剂之间的显著联系.
- 发现特拉贝克丁因调节的基因参与细胞周期,PPARalpha和Rho GTPases途径.
- 证明trabectedin与其他药物共享途径调节,表明潜在的协同效应.
结论:
- 开发的in-silico方法有效地识别了潜在的药物协同作用.
- 特拉贝克丁对特定途径的调节表明,它与其他药物有着有前途的协同作用.
- 这一策略有助于在瘤学中发现新的治疗策略.
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