使用下一代知识发现方法,探索抗癌药物的潜在分子机制和基因毒性
Peter Natesan Pushparaj1, Mahmood Rasool2, Muhammad Imran Naseer3
1Peter Natesan Pushparaj, PhD Associate Professor Center of Excellence in Genomic Medicine Research, Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences King Abdulaziz University, Jeddah, Saudi Arabia.
这项研究使用了学方法来评估抗癌药物毒性和分子机制,识别了像TP53信号传递等参与细胞死亡和基因毒性相关的途径,以获得更安全的药物开发.
科学领域:
- 计算毒理学计算毒理学
- 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:
- 精确识别分子和毒理学功能对于药物发现和开发至关重要.
- 药物的in silico表征有助于评估基因毒性和致癌风险.
- 了解药物机制可以为抗癌治疗的发展提供信息.
研究的目的:
- 通过下一代知识发现 (NGKD) 建立抗癌药物的分子机制和基因毒性风险评估.
- 识别抗癌药物调节的独特的毒理学特征和信号通路.
- 探索潜在的生物标志物来评估治疗的安全性和有效性.
主要方法:
- 用于在模型系统中评估20种抗癌药物的分子机制和毒性.
- 运用创造力路径分析 (IPA) 来确定药物点和分析生物/毒理活动.
- 使用SwissTargetPrediction和WebGestalt进行目标识别,途径分析和基因本体学映射.
主要成果:
- 鉴定出明显的毒理学特征和规范信号通路,包括细胞死亡,细胞亡,p53信号和基碳化合物受体信号.
- 证实TP53信号通路被抗癌药物利用来诱导细胞死亡和细胞亡.
- 确定p53是细胞应激反应的主调节者,包括遗传毒性应激.
结论:
- 该研究为发现生物标志物以评估治疗安全性和有效性提供了基础.
- 对于识别更安全的疗法和合理选候选药物而言,NGKD工具很重要.
- 结合分子形状可能是开发可翻译的药物安全性和有效性生物标志物的必要条件.
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