由剂量驱动的生物活性中断:对药物发现的挑战
David Ramírez-Palma1, Karina Martinez-Mayorga1
1Institute of Chemistry, Campus Merida, National Autonomous University of Mexico, Merida-Tetis Highway, Km. 4.5, Ucu, 97357, Yucatan, Mexico.
药物发现必须考虑结构之外的剂量依赖性活性变化. 了解这些度驱动的效应可以改进预测模型,并指导机制知情药物开发.
科学领域:
- 药理学 药理学是指药理学的学科.
- 计算化学的计算化学
- 药物发现 药物发现 药物发现
背景情况:
- 传统的药物发现优先考虑分子结构,往往忽视剂量依赖的生物活性变化.
- 经典的剂量反应模型量化了效应的大小,但错过了复杂的度依赖活性转移.
研究的目的:
- 突出剂量驱动的生物活性中断对药物发现的影响.
- 倡导将非线性剂量反应概况纳入预测模型.
主要方法:
- 审查双相和反转剂量反应概况的证据.
- 提出非线性建模和生物上下文化的数据集的需要.
- 建议对活动预测模型 (APM) 进行以生物宏分子为中心的分类.
主要成果:
- 化合物可以在活性类型中表现出剂量依赖的变化,而不仅仅是大小.
- 集中驱动活动开关可以模仿结构性活动悬崖.
- 当前的预测模型往往无法捕捉到这些复杂的剂量反应现象.
结论:
- 承认逐渐和破坏性的剂量反应行为对于提高预测准确性至关重要.
- 整合度依赖效应将推进机制知情的药物发现管道.
- 重新考虑药物发现,包括剂量反应复杂性,对于开发有效的治疗方法至关重要.
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