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预测已知药物的新分子标
Michael J Keiser1, Vincent Setola, John J Irwin
1Department of Pharmaceutical Chemistry, University of California San Francisco, 1700 4th Street, San Francisco, California 94143-2550, USA.
Nature
|November 3, 2009
概括
计算药物向相互作用预测发现了成千上万的新关联. 实验验证证了23种新的药物标链接,揭示了现有药物的潜在新用途和副作用.
科学领域:
- 药理学 药理学是指药理学的学科.
- 计算化学计算化学
- 药物发现 药物发现 药物发现
背景情况:
- 药物往往与多个生理目标相互作用,导致既有预期的效果和副作用.
- 探索这些药物向相互作用对于理解药物的有效性和安全性至关重要.
研究的目的:
- 通过计算预测大量已批准和正在研究的药物的新药向关联.
- 通过实验验证预测的药物向相互作用,并评估它们的生理相关性.
主要方法:
- 使用化学相似性方法,将3665种美国食品和药物管理局 (FDA) 批准的和正在研究的药物与数百种由它们的连接体定义的标进行比较.
- 30个预测的药物标协会被选择用于实验测试.
主要成果:
- 基于化学相似性,预测了成千上万的意想不到的药物标关联.
- 实验证实了23种新的药物标关联,其中5种显示出高强度 (<100nM).
- 在淘汰赛小鼠模型中证实了N,N-二甲基三胺 (DMT) 对血清受体的生理相关性.
结论:
- 化学相似性方法是一种系统和全面的方法,用于预测药物向相互作用.
- 这种方法可以识别潜在的药物副作用,并为现有药物提出新的治疗指示.
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