从COVID-19大流行中吸取教训,以推进计算药物重定向策略的发展
Gihanna Galindez1, Julian Matschinske1, Tim Daniel Rose2
1Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
Nature computational science
|January 13, 2024
概括
计算药物重新定位加速了对 COVID-19 等新型病原体的治疗方法的发现. 本综述探讨了用于识别现有药物的计算方法和数据资源,以加快疫情应对.
科学领域:
- 计算生物学和药理学 计算生物学和药理学
- 传染病研究传染病研究.
- 药物的发现和开发.
背景情况:
- 对新型病原体的快速反应对于预防流行病和最大限度地减少社会影响至关重要.
- 计算方法,特别是药物重定向,可以显著加快药物发现时间表.
- 识别新用途的现有药物绕过了漫长的传统批准程序.
研究的目的:
- 审查用于识别可重复使用的抗COVID-19药物的计算方法.
- 检查支持这些计算方法的数据资源.
- 将计算预测的候选药物与临床试验中的药物进行比较,并为未来的疫情提出统一的战略.
主要方法:
- 对COVID-19的计算药物重新定位策略进行系统审查.
- 在计算药物发现中使用的数据资源的分析.
- 预测候选药物和临床试验数据的比较分析.
主要成果:
- 研究了一组用于药物重定位的计算方法.
- 确定和评估了这些方法的基础数据资源.
- 突出了计算预测和临床试验进展之间的差异和协议.
结论:
- 将计算策略与实验验证联系起来,是药物重定向成功的关键.
- 一个统一的药物重定向战略可以提高对未来传染病爆发的准备.
- 计算药物重定向提供了一个至关重要的工具,用于快速应对新出现的健康威胁.
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