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检索增强对接使用层次导航可导航的小世界.

Brendan W Hall1,2, Michael J Keiser1,3,4,5

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概括
此摘要是机器生成的。

检索增强对接 (RAD) 有效地导航广的化学空间,通过对接大图书馆的仅一小部分来恢复大多数虚拟药物候选者. 这种蛋白质不可知方法显著降低了药物发现的计算需求.

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科学领域:

  • 计算化学是一种计算化学.
  • 药物发现 药物发现
  • 生物信息学是一种生物信息学.

背景情况:

  • 按需制造的化学图书馆,例如拥有近64亿分子的ZINC-22图书馆,已经扩大了分子对接能力.
  • 这些图书馆的巨大规模带来了重大的计算挑战,使得大多数研究人员无法进行详尽的对接.

研究的目的:

  • 引入和验证一种新的方法,即检索增强对接 (RAD),用于高效地搜索大型化学空间.
  • 为了证明RAD能够恢复高比例的虚拟活性化合物,同时显著减少需要对接的分子数量.

主要方法:

  • 组织和穿越化学空间使用等级可导航的小世界图.
  • 将检索增强对接 (RAD) 方法应用于针对特定蛋白质目标 (D4和AmpC) 和多种蛋白质 (DUDE-Z) 的大规模对接活动.

主要成果:

  • 在对应图书馆 (分别为9950万和13800万个分子) 的仅10%的对接后,RAD成功地恢复了D4和AmpC目标的95%的虚拟活动.
  • 在43个DUDE-Z蛋白中,RAD平均恢复了87%的虚拟活体,而对接只有10%的评估分子 (50.3万个关联).
  • 该方法证明了蛋白质不可知性适用性,并保持了化学多样性,而不会牺牲性能.

结论:

  • 检索增强对接 (RAD) 提供了一个计算效率高的解决方案,用于在药物发现中探索大规模的化学库.
  • RAD显著降低了虚拟选的计算负担,使大规模对接更容易获得.
  • 由于RAD的蛋白质不可知性,可以灵活且具有成本效益的对抗多个目标的对接活动.