形状感知合成搜索 (SASS) 用于基于合成的化学空间的虚拟选
1Discovery Chemistry, Genentech, South San Francisco, California 94080, United States.
Journal of chemical information and modeling
|February 9, 2024
概括
形状感知合成搜索 (SASS) 通过在合成空间中执行形状相似性搜索来加速药物发现,而不是列举的产品. 这种方法可以有效地浏览庞大的化学图书馆,更快地识别候选药物.
科学领域:
- 计算化学是一种计算化学.
- 化学信息学 化学信息学
- 药物发现 药物发现
背景情况:
- 虚拟查对于从大型化学图书馆中识别候选药物至关重要.
- 对数十亿种化合物的详尽选是计算密集的.
- 需要基于synthon的方法来导航更大的化学空间.
研究的目的:
- 介绍Shape-Aware Synthon Search (SASS),这是一个新的虚拟选方法.
- 为了实现超大,基于synthon的虚拟化学空间的高效导航.
- 为了加速大规模的,基于形状的虚拟选用于药物发现.
主要方法:
- 开发了基于synthon的虚拟选技术SASS.
- 在synthon空间内实现了形状相似性搜索.
- 与详尽的选方法比较SASS的性能.
主要成果:
- SASS复制了各种查询分子的详尽的搜索结果,具有高回忆力.
- 与详尽的查相比,该方法显著减少了得分产品的数量.
- 在超大,组合化学空间的导航中,SASS表现出高效率.
结论:
- SASS为大规模的基于形状的虚拟选提供了显著的加速.
- 该方法提供了一种计算效率高的替代方案,用于彻底选.
- 在早期的药物发现中,SASS 增强了对高质量的候选药物的鉴定.
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