基于相似性的功能化,用于列举围绕目标的合成可信化学库
Karthik Sankaranarayanan1,2, Klavs F Jensen2
1Department of Agriculture and Biological Engineering, Purdue University West Lafayette Indiana 47907 USA ksankara@purdue.edu.
Chemical science
|July 5, 2024
概括
这项研究引入了一种新的分子相似性方法,用于预测化学合成中的单步功能化反应. 这种方法通过分析先前的反应,帮助发现新的分子,节省药物和农业化学品开发的时间和资源.
科学领域:
- 药用化学 医学化学
- 有机合成 有机合成
- 计算化学的计算化学
背景情况:
- 化合物的功能化对于在制药和农业化学品中发现具有理想性质的新分子至关重要.
- 这个过程往往是耗时的,昂贵的,并且严重依赖于专家的直觉和经验.
研究的目的:
- 为了应对后期阶段功能化中的合成规划挑战.
- 开发一种计算方法,以基于分子相似性和先例反应提出单步功能化反应.
主要方法:
- 开发了一种分子相似性方法来预测功能化反应.
- 利用来自专利文献的约348,000个反应的知识库.
- 模仿反应策略和暗示由已知的反应隐含定义的协同反应物.
主要成果:
- 开发的方法成功地提出了记录的产品或接近的类似物在约44,000个测试反应中的74%的前20个预测中.
- 证明了在目标化合物周围编列化学库的组合增长能力.
- 确保每个合成步骤都利用了化学家可以接触到的常见化学转换.
结论:
- 分子相似性方法有效地帮助合成计划后期阶段的功能化.
- 该工具通过利用大量的化学反应来促进新分子的发现.
- 这种方法提高了化学模拟开发的效率和可访问性.
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