FragmentRetro:一个基于碎片化算法的二次复合方法
Yu Shee1, Anthony M Smaldone1, Anton Morgunov1
1Department of Chemistry, Yale University, P.O. Box 208107, New Haven, Connecticut 06520-8107, United States.
Journal of chemical theory and computation
|January 6, 2026
概括
FragmentRetro通过使用碎片化算法来实现二次复杂度,显著改善了计算机辅助合成规划,优于传统的树搜索方法. 这种新的方法提高了复杂分子发现的逆合成效率.
科学领域:
- 计算化学计算化学
- 有机合成 有机合成
- 化学信息学 化学信息学
背景情况:
- 复合成对于计算机辅助合成计划 (CASP) 是必不可少的.
- 在CASP中现有的树搜索方法面临着指数级计算复杂性的挑战.
- 有效的复合分析对于加速药物发现和化学合成至关重要.
研究的目的:
- 为了介绍FragmentRetro,一种用于逆合成的新方法.
- 为了解决当前CASP方法的计算复杂性限制.
- 开发一种可扩展和高效的方法来识别回合成解决方案.
主要方法:
- FragmentRetro使用碎片化算法 (BRICS,r-BRICS) 与库存意识的勘探相结合.
- 采用模式指纹选,以减少亚结构匹配的复杂性.
- 与树搜索的指数复杂度相比,实现二次时间复杂度,O(h^2).
主要成果:
- FragmentRetro在基准数据集 (PaRoutes,USPTO-190,自然产品) 上显示了高的解决率和竞争性的运行时间.
- 该方法成功地解决了树搜索方法失败的情况.
- 指纹查显著提高了基结构匹配的效率.
结论:
- FragmentRetro提供了一种具有计算优势的回复合成方法,实现二次复杂度.
- 该方法为合成规划提供了战略性起始候选人.
- FragmentRetro 作为可扩展和自动化合成规划系统的基础组件.
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