复杂自然产品合成的计算规划
Barbara Mikulak-Klucznik1, Patrycja Gołębiowska1, Alison A Bayly2
1Institute of Organic Chemistry, Polish Academy of Sciences, Warsaw, Poland.
Nature
|October 13, 2020
概括
复杂有机合成的自动化规划现在是可行的. 通过将因果推理整合到人工智能中,算法可以制定多步骤路线,实现与人类化学家相提并论的专家级别性能.
科学领域:
- 计算化学
- 合成中的人工智能
- 有机合成计划
背景情况:
- 有机合成的自动化规划已经是一个长期的挑战超过50年.
- 现有的自主规划软件仅限于简单的目标和一次性思维.
- 没有一个算法能够成功设计出需要远见规划的复杂自然产品路线.
研究的目的:
- 证明复杂目标的计算合成规划的可行性.
- 开发一种能够在多个合成步骤中制定战略的算法.
- 通过专家评估和实验室实验来验证计算机设计的合成路径.
主要方法:
- 增强人工智能与多步策略的因果关系.
- 使用与合成专家类似的图灵测试来评估路径质量.
- 对自然产品进行计算机设计合成的实验室验证.
主要成果:
- 开发的算法可以为复杂的天然产品设计合理的合成路径.
- 在专家评估中,算法生成的路线与人类设计的路线无法区分.
- 在实验室中成功验证了三种计算机设计的合成.
结论:
- 专家级的自动化合成规划可以通过当前的人工智能和因果推理实现.
- 这种方法可以实现远见,多步计划,克服以前的方法的局限性.
- 反应知识库的进一步改进和代码优化将提高能力.
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