Li Chunyu, Shenvi Ryan A
Department of Chemistry, Scripps Research, La Jolla, CA, USA.
Graduate School of Chemical and Biological Sciences, Scripps Research, La Jolla, CA, USA.
Nature. 2025 Feb;638(8052):980-986. doi: 10.1038/s41586-024-08538-y. Epub 2024 Dec 23.
The synthesis of a complex molecule begins from an initial design stage in which possible routes are triaged by strategy and feasibility, on the basis of analogy to similar reactions. However, as molecular complexity increases, predictability decreases; inevitably, even experienced chemists resort to trial and error to identify viable intermediates en route to the target molecule. We encountered such a problem in the synthesis of picrotoxane sesquiterpenes in which pattern-recognition methods anticipated success, but small variations in structure led to failure. Here, to solve this problem but avoid tedious guess-and-check experimentation, we built a virtual library of elusive late-stage intermediate analogues that were triaged by reactivity and altered the synthesis pathway. The efficiency of this method led to concise routes to 25 naturally occurring picrotoxanes. Costly density-functional-theory transition-state calculations were replaced with faster reactant parameterizations to increase scalability and, in this case, inform the mechanism. This approach can serve as an add-on search to human or computer-assisted synthesis planning applicable to high-complexity targets and/or steps with little representation in the literature or reaction databases.
复杂分子的合成始于初始设计阶段,在此阶段,根据与类似反应的类比,通过策略和可行性对可能的路线进行筛选。然而,随着分子复杂性的增加,可预测性降低;不可避免地,即使是经验丰富的化学家也会通过反复试验来确定通往目标分子途中可行的中间体。我们在合成印防己毒素倍半萜烯时遇到了这样一个问题,其中模式识别方法预期会成功,但结构上的微小变化却导致了失败。在这里,为了解决这个问题但避免繁琐的猜测和检验实验,我们构建了一个难以捉摸的后期中间体类似物的虚拟库,通过反应性对其进行筛选,并改变了合成途径。这种方法的效率带来了合成25种天然印防己毒素的简洁路线。用更快的反应物参数化取代了昂贵的密度泛函理论过渡态计算,以提高可扩展性,并在这种情况下阐明反应机理。这种方法可以作为对人工或计算机辅助合成规划的附加搜索,适用于高复杂性目标和/或在文献或反应数据库中几乎没有实例的步骤。