Lin Yingfu, Zhang Rui, Wang Di, Cernak Tim
Department of Medicinal Chemistry, University of Michigan, Ann Arbor, MI 48109, USA.
Department of Chemistry, University of Michigan, Ann Arbor, MI 48109, USA.
Science. 2023 Feb 3;379(6631):453-457. doi: 10.1126/science.ade8459. Epub 2023 Feb 2.
Efficient chemical synthesis is critical to satisfying future demands for medicines, materials, and agrochemicals. Retrosynthetic analysis of modestly complex molecules has been automated over the course of decades, but the combinatorial explosion of route possibilities has challenged computer hardware and software until only recently. Here, we explore a computational strategy that merges computer-aided synthesis planning with molecular graph editing to minimize the number of synthetic steps required to produce alkaloids. Our study culminated in an enantioselective three-step synthesis of (-)-stemoamide by leveraging high-impact key steps, which could be identified in computer-generated retrosynthesis plans using graph edit distances.
高效的化学合成对于满足未来对药品、材料和农用化学品的需求至关重要。在过去几十年里,对适度复杂分子的逆合成分析已实现自动化,但路线可能性的组合爆炸一直挑战着计算机硬件和软件,直到最近情况才有所改观。在此,我们探索了一种计算策略,该策略将计算机辅助合成规划与分子图编辑相结合,以尽量减少合成生物碱所需的合成步骤数。我们的研究最终通过利用具有高影响力的关键步骤,实现了对映选择性三步合成(-)-斯替莫酰胺,这些关键步骤可在使用图编辑距离的计算机生成的逆合成计划中识别出来。