Efficient chemical synthesis is critical to satisfying future demands for medicines, materials and agrochemicals. Retrosynthetic simplification 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 high-throughput computer-aided synthesis planning with molecular graph editing to minimize the number of synthetic steps required to produce alkaloids. Our study culminated in enantioselective syntheses of stemona alkaloids by leveraging high-impact key steps, which could be identified and repurposed using graph edit distances.

Computer-aided key step generation in analysis of synthetic pathways

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