SynthEx用LLM规划天然产物合成路线，盲评中专家觉得它设计的关键步骤不输人类，还开源了上千条路线数据库。
SynthEx是一个基于大语言模型的智能体框架，用于规划复杂天然产物的全合成路线。它能够提出多种竞争策略，并自行评判和改进路线设计，其路线比传统目录式工具更具收敛性。在盲评中，专家化学家认为SynthEx的关键步骤与已发表的人工合成相当，这是算法路线预测首次获得这样的回应。该团队发布了SynthAtlas，一个开放交互数据库，包含超过一千条天然产物的合成路线，其中许多缺乏现有文献路线。
Strategy-first synthesis planning for complex natural products
The total synthesis of a complex molecule is among the most demanding intellectual and experimental feats in chemistry: a chemist must plan many steps ahead for how to assemble simple building blocks into an intricate target, devise backup strategies, and anticipate procedural challenges. It is also a profoundly creative activity. For half a century, efforts to automate the retrosynthetic design of natural products and other complex molecules have drawn on catalogued reactions, and the resulting tools now report near-complete success on benchmarks built from that same source. But these tools were shaped to fit benchmarked chemistry, and they falter on many natural products, the frontier of the field, whose densely functionalized, polycyclic architectures demand precisely the inventive chemistry the record contains least. Whether a machine could reasonably design such syntheses like an expert chemist does has remained unclear. Here, we show that SynthEx, an agentic framework built on large language models, plans routes to complex natural products that lie beyond the reach of conventional design algorithms. SynthEx proposes competing strategies, assembles a sequence of routine and key steps into a cohesive route, and critiques and improves its own design; the chemistry it favours is more convergent than existing tools produce, and spans a region of reaction space that catalogue-based tools cannot match. Most notably, in blinded assessments, expert chemists judged its key steps comparable to those of published human syntheses and engaged with them as genuine synthesis plans, a response algorithmic route prediction has not previously accomplished. We release routes to more than a thousand natural products as SynthAtlas, an open, interactive database, and anticipate it will become a shared resource for a collection of complex target molecules that lack existing literature routes.