复杂天然产物的优先策略合成规划
Strategy-first synthesis planning for complex natural products
- École Polytechnique Fédérale de Lausanne (EPFL)（洛桑联邦理工学院）
- National Centre of Competence in Research (NCCR) Catalysis（国家催化研究能力中心）
- Ghent University（根特大学）
- University of Arizona（亚利桑那大学）
- University of Pittsburgh（匹兹堡大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
基于大语言模型的智能体框架SynthEx，可规划出传统算法无法实现的复杂天然产物合成路线，其关键步骤获化学家认可，相关路线数据库SynthAtlas已开放。
AI中文摘要：
复杂分子的全合成是化学领域中最具挑战性的智力与实验成就之一：化学家必须提前规划多步反应，将简单构建模块组装成复杂的目标分子，设计备用策略并预判操作挑战，这也是一项极具创造性的活动。半个世纪以来，实现天然产物及其他复杂分子逆合成自动化设计的研究，均基于已收录的反应数据库，由此开发的工具在基于相同数据源构建的基准测试中已能实现近乎完全的成功率。但这些工具是为适配基准化学而设计的，在该领域的前沿——众多天然产物上表现不佳，这些天然产物具有密集官能化、多环的结构，恰好需要现有收录反应中最少的创造性化学方案。机器能否像专业化学家那样合理设计此类合成路线，此前仍不明确。在此，我们展示了基于大语言模型构建的智能体框架SynthEx，其规划出的复杂天然产物合成路线超出了传统设计算法的能力范围。SynthEx会提出多种竞争策略，将常规步骤与关键步骤组合成连贯路线，并对自身设计进行批评与改进；其偏好的化学方案比现有工具生成的更具汇聚性，且覆盖了基于数据库的工具无法企及的反应空间区域。最值得注意的是，在盲评中，专业化学家判定其关键步骤与已发表的人工合成路线相当，并将其作为真正的合成方案进行评估，这是此前算法路线预测从未实现的反应。我们发布了超过1000种天然产物的合成路线，作为开放的交互式数据库SynthAtlas，预计它将成为缺乏现有文献路线的复杂目标分子集合的共享资源。
英文摘要：
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.
