Department of Chemistry, Scripps Research, 10550 North Torrey Lines Road, La Jolla, California 92037, United States.
Acc Chem Res. 2021 Mar 2;54(5):1157-1167. doi: 10.1021/acs.accounts.0c00791. Epub 2021 Feb 12.
Retrosynthetic analysis emerged in the 1960s as a teaching tool with profound implications. Its educational value can be appreciated by a glance at total synthesis manuscripts over 50 years later, most of which contain a retrosynthesis on page one. Its vision extended to computer language-a pioneering idea in the 20th century that continues to expand the frontiers today. The same principles that guide a student to evaluate, expand, and refine a series of bond dissections can be programmed, so that computer assistance can perform the same tasks but at faster speeds.The slow step in the synthesis of complex structures, however, is seldom route design. Compression of molecular information into close proximity (/Å) requires exploration and empiricism, a close connection between theory and experiment. Here, retrosynthetic analysis guides the choice of experiment, so that the most simplifying-but often least assured-disconnection is prioritized: a high-risk, high reward strategy. The reimagining of total synthesis in a future era of retrosynthetic software may involve, counterintuitively, target design, as discussed here.Compared to the 1960s, retrosynthetic analysis in the 21st century finds itself among computers of unimaginable power and a biology that is increasingly molecular. Put together, the logic of retrosynthesis, the insight of structural biology, and the predictions of computation have inspired us to imagine an integration of the three. The synthetic target is treated as dynamic-a constellation of related structures-in order to find the nearest congener with the closest affinity but the shortest synthetic route. Such an approach merges synthetic design with structural design toward the goal of improved access for improved function.In this Account, we detail the evolution of our program from its inception in traditional natural product (NP) total synthesis to its current expression through the lens of chemical informatics: a view of NPs as aggregates of molecular parameters that define single points in a chemical space. Early work on synthesis and biological annotation of apparent metal pool binders and nonselective covalent electrophiles (asmarine alkaloids, isocyanoterpenes, dimers) gave way to NPs with well-defined protein targets. The plant metabolite salvinorin A (SalA) potently and selectively agonizes the κ-opioid receptor (KOR), rapidly penetrates the brain, and represents an important lead for next-generation analgesics and antipruritics. To synthesize and diversify this lead, we adopted what we now call a dynamic approach. Deletion of a central methyl group stabilized the SalA scaffold, opened quick synthetic access, and retained high potency and selectivity. The generality of this idea was then tested against another neuroactive class. As an alternative hypothesis to TrkB channels, we proposed that the so-called "neurotrophic" terpenes may bind to γ-aminobutyric acid (GABA)-gated ion channels to cause weak, chronic excitation. Syntheses of (-)-jiadifenolide, 3,6-dideoxy-10-hydroxypseudoanisatin, (-)-11-debenzoyltashironin, (-)-bilobalide, and (-)-picrotoxinin (PXN) allowed this hypothesis to be probed more broadly. Feedback from protein structure and synthetic reconnaissance led to a dynamic retrosynthesis of PXN and the identification of 5MePXN, a moderate GABAR antagonist with greater aqueous stability available in eight steps from dimethylcarvone. We expect this dynamic approach to synthetic target analysis to become more feasible in the coming years and hope the next generation of scientists finds this approach helpful to address problems at the frontier of chemistry and biology.
回溯分析诞生于 20 世纪 60 年代,是一种具有深远意义的教学工具。通过观察 50 多年后的全合成手稿,可以欣赏到它的教育价值,其中大多数在第一页都包含一个回溯合成。它的视野扩展到计算机语言——这是 20 世纪的一个开创性想法,今天仍在不断拓展前沿。指导学生评估、扩展和改进一系列键切割的原则可以被编程,这样计算机辅助就可以更快地完成相同的任务。然而,在合成复杂结构时,缓慢的步骤很少是路线设计。将分子信息压缩到接近 (/Å) 需要探索和经验主义,需要在理论和实验之间建立紧密的联系。在这里,回溯分析指导实验的选择,以便优先选择最简化但通常最不可靠的断开连接:一种高风险、高回报的策略。在未来的回溯合成软件时代,全合成的重新想象可能涉及目标设计,如这里所讨论的。与 20 世纪 60 年代相比,21 世纪的回溯分析发现自己置身于功能强大的计算机和日益分子化的生物学之中。将回溯合成的逻辑、结构生物学的洞察力和计算的预测结合起来,激发了我们想象将这三者结合起来。将合成目标视为动态的——一组相关结构——以便找到最接近的同系物,具有最接近的亲和力,但最短的合成途径。这种方法将合成设计与结构设计结合起来,以提高功能的可及性。在本报告中,我们详细介绍了我们的程序从传统天然产物 (NP) 全合成到当前通过化学信息学视角的演变:将 NPs 视为定义化学空间中单个点的分子参数的集合。早期对明显金属池结合物和非选择性共价电亲核体(asmarine 生物碱、异氰萜烯、二聚体)的合成和生物注释的工作让位于具有明确蛋白质靶标的 NPs。植物代谢产物萨林诺林 A (SalA) 强烈且选择性地激动 κ-阿片受体 (KOR),迅速穿透大脑,是下一代镇痛药和抗瘙痒药的重要先导化合物。为了合成和多样化这个先导化合物,我们采用了我们现在所说的动态方法。中央甲基的删除稳定了 SalA 支架,开辟了快速合成途径,并保持了高活性和选择性。然后,我们用这个想法来测试另一个神经活性类别的普遍性。作为对 TrkB 通道的替代假设,我们提出所谓的“神经营养”萜类可能与 γ-氨基丁酸 (GABA) 门控离子通道结合,导致微弱、慢性兴奋。(-)-jiadifenolide、3,6-二脱氧-10-羟伪阿曲汀、(-)-11-去苯甲酰基塔希罗宁、(-)-bilobalide 和(-)-picrotoxinin (PXN) 的合成为这一假设提供了更广泛的研究。来自蛋白质结构和合成侦察的反馈导致了 PXN 的动态回溯合成以及 5MePXN 的鉴定,这是一种温和的 GABAR 拮抗剂,在从二甲基香芹酮开始的八个步骤中具有更大的水稳定性。我们预计这种动态的合成目标分析方法在未来几年将变得更加可行,并希望下一代科学家发现这种方法有助于解决化学和生物学前沿的问题。