Suppr超能文献

用于基于片段药物发现的多种杂环螺环合成的环加成策略

Cycloaddition Strategies for the Synthesis of Diverse Heterocyclic Spirocycles for Fragment-Based Drug Discovery.

作者信息

King Thomas A, Stewart Hannah L, Mortensen Kim T, North Andrew J P, Sore Hannah F, Spring David R

机构信息

Department of Chemistry University of Cambridge Lensfield Road 1EW Cambridge CB21EW.

出版信息

European J Org Chem. 2019 Sep 1;2019(31-32):5219-5229. doi: 10.1002/ejoc.201900847. Epub 2019 Jul 29.

Abstract

In recent years the pharmaceutical industry has benefited from the advances made in fragment-based drug discovery (FBDD) with more than 30 fragment-derived drugs currently marketed or progressing through clinical trials. The success of fragment-based drug discovery is entirely dependent upon the composition of the fragment screening libraries used. Heterocycles are prevalent within marketed drugs due to the role they play in providing binding interactions; consequently, heterocyclic fragments are important components of FBDD libraries. Current screening libraries are dominated by flat, sp-rich compounds, primarily owing to their synthetic tractability, despite the superior physicochemical properties displayed by more three-dimensional scaffolds. Herein, we report step-efficient routes to a number of biologically relevant, fragment-like heterocyclic spirocycles. The use of both electron-deficient and electron-rich 2-atom donors was explored in complexity-generating [3+2]-cycloadditions to furnish products in 3 steps from commercially available starting materials. The resulting compounds were primed for further fragment elaboration through the inclusion of synthetic handles from the outset of the syntheses.

摘要

近年来,制药行业受益于基于片段的药物发现(FBDD)的进展,目前有30多种基于片段的药物已上市或正处于临床试验阶段。基于片段的药物发现的成功完全取决于所使用的片段筛选库的组成。杂环在市售药物中很常见,因为它们在提供结合相互作用方面发挥着作用;因此,杂环片段是FBDD库的重要组成部分。目前的筛选库主要由平面的、富含sp的化合物主导,这主要是由于它们的合成易处理性,尽管更多的三维支架显示出更优越的物理化学性质。在此,我们报告了一些与生物学相关的、类似片段的杂环螺环化合物的高效合成路线。在生成复杂性的[3+2]环加成反应中,探索了使用缺电子和富电子的双原子供体,以便从市售起始原料分三步制备产物。从合成一开始就通过引入合成手柄,使所得化合物为进一步的片段修饰做好准备。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b4c/6774287/439c90c5ee6a/EJOC-2019-5219-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验