A Heterocycle Vending Machine: Towards the autonomous and self-optimising synthesis of a heterocyclic screening collection of fragments and lead-like

杂环自动售货机：实现碎片和类先导杂环筛选集合的自主和自我优化合成

基本信息

批准号：
2896336
负责人：
金额：
--
依托单位：
Imperial College London
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2023
资助国家：
英国
起止时间：
2023 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2896336
关键词：
Heterocycle Vending Machine Towards autonomous

项目摘要

This project will develop an end-to-end heterocycle synthesis 'vending machine' that will enable the diversity-oriented synthesis of heterocycles in an autonomous and self-optimised fashion. By combining recent advances in light-activatedfundamental organic transformations, flow chemistry technology and self-optimisation algorithms, a telescoped multi-step process will be developed for the synthesis of novel heterocylic compounds. A variety of activated-methylene compounds and halo-alcohols/-amines with varied substitution patterns and chain length will be combined through the same sequence via formation and reaction of diazo compounds, and sequential cyclisation. It is envisioned that these simple commercially available building blocks will be fed into the machine, reacted in a self-optimised process to produce high value heterocyclic compounds with potential applications in the pharmaceutical sector. This approach, will deliver varied substituted heterocycles on demand, avoiding many repetitive steps by being directly applicable across different substrates. Compounds will be targeted to be appropriate as fragments or lead-like compounds for screening against biological targets. The integration of in-line optical detection in the flow process will facilitate the generation of real-time continuous data that will be fed into a self-optimising algroithim enabling reaction parameters (light, reaction time/flow rate, heat etc.) to be changed 'on the fly' in order to map out the optimum reaction conditions for a specific reaction.

该项目将开发出端到端的杂环合成“自动售货机”，该合成将以自主和自我优化的方式以多样性为导向的杂环合成。通过结合光活化的有机转化，流化学技术和自我优化算法的最新进展，将开发出望远镜的多步骤过程，以合成新型的异源化合物。各种具有多种取代模式和链长的活化的亚甲基化合物和卤代醇/胺通过相同的序列结合通过形成和反应，并进行连续循环。可以预见的是，这些简单的市售构建块将被馈入机器，以自比的过程反应，以产生高价值的杂环化合物，并在药物领域中使用潜在的应用。这种方法将按需提供各种替代的杂环，从而通过直接适用于不同的基板来避免许多重复步骤。化合物的目标是作为片段或铅状化合物，用于筛选生物学靶标。流动过程中的在线光学检测的整合将促进实时连续数据的产生，这些数据将被送入自我优化的算法促进反应参数（光，反应时间/流量，热量，热量等），以绘制特定反应的最佳反应条件。