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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.

该项目将开发一种端到端的杂环合成“自动售货机”，使杂环以自主和自我优化的方式进行多样性合成。通过结合光活化基本有机转化、流动化学技术和自优化算法的最新进展，将开发用于合成新型杂环化合物的伸缩多步骤过程。具有不同取代模式和链长的各种活化亚甲基化合物和卤代醇/卤代胺将通过相同的顺序经由重氮化合物的形成和反应以及顺序环化来组合。据设想，这些简单的市售构建块将被送入机器，在自我优化的过程中反应，以生产高价值的杂环化合物，在制药领域具有潜在的应用。这种方法将根据需要提供各种取代的杂环，通过直接应用于不同的底物而避免许多重复步骤。化合物将被靶向为适合作为片段或铅样化合物用于针对生物靶标进行筛选。在线光学检测在流动过程中的集成将促进实时连续数据的生成，所述数据将被馈送到自优化算法中，从而使反应参数（光、反应时间/流速、热等）为了绘制出特定反应的最佳反应条件，