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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

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
批准号:
2896336
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
翻译
该项目将开发端到端杂环合成“自动售货机”,以自主和自我优化的方式实现杂环的多样性合成。通过结合光激活基本有机转化、流动化学技术和自优化算法的最新进展,将开发一种可伸缩的多步骤工艺,用于合成新型杂环化合物。各种具有不同取代模式和链长的活化亚甲基化合物和卤醇/-胺将通过重氮化合物的形成和反应以及顺序环化,按照相同的顺序组合。设想这些简单的商业上可用的构建块将被输入机器,在一个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不同的取代杂环,通过直接适用于不同的基材,避免了许多重复的步骤。化合物将被定位为适合作为片段或类似铅的化合物来筛选生物靶点。在流动过程中集成在线光学检测将有助于生成实时连续数据,这些数据将被输入到自优化算法中,使反应参数(光、反应时间/流速、热量等)能够“在飞行中”改变,以便为特定反应绘制最佳反应条件。
英文摘要
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.
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