Predicting and switching the site of heteroaromatic C-H functionalisation

预测和切换杂芳族 C-H 官能化位点

• 批准号: 2278690
• 金额: --
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2278690
• 关键词: Predicting; switching; site; heteroaromatic; functionalisation

Heterocyclic CH functionalisation reactions have gathered much interest over the last decade as viable green alternatives to classic cross-coupling reactions, requiring fewer steps and producing less waste. Despite the increasing advances in this field, the issue of regioselectivity remains mostly unsolved. Though some direct heterocyclic CH functionalisations do occur selectively at one position, this is often at the "natural site" of reactivity and does not demonstrate any real regiocontrol. In a recent publication, Bedford et al. proved that it was possible to control the site selectivity of these heteroaromatic CH functionalisation reactions by switching the mechanism the reaction proceeded by. DFT was used to predict the most acidic and electron rich positions of the heterocycle and then these positions were targeted through base assisted deprotonation (BAD) and electrophilic palladation (EP) mechanisms respectively, allowing full regiocontrol between these two positions. Having proven that this strategy is effective, it is now of interest to apply this to other heterocycles and further evaluate both the predictive capabilities and regiochemical control. This project will undertake preliminary investigations, using DFT to identify the acidic and electron rich sites of other common heterocycles and then subjecting them to the BAD or EP conditions. If this proves successful, the next step will be to target other positions of the heterocycles, exploiting different innate properties to ensure regiocontrol. Once these investigations are complete, the project will then aim to try and consolidate the vast amount of DFT data that will have been collected and apply machine learning to speed up the computational prediction.

杂环 CH 官能化反应在过去十年中作为经典交叉偶联反应的可行绿色替代方案引起了人们的广泛关注，它需要更少的步骤并产生更少的废物。尽管该领域不断取得进展，但区域选择性问题仍未得到解决。尽管一些直接的杂环CH官能化确实选择性地发生在一个位置，但这通常是在反应性的“天然位点”并且没有表现出任何真正的区域控制。在最近的出版物中，贝德福德等人。证明可以通过切换反应进行的机制来控制这些杂芳族CH官能化反应的位点选择性。 DFT 用于预测杂环中酸性最强、电子最丰富的位置，然后分别通过碱辅助去质子化 (BAD) 和亲电钯化 (EP) 机制来定位这些位置，从而实现这两个位置之间的完全区域控制。证明该策略是有效的，现在有兴趣将其应用于其他杂环化合物并进一步评估预测能力和区域化学控制。该项目将进行初步研究，利用DFT识别其他常见杂环的酸性和富电子位点，然后将其置于BAD或EP条件下。如果证明成功，下一步将是瞄准杂环的其他位置，利用不同的固有特性来确保区域控制。一旦这些调查完成，该项目将尝试整合已收集的大量 DFT 数据，并应用机器学习来加速计算预测。