Complexity-Building Approaches in Photoassisted Synthesis of Heterocycles

在化学系化学合成计划的支持下，丹佛大学的Andrei Kutateladze教授正在研究开发新的分子复杂性构建方法，用于合成具有潜在有用特性的有机化合物。这项研究的主要重点是基于光辅助方法，即利用光作为一种现成的能源，允许快速获得复杂的分子结构。除了在合成化学的背景下了解光和物质的相互作用的基本重要性之外，目标复杂杂环，即含有氮，硫或氧原子作为环的一部分的分子，被故意设计成类似生物碱，这是一类重要的天然产物，可能具有有用的治疗特性。重要的是，该奖项还将支持本科生和研究生的研究经验，包括那些历史上代表性不足的科学群体，从而努力在有机化学领域实现包容性卓越。本研究旨在进一步扩展合成光化学工具箱，特别是进一步开发基于激发态分子内质子转移（ESIPT）的光辅助合成反应级联。例如，Kutateladze小组的目标是三重态的氢原子转移（HAT），旨在实现复杂杂环分子结构合成中的大步长归一化复杂性增加。这项工作还将包括通过后光化学转化实现复杂性的垂直增长。将研究这些ESIPT触发级联的反应机制和立体化学，以更好地了解这些转化如何实现其立体和区域化学结果。实验工作将增加计算，旨在促进解决方案的复杂的杂环产物的结构阐明核磁共振（NMR）光谱。用于快速准确计算NMR参数的新集成机器学习增强密度泛函理论（DFT）方法将被扩展，以明确解释溶剂对预测光谱的影响。由于目标分子的结构复杂性，拟议研究的这一子主题对于该项目的成功至关重要。此外，该方法的进一步发展可能会对复杂有机分子的结构解析产生更广泛的影响。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

With the support of the Chemical Synthesis Program in the Division of Chemistry, Professor Andrei Kutateladze of University of Denver is studying the development of new molecular complexity-building methods for the synthesis of organic compounds that possess potentially useful properties. The major thrust of this research is based on photoassisted approaches, i.e. using light as a readily available energy source, allowing for rapid access to complex molecular architectures. Besides the fundamental importance of learning about the interactions of light and matter in the context of synthetic chemistry, the targeted complex heterocycles, i.e. molecules that contain nitrogen, sulfur, or oxygen atoms as a part of a ring, are intentionally designed to resemble alkaloids, an important class of natural products that may possess useful therapeutic properties. Importantly, this award will also support research experiences for undergraduate and graduate students, including those from historically underrepresented groups in science, thereby working toward inclusive excellence in the field of organic chemistry. This research aims to further expand the synthetic photochemistry toolbox, specifically to further develop excited state intramolecular proton transfer (ESIPT)-based photoassisted synthetic reaction cascades. For example, the Kutateladze group is targeting hydrogen atom transfer (HAT) in triplet states, designed to achieve large step-normalized complexity increases in the synthesis of complex heterocyclic molecular architectures. This work will also include a vertical growth in complexity through post-photochemical transformations. Reaction mechanisms and the stereochemistry of these ESIPT-triggered cascades will be investigated to better understand how these transformations achieve their stereo- and regiochemical outcomes. The experimental work will be augmented by computations that have been designed to facilitate solution structure elucidation of the complex heterocyclic products by nuclear magnetic resonance (NMR) spectroscopy. The newly integrated machine learning-augmented density functional theory (DFT) method for fast and accurate calculations of the NMR parameters will be expanded to explicitly account for the effect of solvents on the predicted spectra. This sub-theme of the proposed research is critical for the success of this project because of the structural complexity of the target molecules. Moreover, further development of this method will likely have broader implications for the structure elucidation of complex organic molecules, in general.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.