OPTICAL SENSING AND CHEMOMETRIC ANALYSIS OF CHIRAL COMPOUNDS

在化学部化学结构、动态和机制B项目的支持下，乔治城大学化学系的Christian Wolf教授的研究小组正在开发光学传感方法，通过引入广泛应用的小分子探针、概念上的新分子识别策略、人工智能工具和自动化高通量实验技术，加速和拓宽手性化合物分析。这项研究有可能推动当前的研究和开发边界，改变繁琐的分析协议，并揭示新的机会，例如，消除缓慢和工作密集型实验室实践的连续不对称反应开发工作流程。拟议的工作是高度协作的，涉及工业和学术合作伙伴，并为来自科学领域代表性不足的群体的研究生、本科生和高中生提供多种培训机会。迄今为止，已经介绍了对伯胺和仲胺、氨基醇、氨基酸、醇和羟基酸的热感测测定。然而，全面的传感——确定绝对构型、选择性和浓度——对许多系统来说仍然是一个挑战。这些包括(a)无官能团的化合物，如腈、酯、酰胺、叔胺或芳香支架，(b)具有一个以上手性中心的底物和(c)多组分混合物。为了克服这些限制，将引入新的分子探针设计，快速捕获溶液中目前难以捉摸的手性靶化合物，并通过立体动力学受体支架上的自发手性扩增报告分子识别事件，形成独特的可量化的手性（圆二色性和紫外/可见吸收）响应。此外，将开发基于有机反应的多模态光学手性传感方法和能够进行正交数据融合和光谱反褶积的化学计量学，通过消除分析前通常需要的物理分离来实现对复杂混合物的全面传感。最后，机器学习将与热带高通量筛选技术相结合，以实现原始的不对称催化发现。该奖项反映了美国国家科学基金会的法定使命，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 support of the Chemical Structure, Dynamic & Mechanism B Program of the Chemistry Division, Professor Christian Wolf’s research group of the Department of Chemistry at Georgetown University is developing optical sensing methodology that accelerates and broadens chiral compound analysis by introducing widely applicable small-molecule probes, conceptually new molecular recognition strategies, artificial intelligence tools, and automated high-throughput experimentation technology. This research has the potential to push current research and development boundaries, transform cumbersome analysis protocols, and unfold new opportunities, for example, continuous asymmetric reaction development workflows that eliminate slow and work-intensive laboratory practice. The proposed work is highly collaborative involving industrial and academic partners and provides multiple training opportunities for graduate, undergraduate and high school students from groups underrepresented in science.Chiroptical sensing assays for primary and secondary amines, amino alcohols, amino acids, alcohols and hydroxy acids have been introduced to date. However, comprehensive sensing--determination of absolute configuration, selectivity, and concentration--remains a challenge for a number of systems. These include (a) compounds devoid of functionalities such as nitriles, esters, amides, tertiary amines or aromatic scaffolds, (b) substrates that possess more than one chirality center and (c) multicomponent mixtures. To overcome these limitations, new molecular probe designs that quickly capture currently elusive chiral target compounds in solution and report the molecular recognition event via spontaneous chirality amplification across stereodynamic receptor scaffolds into a distinct and quantifiable chiroptical (circular dichroism and UV/vis absorption) response will be introduced. In addition, organic reaction based multi-modal optical chirality sensing methodology and chemometrics capable of orthogonal data fusion and spectral deconvolution will be developed to achieve comprehensive sensing of complicated mixtures by eliminating the common need for physical separation prior to the analysis. Finally, machine learning will be integrated with chiroptical high-throughput screening technology to enable original asymmetric catalysis discoveries.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.