A Data-Driven Approach to the Development and Understanding of Chiroptical Sensors for Alcohols with Remote γ-Stereocenters.
A Data-Driven Approach to the Development and Understanding of Chiroptical Sensors for Alcohols with Remote γ-Stereocenters.
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DOI：
10.33774/chemrxiv-2021-zqpq8
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发表时间：
2021-09
影响因子：
15
通讯作者：
Jordan J. Dotson;E. Anslyn;M. Sigman
中科院分区：
文献类型：
--
作者：
Jordan J. Dotson;E. Anslyn;M. Sigman
基于动态共价化学的传感器最近成为快速确定有机小分子对映体过量的强大工具。虽然已经开发出了大量的传感器，但那些具有立体中心的柔性分子的传感器仍然很少，而这些分子的官能团与触觉传感器相结合。在这项研究中，我们开发了一个迭代的，数据驱动的工作流程来设计和分析一个能够评估具有挑战性的无环γ-立体醇的热感测器。在传感器优化之后，结合传感器分子的计算参数化、统计建模和高密度泛函理论（DFT）计算，探讨了传感机制。这些被用来阐明立体化学识别的机制，并揭示竞争吸引非共价相互作用（NCIs）决定传感器的整体性能。预计本文开发的数据驱动工作流程将普遍适用于动态共价和超分子传感器的开发和理解。
Dynamic covalent chemistry-based sensors have recently emerged as powerful tools to rapidly determine the enantiomeric excess of organic small molecules. While a bevy of sensors have been developed, those for flexible molecules with stereocenters remote to the functional group that binds the chiroptical sensor remain scarce. In this study, we develop an iterative, data-driven workflow to design and analyze a chiroptical sensor capable of assessing challenging acyclic γ-stereogenic alcohols. Following sensor optimization, the mechanism of sensing was probed with a combination of computational parametrization of the sensor molecules, statistical modeling, and high-level density functional theory (DFT) calculations. These were used to elucidate the mechanism of stereochemical recognition and revealed that competing attractive noncovalent interactions (NCIs) determine the overall performance of the sensor. It is anticipated that the data-driven workflows developed herein will be generally applicable to the development and understanding of dynamic covalent and supramolecular sensors.