ArticleJournal of the American Chemical Society2021
A Data-Driven Approach to the Development and Understanding of Chiroptical Sensors for Alcohols with Remote γ-Stereocenters.
Article in Journal of the American Chemical Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Article
- Optical Enantiodifferentiation of Chiral Nitriles.Organic letters · 2024Article
- Chemometric sensing of stereoisomeric compound mixtures with a redox-responsive optical probe.Chemical science · 2024Article
- Identifying structure-function relationships to modulate crossover in nonaqueous redox flow batteries.Journal of materials chemistry. A · 2023Article
- Determination of Enantiomeric Excess and Diastereomeric Excess via Optical Methods. Application to α-methyl-β-hydroxy-carboxylic acids.Organic chemistry frontiers : an international journal of organic chemistry · 2023Article
- Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery.Chemical science · 2023Review
- Data-Driven Prediction of Circular Dichroism-Based Calibration Curves for the Rapid Screening of Chiral Primary Amine Enantiomeric Excess Values.Journal of the American Chemical Society · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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.
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Registered trials
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