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Title: Deoxyfluorination with Sulfonyl Fluorides
Authors: Nielsen, Matthew K
Advisors: Doyle, Abigail G
Contributors: Chemistry Department
Keywords: deoxyfluorination
machine learning
random forest
sulfonyl fluoride
Subjects: Organic chemistry
Issue Date: 2018
Publisher: Princeton, NJ : Princeton University
Abstract: In drug design, the carbon-fluorine bond plays an important role in increasing metabolic stability while modulating the reactivity, conformation, and solubility of pharmaceutical candidates. The most straightforward method for selective aliphatic fluorination is the deoxyfluorination of alcohols. Although reagents such as DAST are routinely used by medicinal chemists for derivatization, the large scale deployment of deoxyfluorination is rare because existing reagents suffer from a combination of high cost, poor selectivity, and thermal instability. We have identified the sulfonyl fluoride motif as an inexpensive, thermally stable deoxyfluorination reagent class that can be tuned to maximize selectivity for specific substrates. For example, 2-pyridinesulfonyl fluoride (PyFluor) affords superior yields with unactivated acyclic secondary alcohols by minimizing elimination side reactions. Further exploration of existing and new reagents has revealed a complex reaction landscape in which all major classes of alcohols may be fluorinated in moderate to high yield through the judicious selection of a sulfonyl fluoride and base possessing complementary stereoelectronics. Additionally, we demonstrate that machine learning algorithms can be used to identify non-intuitive reactivity trends from high throughput screening data and predict the optimal conditions for new, untested substrates. We also investigate the application of sulfonyl fluoride deoxyfluorination to the radiosynthesis of 18F-labelled compounds, which are vital to medical imaging with positron emission tomography.
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog:
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Chemistry

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