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Data Science-Guided Development of Deoxyfluorination Reagents with Enhanced Reactivity, Practicality, and Safety.

Madeline E Ruos1, Natalie P Romer2, Julie A Deichert3

  • 1Department of Chemistry and Biochemistry, University of California-Los Angeles, Los Angeles, California 90095, United States.

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New sulfonyl fluoride reagents offer enhanced deoxyfluorination reactivity and safety. Data science guided the development of these versatile reagents for synthesizing complex molecules like RIPK1 inhibitors.

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Area of Science:

  • Organic Chemistry
  • Medicinal Chemistry
  • Computational Chemistry

Background:

  • Deoxyfluorination is a critical transformation in organic synthesis.
  • Existing reagents like PyFluor, PBSF, and DAST have limitations in reactivity, safety, or physical properties.
  • Development of novel, safer, and more effective deoxyfluorination reagents is essential for pharmaceutical synthesis.

Purpose of the Study:

  • To discover and develop novel (hetero)aryl sulfonyl fluoride reagents with improved deoxyfluorination capabilities.
  • To optimize reagents for the synthesis of a key intermediate for the RIPK1 inhibitor GDC-8264.
  • To explore structure-activity relationships and enable data science-driven reagent design.

Main Methods:

  • Computational screening of a virtual library of (hetero)aryl sulfonyl fluorides.
  • Application of training set design principles to survey structure-activity relationships.
  • Development of predictive models for reagent optimization.
  • Testing of top-performing reagents in deoxyfluorination reactions with diverse alcohol substrates.

Main Results:

  • Several new (hetero)aryl sulfonyl fluoride reagents were discovered and developed.
  • These new reagents exhibit enhanced deoxyfluorination reactivity and improved safety profiles compared to existing methods.
  • Optimized reagents were successfully applied to the deoxyfluorination of a key intermediate for RIPK1 inhibitor synthesis.
  • The developed reagents showed broad applicability across various alcohol classes, including natural products and active pharmaceutical ingredients.

Conclusions:

  • Novel (hetero)aryl sulfonyl fluoride reagents with superior performance were successfully developed.
  • Data science and computational approaches are powerful tools for accelerating reagent discovery and development.
  • These new reagents represent a significant advancement in deoxyfluorination chemistry with broad applications in pharmaceutical synthesis.