# Free radical strategies for bioactive molecule synthesis

> **NIH NIH R35** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $640,172

## Abstract

Project Summary
Through our expertise in photo- and electrochemical methodology, the proposed work will afford
novel molecular scaffolds relevant and of interest to modern drug discovery. Through the
utilization of single-electron methodologies described herein, we can generate previously
inaccessible saturated carbocylces that have the potential to advance long standing challenges
within drug discovery. Through companion photochemical methodologies, novel access to 1-
aminonobornanes (1-aminoNBs), aminocyclopentanes, and bicyclo[3.1.1]heptan-1-amines has
established a robust platform from which to explore new carbocyclic frameworks as diverse, sp3-
rich chemical building blocks. Fundamental investigations of the imine photochemistry underlying
these transformations will yield further applications beyond carbocycle formation. The intersection
of our photochemical methods with transition metal catalyzed reactions provides a practical
means of introducing desirable functionality (i.e. saturated motifs) onto ubiquitous aromatic
backbones. Ultimately, we will utilize the power of single-electron transformations to gain access
to new chemical space which we are confident will afford translational opportunities in drug
discovery and beyond.

## Key facts

- **NIH application ID:** 10754872
- **Project number:** 5R35GM144286-03
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Corey Stephenson
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $640,172
- **Award type:** 5
- **Project period:** 2022-01-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10754872

## Citation

> US National Institutes of Health, RePORTER application 10754872, Free radical strategies for bioactive molecule synthesis (5R35GM144286-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10754872. Licensed CC0.

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