# Modular Synthesis of 1,2-Azaborines via Boron-mediated Strain-release Reductive Cyclization

> **NIH NIH R21** · UNIVERSITY OF CHICAGO · 2022 · $205,000

## Abstract

Abstract: As an emerging class of bioisosteres of aromatic compounds, 1,2-azaborines have
received increasing attention in drug discovery. However, the current synthesis of 1,2-
azaborines encounters substantial difficulties, including how to access poly-substituted 1,2-
azaborines and BN-heteroarenes, how to avoid using expensive catalysts and handling
sensitive intermediates, how to increase modularity and scalability, etc. Here, we propose to
develop a boron-mediated strain-release reductive cyclization (BSRC) strategy to address these
accessibility and practicality challenges. Our objective, in the proposed funding period, is to
establish the BSRC method for preparing multi-substituted 1,2-azaborines and 4,9-BN-
quinolines from readily available cyclopropyl ketones and aziridyl pyridines (AZPs), respectively.
Specifically, we will conduct the reaction discovery, method optimization, scope exploration, and
mechanism studies. The proposed research is expected to offer a new approach for streamlined
synthesis of 1,2-azaborines, which, in turn, should accelerate preparation of novel
pharmaceutical analogues and expand the chemical space for drug discovery.

## Key facts

- **NIH application ID:** 10491122
- **Project number:** 5R21GM144048-02
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Guangbin Dong
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $205,000
- **Award type:** 5
- **Project period:** 2021-09-20 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10491122

## Citation

> US National Institutes of Health, RePORTER application 10491122, Modular Synthesis of 1,2-Azaborines via Boron-mediated Strain-release Reductive Cyclization (5R21GM144048-02). Retrieved via AI Analytics 2026-06-10 from https://api.ai-analytics.org/grant/nih/10491122. Licensed CC0.

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