# Toolkit for Fast, Multipurpose and Inducible Bioorthogonal Chemistry

> **NIH NIH R01** · UNIVERSITY OF DELAWARE · 2020 · $129,288

## Abstract

Project Summary
The goal of this Competing Revision will be to extend the tools being developed in the
R01 GM132460 to glycoscience applications in collaboration with carbohydrate chemical
biologists Catherine Leimkuhler Grimes (UD) and Jennifer Kohler (UTSW). This
Competing Revision will expand the toolkit being developed under the parent award to
develop bioorthogonal N-acylmuramic acid (NAM) and N-acylglucosamine (NAG)
molecules for use in probe applications in microbiology and immunology research. The
technology to be developed will enable dramatically faster kinetics than is possible with
current bioorthogonal methods for metabolic glycoengineering which generally require
the prolonged incubation with labeling reagents at millimolar concentration. The Fox
group will collaborate with Grimes and Kohler to develop a general platform for creating
common intermediates that can be subjected to late-stage, catalytic cross-coupling or
reduction to produce a variety of tetrazine-monosaccharide analogs for metabolic
oligosaccaride engineering. The method will be applied to the NAM platform developed
by collaborator Grimes and will be extended to the development of GlcNAc analogs
developed by collaborator Kohler.

## Key facts

- **NIH application ID:** 10052552
- **Project number:** 3R01GM132460-02S1
- **Recipient organization:** UNIVERSITY OF DELAWARE
- **Principal Investigator:** JOSEPH M FOX
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $129,288
- **Award type:** 3
- **Project period:** 2019-04-01 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10052552

## Citation

> US National Institutes of Health, RePORTER application 10052552, Toolkit for Fast, Multipurpose and Inducible Bioorthogonal Chemistry (3R01GM132460-02S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10052552. Licensed CC0.

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