# TR&D1: Experimental design in solution NMR spectroscopy

> **NIH NIH P41** · NEW YORK STRUCTURAL BIOLOGY CENTER · 2020 · $339,205

## Abstract

TR&D 1 - Experimental design in solution NMR spectroscopy
Summary
 A major effort of the Center on Macromolecular Dynamics by NMR Spectroscopy
(CoMD/NMR) will capitalize on and extend the dramatic advances in solution NMR methods for
characterizing macromolecular conformational dynamics that have occurred over the past 25 years.
TR&D1 has three major foci: (i) spin relaxation for fast (ps-ns) internal dynamics and overall
rotational diffusion, (ii) chemical exchange for µs-ms internal dynamics and interaction kinetics, and
(iii) residual dipolar coupling constants, scalar coupling constants, and chemical shifts that report
averaging over conformational distributions on time scales faster than 1/Δω, where Δω is the variation
in the given parameter between conformations. Experimental and analytical methods in all three
areas will be developed with a focus on application to the really challenging protein and nucleic acid
targets with complex dynamics and large molecular masses represented by the Driving Biomedical
Projects. This TR&D will be strongly integrated to the other three TR&D components of CoMD/NMR,
through synergistic applications with relaxometry in TR&D2 and solid-state NMR in TR&D3 as well
as through tight integration with software development in TR&D4.

## Key facts

- **NIH application ID:** 9967025
- **Project number:** 5P41GM118302-04
- **Recipient organization:** NEW YORK STRUCTURAL BIOLOGY CENTER
- **Principal Investigator:** ARTHUR G PALMER
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $339,205
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9967025

## Citation

> US National Institutes of Health, RePORTER application 9967025, TR&D1: Experimental design in solution NMR spectroscopy (5P41GM118302-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9967025. Licensed CC0.

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