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Updated: Oct 21, 2025

Author Spotlight: Exploring Intrinsically Disordered Protein Dynamics Through NMR Relaxation Experiments
Published on: November 1, 2024
TRACT revisited: an algebraic solution for determining overall rotational correlation times from cross-correlated
Scott A Robson1, Çağdaş Dağ1,2, Hongwei Wu3
1Department of Molecular and Cellular Biochemistry, Indiana University, 212 S. Hawthorne Drive, Bloomington, IN, 47405, USA.
Abstract:
Accurate rotational correlation times ([Formula: see text]) are critical for quantitative analysis of fast timescale NMR dynamics. As molecular weights increase, the classic derivation of [Formula: see text] using transverse and longitudinal relaxation rates becomes increasingly unsuitable due to the non-trivial contribution of remote dipole-dipole interactions to longitudinal relaxation. Derivations using cross-correlated relaxation experiments, such as TRACT, overcome these limitations but are erroneously calculated in 65% of the citing literature. Herein, we developed an algebraic solutions to the Goldman relationship that facilitate rapid, point-by-point calculations for straightforward identification of appropriate spectral regions where global tumbling is likely to be dominant. The rigid-body approximation of the Goldman relationship has been previously shown to underestimate TRACT-based rotational correlation time estimates. This motivated us to develop a second algebraic solution that employs a simplified model-free spectral density function including an order parameter term that could, in principle, be set to an average backbone S2 ≈ 0.9 to further improve the accuracy of [Formula: see text] estimation. These solutions enabled us to explore the boundaries of the Goldman relationship as a function of the H-N internuclear distance ([Formula: see text]), difference of the two principal components of the axially-symmetric 15N CSA tensor ([Formula: see text]), and angle of the CSA tensor relative to the N-H bond vector ([Formula: see text]). We hope our algebraic solutions and analytical strategies will increase the accuracy and application of the TRACT experiment.
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