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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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Updated: May 14, 2026

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

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Published on: December 16, 2013

Harmonizing Peak Matching Between Multidimensional NMR Spectra.

Anthony C Bishop¹, Kyle Mimun¹, Weimin Tan¹

¹Department of Biochemistry & Biophysics, Texas A&M University, College Station, Texas 77843 USA.

Biorxiv : the Preprint Server for Biology

|May 13, 2026

Summary

This summary is machine-generated.

This study introduces pHarmony, an automated algorithm for mapping cross-peaks in multidimensional NMR spectra. It provides reliable, harmonized matches by modeling deviations and using Bayesian inference for confidence estimates.

Keywords:

Bayesian statistics automation confidence estimation cross-peak matching heteronuclear NMR peak tracking

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Nuclear Magnetic Resonance Spectroscopy for the Identification of Multiple Phosphorylations of Intrinsically Disordered Proteins

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Area of Science:

Structural Biology
Analytical Chemistry
Computational Chemistry

Background:

Manual cross-peak mapping in multidimensional NMR is time-consuming and subjective.
Ambiguities arise in high degeneracy regions and when samples are perturbed.
Automated, reliable, and consistent cross-peak matching is needed for NMR data analysis.

Purpose of the Study:

To develop a novel, automated algorithm for harmonized cross-peak matching between multidimensional NMR spectra.
To provide confidence estimates for proposed cross-peak matches.
To address challenges in comparing spectra with perturbed samples or partial dimension matching.

Main Methods:

Developed a novel model for the distribution of apparent deviations between cross-peaks.
Applied Bayesian inference to harmonize potential mappings and provide confidence estimates.
Implemented the pHarmony algorithm for automated cross-peak matching.

Main Results:

The pHarmony algorithm successfully harmonizes cross-peak matching across spectra.
Confidence estimates indicate the reliability of proposed matches.
Demonstrated effectiveness in mapping between triple resonance spectra and heteronuclear NMR spectra from fragment-based screening.

Conclusions:

pHarmony offers a well-defined, consistent, and automated solution for multidimensional NMR cross-peak mapping.
The algorithm enhances the reliability and efficiency of NMR spectral comparison.
pHarmony is applicable to diverse NMR datasets, including those from fragment-based ligand discovery.