Copyright 2014-2020 by Evgueni Kovriguine

Back to main index


1D NMR line shapes




Back to Contents


    Source code

This is a summary of all folders relevant to line shape analysis. See my lecture notes on theory of line shape analysis in Mathematical_models/NMR_line_shape_models/My_lectures.



Back to Contents



     Specific line-shape models

Specific models for one-dimensional NMR line shapes are defined by modules in code/+line_shape_equations_1D/ and included in the body of  NMRLineShapes1D class (code/@NMRLineShapes1D/NMRLineShapes1D.m). Below is brief outline of the existing models, their purpose and capabilities. For a rigorous way of deriving them see Mathematical_models/NMR_line_shape_models.

Below is a partial list of  models implemented in IDAP.  For a full list of the line shape models see @NMRLineShapes1D/NMRLineShapes1D.m. Their development and testing is documented in IDAP/Mathematical_models/NMR_line_shape_models/index.htm



Back to Contents




     A workflow for introducing a new model






Back to Contents





     Using IDAP 1D NMR

Important considerations on data acquisition and processing:

  1. Spectra must be prepared using Exponential apodization window (EM in NMRPipe). Bloch-McConnell equations describe lorentzian signals therefore any other apodization windows are not acceptable.
  2. If the heteronuclear spectrum was obtained using a constant-time experiment---the indirect dimension line shapes are (most likely) not useful because there was no free "induction decay" collected due to constant-time acquisition mode of t1. Experiments like that are most frequently performed to record proton-carbon correlations.
  3. Zero-filling must be adjusted to have about 5-10 data points per signal envelope (above baseline). More points only overload CPU but do not add any new information. Fewer points make fitting much less stable.
  4. It is important that all spectra are processed with the same zero-filling so that each dataset contributions similarly to the the overall sum of squares of deviations for the the series. is a utility one can use to perform automated processing of a large number of experimental 2D datasets. See NMR_series_processing.htm for more details.

Experimental NMR line shapes are extracted from 2D HSQC spectra using a custom extension IDAP 1D NMR in Sparky spectral analysis software (obtain Sparky from The IDAP 1D NMR extension is written in Python and described in the document IDAP 1D NMR Sparky extension.


A subclass of NMRLineShapes1D called IDAP_1D_NMR.m enables import the exported spectral slices into a TotalFit session.



Back to Contents

    Frequently asked questions

Q: How many residues do you typically use for a Monte-Carlo fit? I've been trying to do global fits with 10-12 traces (& ~8 titration points each) -- I'm wondering if I might just be overloading my system?

This is very variable. It depends on data quality and number of points in your traces. You should have about 10 points in the peak envelope, and some stretch of the baselines around the peak. Too many points directly overload the system, too few make fitting unstable. If you are in fast exchange seeing only one peak, you may want to use individual slice extraction mode to make shorter overall baselines.

Otherwise, I would start with 2-3 residues and see.







Back to Contents