Fitting peak heights in a series of 1D spectra

Analysis Version 3
1

Dear all,

I’m looking for a good routine to pick and assign a series of 1D spectra and subsequently follow/fit intensity changes, generate a figure of the fitting and calculate a decay rate constant.

I wonder if there is something like this implemented in analysis v3 directly or if there is a macro out there that I could use?

Thanks a lot,
Andras

2

Hi Andras,
Yes we have a new workflow for this in development. If you don’t mind using it as a macro/alpha-release. We can make it availabe to download with a short video before the official documentation and release.

3

Dear Luca,

It is very nice to hear from you.

Yes, I would be happy to test this in alpha phase.

Best regards,

Andras

4

Hi Luca,
Just wanted to check in.
Did you make the macro/alpha release available some where?
Best regards,
Andras

5

Hi Andras,
Sorry the delay. Yes @Vicky wrote the tutorials for alpha version of the Relaxation module. You can find here or in the support page.
The only difference is that is for nDs and there is a project with the initial assignment.
But you can simply pick the peaks and skip the parts you don’t need:

In summary:

  • Load Data

  • Pick peaks. Keep open only the first spectrum in the series in a new display
    Go to the region of interest and pick all the peaks, either with a region (cmd+shit+left drag) or one at the time, cmd+shit + single click at position.

  • Assign placeholders. Not strictly necessary, but if you want have labels on each peak,
    Main menu → assign → Setup nmrResidues, Click setup NMR Residue button.

  • The rest is the same as the tutorial

Find a quick video for you with all steps here:
I also assume you are doing for a single series.
If you are screening many samples, then we will need some automation… Either way, let us know any feedbacks and suggestions.

6

Obviously, download the software 3.1.1 and run the updates from the help menu.

7

Thanks Luca,

This is fantastic.

I just found one bug: The fitting algorithm is great when data are given in seconds, but it doesn¡¯t seem to work well with the time series given in ms.

With best regards and lots of thanks,

Andras

8

Hi Andras,

thanks for the bug report. We’re already aware of this (which is why the tutorial says to use seconds :slight_smile:). At the moment the program still doesn’t understand that 1ms = 0.001s, but we shall certainly be adding that.

Vicky

9

Hi Vicky,

Thank you for the explanation. This is very helpful.

Also, the Macro is really great.

With best wishes,

Andras