Exercises NMRPipe data processing of 2D and 3D NMR data These exercises assume that a recent version of the NMRPipe package is installed on your system, and should work irrespective of the platform you use. For downloads, know bugs, documentation, demos and reference material please refer to http://spin.niddk.nih.gov/NMRPipe or the mailing list http://groups.yahoo.com/subscribe.cgi/nmrpipe. In the directory "NMRCourse" you will find three Varian datasets: c13hsqc.fid n15hsqc.fid hnco.fid Each of these data directories is wrapped up in a tar file, and compressed. Download them to your computer. The data can now be extracted in the following fashion: zcat hnco.tar.Z | tar xvf The purpose of the 2D datasets is to illustrate the use of functions and parameters in NMRPipe. Acquisition parameters are contained in the file "procpar", and can be extracted with the auxiliary "varian" conversion utility supplied with the NMRPipe suite. For Bruker data a similar tool exists. Be aware that these scripts extract parameters based on a likely implementation and execution of the experiment. The utility will guess the order and associated frequencies of the n-dimensional experiment. Also it will assume that the carrier frequencies were tof, dof, dof2, etc (Varian) or O1, O2, O3, etc (Bruker), and not modified by changing the carrier during the experiment (either in the pulse sequence, or by a parameter associated with it). The HNCO dataset is used to illustrate conversion and processing of 3D data, again including the use of linear prediction. Good luck with the exercises! Frans Mulder University of Groningen, May 2008 n15hsqc The purpose of this exercise is to familiarize your self with processing from the UNIX shell command line, as well as with the nmrDraw program. The dataset was obtained using a gradient sensitivity enhanced 2D 15N- 1H HSQC experiment (pulse sequence from the Toronto library of Lewis Kay). 1) conversion Start the program "varian" from the shell inside the .fid directory. Us e Read parameters to extract standard parameters from the procpar file. Then check the parameters, and adjust those that you think - or already know - were not interpreted correctly. If you miss anything at this point it may become apparent later, and you can return to this point. When you are satisfied with the parameters select Save script and Execute script. Alternatively one can use from within nmrDraw File>Macro Edit to create a conversion script under Varian Conversions>2D conversion. This will then require you to know which parameters to look for in procpar. 2) checking your time domain data Start nmrDraw by calling it from the shell command line. Be aware that items from the pulldown menus are selected by using the right mouse button. Select the converted FID, and read/draw it to inspect the data. For example, have a look at the first FID by use of Mouse>1D horizontal. Is everything as expected? If the conversion went well the time domain dataset consists of (512x2)x(128x2) points. Realize that you are now looking at only half of the data! You only see the "real" FIDs in the acquisition dimension, i.e. collected and compared with a cosine carrier wave. The imaginary FIDs are hidden to your view. If you want to look at one of them then you can select this FID and choose: proc>NMRPipe command. On this command line you can type "SHUF -swap". Now you are looking at the imaginary part of the data. Sometimes there may be corrupted FIDs, for example due to receiver overflows. So it is important to be able to inspect all the time domain data. Using macro edit write a small processing script that reads in the data; shuffles the real and imaginaries; writes out the data file. Now you are ready to inspect the hidden part of your data. 3) Processing from nmrDraw Choose Proc>NMRPipe command for the processing popup window. Using the first FID perform a sequence of 1D processing commands to obtain a frequency domain spectrum. You may start over when trying the effect of another command, or changing some paramaters (e.g. window function). If you would like to visualize a window function you can type "set �r 1" when a sequence of points (an FID ...) has been read in. This will replace all the points of the original vector with ones. If you now apply the function of the desired function you can inspect the result on the screen. For example, try a Lorentz-to-Gauss transformation and see how the parameters influence the resulting window function. Select a window function that enhances the resolution of your data, with little ripple, that can be used for 2D processing. Determine the phase corrections from the nmDraw window. For this you must first activate the phasing tool! 4) Creating an interferogram Within the File>Macro Edit window select Process 2D>Basic 2D. Edit the macro to incorporate the processing of the acquisition domain. Comment out processing of the indirect domain by placing # at the start of any lines associated with this dimension. Add additional Windows, Transforms, Corrections where needed. Save the script with an appropriate name when ready. Use the help button to get information about a function and its arguments. Execute your script and inspect the result: Select a vertical trace to try out the processing parameters in the indirect dimension. Phasing parameters are often known before hand, depend on how much evolution has taken place when the first point was measured. In the present experiment acquisition started at zero. Remember what that means for the first point? 5) Processing the 2D spectrum Now complete the 2D processing script with all operations you want included, and execute it. Check the result. If you notice any undesired features then go back to the conversion or processing scripts and then edit and rerun these. 6) Comparison with a reference spectrum Below is the final spectrum I obtained. How did you do? If your spectrum contains mirrored peaks in the 15N dimension, and it appears impossible to phase it means that you have set -yMODE to Complex in fid.com. However, since this data was obtained with sensitivity enhancement, employing field gradient coherence selection you first need to make linear combinations of the input data. This is done implicitly by setting - yMODE to Rance-Kay. To learn more about this procedure please refer to recent textbooks on (biomolecular) NMR spectroscopy, or the original paper: L.E. Kay, P. Keifer, T. Saarinen, J. Am. Chem. Soc. 114, 10663- 10665 (1992). c13hsqc This is an example of constant-time data in the indirect domain. The experiment was recorded on a 50% deuterated sample, as you will notice in a short while. The purpose of the exercise is to process truncated data correctly, and to use linear prediction. 1) conversion Start the program "varian" from the shell inside the .fid directory and convert the varian fid file to NMRPipe format. Process the acquisition dimension. This may be difficult. 2) Process the indirect dimension Select a trace in the t1 direction. Convince yourself that this is really constant-time data. Find an appropriate apodization function. Think of S/N, resolution, ripple. Can you phase this data? Can you rationalize the phasing parameters? How do you think I decoupled the carbonyl carbons? 3) Linear prediction Now extend the original t1 data by linear prediction. There are various options for this in the package. Which would be appropriate? Does the resolution increase? How would you adjust your apodization on the extended data? How does this influence your S/N? 4) 2D processing Process the 2D to your satisfaction. Do this once with LP and once without. Compare the two spectra as whole. How does it look? Now zoom in on area with a few peaks in a crowded region. Look carefully at both spectra. What do you think now? Can you explain the peak shapes in the spectrum that used LP? hnco 1) conversion Start the program "varian" from the shell inside the .fid directory and convert the varian fid file to NMRPipe format. The way that 3D data are recorded is usually to acquire the complex points in the indirect dimensions consecutively. There are two possibilities for this for 3D data. In var2pipe the order is indicated by the parameter aqORD: -aqORD aqOrd  Acquisition Order Code. 0 = 3D d3,d2,phase2,phase 1 = 3D d3,d2,phase,phase2 Check procpar to know which option is appropriate. Convert the 3D. 2) 2D plane processing Under Process 2D you can find scripts to process the XY and XZ planes of the 3D dataset. Edit to your liking and process the two planes. Check how LP may be implemented in each of the indirect domains. 3) 3D processing Using the parameters optimized for the 2D plane processing build a 3D processing script with help from File>Macro Edit, excluding LP. This should be quick. Make sure you are happy with the results. For example, are the frequency axes running in the correct sense? Next we will try to implement LP in both indirect dimensions. This will take longer so inspect your scripts well before execution. Propes use of LP requires that it is applied to a dataset that has only the dimension to be predicted in the time domain, and all other dimensions processed. This will require the use of inverse functions as well. Check in File>Macro Edit>3D processing. Finally transpose the 3D spectrum without LP so that you can now inspect both (H,N) planes as a function of 13C' (z), as well as (H,C') planes as a function of 15N (z). Unfortunately nmrDraw does not allow to "role the axes". Export the result to your favourite analysis program (Sparky, NMRview, ...) Additional remarks and questions to the n otes of Cornilescu CHAPTER 1 Before you "process the data in the usual way" have a look at the fid.com and ft2.com scripts and convince yourself that you understand them. After you have gone through this chapter note the following: To a slightly experienced NMR spectroscopist the 2D spectrum appears "funny". What are those signals that appear near 145 ppm in the nitrogen dimension? Are there any nitrogen nuclei in a protein that resonate in this range? Apropos, around which chemical shifts should you expect signals of (a) backbone amide (b) histidine protonated and deprotonated side chain (c) arginine N and N (d) the N-terminal -amino group (e) lysine N (f) asparagine and glutamine amide (g) tryptophan indole nitrogen nuclei? Reprocess the spectrum with the nitrogen frequency axis running in the opposite direction by changing the argument to the function �fn FT. What are those signals around 85 ppm due to? CHAPTER 2 Before you start picking peaks make sure that phasing is already perfect. Then adjust the script to pick only positive peaks. How many peaks are there in the HSQC spectrum? And divided into how many peak clusters? CHAPTER 5 After processing the ipap spectra have a look at the level at which you see "dif" peaks in the "sum" spectrum. Have a look at the included coad_1234.M macro and see if you can improve this. CHAPTER 7 After processing the data inspect the scripts that are called by fit.com. After running fit.com we will not proceed with model.com, but run the interactive script showEvolve.tcl and fit some curves interactively. Next, change the processing script to use matched filters in F1/F2. Inspect the difference spectrum (between the input and simulated data). How good is the fit? In which way does your choice of window function change the goodness of the fit? And how the completeness of fitted peaks?