nmr Archives - Michael's Bioinformatics Blog

October 20, 2014

Automate your Topspin NMR workflow

Here is a tip for scientists that need to batch process NMR data quickly and uniformly for analysis. This approach could be a big time-saver in situations where you have a large series of 1D reference spectra collected by sample automation, for example. Or in NMR screening applications, where dozens of STD-NMR experiments are being collected during an overnight run.

Hidden away in the Topsin “Processing” menu is a feature called “Serial Processing:”

Select this menu option and you will see the following dialogue:

Since this is first time you are doing this operation, you need to select “find datasets” in order to first find the data to process. In the future, you will have a “list” created for you by the program that you can reuse to reference datasets in combinations that you specify.

When you click “find datasets” you will see this dialogue:

Select the data directory to search from the “data directories” box at the bottom of the window. (If your NMR data directory is not here, it is because you haven’t added it to the Topspin file brower in the main Topspin window. Go do that first, and come back and try this operation again.)

Under the “name” field, enter the name of the specific dataset directory you wish to search, or leave it blank to search across many directories. You can also match on experiment number (EXPNO) or process number (PROCNO). The check boxes enforce exact matching. You can select 1D or higher dimensional datasets for processing. You can also match by date.

When you’ve made your selections, it will look like this:

In this search, I am selecting for all 1D data contained in the “Oct16-2014-p97” subdirectory of my NMR data repository at “/Users/sandro/UCSF/p97_hit2lead/nmr”.

Click “OK” and wait for the results. Mine look like the following:

The program has found 24 datasets that match my criteria. At this point, you want to select only those you wish to batch process. I will select all files like this:

Now click “OK” and you are returned to this prompt:

Notice that the program has now created a list of datasets for batch processing for you, store in the ‘/var/folders/’ temporary directory. The list is a text-based list of the filenames you specified by your selection criteria. You can edit by hand or proceed to the next step. To proceed, click “next.” You will now see this dialogue:

This is where the useful, time-saving stuff happens. This dialogue takes the list you defined and applies whatever custom command sequence you would like to apply to your data. You define this sequence in the text box at the bottom. As you can see, I have chosen to perform “lb 1; em; ft; pk.” This is line broadening = 1, exponential multiplication, fourier transform, and phase correction. You can also specify a path to a python script for the Topspin API.

Once you have your desired processing commands, click “Execute” and go grab a coffee! You just saved yourself many minutes of routine processing of NMR spectra. Hope you find this tip useful and that it can save you some time in your day.

July 9, 2014

Isotopic labeling of proteins in non-bacterial expression systems

As therapeutic proteins gain importance alongside traditional small molecule drugs, there is increasing interest in using NMR methods to examine their structure, dynamics, and stability/aggregation in solution.

Modern heteronuclear NMR of proteins relies on isotopically-labeled samples containing NMR active nuclei in the peptide backbone, sidechains, or both.

Although isotopic-labeling of recombinant protein is typically carried out in E. Coli expression systems, many biotherapeutic proteins must be expressed in eukaryotic systems to insure proper folding and/or post-translational modifications. In practice, this means overexpression in either yeast, insect or mammalian cells.

Increased interest in attaining labeled protein samples for analysis by NMR is leading to better commercial availability of isotopically-labeled expression media and improved vectors for overexpression in non-bacterial systems.

Comprehensive reviews of state-of-the-art protocols and procedures for expression of isotopically-labeled proteins in non-standard systems are available here: yeast, insect cells, and mammalian cells.

May 23, 2014

10 Common Mistakes in Fragment Screening

There is an excellent review paper from Dan Erlanson and Ben Davis that came out last year detailing some of the more common mistakes and artifacts that can arise in fragment-based screening campaigns (so-called “unknown knowns”). I encourage readers to go read the original paper. I have summarized some of the key points below:

1) Not checking compound identity to make sure what you think you purchased is what you actually have.

2) Low-level impurities in compound stocks can cause problems at the high concentrations used in fragment screens.

3) DMSO, commonly used to store fragments in plates, can act as a mild oxidant and is also hygroscopic.

4) Pan-assay interference compounds (PAINS) are common in many libraries and are found to give false positives to many targets.

5) Reactive functional groups in fragment hits can cause covalent binding or aggregation of the target.

6) Many fragments can show binding or inhibition while acting as aggregators rather than reversible binders. Including a small % of detergent can help eliminate these kinds of fragments from giving positive signals.

7) STD-NMR is very sensitive to weak binders, but because it relies on a relatively fast disassociation rate for the ligand, tight binders (<1 uM) can be missed by this method.

8) X-ray crystallographic structures are often taken as the “truth” when they are in fact a model of an electron density. Fragments can often be modeled into the density in incorrect orientations or in place of solvent atoms.

9) SPR methods are very sensitive to fragment binding, but can be confounded by non-specific binding of fragment to the target or chip, as well as compound-dependent aggregation.

10) Fragment hits should be validated by more than one method before embarking on optimization. They should also be screened for being aggregators by DLS or other methods.

November 13, 2013

Saving current shims for an automation run

Here is an important tip if you are setting up an automation run using Bruker’s ICON-NMR software. Before the run, lock and shim on your first sample. Once you have a very good shim, write your shim settings (‘wsh’) to a new shimset called “automation.” If you specify the “automation” shimset in the gradshim menu as the one to be used by ICON, it will use this shimset as a starting point for automated shimming before each sample rather than a default shim.