Hi Edward,

thanks for your reply.

On 07.02.2013, at 10:57, Edward d'Auvergne <[email protected]> wrote:

>> Neighbouring regions have a lot of "m0" (in 62 of ~220 assigned residues 
>> minus 28 unresolved) and in the ellipsoidal diffusion model there is also a 
>> lot of strange Rex = 0.0000 terms, the other models show Rex of around 
>> 10^-18 (=nearly zero). Convergence is reached in 20-30 rounds for each 
>> diffusion model, no oscillations are visible.
> 
> Is this Rex in the results file or in the extracted version?  Note
> that relax stores Rex internally as the field strength independent
> value of:
> 
> sigma_ex = Rex / omega**2

I extract Rex with the following command, I guess this is then the already 
field-corrected value?
        > value.write( param = 'rex', file = 'example/rex.txt')

I also forgot to mention, that while for the spherical and spheroid models 
convergence was reached pretty soon, the ellipsoidal calculations are still 
ongoing for two days now, but I can see that the parameter values are not 
really changing anymore, and chi^2 and AIC values do not converge but differ by 
only a factor of 10^10 from each other in the last ~20 rounds. I guess it is 
safe to pull the plug here? 

Will the "final" run of relax still be able to see the final optimization 
results?

> Also note that
> currently in all model-free software, Rex is assumed to be fast and
> hence scales quadratically with field strength - this might be another
> source of problems for your analysis.

You mean, because my Rex is too slow or because I have too few fields available 
(600 & 750 MHz)?

> R1 temperature compensation is generally not needed as it is quite a
> cold experiment, hence will almost always match the normal
> spectrometer calibration.  

No, what I meant is off-resonance "heating pulses" that make my R1 experiment 
just as warm as the R2 experiment which heats the sample due to the CPMG train 
in the relaxation period. In practice I just irradiate for ~100 ms (which is 
the mean of the delay times I have during my R2 experiments) before the actual 
pulse sequence begins, i.e. during d0. 

Single-scan interleaved is standardly employed, of course. This is true for all 
our experiments: R1, R2, NOE.

> Everything else seems fine.

Hey, that's something! At least the procedure as such seems ok. 

> Relaxation dispersion might be interesting, but from what you describe
> I don't think dispersion data will tell you much other than what you
> already see with weak peaks.  Actually, as your system is 45 kDa, I
> would not expect that you would see much dispersion at all - your weak
> peaks are due to protein size and not Rex.  

I don't get that – certainly the protein size is determining signal intensity 
but Rex is an additional factor, right? And I have 4 highly similar complexes – 
two different proteins which are mutated at one position which each bind two 
identical peptides. X-ray crystal data show virtually identical structures. 
Chemical shifts are also mostly very, very similar, but – with everything else 
totally the same – strips of signals go missing in one set of the complexes, 
and *not* the other. 

So there are definitely differences between highly similar complexes, which is 
breathtakingly interesting (and which no-one showed before with experimental 
data), but what I reached out for is to quantify these differences. S2 or Rex 
values from mf analysis seemed like a good bet ;)

> As for a guide about
> relaxation dispersion, I know no equivalent to Seb's guide. [...] If you do 
> find something, I'd be interested to have the
> reference.

I asked around at Researchgate and got a few reviews by Loria and Palmer. I 
feel that the Kay papers usually are so leading edge, they do not cover the 
basics and all the practical stuff. The other papers look promising (especially 
1 and 4) but I didn't have the time to look at yet. Here they are:

1.      Palmer AG, Grey MJ, Wang C (2005) Solution NMR spin relaxation methods 
for characterizing chemical exchange in high-molecular-weight systems. Meth 
Enzymol 394: 430–465. doi:10.1016/S0076-6879(05)94018-4.
2.      Loria JP, Berlow RB, Watt ED (2008) Characterization of enzyme motions 
by solution NMR relaxation dispersion. Acc Chem Res 41: 214–221. 
doi:10.1021/ar700132n.
3.      Palmer AG, Kroenke CD, Loria JP (2001) Nuclear magnetic resonance 
methods for quantifying microsecond-to-millisecond motions in biological 
macromolecules. Meth Enzymol 339: 204–238. doi:10.1016/S0076-6879(01)39315-1.
4.      Kovrigin EL, Kempf JG, Grey MJ, Loria JP (2006) Faithful estimation of 
dynamics parameters from CPMG relaxation dispersion measurements. Journal of 
Magnetic Resonance 180: 93–104. doi:10.1016/j.jmr.2006.01.010.

>>> Maybe this relates to model m9 in relax.  Sometimes the very weak
>>> peaks, broadened by chemical exchange, are too noisy to extract
>>> model-free motions from.  This is visible in relax as the selection of
>>> model m9.  In such a case, model m0 will probably not be picked.
>> 
>> I excluded the really noisy/weak peaks beforehand and m9 gets picked 
>> sometimes (9 times m9 opposed to 62 times m0 out of ~220 picked signals).
> 
> How many did you exclude?  There is no need to exclude such peaks as
> the protocol I developed will handle this.  

I excluded 6 where the peaks have been so weak that it was essentially only 
noise and a fit should give something close to a straight line.

>>> I don't know if this is completely relevant to your question, but
>>> noise is another issue which affects the reliability of the te
>>> parameters.  As te increases, so does the errors.  [...]
>> 
>> So do you think if my data are too noisy this could be a consequence? I 
>> already reached the limit in terms of scans, protein concentration and 
>> measuring time. Maybe I should write a grant for two new magnets ...
> 
> For the spins where m0 are selected, do their errors look larger than
> the other spins?  

I wouldn't say so:
https://dl.dropbox.com/u/4019316/boxplot.error.pdf

> Or if you plot the I0 values from the relaxation
> exponential curve-fitting, are these residues much lower than the
> rest?  

There definitely seems to be a tendency:
https://dl.dropbox.com/u/4019316/boxplot.pdf

> Maybe you could try out reduced spectral density mapping (very
> easy in relax) and compare errors for the J(w) values.  

I will try that in the following days. 

> As for new spectrometers, having more data would certainly help.  
> Especially if you have this mixed diffusion tensor problem and have derived a
> solution to test - then having data at 3 or 4 fields would be
> incredibly powerful.  Maybe you should get your boss to talk to
> Griesinger ;)  But if you have data at two field strengths, that
> should be sufficient.

Ha, we even would have 4 fields at hand around Berlin: We have a a bunch of 
600MHz magnets, but also an 750MHz and a 900 MHz field, and the Free University 
would have a 800 MHz field. Not all of them are capable of recording 
single-scan interleaved pseudo-3D spectra, and that's where the problems are 
starting already ... So if anyone should be interested to devote his life to 
this question, Berlin might be not the worst place to start working on it ;)

> > [HetNOE, deuterated 45 KDa protein]
> Oh, it's deuterated.  Ok, then you'll need much more time.  Though as
> it is 45 kDa, the relaxation should be nevertheless relatively fast.
> You can quite easily test this if you are curious.  You can simply
> compare 1D versions of your 2D experiments.

Should be interesting to see. It's always nice to save a bit measuring time – I 
need a lot of scans due to the insensitive experiment, a lot of points in the 
indirect dimension due to overlap and a lot of d0 time due to deuteration. One 
sample sits in the spectrometer for almost an entire week to get decent HetNOE 
data. And then I need a second field. And then I two different proteins, two 
ligands and the protein complex is a trimer, with each component labeled 
individually (twelve differently labeled sample types). That means I need many 
weeks  measuring time only for all HetNOE data if I decide to measure 
absolutely every component from the beginning to the end ... shaving a bit off 
isn't probably the worst idea.

> Actually, the 45 kDa size could be the reason for the m0 model being
> selected.  It could simply be too big, the relaxation from tumbling
> could be so fast that the internal motions have been hidden in the
> data.  

So if I see differences between samples that should still mean something. One 
protein behaves properly, the other doesn't – there is something going on.

> I can only recommend switching to Sparky for this type of analysis.

The main reason for not using sparky was that it cannot read Bruker pseudo 3D 
data and converting the individual planes from all the different data sets 
without mixing up the different delay times I tried is a incredible pain. Also, 
I'd have duplicate data where I could easily mix up file names and lose 
information where a specific set of data originally came from. Additionally, 
there is the assignment that has been done in CCPN, and which has to be 
exported into Sparky. I hope that it is possible, I guess I have to write and 
read and validate shift lists.

*But* I will give it a try. It seems like CCPN can't help me here.

>> Sorry for the long sermon. I appreciate that you always read my stuff and 
>> also answer in a really helpful and extensive manner.
> 
> Well, I hope some of my long answers helped.

They do!

>  If I was you, I would
> first redo the relaxation analysis using Sparky (and relax to fit the
> exponentials) and compare the data to CCPN.  

That's the first thing I'll try. 

> Then if m0 is still
> present, consider if you should blame it on the size of your system
> hiding data (more field strengths should then help uncover the
> dynamics).  

Too bad the console for our 900MHz magnet is so old. I'd have to measure 
non-interleaved spectra, which is probably as good as just not doing it at all.


> As you are working with complexes, then maybe an issue is that a
> single diffusion tensor is not an adequate representation of the
> system, resulting in the model m0 appearing more than it should.  This
> might be the case if the complex is not tight and you have a mixture
> of complex and free monomers.  [...]
> Finally, you should consider if your complex is tight or
> not.  If you think it is not [...]

I think it is a pretty tight complex. If one of the components leaves the 
heterotrimer, it falls apart, and the "primary" subunit unfolds and 
precipitates. But the other component (which I did not look at yet) is still 
soluble, which could cause trouble as soon as I start recording data for it ...

Regarding solving a maybe unsolvable statistical / applied physics / 
mathematical problem: I'm not sure if I'm the right person to go after it, I'd 
need somebody with better stat / physics / math skills ;)

Regards,
Martin


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