Hi, >>> 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')
This is clearly a bug! For example on an 800, you should multiply 1e-18 with the value of ~2.6e17. Could you file a bug report for this? A value of 1e-18 should give a significant, yet low, Rex value of 0.15-0.3 rad.s^-1. > 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? How many rounds is it up to? If it runs infinitely, then maybe you have run into a chaotic system. Now that would be fascinating! Theoretically anyway, biologically it would be irrelevant. I'm guessing you mean 1e-10. Can you see which models are changing? Can you find any chi2 or AIC values which match between the rounds? If you make a table of total parameter number, chi2, and AIC, can you see any patterns? At some point, an optimisation problem should have a solution which, when calculated on a computer, should result in numerically identical solutions (parameter values, chi2, diffusion tensor, etc) between two iterations. In this case, we have a combined optimisation/modelling problem. This can result in a circling around the minimum, which has been seen a number of times before by relax users. The protocol now detects this and terminates. However I don't think I've seen a problem which runs forever - that would just be theoretically weird. If none of this makes sense, you should have a read of my 2007 paper (http://www.nmr-relax.com/refs.html#dAuvergneGooley07). > Will the "final" run of relax still be able to see the final optimization > results? You can set a maximum number of iterations for this protocol. Otherwise when using the prompt/script modes you can kill relax, and restart it again (though this will result in a few extra rounds of optimisation of each global model before relax realises that convergence has occurred). Only after rerunning after killing will you have 'final' 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)? No, this is just the underlying and fixed assumption in all model-free analysis software. The reason is because what you measure is not the pure chemical exchange but a mix of a few different things. You don't need to worry about this. >> 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. You shouldn't need to warm up your experiment to the level of the R2 in this way. For one, this will not work because the time for a 1D is much, much longer in the R1 than in the R2. Therefore the real-time cooling from the VT unit will probably make these heating pulses irrelevant. Actually you could end up with a temperature gradient over the R1 evolution time - this would not be good. Note that for BMRB submission, this technique is not in the recommend list of options for temperature compensation. The best way to do this is to run the R1 experiment on a MeOH/ethylene glycol sample. Then calibrate the temperature as you would normally calibrate a spectrometer, just using shortened R1/R2/NOE pulse sequences. >> 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? True, but don't make the mistake of concluding that differentially weakened peaks is due to a slow process on the Rex timescale. > 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. It could be due to slow motions, but you will have to prove that ;) > 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 ;) S2 and Rex would be an important part of understanding what is happening. I would suggest the internal correlation times, as well as diffusion tensors, could also be quite interesting, if you see differences. Really any dynamical differences would be of interest. Relaxation dispersion may also give interesting information, but there is a chance that you will not see much. >>>> 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 For referencing files, it is best to create a relax support request for this and attach the files there (https://gna.org/support/?func=additem&group=relax). That way there will be a permanent, non-deletable copy that relax users can view in the future when reading the archives of these messages. Cheers. >> 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 Those are quite interesting plots. Though I'm not sure why m0 is selected so often. I've never seen such a phenomenon. >> 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. You can use Topspin to split up the file and create a set of 2D fids. These can then be used for processing in nmrPipe, if you like, and converted to Sparky format. >> 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. If you do single FID interleaving with temperature compensation blocks in the R2 pulse sequence, the data is usually good enough for a model-fre eanalysis.. > 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 ;) Well, I was a pure biochemist before I looked at performing a model-free analysis of a protein! So it's not impossible. Regards, Edward _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-users mailing list [email protected] To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-users
