Hi Romel, The nanosecond motions you are seeing are interesting. Whether or not they are real is a valid question. However like most NMR spectroscopists, you are completely wrong in your assumption ;) You just need to carefully read the second of the Lipari and Szabo papers, something many people do not do, wherein they check the validity of internal motions slower than the global tumbling of the molecule. You can also perform your own tests by setting up synthetic models in relax - just load a PDB file, set a diffusion tensor to the values you like, set the internal model-free parameters, and then back calculate the relaxation data. Then perform a simple single model model-free fit and see what happens. I.e. what they do in the second Lipari and Szabo paper (well, without relax). You will see that with no experimental noise, you can easily extract internal motions slower than the global correlation time. Think of it as follows: After one time period of the global tumbling tau_m, the exponential total correlation function has not hit zero! It takes a few periods of tau_m before statistical zero is reached. Therefore other exponential functions can be present in the auto-correlation function. In the case of ellipsoidal diffusion, there are 5 exponential functions mixed in together. So why can, for example, the isotropic diffusion with a single exponential not be mixed in with another exponential coming from the internal motions rather than the global tumbling process? The answer, which is present in the original Lipari and Szabo papers, is that it most definitely can. The problem of parameter extraction is experimental, not theoretical! As soon as you add noise to the synthetic relaxation data, it becomes harder and harder to extract the slow internal motions reliably. Monte Carlo simulations can show this too. Again this can be tested by adding white noise to the back calculated relaxation data. I highly recommend you perform these tests yourself so that you get a good idea of what you can obtain - it will help you understand your system better. You can even use your protein system for the synthetic data tests. Note that if the two correlation times are identical, you will have problems. Just test yourself and see what happens! By learning from these tests, you will be able to formulate much stronger conclusions from your experimental results. As for your experimental data, another check would be to see if these motions are present in the local tm models. I think I discussed this in my second 2008 paper (http://www.nmr-relax.com/refs.html#dAuvergneGooley08b or http://dx.doi.org/10.1007/s10858-007-9213-3). You also have to carefully think if a single diffusion tensor is valid for the entirety of your system, an assumption which may not hold. One question I have though is how did you change the model selection protocol in the dauvergne_protocol.py auto-analysis? This is hardcoded into relax, and the use of both AICc and BIC is invalid for the searching of the universal solution (see http://thread.gmane.org/gmane.science.nmr.relax.user/1356/focus=1357 and my 2007 paper at http://www.nmr-relax.com/refs.html#dAuvergneGooley07 or http://dx.doi.org/10.1039/b702202f). You can only use model selection techniques where the fundamental derivation is based on the Kullback-Leibler discrepancy (http://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence) or the Fisher information metric. AIC and ICOMP model selection are suitable, for example, but AICc and BIC are not as the first is a deliberate divergence from the KL discrepancy and the second arises from quite different Bayesian assumptions. To use AICc or BIC, the universal solution equation of my 2007 paper would need to be reformulated to match the very different fundamental concepts behind these techniques and the model-free protocol redesigned to fit. Regards, Edward P. S. Because of the number of bugfixes since relax 2.0.0, I would recommend updating to relax 2.1.2 (http://marc.info/?l=relax-announce&m=135070664825024). On 11 December 2012 10:28, Romel Bobby <rbob002@xxxxxxxxxxxxxxxxx> wrote:
Dear Ed and relax users, I have recently used relax (ver 2.0.0) to obtain the model-free dynamics of a small protein with a molecular mass of 6 kDa. In fact, it's a protein in complex with a small peptide, but only the protein is 15N isotope labelled. R1, R2 experiments were recorded at 600, 800 and 900 MHz, and the steady-state NOE at 800 and 900 MHz. Temperature calibration was performed before running the experiments for all the fields. I used the fully automated analysis (dauvergne_protocol.py) and that went well. At the end of the run, the selected diffusion tensor had the form of an oblate spheroid with a global rotational correlation time of 3.2 ns. Now, I have observed that some residues display slow internal correlation times (ts) that are in the range of 1-4 ns. Considering the tm is only 3.2 ns, this would mean, that motions slower than the overall tumbling were captured. However, my understanding is and please correct me if I'm wrong, that except for Rex contributions, relaxation measurements are insensitive to motions on a time scale equal to or slower than the overall tumbling. I'm a bit puzzled about the validity of these motions, that is to say, are they physically meaningful? Is it possible that some of the motional models were not adequately fit and poorly chosen? Also, I've used the AICc selection method to reduce the probability of overfitting. Cheers, Romel Bobby Biomolecular NMR Research Group School of Chemical Sciences/School of Biological Sciences The University of Auckland +64 (09) 3737599 Ext 83157 _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-users mailing list relax-users@xxxxxxx 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