Hi, The help wasn't a problem, and don't worry about the length of the message - the details will be very useful. Unfortunately you may need to wait a little while as I'll be taking holidays for a week or so, starting in 5 minutes time. I'll have to look at the details after that.
Regards, Edward On Fri, May 9, 2008 at 5:45 PM, Sébastien Morin <[EMAIL PROTECTED]> wrote: > Hi Ed, > > First, thanks a lot for this help ! > > Second, I have to apologize for the length of this mail... > > > Ok... > > > My system is a 271 residue globular protein (230 residues with data at 3 > fields = 2070 observables). An homologous protein is being studied in > the lab and analysing relaxation data using either the diffusion seeded > approach in ModelFree or the new protocol of the full_analysis script > yields similar results with a high mean S2 (~0.90) and a few Rex (15-20) > throughout the protein. Thus, the problem here with my system is > probably external to the approaches and the user... > > > Ok... > > > I tried using ModelFree with relax (script palmer.py : ModelFree as an > engine for optimization, but relax for automating and AIC model > selection) and got similar results than with the full_analysis.py > approach... For the two situations tested (see below), no oscillation > occured. Here are some stats : > > ======================================================================= > Approach Diff Iter Chi2 AIC Nb_Rex <Rex>_+-_StdDev > ============== ======= ==== ====== ====== ====== =============== > palmer prolate 15 ~12990 ~14060 182 1.602_+-_0.770 > > palmer_hybrid prolate 12 ~ 2715 ~ 3660 129 0.902_+-_0.571 > > full prolate 5 ~13090 ~14125 181 1.671_+-_0.782 > > full_hybrid prolate 7 ~ 2750 ~ 3720 145 2.431_+-_1.546 > ======================================================================= > > It seems that the new protocol is not the source of the problem. > Moreover, it is obvious from the AIC value (and also from the diffusion > tensor details, not shown here) that the hybrid (without the highly > flexible C-terminus) is a better description of the system. However, as > is seen here, the Rex values seem quite small and there are way too much > Rex (> 50 % of all residues)... These may thus be non significative, but > then, how can one exclude such "artifacts" when doing iterative > optimization (with either approach)..? How can one decide to choose > another model than with Rex when iterating to find the best diffusion > tensor..? > > > Ok... > > > Maybe, as you proposed, the problem arises because of the crystal > structure being inappropriate for describing the solution structure... > The crystal structure I use has a resolution of 1.95 A. Protons were not > visible but were added using CHARMM. Moreover, different snapshots from > molecular mechanics in CHARMM were also tested to see if fluctuations in > NH bond orientation could yield better optimizations... It was not the case. > > I'll try to assess this issue of the crystal structure by running tests > (with palmer.py and also full_analysis.py approaches) using a different > structure (a ponctual mutant) also from crystallography... The > resolution of this structure is also quite low (1.75 A). Anyway, I don't > have choice since no solution structure exists, neither better crystal > structures... If ever the crystal structure is the cause of this > problem, what can one do ? Is one obliged to do his analysis with a > local_tm or a sphere diffusion tensor ? Is it a waste if on does so with > good quality data at three fields ??? > > > Ok... > > > What about the AIC for the local_tm model VS the ellipsoid in the > full_analysis approach ? Here are some stats : > > ======================================================================= > Approach Models Diff AIC > =========== ====== ========= ====== > full m1-m5 local_tm ~ 4510 > full m1-m5 ellipsoid ~12710 > > full m0-m9 local_tm ~ 4410 > full m0-m9 ellipsoid ~ 5210 > > full_hybrid m1-m5 local_tm ~ 4510 > full_hybrid m1-m5 ellipsoid ~ 4720 * > > full_hybrid m0-m9 local_tm ~ 4410 > full_hybrid m0-m9 ellipsoid ~ 4570 ** > ======================================================================= > * not converged after 35 rounds (oscillates) > ** not converged after 26 rounds (oscillates) > > As said before, the hybrid improves the description of the diffusion, > however, there is still a problem : first, the local_tm diffusion is > still selected over the ellipsoid (even if the difference is now > smaller), second, the ellipsoid optimizations don't converge and > oscillate... > > Now, what about the Rex and slow motions (ts) in the local_tm diffusion > ? Here are some stats : > > ======================================================================= > Approach Models Diff Nb_Rex Nb_ts > =========== ====== ========= ====== ===== > full m1-m5 local_tm 58 30 > full m1-m5 ellipsoid 171 21 > > full m0-m9 local_tm 63 41 > full m0-m9 ellipsoid 144 49 > > full_hybrid m1-m5 local_tm 58 30 > full_hybrid m1-m5 ellipsoid 142 * 28 > > full_hybrid m0-m9 local_tm 64 41 > full_hybrid m0-m9 ellipsoid 145 ** 50 > ======================================================================= > * not converged after 35 rounds (oscillates) > ** not converged after 26 rounds (oscillates) > > As you can see, there are way more Rex in the ellipsoid, which probably > means that there is a problem with the diffusion tensor... For the slow > ns motions, there doesn't seem to be significantly more in the ellipsoid > description... Moreover, the sphere diffusion tensor which is not > NH-vector-orientation-dependent, also as a high degree of Rex, similar > ns motions and AIC values similar (just a bit higher) to what is > observed for the ellipsoid : > > ======================================================================= > Approach Models Diff Nb_Rex Nb_ts AIC > =========== ====== ========= ====== ===== ====== > full m1-m5 sphere 191 20 ~15200 > > full m0-m9 sphere 155 47 ~ 5640 > > full_hybrid m1-m5 sphere 145 31 ~ 5190 > > full_hybrid m0-m9 sphere 153 47 ~ 5030 > ======================================================================= > > Should the sphere diffusion tensor yield similar results as the local_tm > ? If there is a major difference between those two, does it mean that > concerted motions may be present and that an hybrid model could solve > the issue ? > > > Ok... > > > Now, are there concerted motions apparent from the local_tm results..? I > plotted the results from the local_tm run after aic model selection > (Would it be better if I'd look at the local_tm run for model 1 or 2 > only ? Can model selection here bias the results ?) and couldn't find > any obvious link between different parts of the protein for one or more > parameters among S2, S2f, S2s, Rex, te, tf, ts, chi2. > > However, a small relation seems to exist for the local_tm distribution > and the domain (The inverse is seen for the S2, but to a lesser extent. > When looking at the tm1 run, the local_tm is also a bit smaller in the > same domain [a small difference of 0.5-1.0 ns for values of ~13 ns], but > the S2 are similar, which points to a difference for the two domains). > > My protein is globular, but has two structural domains side by side, an > all alpha domain and an alpha/beta domain. In the homologous protein, > there seems to exist Rex at the interface (which spans a surface of four > 10 residue beta strands, which is big and is expected to be quite > rigid). Maybe the two domains are a bit different in my system which > could cause the problems I encounter. I'll try to assess this by running > full_analysis runs on the different domains alone... > > > Ok... > > > Well, I'm out of idea now... If you have any idea that could help, these > will be more than welcome ! > > I hope this discussion can also help other people solving difficulties > encountered in their analysis or help them get more information out of > their system... > > Thanks a lot once more ! > > Cheers ! > > > > Sébastien > > > P.S. Again, sorry for the length of the mail... > > > > > > > > > > > > Edward d'Auvergne wrote: >> Hi, >> >> I've been thinking about this one for a while, but I don't know >> exactly what the problem is. I have a few ideas that may help though. >> This could either be some type of interesting dynamics, or be caused >> by something a bit more sobering. >> >> Firstly though, it is worth comparing the local tm model to the best >> of the global diffusion tensor models (the ellipsoid). It could be >> that if the AIC values are similar, then the local tm model and the >> global diffusion model are statistically similar and that it would be >> safe to go with either. In this case, it is worth very carefully >> comparing the description of the internal dynamics. For this, do not >> compare selected models - that is not what is of interest. It should >> be the overall picture of the dynamics reported by the parameters. >> For example if Rex is statistically close to zero then, from the >> perspective of the internal motions, models m2 and m4 are the same. >> >> Assuming that the local tm global model is significantly better than >> the other models, another option could be that you have very >> interesting global concerted dynamics occurring in the molecule. This >> would mean that the standard single global diffusion model (sphere, >> spheroid, or ellipsoid) is insufficient to describe these motions. >> This is what the hybrid models in relax were designed for, but maybe >> these don't describe certain large scale motions well enough (hence >> your use of these didn't resolve the problem). These aren't a proper >> mathematical solution to the complex physics of coupled diffusion >> processes and hence may be insufficient. >> >> It might be worth trying the normal model-free analysis of starting >> with the diffusion tensor, rather than my new technique which starts >> with the internal dynamics, to see if you end up with a different >> result. It could be that the new technique in the full_analysis.py >> script is somehow failing, although I doubt that will be the case. >> The oscillation you see in point 3 is found by using Art Palmer's >> Modelfree program as well with a standard analysis - this was one of >> the motivators for me to start looking into and fixing problems with >> model-free analysis - but it is inherent to the iterative procedure >> required for convergence. Have you tried the analysis with Modelfree >> or Dasha? And if so, how do the chi-squared and AIC values compare? >> >> Alternatively, the reason could be quite simple. It could possibly be >> that the structure you have used in the analysis is not accurate >> enough. If it is a crystal structure, maybe it doesn't represent the >> solution structure well. The analysis is highly dependent upon the XH >> bond vector orientations, and if this is slightly out it could cause a >> bias and the introduction of artificial motions (either Rex or >> nanosecond motions). It will also affect the determination of the >> diffusion tensor. These artificial motions are unlikely to be present >> in the local tm model though, so this is a good check. >> >> The Rex in the ellipsoid model is an indication that something could >> be wrong with the global model. Whether it is interesting large scale >> motions which are insufficiently described by the ellipsoid, whether >> the technique cannot find the real solution, or whether this is caused >> by structural inaccuracies, that I cannot tell. Is the structure of >> the protein released? What is the system which is being studied? >> What are the AIC values like for each global model? Anyway, hopefully >> one of these ideas may be of help in sorting out the problem. >> >> Regards, >> >> Edward >> >> >> >> >> >> On Mon, May 5, 2008 at 9:23 PM, Sébastien Morin >> <[EMAIL PROTECTED]> wrote: >> >>> Hi, >>> >>> I am currently using relax with the full_analysis.py script. >>> >>> I face several problems for which I can't find any solution... >>> >>> 1. >>> With all my data (230 residues at 3 fields, for a total of 2070 >>> observables), the best diffusion model is the local tm. This is not >>> normal as this protein is globular. Hence, the C-terminus residues have >>> really high chi2 values... Thus, when excluding the C-terminus, the best >>> diffusion model is still the local tm. Maybe some other residues are >>> highly flexible and should be rejected... Maybe also some residues have >>> bad data... What is a good strategy to find residues I should exclude >>> from my analysis ? >>> >>> >>> 2. >>> When I look at optimized results from the ellipsoid runs (second best >>> choice after local tm), I see lots (~ 50 % residues) of Rex, which is a >>> bit anoying... The diffusion tensor may not be well optimized... This >>> may be related to problem 1... >>> >>> >>> 3. >>> In different situations, some runs (prolate or ellipsoid, i.e. the >>> diffusion tensor that should best describe my system) never converge and >>> oscillate between 2 or more AIC values. Some residues oscillate between >>> 2 or more models, but these residues are not special as to their >>> relaxation data or position in the protein... >>> >>> >>> Consistency testing and reduced spectral density mapping show that my >>> data are of good quality and are consistent with each other... >>> >>> I tried with different structures (crystal structure with added protons, >>> MM snapshots), but always got the same kind of results... >>> >>> I tried several hybrids (with no C-ter, with no C-ter and several loops, >>> etc), but always got the same kind of results... >>> >>> Also, chi2 values are quite high for most residues (5-20 on average)... >>> >>> What should I do now ? Do you have any idea ? >>> >>> Thanks a lot for any help or idea !!!!!!! >>> >>> >>> Exhausted Séb >>> >>> _______________________________________________ >>> relax (http://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 >>> >>> >> >> > > _______________________________________________ relax (http://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
