Hi Ed, Fine !
That'll give me time to think a bit more about all that... Cheers ! Séb :) Edward d'Auvergne wrote: > 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
