Hi, If the zip file is ok, then you won't need MS Visual C++ (at any version). This is only needed to compile the small C modules in relax which perform relaxation curve-fitting. You'll only need to do that if you decide to improve the analysis and develop code for relax yourself. And for that, the full MS Windows development environment is recommended (http://www.nmr-relax.com/windows_devel.html). You will, however, require all of the obligatory relax dependencies to be installed.
Regards, Edward On 28 February 2012 10:38, James Nyirenda <[email protected]> wrote: > The current zip file opens and extracts perfectly ok. For those using > windows 7, probably no need of installing MS visual c++ 2005 exp edition > due to compatibility issues. I will equally try in windows xp and come back > on the forum asap. > > ________________________________ > From: Edward d'Auvergne <[email protected]> > To: Hugh RW Dannatt <[email protected]> > Cc: [email protected] > Sent: Tuesday, 28 February 2012, 5:50 > > Subject: Re: Anisotropic Diffusion coefficients > > Hi Hugh, > > I'll answer below: > > >> This has given me more interpretable numbers. From reading all the >> previous correspondance (some of which has touched upon this issue), I >> still remain a little concerned as to the dependence of the results on >> the input .pdb file. I am almost certainly being overly cautious but >> as this is probably a common concern it'd be nice to hear your >> thoughts. > > This is an issue which I don't think anyone has studied in depth and > comprehensively before. It's also difficult to study as structural > issues are likely to be a bias (directional randomness) rather than a > variance (pure randomisation). For example a whole structural element > could be reoriented. Or there could be domain motions which are not > taken into account in the current level of theory. There is a lot of > potential to develop this area of analysis in the future ;) > > >> The Dratio that has resulted from the fitting of my apo protein is >> 1.55, as compared to that predicted by HydroNMR (1.75). For HydroNMR >> to overestimate values by this much is not itself a surprise or >> concern, but it is striking that the predicted Dratio for the closed >> complex is closer (1.43). I should emphasize that this is 2-domain >> protein with 2 "hinge" regions - one of which is mobile on the ms-us >> timescale and thus not amenable to study, and the other has fitted Rex >> terms. Infact about a third of the residues studied have fit Rex terms >> in the chosen ellipsoid model. On face value this is not actually a >> surprise seeing as various parts of the protein are flexible on the >> ms-us timescale as evidenced by line-broadening. > > HydroNMR, from what I've heard, is terrible at prediction when there > are domain motions. The program is also not very good at predicting > the behaviour of proteins at the concentrations you have in the NMR > tube. It is designed for prediction of the diffusion tensor of an > isolated molecule, but your molecules are very close together in the > NMR tube and this has significant consequences. > > The lower Dratio is understandable as you have domain motions and the > core is only partly affected by the other domain. Did you perform an > analysis with the two domains separately? For example as in my > analysis at > http://www.sciencedirect.com/science/article/pii/S0022283607007073 > for the DsbA oxidoreductase. > > >> It is possible that flexibility of the hinge regions is causing >> fluctuations in not only the principle diffusion tensor, but also the >> amide bond vectors relative to it. How could one ever test for this? >> Obviously the long-winded way is to fit the data with the closed >> complex coords and see if the X2 value is lower. But is there >> something more sophistocated and quick? > > You could treat each domain in a separate model-free analysis. But > model-free analysis assumes a static, perfectly averaged structure as > the backbone of the analysis. If you do not have this, i.e. there are > internal reorientations caused by the domain motions, you then have to > rely on the local tm models. Though these models can easily absorb > and hide motions if you have data at only 1 or 2 fields. Or > alternatively you could consider developing a theory or method of > analysis to handle this situation. > > >> I have looked at residues with fitted Rex terms in the spherical model >> which are absent in the ellipsoid model, and also residues with ns Ts >> terms in the spherical model which are absent in the ellipsoid. Both >> of these have VERY strong dependence on bond vector relative to the >> principle diffusion axis, which was unsurprising based on what you >> have said elsewhere. Encouragingly this relationship is not so strong >> if you compare to the bond vectors taken from the closed structure. On >> the other hand, the local_tm model fit very few Rex terms which is a >> little concerning. I have looked if the residues with fit Rex terms in >> the ellipsoid model but not in the local_tm model have a bond vector >> dependence, which they don't. Are there any other consistency tests >> you would recommend? > > If there are Rex terms in the spherical model but not in the > ellipsoid, then these are almost guaranteed to be false motions (as > described by Tjandra et al, 1995). The additional ns terms are also > likely to be fake as described by Schurr 1994. Note that the local_tm > models could sometimes absorb the Rex values into the local tm value > as the data for these residues is usually very noisy. The only real > way to determine if the Rex terms are real would be to perform some > relaxation dispersion measurements, although that is not always > conclusive. Data at 3 field strengths is also very powerful for > determining if the Rex values are real. You must also remember that > we assume that Rex in a model-free analysis is in the fast exchange > limit, which is not always the case, and the only way to differentiate > between quadratic fast exchange and linear slow exchange (and > everything inbetween) would be to have 3 or more field strength data. > Or, of course, relaxation dispersion data. I hope this helps. > > Regards, > > Edward > > _______________________________________________ > 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
