Dear Edward,
Sorry for the confusion. I tried to compare the results obtained from
Modelfree4
and relax using the isotropic model (since I cannot get Modelfree4 works on
axial symetric model at moment). 't-rex-sim.agr' corresponds to results from
Modelfree4 and 't-rex-relax.agr' corresponds to the results from relax. Using
Modelfree4 there are more residues fitted to M5 where using relax, more
residues were fitted by M2 and M4, I supposed that is due to different
criteria
on model selections. However, one thing I don't understand is that te
extracted
from M2 and M4 should be on a scale of several hundreds ps (fast) instead of
several thousands ps (slow). In this regards, Modelfree4 is more resonable and
there seems some problem in terms of model elimination and model selection for
the Relax.
Best wishes,
Hongyan
Quoting Edward d'Auvergne <edward.dauvergne@xxxxxxxxx>:
Hi,
Sorry, I'm not exactly sure what the graphs correspond to. Is
't-rex-sim.agr' Modelfree4 using the prolate (or oblate) spheroid
(this is axially symmetric anisotropic Brownian rotational diffusion)?
And is 't-rex-relax.agr' the results from relax using the spheroid
tensor? Have you used constraints on Da in relax to isolate the
oblate and prolate spheroids? Also how many iterations of the
model-free optimisation; model elimination; model selection; and
global minimisation (the optimisation of the model-free parameters of
all spin systems together with the diffusion parameters) have you
used? What is the input data and do you have data at more that one
field strength?
I'll try to answer some of your questions, but without more
information these may not be the answers you are after. The first
thing which is a little worrying is that in 't-rex-sim.agr' there are
many ts values between 6 to 8 nanoseconds. Unless you are working
with an unfolded protein or a system that is far from globular, this
is a very strong indication that the diffusion tensor is significantly
underestimated. How did you determine the initial diffusion tensor in
the analyses? Did you use the full_analysis.py script when using
relax (which requires data at minimally 2 field strengths)? The
errors on the Modelfree ts results are also worrying. This, to me,
looks like that there has been failures in the MC simulations causing
very similar errors on all the high ts values. Did you use an upper
limit of 10 ns in Modelfree?
Another worry is that you obtained similar results from relax using
the spherical and spheroidal diffusion! How many iterations of
model-free analysis did you use? And how did you determine the
initial diffusion tensor? As for the te values in the nanosecond
range, this is perfectly normal. This is modelling slow internal
motions. Model m5 was designed for this purpose, but if the fast
internal motion is close to insignificant due to experimental noise,
then model m2 is perfectly capable in modelling the slow motion. Also
if you set the range of the y-axis in all the correlation time graphs
from 0 to 10 ns, then you can see that the results from Modelfree4 are
more worrying. For the correlation time results, it is better to make
two graphs - one for fast motions up to 200 or so picoseconds and one
for slow motions from 200 ps up. Don't forget that what you are doing
is modelling. The models don't care what the underlying true dynamics
are - they will model that motion as best as they can. So classifying
the dynamics based on which model is selected is at best distracting
or at worst misleading. It's the results that matter, not the model.
I hope this answers some of your questions.
Regards,
Edward
Re: relax and modelfree