I see that Dale and I are in pretty well complete agreement on this
subject (even though I honestly hadn't read Dale's response when I sent
mine!) - I think we now have a definitive explanation, so hopefully this
will be the last time that this question comes up, or if not at least we
now have a useful thread that future queries on this subject can be
referred to!
I would like to make one further point, and in fact caution *against*
using Rfree directly as an indicator of the optimal weight as has been
suggested in the literature & elsewhere. I gave some reasons why Rfree
is not sufficiently accurate for this in my previous response: what
theory we have suggests strongly that the free log-likelihood gain
(LLGfree) is the correct statistic to use, and that the Rfree minimum
approximates the LLGfree maximum only poorly. My point is that not all
SF calculation programs even compute R factors using the same formula!
The 'conventional/textbook' definition of R (which I believe I'm correct
in saying is the way it's defined in Refmac) is R = Sum|Fo-Fc|/Sum(Fo)
where Fo and Fc are the observed & calculated structure amplitudes.
This is the form of R factor that is really appropriate only when
least-squares is the optimisation method. The program I used
(Buster-TNT) computes R factors using the phase-probability weighted F
('Fexpect') in place of Fc, which is the more appropriate form when
maximum likelihood optimisation is used, and means that this form of
Rfree gives a much better approximation of the LLGfree maximum (even
though it is still actually quite poor!).
Clearly the solution to all this is *not* to use Rfree at all for this
purpose and use LLGfree instead, which all ML-based programs can
actually easily calculate.
One last point: when this subject came up last, the issue of whether
it's valid at all to 'contaminate' the test set by using any kind of
'free' statistic in this way was raised. The answer is I think that
there is inevitably some contamination, but that it's insignificant.
The reason is that the number of weighting parameters determined in this
way (don't forget that the test set is also used to determine sigma-A
values), is very small compared with the number of variable parameters
in restrained refinement (i.e. typically 4 per atom), so that the
reduction in the number of degrees of freedom is insignificant. The
alternative of not using the test set in the calculation would
undoubtedly lead to even bigger errors.
Cheers
-- Ian
> -----Original Message-----
> From: CCP4 bulletin board [mailto:[EMAIL PROTECTED] On
> Behalf Of Dale Tronrud
> Sent: 04 April 2007 22:33
> To: CCP4BB@JISCMAIL.AC.UK
> Subject: Re: [ccp4bb] Summary - Valid to stop Refmac after
> TLS refinement?
>
> Bernhard Rupp wrote:
> >> People also felt that the RMSD bond/angle of 0.016/1.6 was
> still a little
> > high.
> >
> > This was subject of a discussion before on the board and I
> still don't
> > understand it:
> >
> > If I recall correctly, even in highly accurate and precise
> > small molecule structures, the rmsd of corresponding
> > bonds and angles are ~0.014A and 1.8deg.
> >
> > It always seems to me that getting these values much below
> is not a sign
> > of crystallographic prowess but over-restraining them?
> >
> > Is it just that - given good resolution in the first place
> - the balance
> > of restraints (matrix weight) vs low R (i.e., Xray data)
> gives the best
> > Rfree or lowest gap at (artificially?) lower rmsd?
> >
> > Is that then the best model?
> >
> > I understand that even thermal vibration accounts for about 1.7 deg
> > angle deviation - are lower rmsd deviations then a manifestation
> > of low temp? But that does not seem to be much of an effect, if
> > one looks at the tables from the CSD small mol data (shown in
> > nicely in comparison to the 91 Engh/Huber data in Tables F, pp385).
> >
> >
> This is an on-going topic of discussion so let me put in
> my two cents.
>
> We calculate libraries of "ideal geometry" based on precise, small
> molecule structures. When these small molecule crystal structures are
> compared to our derived libraries they are found to contain
> deviations.
> These deviations are larger than the uncertainty in these models and
> are presumed to reflect real features of the molecule; perturbations
> due to the local environment in the crystal.
>
> These same perturbations are present in our crystals and we should
> expect to find deviations from "ideal geometry" on the same scale as
> that seen in the precise models. This expectation lead to
> the practice
> in the 1980's of setting r.m.s. targets of 0.02A and 3 degrees for
> agreement to bond length and angle libraries.
>
> While this seems quite reasonable, we are left with the question:
> Are the deviations from "ideal geometry" we see in a particular model
> in any way related to the actual deviations of the molecule in the
> crystal? The uncertainties (su's) of the bond lengths in a
> model based
> on 4A diffraction data are huge compared to the absolute value of the
> true deviation. For example, if the model had a deviation from "ideal
> geometry" of 0.02A but the uncertainty of the distance is 0.2A can we
> say that we have detected a signal that is significantly
> different than
> zero, the null hypothesis?
>
> If we have a model with a collection of deviations from
> "ideal geometry"
> but we have no expectation that those deviations are indicative of the
> true deviations of the molecule in the crystal, are those deviations
> serving any purpose? If they do not reflect any property of
> the crystal
> they are noise and should be filtered out.
>
> By this argument a model based on 4A resolution
> diffraction data should
> have no deviation from "idea geometry" while one based on
> 0.9A diffraction
> data should have no restraints on "ideal geometry" since the
> deviations
> are probably all real and significant (except for specific regions of
> the molecule that have problems).
>
> The problem we all face is the vast area between these extremes,
> compounded by our inability to calculate proper uncertainties for the
> parameters of our models. The free R is our current
> tool-of-choice when
> it comes to attempting to judge the statistical significance
> of aspects
> of our model, without performing proper statistical tests
> which we don't
> know how to do. If we allow our model the freedom to deviate from our
> library and the free R improves a "significant" (??) amount then the
> resulting deviations must have some similarity to the true deviations
> in the crystal, but if the free R does not improve then the deviations
> must not be related to reality and should be suppressed. This is the
> type of assumption we make whenever we use the free R to make
> a choice.
>
> What we end of doing is not making a yes/no decision but
> instead we
> variably suppress the amplitude of the deviations from "idea geometry"
> and that is harder to justify. I think a reasonable argument can be
> made, but I have already written too many words in this
> letter. It doesn't
> really matter because we left the road of mathematical rigor
> when we took
> the R free path.
>
> Unfortunately, many people have ignored what Brunger said
> in Methods
> in Enzymology about choosing your X-ray/geometry weight based on the
> free R and just starting saying "the rms bond length deviation must
> be 0.007A". The deviations from "idea geometry" of your
> model should be
> no more or no less than what you can justifiably claim is a reflection
> of the true state of the molecule in your crystal.
>
> Dale Tronrud
>
>
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