[phenixbb] geometry_minimization makes molprobity score worse

James Holton jmholton at lbl.gov
Thu Jul 8 10:24:10 PDT 2021

Thank you Pavel for your prompt response!

I agree with everything you wrote below, and that is a good point about 
2nd derivatives.

However, what I'm seeing is the opposite of what you might predict. See 

On 7/7/2021 11:27 PM, Pavel Afonine wrote:
> Hi James,
> thanks for email and sharing your observations!
>> Greetings all, and I hope this little observation helps improve 
>> things somehow.
>> I did not expect this result, but there it is. My MolProbity score 
>> goes from 0.7 to 1.9 after a run of phenix.geometry_minimization
>> I started with an AMBER-minimized model (based on 1aho), and that got 
>> me my best MolProbity score so far (0.7). But, even with hydrogens 
>> and waters removed the geometry_minimization run increases the 
>> clashscore from 0 to 3.1 and Ramachandran favored drops from 98% to 
>> 88% with one residue reaching the outlier level.
> It is not a secret that 'standard geometry restraints' used in Phenix 
> and alike (read Refmac, etc) are very simplistic. They are not aware 
> of main chain preferential conformations (Ramachandran plot), 
> favorable side chain rotamer conformations. They don't even have any 
> electrostatic/attraction terms -- only anti-bumping repulsion! 
> Standard geometry restraints won't like any NCI (non-covalent 
> interaction) and likely will make interacting atoms break apart rather 
> than stay close together interacting.

Yes, there's the rub: I'm not seeing "interacting atoms break apart", 
but rather they are being smashed together.  Torsion angles are also 
being twisted out of allowed regions of the Ramachandran plot.

All this with the x-ray term turned off!

> With this in mind any high quality (high-resolution) atomic model or 
> the one optimized using sufficiently high-level QM is going to have a 
> more realistic geometry than the result of geometry regularization 
> against very simplistic restraints target. An example:
> https://journals.iucr.org/d/issues/2020/12/00/lp5048/lp5048.pdf
> and previous papers on the topic.

I agree, but what doesn't make sense to me is how the "simplistic 
restraints" of phenix.geometry_minimization would be so inconsistent 
with the "simplistic restraints" in phenix.molprobity ?

What I am doing here is starting with an energy-minimized model of a 1.0 
A structure (1aho). It's not a fancy QM, just the ff14SB potential in 
AMBER.  I get my best molprobity scores this way, but I need an x-ray 
refinement program like phenix.refine to compare these models with 
reality.  It troubles me that the "geometry" in the x-ray refinement 
program all by itself messes up my molprobity score.

>> Just for comparison, with refmac5 in "refi type ideal" mode I see the 
>> MolProbity rise to 1.13, but Clashscore remains zero, some Ramas go 
>> from favored to allowed, but none rise to the level of outliers.
> I believe this is because of the nature of minimizer used. Refmac uses 
> 2nd derivative based one, which in a nutshell means it can move the 
> model much less (just a bit in vicinity of a local minimum) than any 
> program that uses gradients only (like Phenix).
good point.

So, what should I do to stabilize phenix.geometry_minimization? Crank up 
the non-bonded weight?  Restrain to starting coordinates?

>> Files and logs here:
>> https://bl831.als.lbl.gov/~jamesh/bugreports/phenixmin_070721.tgz
>> I suspect this might have something to do with library values for 
>> main-chain bonds and angles?  They do seem to vary between programs. 
>> Phenix having the shortest CA-CA distance by up to 0.08 A. After 
>> running thorough minimization on a poly-A peptide I get:
>> bond   amber   refmac  phenix  shelxl Stryer
>>  C-N   1.330   1.339   1.331   1.325     1.32
>>  N-CA  1.462   1.482   1.455   1.454     1.47
>> CA-C   1.542   1.534   1.521   1.546     1.53
>> CA-CA  3.862   3.874 *3.794* 3.854
>> So, which one is "right" ?
> I'd say they are all the same, within their 'sigmas' which are from 
> memory about 0.02A:
I note that 3.874 - 3.794 = 0.08 > 0.02

This brings me to my pet theory.  I think what is going on is small 
errors like this build up a considerable amount of tension in the long 
main chain. For this 64-mer, the contour length of the main chain after 
idealization is ~5 A shorter after phenix.geometry_minimization than it 
is after shelxl or amber.  That 5 A has to come from somewhere.  Without 
stretching bonds or bending angles the only thing left to do is twisting 
torsions. A kind of "whirlygig" effect.

The question is: is the phenix CA-CA distance too short?  Or is the 
amber CA-CA distance too long?

Shall we vote?


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