[phenixbb] geometry_minimization makes molprobity score worse

Nigel Moriarty nwmoriarty at lbl.gov
Thu Jul 8 11:16:52 PDT 2021


James

This is very interesting from a different perspective but I should point
out a few things.

1. The CDL, which is the default, changes the backbone bonds and angles
based on phi/psi. Maybe in geometry minimisation this is causing the
"whirlygig." Can you check with cdl=False?

2. In a recent pub

   1. Sobolev OV, Afonine PV, Moriarty NW, Hekkelman ML, Joosten RP,
   Perrakis A, Adams PD: *A Global Ramachandran Score Identifies Protein
   Structures with Unlikely Stereochemistry.* *Structure* 2020, *28*
   :1249-1258.e2. <http://dx.doi.org/10.1016/j.str.2020.08.005> [PMID:
   32857966] [PMCID: PMC7642142]

we argue that percent favoured is not an accurate measure of Rama health.
Could also provide these numbers?

Cheers

Nigel

---
Nigel W. Moriarty
Building 33R0349, Molecular Biophysics and Integrated Bioimaging
Lawrence Berkeley National Laboratory
Berkeley, CA 94720-8235
Phone : 510-486-5709     Email : NWMoriarty at LBL.gov
Fax   : 510-486-5909      Web  : CCI.LBL.gov
ORCID : orcid.org/0000-0001-8857-9464


On Thu, Jul 8, 2021 at 10:28 AM James Holton <jmholton at lbl.gov> wrote:

> 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
> below.
>
> 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?
>
> -James
>
>
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