Hi Pavel: Never mind. The data.mtz is missing about 10% reflections, without which the Fc map (by model_vs_data --map=fc) looks weird (showing some big density like heavy metal not in the model). Thats why I wondered whether model_vs_data --map=fc involved something else. Just curious, why missing 10% reflections generated "heavy-metal" like density in solvent region? And in this case, is that more reasonable to manally adding the missing reflection by setting Fo=Fc? Best Regards, Hailiang

Hi Pavel:

Just want to make sure, by doing:

********* phenix.model_vs_data model.pdb data.mtz --map=fc *********

will 0Fobs+Fmodel/P0Fobs+Fmodel in the output mtz file (fo_0Fobs+Fmodel_map_coeffs.mtz) be the calculated results from model.pdb, which is independent (eg NO sigmaa weighting) from the experemental Fo in data.mtz?

Thanks!

Best Regards, Hailiang

...

Hi Hailiang,

...

I want to calculate Fc based on the PDB file and reproduce the R factor in it.

then phenix.model_vs_data is the right tool to accomplish this.

...

I first tried phenix.model_vs_data. It optimized ksol bsol and b_cart, and the output R factor (0.2143) is close enough to that in PDB (0.215).

The difference between the R-factors is very small. See

J. Appl. Cryst. (2010). 43, 669-676. phenix.model_vs_data: a high-level tool for the calculation of crystallographic model and data statistics P. V. Afonine, R. W. Grosse-Kunstleve, V. B. Chen, J. J. Headd, N. W. Moriarty, J. S. Richardson, D. C. Richardson, A. Urzhumtsev, P. H. Zwart and P. D. Adams

for explanations of possible differences between published and re-computed R-factors.

...

However, it didn't generate mtz files containing the calculated Fc.

Yes, it's not supped to do that. Actually, phenix.model_vs_data can output the map defined as:

[p][m]Fo+[q][D]Fc[kick][filled].

Examples: 2mFo-DFc, 3.2Fo-2.3Fc, Fc, anom, fo-fc_kick.

So, if you say

phenix.model_vs_data model.pdb data.mtz --map=fc

you will get an MTZ file with desired structure factors. So, yes, you can get what you want out of phenix.model_vs_data !

...

Then, I take the optimized ksol bsol and b_cart as the input and tried phenix.fmodel.

This should (to some accuracy) reproduce the R-factor reported by phenix.model_vs_data.

...

I wrote my own code to calcuate the R factor. However, I got a lower R factor (0.2078).

Any bugs ?

...

I think the reason might be my R calculation formula (sigma(fo-fc)/sigma(fo)) is wrong; or model_vs_data did more than just did flat solvent correction and anisotropic scaling.

Yup, you are missing the scale factor (unless you applied it to your fc already). See previous email for details - the script there shows the R-factor formula.

Good luck! Pavel.

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Hi Hailiang,

Just want to make sure, by doing:

********* phenix.model_vs_data model.pdb data.mtz --map=fc *********

will 0Fobs+Fmodel/P0Fobs+Fmodel in the output mtz file (fo_0Fobs+Fmodel_map_coeffs.mtz) be the calculated results from model.pdb, which is independent (eg NO sigmaa weighting) from the experemental Fo in data.mtz?

yes, this is correct. The equivalent command would also be: phenix.fmodel model.pdb data.mtz Pavel.

Hi Hailiang,

It is basically same as mine, so I think the reason for the R-factor discrepancy should be that I can't simply read in ksol/bsol/b_cart from model_vs_data output

The values may be slightly different since model_vs_data may remove some bad Fobs outliers, and the numerical precision for k_sol, B_sol and B_cart may not be good enough to reproduce the R-factor exactly. Here is the example that illustrates this: http://cci.lbl.gov/~afonine/model_vs_data_and_fmodel/ To run: phenix.python run.py

Then, do you think phenix cand o the similar thing as model_vs_data (hope can be somehow faster:), but generate Fc-containing mtz file?

This is exactly what I described in my previous email: use "--map" option. Pavel.