Dear Pavel Thanks for the reply. I am trying to prove the presence of ligand as well as to 'push' some density for the weaker part of the ligand. (This relates to another thread I initiated.) In short density for first part of ligand is very good and can confidently be modelled but not the other part. I have tried Polder Map as well as the conventional SA-OMIT map. My feeling is that the conventional way gives better map for the ligand at the 'good' region than Polder, but neither way improves density at the 'poor' region. There seems less keywords to manipulate in Polder than in the conventional way though. Best regards Sam On 3 June 2017 at 21:44, Pavel Afonine wrote:

I'm not sure I understand the concept of individual selection when doing composite OMIT map. The whole purpose of composite OMIT map is to do iterative omits and then put the entire mosaic back into full map so that each region of the map is "omit". This way you are expecting to get a less biased map that this map also may appear of a lesser quality.

It depends what question you are trying to answer. If you the question is to prove the presence of a ligand then simply compute Polder map:

http://journals.iucr.org/d/issues/2017/02/00/ba5254/ba5254.pdf https://www.youtube.com/channel/UCcdI0hfHngWAZLJWynxPQWg/videos

Pavel

On 6/3/17 19:48, Sam Tang wrote:

Dear all

Sorry for a very basic question about generating an omit map.

I am trying to generate a SA-omit map for only my ligand but not the protein core of my complex. I presume I can use phenix.composite_omit_map GUI and specify my ligand chain in Atom Selection?

All other parameters being the same, I notice that when I did not select any atom the whole structure was divided to 30-40 regions but when I selected my ligand chain it now divides into 89 regions. Is there a reason why and is there any advantage to manually adjust the number of omit regions?

Many thanks and regards

Sam Biochemistry Programme, School of Life Sciences, CUHK

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Hi Pavel Thanks again for the advice. I have run Polder map on two of the nucleotides in doubt. The CC for one of them: N1:CC(1,2): 0.5610 CC(1,3): 0.6212 CC(2,3): 0.5193 Peak CC: CC(1,2): 0.5444 CC(1,3): 0.5798 CC(2,3): 0.4921 The embarrassing issue here is that these two nucleotides make complete sense biologically if they turn out to be flexible. Will the high B-factor hinders the calculation of CC in Polder map? Meanwhile, I notice there is a column labeled 'q' in the log output like the below q D(1,2) D(1,3) D(2,3) 0.10 0.4162 0.7689 0.6533 0.20 0.4748 0.6926 0.6796 0.30 0.5252 0.6516 0.6466 0.40 0.6243 0.6590 0.6937 0.50 0.6576 0.6160 0.7034 0.60 0.6851 0.5420 0.6807 0.70 0.7606 0.5029 0.6442 0.80 0.8422 0.4325 0.6959 0.90 0.9365 0.4567 0.7226 0.91 0.9783 0.4447 0.7750 0.92 0.9614 0.4666 0.7352 0.93 0.9591 0.4955 0.7513 0.94 0.9594 0.5258 0.8026 0.95 0.9639 0.5805 0.7558 0.96 1.0026 0.6504 0.8130 0.97 0.9655 0.6079 0.7867 0.98 1.0087 0.9025 0.8495 0.99 0.8934 0.9460 0.8934 Could you enlighten me as to the meaning of these or where I could go for relevant readings? Many thanks indeed. Kind regards Sam On 4 June 2017 at 11:23, Pavel Afonine wrote:

Hi Sam,

I have tried Polder Map as well as the conventional SA-OMIT map. My

...

feeling is that the conventional way gives better map for the ligand at the 'good' region than Polder, but neither way improves density at the 'poor' region.

I'd say it's more about getting convincing map rather than (artistically) looking better one. If three CC numbers that Polder map tool reports are in favor of the ligand then this is what you've got. By design, any sort of OMIT map is expected to appear worse than say usual 2mFo-DFc map (it is naive to expect that by removing bits of model you get a better looking map).

Both methods you quote are to show you the map, not to improve the model so that in turn you get an improved map.

Pavel