Hi Tom,
Thank you so much for the feedback.
By “cutting the resolution” does that mean that I should put a smaller or higher number for the density modification resolution? I guess I should try both lower and higher...
The solvent content using default settings is very high, more than 97%. My guess is that this is because there is a lot of nucleic acid and perhaps the density is being more localized (e.g. to the phosphate groups) than what is normal for proteins. I tried to force a lower solvent content, such as 90%, but that did not change the R-value. I will try with model-based density modification and see if that helps.
Regards,Daniel
On 8 Jun 2022, at 21:39, Tom Terwilliger <tterwilliger@newmexicoconsortium.org> wrote:
Hi Daniel,
We don't have a standard way to interpret the R value for density modification...hence the rough guide of "0.25 is good and 0.5 is poor" but no documentation. This applies to both X-ray and cryoEM density modification.
This R value describes the mismatch between measured and map-based structure factor amplitudes. Usually these match pretty well in cases where the map is improved a lot and not when the map does not improve, but there is no obvious and simple relationship.
My recommendation would be to use the estimate of map resolution and visual quality as your guide as to whether it has improved your map, and the R value in density modification as a possible indication that some change of parameters might help if things are not going well (not that it tells you what to change, but a good one is always resolution and another is solvent content.)
In your case I might try cutting the resolution or randomly changing solvent content and testing...but as the map looks ok I would not try too hard.
I hope that helps!All the best,Tom T--
On Wed, Jun 8, 2022 at 14:25 Daniel Larsson <daniel.larsson@icm.uu.se> wrote:
Hi all,
I tried to do density modification using the resolve_cryo_em tool. The resolution improves quite a lot from around 2.60 to around 2.35 and the density looks significantly better than the autorefined original map. However, the R-values is close to 0.5, which seems very high. How should the R-value generated by this tool be interpreted? It is very poorly documented and not mentioned in the paper or on the manual page, but Tom Terwilliger mentioned in a workshop that “low number is good” and “point two-four is a very good number, point five is not a good number”, which makes me worried.
Regards,
Daniel
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Thomas C TerwilligerLaboratory Fellow, Los Alamos National LaboratorySenior Scientist, New Mexico Consortium100 Entrada Dr, Los Alamos, NM 87544Tel: 505-431-0010