Hi Conor,
If you wanted to play with parameters, you can consider trying CHAPI -
Coot Headless API. There is an example regarding the water addition in
the documentation:
https://www.mrc-lmb.cam.ac.uk/lucrezia/libcootapi-documentation/read_coordinates.html#adding-water-molecules
Cheers,
Martin
On 25/11/2025 17:26, Paul Bond wrote:
There is also a standalone findwaters executable from Coot if you
prefer a command line tool to using the library:
> findwaters
Usage: findwaters --pdbin pdb-in-filename --hklin mtz-filename --f
f_col_label --phi phi_col_label --pdbout waters-filename --cifout
waters-filename --sigma sigma-level --min-dist min-dist-to-protein
--max-dist max-dist-to-protein --flood --flood-atom-radius --chop
--mapin ccp4-map-name can be used instead of --hklin --f --phi
where pdbin is the protein (typically)
and pdbout is file for the waters.
The default sigma level is 2.0
Use --chop to remove waters below given sigma-level
In this case, pdbout is the modified input coordinates
Use --flood to fill everything with waters (not just water peaks)
and --flood-atom-radius to adjust contact distance
(default 1.4A).
On Tue, 25 Nov 2025 at 17:19, Martin Noble
<[email protected]> wrote:
Coot and the gui free library versions thereof can provide a very
long list of candidate water positions !
Sent from Outlook for iOS <https://aka.ms/o0ukef>
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*From:* CCP4 bulletin board <[email protected]> on behalf of
Wild, Conor (DLSLtd,RAL,LSCI)
<[email protected]>
*Sent:* Monday, November 24, 2025 12:15:26 PM
*To:* [email protected] <[email protected]>
*Subject:* [ccp4bb] Experience with Automated Water Completion
Software
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not provide your login details.
Hey folks, I was just wondering what people's experience with
automated water completion methods was.
I'm hoping to experiment with blind water placement into PanDDA
event maps in the near future, which is obviously not a use case
any of these methods were designed for.
I've got a fairly reliable method for evaluating waters in these
maps given candidate positions, but I was hoping to avoid
reimplementing the generation of the candidate water model by
hooking into an existing framework. As I'm fairly happy with the
evaluation I'm actually not very concerned about false positive
errors, and so a method that can avoid false negatives at the cost
of many false positives is actually fairly ideal.
PanDDA event maps are obviously real space maps that are highly
non-crystallographic in the sense that large parts of the unit
cell are masked to zero, which means that software that is real
space native would probably be preferable, but reciprocal space is
only an FFT away so I doubt it matters. Structural models are
still related to the map unit cell by symmetry rather than offsets
so cryo-em software might take some hacking but that also seems fine!
Thanks!
Conor
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