Hi Jose,
As you have shown there is no single method which would be perfect for
everything. If you don’t care that much about speed, the possible solution
could be to compute coordinates with all three approaches and then simply
select the best conformer based on some criteria.
The solution I use is to generate 2D coordinates using multiple approaches and
then I have a set of methods which computes number of bond collisions and atoms
being close to each other using KD-tree. Altogether this all is expressed as
penalty score, where the lower is better.
Should you need any code, let me know.
Lukas
On 09/04/2019, 14:35, "Jose Manuel Gally" <jose.manuel.ga...@gmail.com> wrote:
Dear all,
This might sound naive, but I want to compute 2D coordinates for a set
of molecules.
For now I am considering the 3 methods below [1].
I was wondering if there was any recommendation to use one method over
another in some cases?
For instance, very large rings are not displayed round for CoordGen but
sometimes this method performs worse than the default (AllChem).
Computational time is not really an issue here as I generate those
coordinates on the fly for a very small set of compounds.
Here is a gist with a few examples:
https://gist.github.com/jose-manuel/0f2a5e8eae8bf2a72c0faad7f2f2a263
Thanks in advance, any suggestion is welcome!
Cheers,
Jose Manuel
[1] Methods:
1) rdkit.AllChem.Compute2dCoors (equivqlent to
rdkit.Chem.rdDepictor.Compute2DCoords)
2) rdkit.Avalon.pyAvalonTools.Generate2DCoords
3) rdkit.Chem.rdCoordGen.AddCoords + rescale
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