I was very happy to hear about the integration of MolVS into RDKit core
in the talk by Susan Leung at the recent UGM.
https://github.com/rdkit/UGM_2018/blob/master/Presentations/Leung_GSoC_RDKit-MolVS_Integration.pdf
This is going to be incredibly useful once it gets released.
To help with testing of this I have created a Docker image based on the
code on Susan's fork
(https://github.com/susanhleung/rdkit/tree/dev/GSOC2018_MolVS_Integration)
which I believe is what is used for the PR on the RDKit repo
(https://github.com/rdkit/rdkit/pull/2002).
I will try to keep this updated at suitable intervals until the code is
merged into the main RDKit repo.
To run the Docker image try something like this:
$ docker run -it --rm
informaticsmatters/rdkit-python-debian:standardizer python
Python 2.7.15+ (default, Aug 31 2018, 11:56:52)
[GCC 8.2.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from rdkit import Chem
>>> from rdkit.Chem.MolStandardize import rdMolStandardize
>>> m =
rdMolStandardize.StandardizeSmiles('[Na]OC(=O)c1ccc(C[S+2]([O-])([O-]))cc1')
[09:18:41] Initializing MetalDisconnector
[09:18:41] Running MetalDisconnector
[09:18:41] Removed covalent bond between Na and O
[09:18:41] Initializing Normalizer
[09:18:41] Running Normalizer
[09:18:41] Rule applied: SulfonetoS(=O)(=O)
>>> m
'O=C([O-])c1ccc(C[S](=O)=O)cc1.[Na+]'
>>>
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