Thank you Greg!
That is a great example. It works perfectly on my toy example. :)
I would like to clarify a question related to indexing in DB. In the
examples on RDKit cartridge page gist indices are created on fields
containing fingerprints. In the provided notebook you did not do this.
Do indices speed up similarity search or what is a reason to add them?
Pavel.
On 04/26/2017 02:36 PM, Greg Landrum wrote:
Hi Pavel,
On Wed, Apr 26, 2017 at 8:41 AM, Pavel Polishchuk
<pavel_polishc...@ukr.net <mailto:pavel_polishc...@ukr.net>> wrote:
Hello,
is it possible to store custom fingerprints in psql DB and use them
for similarity search? And how to do this?
That's a great question and it took me a bit to get the answer working.
Since the answer isn't completely trivial and since it may be useful
to others, it seems like a good topic for an RDKit blog post. Those
take a while to write, but I've got an early version that lacks most
of the explanatory text up here:
https://github.com/greglandrum/rdkit_blog/blob/master/notebooks/Custom%20fingerprint%20in%20PostgreSQL.ipynb
I hope this helps,
-greg
I foundtwo commands bfp_to_binary_text(bfp) and
bfp_from_binary_text(bytea)in RDKit cartridge but cannot
understand how
to use them.
I want to store pharmacophore fingerprints. There is no a built-in
command in RDKit cartridge to calculate them so I have to
calculate them
in a Pythonscript. Then I need to store them in psql DB and create
similarity search index but I could not find a solution yet.
It might be of general interest how to store and use arbitrary
fingerprints in DB.
An example of pharmacophore FP generation:
from rdkit import Chem
from rdkit import RDConfig
from rdkit.Chem.Pharm2D.SigFactory import SigFactory
from rdkit.Chem.Pharm2D import Generate
import os
fdefName = os.path.join(RDConfig.RDDataDir,'BaseFeatures.fdef')
factory = ChemicalFeatures.BuildFeatureFactory(fdefName)
sigFactory = SigFactory(factory, minPointCount=2, maxPointCount=3,
trianglePruneBins=False)
sigFactory.SetBins([(0,2),(2,5),(5,8)])
sigFactory.Init()
mol =
Chem.MolFromSmiles('Cc1nc(CN(C)c2ncnc3ccc(-c4ccc5c(c4)OCO5)cc23)cs1')
fp = Generate.Gen2DFingerprint(mol, sigFactory)
Pavel.
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