Re: [Rdkit-discuss] Source of the solubility data?
Hi Zhenting, That's the Huuskonen dataset. The reference is here: https://pubs.acs.org/doi/10.1021/ci9901338 The origins of the SDF itself are unfortunately lost in antiquity. I originally got them here: http://cheminformatics.org/datasets/huuskonen/index.html but cheminformatics.org no longer exists. archive.org isn't working at the moment, but when it's back someone could check there to try and figure out who curated the SDF -greg On Mon, Feb 24, 2020 at 11:53 PM Gao Zhenting wrote: > Hi Greg, > > I am trying to reproduce some machine learning scripts using > > https://github.com/rdkit/rdkit/blob/master/Docs/Book/data/solubility.test.sdf > > > https://github.com/rdkit/rdkit/blob/master/Docs/Book/data/solubility.train.sdf > > > What is the source of these data? How are they organized? Any citation? > > Best regards > Zhenting > ___ > Rdkit-discuss mailing list > Rdkit-discuss@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/rdkit-discuss > ___ Rdkit-discuss mailing list Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
Re: [Rdkit-discuss] RDkit in Python vs. on PostgreSQL?
I think you need to explain what benchmarks you are running and what is
really meant by "faster".
And what hardware (for Spark how many nodes, how big; for PostgreSQL
what size server, what settings esp. the shared_buffers setting).
A very obvious critique of what you reported is that what you describe
as "running in Python" includes generating the fingerprints for each
molecule on the fly, whereas for "the cartridge" these are already
calculated, so will obviously be much faster (as the fingerprint
generation dominates the compute).
Tim
On 25/02/2020 11:14, Deepti Gupta via Rdkit-discuss wrote:
Hi Gurus,
I'm absolutely new to Chem-informatics domain. I've been assigned a
PoC where I've to compare RDKit in Python and RDKit on PostgreSQL.
I've installed both and am trying some hands-on exercises to
understand the differences. What I've understood that the structure
searches are slower in Python (Spark Cluster) than in PostgreSQL
database. Please correct me if I'm wrong as I'm a newbie in this and
maybe talking silly.
The similarity search using the below functions (example) -
Python methods -
fps =
FingerprintMols.FingerprintMol(Chem.MolFromSmiles(smile_structure,
sanitize=False))
similarity = DataStructs.TanimotoSimilarity(fps1,fps2)
takes too long (45 minutes) for a 2 million file while the same thing
is very quick (in seconds) on PostgreSQL
Database functions -
select count(*) from (select
modality_id,m,tanimoto_sml(morganbv_fp(mol_from_smiles('CCOC(=O)c1cc2cc(ccc2[nH]1)C(=O)O'::cstring)),mfp2)
as similarity from fingerprints join mols using (modality_id)) as fps
where similarity between 0.45 and 0.50;
Does this conclude that for production workloads one must always use
database cartridge only? Like RDKit, BINGO, etc.?
Regards,
DA
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Re: [Rdkit-discuss] Draw.MolsToGridImage error: got multiple values for keyword argument
Hi Paolo,
Your solution works perfectly. Thank you!
- Konrad
From: Paolo Tosco
Date: Tuesday, February 25, 2020 at 6:34 PM
To: Konrad Koehler , RDKit Discuss
Subject: Re: [Rdkit-discuss] Draw.MolsToGridImage error: got multiple values
for keyword argument
Hi Konrad,
you should use the highlightAtomLists parameter rather than highlightAtoms,
then your example will work.
Cheers,
p.
On 25/02/2020 16:02, Konrad Koehler via Rdkit-discuss wrote:
Hi everyone,
I am having trouble using a mol property value to define highlighted atoms when
generating an image.
Starting from the beginning, I have defined a variable highlight_atom_numbers
as a tuple:
>>> type(highlight_atom_numbers)
>>>
And set a mol property to this value:
mol.SetProp("highlight_atom_numbers",str(highlight_atom_numbers))
I then tried to create a 2D image of the molecule with the
“highlight_atom_numbers” highlighted:
img=Draw.MolsToGridImage(
act_mols,
molsPerRow=4,
subImgSize=(200,200),
legends=[x.GetProp("_Name") for x in act_mols],
highlightAtoms=[literal_eval(x.GetProp("highlight_atom_numbers")) for x in
act_mols]
)
Which generates the following error message:
TypeError: Boost.Python.function() got multiple values for keyword argument
'highlightAtoms'
The literal_eval function should return a single tuple and not multiple values.
Anyone have any ideas for getting this to work? Thanks.
- Konrad
PS: I have tried googling for a solution, for example:
Stack Overflow: TypeError got multiple values for keyword argument
and tried the suggestions there, but that did not help.
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Re: [Rdkit-discuss] Draw.MolsToGridImage error: got multiple values for keyword argument
Hi Konrad,
you should use the highlightAtomLists parameter rather than
highlightAtoms, then your example will work.
Cheers,
p.
On 25/02/2020 16:02, Konrad Koehler via Rdkit-discuss wrote:
Hi everyone,
I am having trouble using a mol property value to define highlighted
atoms when generating an image.
Starting from the beginning, I have defined a variable
highlight_atom_numbers as a tuple:
>>>type(highlight_atom_numbers)
>>>
And set a mol property to this value:
mol.SetProp("highlight_atom_numbers",str(highlight_atom_numbers))
I then tried to create a 2D image of the molecule with the
“highlight_atom_numbers” highlighted:
img=Draw.MolsToGridImage(
act_mols,
molsPerRow=4,
subImgSize=(200,200),
legends=[x.GetProp("_Name") for x in act_mols],
highlightAtoms=[literal_eval(x.GetProp("highlight_atom_numbers")) for
x in act_mols]
)
Which generates the following error message:
TypeError: Boost.Python.function() got multiple values for keyword
argument 'highlightAtoms'
Theliteral_eval function
should
return a single tuple and not multiple values.
Anyone have any ideas for getting this to work? Thanks.
- Konrad
PS: I have tried googling for a solution, for example:
Stack Overflow: TypeError got multiple values for keyword argument
and tried the suggestions there, but that did not help.
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[Rdkit-discuss] Draw.MolsToGridImage error: got multiple values for keyword argument
Hi everyone,
I am having trouble using a mol property value to define highlighted atoms when
generating an image.
Starting from the beginning, I have defined a variable highlight_atom_numbers
as a tuple:
>>> type(highlight_atom_numbers)
>>>
And set a mol property to this value:
mol.SetProp("highlight_atom_numbers",str(highlight_atom_numbers))
I then tried to create a 2D image of the molecule with the
“highlight_atom_numbers” highlighted:
img=Draw.MolsToGridImage(
act_mols,
molsPerRow=4,
subImgSize=(200,200),
legends=[x.GetProp("_Name") for x in act_mols],
highlightAtoms=[literal_eval(x.GetProp("highlight_atom_numbers")) for x in
act_mols]
)
Which generates the following error message:
TypeError: Boost.Python.function() got multiple values for keyword argument
'highlightAtoms'
The literal_eval function should return a single tuple and not multiple values.
Anyone have any ideas for getting this to work? Thanks.
- Konrad
PS: I have tried googling for a solution, for example:
Stack Overflow: TypeError got multiple values for keyword argument
and tried the suggestions there, but that did not help.
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Re: [Rdkit-discuss] Substructure match when using smarts containing more than one part
Hi Greg, Yes, that 's what I was after, recursive smiles... Thanks a lot, Alexis On Tue, 25 Feb 2020 at 14:53, Greg Landrum wrote: > Hi Alexis, > > There's not really. The substructure matching algorithm looks for a match > for each atom of the query. So if your query has 8 atoms in it (as yours > does), then it needs to match 8 separate atoms in the molecule. > > What exactly are you trying to match here? Do you just want to see whether > or not a molecule has an F connected to an aromatic atom and a 6-membered > all-carbon aromatic ring? That SMARTS is Fa.[$(c1c1)] > > -greg > > On Tue, Feb 25, 2020 at 8:46 AM Alexis Parenty < > alexis.parenty.h...@gmail.com> wrote: > >> Dear RDkiter, >> >> Using HasSubstructureMatch() I can match the following smarts “F[a]” and >> “c1c1” with "Fc1c1”. However, when I put the two fragments together >> in "F[a].c1c1" it no longer matches. I suppose this is the desired >> behaviour since the any aromatic [a] from F[a] that is also part of >> c1c1 and would be counted twice anotherwise. >> >> Is there a function parameter in HasSubstructureMatch() that I am not >> aware of and that could make "F[a].c1c1" match "Fc1c1” without me >> having to separate the fragments and check the match for each part? >> >> Thanks, >> >> Alexis >> ___ >> Rdkit-discuss mailing list >> Rdkit-discuss@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/rdkit-discuss >> > ___ Rdkit-discuss mailing list Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
Re: [Rdkit-discuss] Substructure match when using smarts containing more than one part
Hi Alexis, There's not really. The substructure matching algorithm looks for a match for each atom of the query. So if your query has 8 atoms in it (as yours does), then it needs to match 8 separate atoms in the molecule. What exactly are you trying to match here? Do you just want to see whether or not a molecule has an F connected to an aromatic atom and a 6-membered all-carbon aromatic ring? That SMARTS is Fa.[$(c1c1)] -greg On Tue, Feb 25, 2020 at 8:46 AM Alexis Parenty < alexis.parenty.h...@gmail.com> wrote: > Dear RDkiter, > > Using HasSubstructureMatch() I can match the following smarts “F[a]” and > “c1c1” with "Fc1c1”. However, when I put the two fragments together > in "F[a].c1c1" it no longer matches. I suppose this is the desired > behaviour since the any aromatic [a] from F[a] that is also part of > c1c1 and would be counted twice anotherwise. > > Is there a function parameter in HasSubstructureMatch() that I am not > aware of and that could make "F[a].c1c1" match "Fc1c1” without me > having to separate the fragments and check the match for each part? > > Thanks, > > Alexis > ___ > Rdkit-discuss mailing list > Rdkit-discuss@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/rdkit-discuss > ___ Rdkit-discuss mailing list Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
[Rdkit-discuss] Substructure match when using smarts containing more than one part
Dear RDkiter, Using HasSubstructureMatch() I can match the following smarts “F[a]” and “c1c1” with "Fc1c1”. However, when I put the two fragments together in "F[a].c1c1" it no longer matches. I suppose this is the desired behaviour since the any aromatic [a] from F[a] that is also part of c1c1 and would be counted twice anotherwise. Is there a function parameter in HasSubstructureMatch() that I am not aware of and that could make "F[a].c1c1" match "Fc1c1” without me having to separate the fragments and check the match for each part? Thanks, Alexis ___ Rdkit-discuss mailing list Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
[Rdkit-discuss] RDkit in Python vs. on PostgreSQL?
Hi Gurus,
I'm absolutely new to Chem-informatics domain. I've been assigned a PoC where
I've to compare RDKit in Python and RDKit on PostgreSQL. I've installed both
and am trying some hands-on exercises to understand the differences. What I've
understood that the structure searches are slower in Python (Spark Cluster)
than in PostgreSQL database. Please correct me if I'm wrong as I'm a newbie in
this and maybe talking silly.
The similarity search using the below functions (example) -Python methods -
fps = FingerprintMols.FingerprintMol(Chem.MolFromSmiles(smile_structure,
sanitize=False))similarity = DataStructs.TanimotoSimilarity(fps1,fps2)
takes too long (45 minutes) for a 2 million file while the same thing is very
quick (in seconds) on PostgreSQL Database functions -
select count(*) from (select
modality_id,m,tanimoto_sml(morganbv_fp(mol_from_smiles('CCOC(=O)c1cc2cc(ccc2[nH]1)C(=O)O'::cstring)),mfp2)
as similarity from fingerprints join mols using (modality_id)) as fps where
similarity between 0.45 and 0.50;
Does this conclude that for production workloads one must always use database
cartridge only? Like RDKit, BINGO, etc.?
Regards,DA___
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