ld, at the very
> least, generate an error when you try to do this), but it's easy enough to
> fix in your code: just stop specifying the length of the pattern
> fingerprints.
>
> Best,
> -greg
>
>
>
> On Mon, Aug 31, 2020 at 3:57 PM Thomas Evangelidis
> wrote:
>
acilitate linking or extension. What is wrong in this case and the results
do not agree? Am I not using SubstructLibrary correctly?
I thank you in advance.
Thomas
--
==========
Dr. Thomas Evangelidis
Research Scientist
IOCB -
Dne po 2. 12. 2019 4:45 PM uživatel Greg Landrum
napsal:
> [Adding the mailing list back on]
>
Oops, sorry about that.
> But if you add partial charges (a floating point number) then essentially
> every atom is going to end up with its own invariant. That's unlikely to
> end well.
>
>
I
r-defined invariants are much less (795) and the performance of the ML
model is significantly different. Could someone point out what I am doing
wrong?
~Thomas
--
==========
Dr. Thomas Evangelidis
Research Scientist
IOC
ts
>>
>>
>> And then generate the fingerprint like this:
>>
>>
>> fp = AllChem.GetMorganFingerprint(mol, radius=3,
>> invariants=generateAtomInvariant(mol))
>>
>>
>>
--
==
Dr. Thomas Eva
ffice to add this extra line in generateAtomInvariant() function?
descriptors.append(a.GetFormalCharge())
I thank you in advance.
Thomas
--
==========
Dr. Thomas Evangelidis
Research Scientist
IOCB - Institute of Organic Chemistry and
d isn't the slowest thing I came up with):
>>> def np_to_bv(fv):
>>> bv = DataStructs.ExplicitBitVect(len(fv))
>>> for i,v in enumerate(fv):
>>> if v:
>>> bv.SetBit(i)
>>>return bv
>>>
>>> -greg
>>>
&
ow do I do it?
fv1 = numpy.array([1,1,0,0,1,0,1])
fv2 = numpy.array([0,1,1,0,1,0,0])
Thanks in advance.
Thomas
--
==
Dr. Thomas Evangelidis
Research Scientist
IOCB - Institute of Organic Chemistry and Biochemistry of
.
Thanks in advance.
Thomas
--
==
Dr Thomas Evangelidis
Research Scientist
IOCB - Institute of Organic Chemistry and Biochemistry of the Czech Academy
of Sciences <https://www.uochb.cz/web/structure/31.html?lang=en>
__
> 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:
samples to go up to bitvector length 8192 without overfitting the networks,
although that will make the training much slower.
On Wed, 10 Oct 2018 at 14:15, Michal Krompiec
wrote:
> Hi Thomas,
> Radius 2, 2048 bits, 5200 data points.
>
> On Wed, 10 Oct 2018 at 13:13, Thomas Evangeli
risk
> of bit collisions in folded fingerprints.
>
If you increase the fpSize to 8192, won't you reduce the risk of bit
collisions?
>
> Am 04.10.2018 um 19:56 schrieb Thomas Evangelidis:
> > Hi Nils,
> >
> > In general, yes, but there are still cases where RDK5 gives
gt;
>
> On Thu, Oct 4, 2018 at 11:22 AM Thomas Evangelidis
> wrote:
>
>> Dear RDKit community,
>>
>> I need some advice regarding the usage of RDK5 fingerprints for machine
>> learning. I have a big training set (2200 molecules) and a small test set
>> (130
ar
99 46 96 1
100 47 48 ar
101 47 97 1
102 48 98 1
@SUBSTRUCTURE
1 UNK 1 GROUP 0 0 ROOT
--
==
Dr Thomas Evangelidis
Research Scientist
IOCB - Institute
_
> Rdkit-discuss mailing list
> Rdkit-discuss@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
>
--
==
Dr Thomas Evangelidis
R
would.
thanks,
Thomas
--
==
Dr Thomas Evangelidis
Post-doctoral Researcher
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/2S049,
62500 Brno, Czech Republic
email: tev...@pharm.uoa.gr
u think that this is the
source of the problem? You can download the structures (also attached) from
this link:
https://www.dropbox.com/s/pp9srlkemweboaf/failed_compounds.sdf.gz?dl=0
thanks in advance
Thomas
--
==========
Dr Thoma
!??)
molnames_list.append(molname)
if get_molnames:
return molname_SMILES_conformersMol_multidict, molnames_list
else:
> return molname_SMILES_conformersMol_multidict
--
==
Dr Thomas Evangelidis
Post-doctoral Research
gt;
>
> On Tue, Oct 25, 2016 at 2:16 AM, Thomas Evangelidis <teva...@gmail.com>
> wrote:
>
>> Hello everyone,
>>
>> I am a new user of RDkit and I was looking in the documentation for an
>> easy way to load multiple conformers from a structure file like .sdf.
ther poor since it was
>> adapted for screening millions of compounds in short time scales.
>>
>> I would appreciate any advice.
>>
>> best,
>> Thomas
>>
>>
>> --
>>
>>
--
==
Dr Thomas Evangelidis
Post-doctoral Researcher
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/2S049,
62500 Brno, Czech Republic
email: tev...@pharm.uoa.gr
teva...@gmail.com
website: https://sites.google.com/site
division*
>>
>> *mol1 = Chem.MolFromSmiles('CCO')*
>> *mol2 = Chem.MolFromSmiles('CCC')*
>>
>> *fp1 = np.array(AllChem.GetMorganFingerprintAsBitVect(mol1, 8),
>> dtype='bool')*
>> *fp2 = np.array(AllChem.GetMorganFingerprintAsBitVect(mol2, 8),
>>
--
==
Thomas Evangelidis
Research Specialist
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/1S081,
62500 Brno, Czech Republic
email: tev...@pharm.uoa.gr
teva...@gmail.com
website: https
Hi Greg,
Actually this question is relevant to my recent thread about aligning MCS
of 2 compounds. As also seen in the code I have posted in my last email, I
first generate N conformers of each query compound and then optimize them
using distance restraints in order to superimpose their MCS with
OK, I am almost there!
First, I tried the AllChem.ConstrainedEmbed(qmol, core) function to
generate conformers, where core was a mol object created from the MCS with
3D coordinates copied from template's MCS. But is seems that this functions
works only when core is an intact molecule, because I
February 2017 at 07:35, Greg Landrum <greg.land...@gmail.com> wrote:
>
>
> On Mon, Feb 20, 2017 at 6:17 PM, Thomas Evangelidis <teva...@gmail.com>
> wrote:
>
>>
>> Thank you for your useful hints. All the compounds that I want to align
>> are supp
st
>>
>> This might not be what you want, but we had good success with similar
>> methods and virtual screening, especially when using multiple co-crystal
>> active sites. I can send you a reference link if this interests you
>>
>> Cheers,
>> Brian
>>
Greg and Brian,
Thank you for your useful hints. All the compounds that I want to align are
supposed to belong to the same analogue series so they should shave a
common substructure with substantial size.
What I want to emulate is the "core restrained docking" with glide, where
you specify the
, refCid=0,
reflect=True)
AllChem.TransformMol(qmol, bestRMSDTrans[1], confId=bestconfID,
keepConfs=False)
and then I write the qmol in an sdf file. But when I visualize it the qmol
is far from the refmol!
On 20 February 2017 at 02:33, Thomas Evangelidis <teva...@gmail.com> wrote:
>
automatic way to find it on the fly
while aligning the 2 molecules.
--
==
Thomas Evangelidis
Research Specialist
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/1S081,
62500 Brno, Czech Republic
--
==
Thomas Evangelidis
Research Specialist
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/1S081,
62500 Brno, Czech Republic
email: tev...@pharm.uoa.gr
teva...@gmail.com
website: https://sites.google.com/site
gt; A python implementation of this would be a good topic for Friday's UGM
> hackathon, we can see if anyone finds it interesting enough to work on.
>
> -greg
>
>
> On Tue, Oct 25, 2016 at 2:16 AM, Thomas Evangelidis <teva...@gmail.com>
> wrote:
>
>> H
Thomas
--
==
Thomas Evangelidis
Research Specialist
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/1S081,
62500 Brno, Czech Republic
email: tev...@pharm.uoa.gr
teva...@gmail.com
version of Python and that you PYTHONPATH is not set.
>
> -greg
>
>
> _________
> From: Thomas Evangelidis <teva...@gmail.com>
> Sent: Wednesday, October 19, 2016 8:10 AM
> Subject: [Rdkit-discuss] installation issues
> To: <rdkit-discuss@lists.
Greetings everyone,
I use Ubuntu 14.04.4 LTS and first I tried to install RDkit through Conda.
After getting a strange segmentation fault when invoking USRCAT functions
that imported scipy, I managed to fix it by installing accelerate libraries:
conda install accelerate
However, in order to
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