Hi Andrew,
What about building QSAR models to predict activity for a particular ChEMBL
assay? This would allow you to discuss strength and limitations of QSAR
models.
Best,
JW
___________________
JW Feng, Ph.D.
Denali Therapeutics Inc.
151 Oyster Point Blvd, 2nd Floor, South San Francisco, CA 94080
On Wed, Aug 29, 2018 at 7:24 AM <[email protected]>
wrote:
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> Today's Topics:
>
> 1. want advice for good teaching data set (Andrew Dalke)
> 2. Re: Capturing 3D Conformational Flexibility in a Single
> Descriptor (Richard Cooper)
> 3. Re: want advice for good teaching data set (TJ O'Donnell)
> 4. Re: Capturing 3D Conformational Flexibility in a Single
> Descriptor (Ali Eftekhari)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Wed, 29 Aug 2018 14:51:57 +0200
> From: Andrew Dalke <[email protected]>
> To: RDKit Discuss <[email protected]>
> Subject: [Rdkit-discuss] want advice for good teaching data set
> Message-ID: <[email protected]>
> Content-Type: text/plain; charset=us-ascii
>
> Hi all,
>
> I am starting to put together materials for the Python/RDKit training
> course I'm giving just before the RDKit UGM next month.
>
> I would like to structure part of it around the SQLite release of the
> ChEMBL data set. More specifically, I plan to include examples of machine
> learning with scikit-learn, using RDKit descriptors and values from ChEMBL
> 24 (and making sure to use the new schema).
>
> Two problems. First, I'm not a computational chemist and I don't know what
> would constitute a good example to use. "Good" in this case means one whose
> outlines are well-known to likely students. Second, I don't have much
> experience with the ChEMBL data.
>
> My thought is to make a logP model. The easiest would be to based it on
> atom types. For this option, can anyone suggest where I can find logP data
> from ChEMBL?
>
> Another possibility is to use a pre-existing model, like the notebook
> George Papadatos did for Ligand-based Target Prediction at
> http://nbviewer.jupyter.org/gist/madgpap/10457778 .
>
> Perhaps someone here could point me to other existing resources along
> similar lines?
>
> Best regards,
>
> Andrew
> [email protected]
>
>
>
>
>
> ------------------------------
>
> Message: 2
> Date: Wed, 29 Aug 2018 14:32:28 +0100
> From: Richard Cooper <[email protected]>
> To: Ali Eftekhari <[email protected]>
> Cc: RDKit Discuss <[email protected]>
> Subject: Re: [Rdkit-discuss] Capturing 3D Conformational Flexibility
> in a Single Descriptor
> Message-ID:
> <
> cajwsdrteawmtnqrhzfnfojj54orgtsgj+-_6rwly26o98as...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Just to follow up with the details - here is the line in the script to
> change:
>
> conformers = AllChem.EmbedMultipleConfs
> (molecule,numConfs,pruneRmsThresh=0.5, numThreads =3)
>
> to
>
> conformers = AllChem.EmbedMultipleConfs
> (molecule,numConfs,pruneRmsThresh=0.5, numThreads =3, randomSeed=737 )
>
> (where 737 is an integer constant of your choice, but not -1).
>
> Richard
>
>
> On Tue, Aug 28, 2018 at 12:55 PM Richard Cooper <
> [email protected]> wrote:
> >
> > Hi Ali,
> >
> > Sorry I missed your email.
> >
> > The behaviour you describe is correct, due to a random seed in the
> conformer generation step. The descriptor value usually doesn't vary by too
> much.
> >
> > I think you can give the conformer generation a constant random seed if
> you need a reproducible number for nConf20.
> >
> > Regards, Richard
> >
> >
> > On Tue, 28 Aug 2018, 00:25 Ali Eftekhari, <[email protected]>
> wrote:
> >>
> >> Hello all,
> >>
> >> I am trying to calculate 3D Descriptors following this publication:
> >> "Beyond Rotatable Bond Counts: Capturing 3D Conformational Flexibility
> in a Single Descriptor", Jerome G. P. Wicker and Richard I. Cooper. J.
> Chem. Inf. Model. 2016, 56, 2347?2352
> >>
> >> I am essentially using the same script as they have in the supporting
> information and i have attached it here as well. In Table 2 from the above
> calculation, the value of the descriptor (nConf20) for ZINC000290539224
> molecule is listed as 10. However, when I run the exact code as the one
> they used, I get different value at each run.
> >>
> >> I have already contacted the authors but got no response. I am
> wondering if the code they have in the supporting information is not right
> or the value they listed in the table is wrong?
> >>
> >> The SMILES string for this particular molecule is:
> >> 'CC(C)N2CC(NCc1cnc(C(C)O)s1)CC2=O'
> >>
> >> Thanks in advance for your help!
> >>
>
> >
> -------------- next part --------------
> An HTML attachment was scrubbed...
>
> ------------------------------
>
> Message: 3
> Date: Wed, 29 Aug 2018 06:51:45 -0700
> From: "TJ O'Donnell" <[email protected]>
> To: Andrew Dalke <[email protected]>
> Cc: RDKit Discuss <[email protected]>
> Subject: Re: [Rdkit-discuss] want advice for good teaching data set
> Message-ID:
> <
> cadqa_h8xm5difzy7zf_zapphgulb5+uhuavsahuc0vvewdm...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Andrew
> ChEMBL 24 has compound properties in the table compound_properties. I
> think the alogp
> is computed using (Crippen) atom types and the acd_logp is uses ACD labs
> methods.
> TJ
>
> On Wed, Aug 29, 2018 at 5:52 AM Andrew Dalke <[email protected]>
> wrote:
>
> > Hi all,
> >
> > I am starting to put together materials for the Python/RDKit training
> > course I'm giving just before the RDKit UGM next month.
> >
> > I would like to structure part of it around the SQLite release of the
> > ChEMBL data set. More specifically, I plan to include examples of machine
> > learning with scikit-learn, using RDKit descriptors and values from
> ChEMBL
> > 24 (and making sure to use the new schema).
> >
> > Two problems. First, I'm not a computational chemist and I don't know
> what
> > would constitute a good example to use. "Good" in this case means one
> whose
> > outlines are well-known to likely students. Second, I don't have much
> > experience with the ChEMBL data.
> >
> > My thought is to make a logP model. The easiest would be to based it on
> > atom types. For this option, can anyone suggest where I can find logP
> data
> > from ChEMBL?
> >
> > Another possibility is to use a pre-existing model, like the notebook
> > George Papadatos did for Ligand-based Target Prediction at
> > http://nbviewer.jupyter.org/gist/madgpap/10457778 .
> >
> > Perhaps someone here could point me to other existing resources along
> > similar lines?
> >
> > Best regards,
> >
> > Andrew
> > [email protected]
> >
> >
> >
> >
> >
> ------------------------------------------------------------------------------
> > Check out the vibrant tech community on one of the world's most
> > engaging tech sites, Slashdot.org! http://sdm.link/slashdot
> > _______________________________________________
> > Rdkit-discuss mailing list
> > [email protected]
> > https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
> >
> -------------- next part --------------
> An HTML attachment was scrubbed...
>
> ------------------------------
>
> Message: 4
> Date: Wed, 29 Aug 2018 07:24:05 -0700
> From: Ali Eftekhari <[email protected]>
> To: [email protected]
> Cc: [email protected]
> Subject: Re: [Rdkit-discuss] Capturing 3D Conformational Flexibility
> in a Single Descriptor
> Message-ID:
> <CAKWSw4=
> [email protected]>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Dr. Cooper,
>
> Thanks for your response and the suggestions. I added randomSeed=737 and I
> now get value of 14 for descriptor nConf20 for ZINC000290539224 molecule
> (although it is different than your paper [the value is 10] it does not
> change on each run). My concern now is on the general usage of nConf20
> descriptor. For instance, is there a limitation on what molecules can be
> used for estimating their nConf20? Since the conformers are generated
> randomly, how reliable is this descriptor to use it as a replacement for
> Rotatable Bond Count (RBC) in all machine learning models.
>
> In my application, the calculated values of RBC for 350 molecules range
> from 0 to 7 with (80% between 0-4 and 20% between 5-7). The calculated
> values of nconf20 is between 0-40 but with 95% between 0-3. Since nConf20
> for majority of molecules is between 0-3, I am concerned on the usage of
> nconf20 as the main descriptor. Could you please comment on that?
>
> Thanks,
> Ali
>
> On Wed, Aug 29, 2018 at 6:32 AM Richard Cooper <
> [email protected]> wrote:
>
> >
> > Just to follow up with the details - here is the line in the script to
> > change:
> >
> > conformers = AllChem.EmbedMultipleConfs
> > (molecule,numConfs,pruneRmsThresh=0.5, numThreads =3)
> >
> > to
> >
> > conformers = AllChem.EmbedMultipleConfs
> > (molecule,numConfs,pruneRmsThresh=0.5, numThreads =3, randomSeed=737 )
> >
> > (where 737 is an integer constant of your choice, but not -1).
> >
> > Richard
> >
> >
> > On Tue, Aug 28, 2018 at 12:55 PM Richard Cooper <
> > [email protected]> wrote:
> > >
> > > Hi Ali,
> > >
> > > Sorry I missed your email.
> > >
> > > The behaviour you describe is correct, due to a random seed in the
> > conformer generation step. The descriptor value usually doesn't vary by
> too
> > much.
> > >
> > > I think you can give the conformer generation a constant random seed if
> > you need a reproducible number for nConf20.
> > >
> > > Regards, Richard
> > >
> > >
> > > On Tue, 28 Aug 2018, 00:25 Ali Eftekhari, <[email protected]>
> > wrote:
> > >>
> > >> Hello all,
> > >>
> > >> I am trying to calculate 3D Descriptors following this publication:
> > >> "Beyond Rotatable Bond Counts: Capturing 3D Conformational Flexibility
> > in a Single Descriptor", Jerome G. P. Wicker and Richard I. Cooper. J.
> > Chem. Inf. Model. 2016, 56, 2347?2352
> > >>
> > >> I am essentially using the same script as they have in the supporting
> > information and i have attached it here as well. In Table 2 from the
> above
> > calculation, the value of the descriptor (nConf20) for ZINC000290539224
> > molecule is listed as 10. However, when I run the exact code as the one
> > they used, I get different value at each run.
> > >>
> > >> I have already contacted the authors but got no response. I am
> > wondering if the code they have in the supporting information is not
> right
> > or the value they listed in the table is wrong?
> > >>
> > >> The SMILES string for this particular molecule is:
> > >> 'CC(C)N2CC(NCc1cnc(C(C)O)s1)CC2=O'
> > >>
> > >> Thanks in advance for your help!
> > >>
> >
> >>
> -------------- next part --------------
> An HTML attachment was scrubbed...
>
> ------------------------------
>
>
> ------------------------------------------------------------------------------
> Check out the vibrant tech community on one of the world's most
> engaging tech sites, Slashdot.org! http://sdm.link/slashdot
>
> ------------------------------
>
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> End of Rdkit-discuss Digest, Vol 130, Issue 35
> **********************************************
>
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