Re: [Rdkit-discuss] Creating Mol Object From SD File
On 08/29/2018 01:54 PM, Chris Murphy wrote: > Hi, > > I finally realized that when passing an sdf string to Chem.MolFromMolBlock, > the Mol object will not retain the properties from the sdf. Ugh. You're right. +1 for a MolFromSdfBlock() that doesn't lose the properties. > Also, it seems that SDMolSupplier.next() does not work anymore? if sys.version_info[0] == 2 : next() elif sys.version_info[0] == 3 : __next()__ else : raise Exception( "Go! is looking better every day" ) -- Dimitri Maziuk Programmer/sysadmin BioMagResBank, UW-Madison -- http://www.bmrb.wisc.edu signature.asc Description: OpenPGP digital signature -- 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 Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
[Rdkit-discuss] Creating Mol Object From SD File
Hi, I finally realized that when passing an sdf string to Chem.MolFromMolBlock, the Mol object will not retain the properties from the sdf. Knowing that, I am wondering if there is a way to create a single Mol object from a SDF string. Right now, the only way I know is by using SDMolSupplier: my_mol = None suppl = Chem.SDMolSupplier(filename, ) for mol in suppl: my_mol = mol ... Are there other ways to do this without needing to create a SDMolSupplier? Also, it seems that SDMolSupplier.next() does not work anymore? I am getting the following: AttributeError: 'SDMolSupplier' object has no attribute 'next' Any help is much appreciated, thanks! Best, Chris Murphy -- 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 Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
[Rdkit-discuss] want advice for good teaching data set
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 wrote: > Send Rdkit-discuss mailing list submissions to > rdkit-discuss@lists.sourceforge.net > > To subscribe or unsubscribe via the World Wide Web, visit > https://lists.sourceforge.net/lists/listinfo/rdkit-discuss > or, via email, send a message with subject or body 'help' to > rdkit-discuss-requ...@lists.sourceforge.net > > You can reach the person managing the list at > rdkit-discuss-ow...@lists.sourceforge.net > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of Rdkit-discuss digest..." > > > 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 > To: RDKit Discuss > Subject: [Rdkit-discuss] want advice for good teaching data set > Message-ID: <8625305a-6b76-4721-bdbf-297f23edc...@dalkescientific.com> > 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 > da...@dalkescientific.com > > > > > > -- > > Message: 2 > Date: Wed, 29 Aug 2018 14:32:28 +0100 > From: Richard Cooper > To: Ali Eftekhari > Cc: RDKit Discuss > 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 < > richardiancooper+rdkitdisc...@gmail.com> 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, > 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
Re: [Rdkit-discuss] Capturing 3D Conformational Flexibility in a Single Descriptor
Thank you very much! This is really helpful! Ali On Wed, Aug 29, 2018 at 7:52 AM Richard Cooper < richardiancooper+rdkitdisc...@gmail.com> wrote: > I think it depends on what you need the descriptor for. If it were for > some kind of fingerprinting, the example implementation would be too noisy. > We used it to estimate how many low energy conformations of a molecule > might be present in a particular system - and it turned out that correlated > well with our classifications of the system. The variability increases > with RBC: for totally rigid systems RBC and nConf20 are zero. For more > reproducible results you can increase the number of conformers generated; > the cost is longer calculations, but if you only have 350 molecules this > might be OK. > > In the paper there are two example molecules with RBC of 1 and 8 > respectively which both have only a single low energy conformation, and it > was this discrimination beyond simple RBC that drove its development. > > Analysis of the spread of nConf20 showed that it was larger than the > spread of RBC, which might give it slightly better properties as an input > descriptor. However, if you are finding less variability in your particular > data set, then it might not be such a good discriminator of whatever you're > trying to discriminate. I wouldn't recommend adopting it as the 'main > descriptor' until you test whether it's useful. > > Regards, > Richard > > > > > On Wed, Aug 29, 2018 at 3:24 PM Ali Eftekhari > wrote: > >> 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 < >> richardiancooper+rdkitdisc...@gmail.com> 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 < >>> richardiancooper+rdkitdisc...@gmail.com> 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, >>> 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! >>> >> >>> -- 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 Rdkit-discuss@lists.sourceforge.net
Re: [Rdkit-discuss] want advice for good teaching data set
Hi Andrew, If you want to build model I guess that what you want is to get experimental logp values. This should give you something to start with: select ACTIVITY_ID, MOLREGNO, STANDARD_VALUE, STANDARD_TYPE from ACTIVITIES where STANDARD_TYPE = 'LogP' and STANDARD_VALUE is not null and data_validity_comment is null and POTENTIAL_DUPLICATE = 0; Eloy. 2018-08-29 14:51 GMT+01:00 TJ O'Donnell : > 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 > 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 >> da...@dalkescientific.com >> >> >> >> >> -- >> 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 >> Rdkit-discuss@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/rdkit-discuss >> > > > -- > 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 > Rdkit-discuss@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/rdkit-discuss > > -- 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 Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
Re: [Rdkit-discuss] Capturing 3D Conformational Flexibility in a Single Descriptor
I think it depends on what you need the descriptor for. If it were for some kind of fingerprinting, the example implementation would be too noisy. We used it to estimate how many low energy conformations of a molecule might be present in a particular system - and it turned out that correlated well with our classifications of the system. The variability increases with RBC: for totally rigid systems RBC and nConf20 are zero. For more reproducible results you can increase the number of conformers generated; the cost is longer calculations, but if you only have 350 molecules this might be OK. In the paper there are two example molecules with RBC of 1 and 8 respectively which both have only a single low energy conformation, and it was this discrimination beyond simple RBC that drove its development. Analysis of the spread of nConf20 showed that it was larger than the spread of RBC, which might give it slightly better properties as an input descriptor. However, if you are finding less variability in your particular data set, then it might not be such a good discriminator of whatever you're trying to discriminate. I wouldn't recommend adopting it as the 'main descriptor' until you test whether it's useful. Regards, Richard On Wed, Aug 29, 2018 at 3:24 PM Ali Eftekhari wrote: > 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 < > richardiancooper+rdkitdisc...@gmail.com> 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 < >> richardiancooper+rdkitdisc...@gmail.com> 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, >> 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! >> >> >> >>> -- 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 Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
Re: [Rdkit-discuss] Capturing 3D Conformational Flexibility in a Single Descriptor
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 < richardiancooper+rdkitdisc...@gmail.com> 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 < > richardiancooper+rdkitdisc...@gmail.com> 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, > 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! > >> > >> -- 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 Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
Re: [Rdkit-discuss] want advice for good teaching data set
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 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 > da...@dalkescientific.com > > > > > -- > 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 > Rdkit-discuss@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/rdkit-discuss > -- 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 Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
Re: [Rdkit-discuss] Capturing 3D Conformational Flexibility in a Single Descriptor
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 < richardiancooper+rdkitdisc...@gmail.com> 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, 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! >> > -- 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 Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
[Rdkit-discuss] want advice for good teaching data set
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 da...@dalkescientific.com -- 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 Rdkit-discuss@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
