Thanks for the responses. I'll merge them into one reply:

On Aug 29, 2018, at 16:56, Eloy Félix <[email protected]> wrote:
> 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;

Yes, that's what I was looking for, including the pointers for validity and if 
it might be a duplicate. Thanks!


On Aug 29, 2018, at 15:51, TJ O'Donnell <[email protected]> wrote:
> 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.

I can see I wasn't clear. I was looking for experimental data.

The ChEMBL blog post at 
https://chembl.blogspot.com/2018/05/chembl-24-released.html says that they 
switched to using RDKit for alogp; acd_logp is still from ACD.


On Aug 29, 2018, at 18:07, JW Feng via Rdkit-discuss 
<[email protected]> wrote:
> 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.


I am, primarily, a software developer working in computational chemistry. Do 
you want fast similarity search? I can do that. Do you want a maximum common 
structure algorithm, or matched molecular pair algorithm? I can do that. Do you 
want to tell me which parameters and learning algorithm you want to use? I can 
make the pieces go together.

What I don't have is the expertise to build a chemically relevant model on my 
own, and discuss its strength and weaknesses.

When I build a model, I do it to predict molecular weight. :)

                                Andrew
                                [email protected]



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