Re: [Rdkit-discuss] suggestions for comprehensive searchable database of natural products

2017-11-28 Thread Curt Fischer 
I'd also be interested in Juptyer notebooks for this.  Thanks Tyler!

Curt

On Tue, Nov 28, 2017 at 8:26 AM, Tyler Backman  wrote:

> Hi Jim,
>
> MiBIG is a useful database of natural product gene clusters and
> structures, which you can download in JSON format here, and use pretty
> easily from within Python:
> https://mibig.secondarymetabolites.org/repository.html This also
> includes pathway and organism information.
>
> Secondly, our ClusterCAD database is built with RDKit and Django, but
> only includes Type I modular PKSs imported from MiBIG. You can use it
> online at clustercad.jbei.org, or view the code and launch a docker
> install locally from https://github.com/JBEI/clusterCAD. Internally,
> it has a RDKit postgresql database, and includes predicted chemical
> intermediates at each step of biosynthesis in addition to final
> products. It is hand curated, to improve on the automatic AntiSMASH
> annotations in MiBIG. I will gradually expand this to support a
> greater diversity of natural products. I could send you an example
> Jupyter notebook for using it programatically.
>
> Sincerely,
> Tyler
>
> On Mon, Nov 27, 2017 at 1:30 PM, James T. Metz via Rdkit-discuss
>  wrote:
> > RDkit Discussion Group,
> >
> > My apologies in advance if my request is not appropriate for this
> > discussion group.
> >
> > Given a small molecule that might have some resemblance to natural
> > products,
> > can someone suggest a free, comprehensive, PYTHON/RDkit searchable
> database
> > of natural products that might be suitable for similarity and
> substructure
> > searching.
> >
> > I am aware of a few websites that permit searching on the website. If
> > possible,
> > I would like to programmatically search by running a PYTHON/RDkit script
> on
> > my
> > local machine and then return the structures of related molecules to my
> > local script.
> >
> > I would prefer not having to download and store a huge database.
> >
> > Also, if possible, it would be important to return the organism(s)
> that
> > creates
> > the natural product.  Pathway information would be also very, very
> helpful.
> >
> > I greatly welcome comments and suggestions.
> >
> > Thank you.
> >
> > Regards,
> > Jim Metz
> > Northwestern University
> >
> >
> >
> >
> >
> > 
> --
> > Check out the vibrant tech community on one of the world's most
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> > ___
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> > https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
> >
>
>
>
> --
> Tyler W. H. Backman
> Postdoctoral Fellow
> Lawrence Berkeley National Laboratory
> Joint BioEnergy Institute
>
> 
> --
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Re: [Rdkit-discuss] suggestions for comprehensive searchable database of natural products

2017-11-28 Thread Tyler Backman 
Hi Jim,

MiBIG is a useful database of natural product gene clusters and
structures, which you can download in JSON format here, and use pretty
easily from within Python:
https://mibig.secondarymetabolites.org/repository.html This also
includes pathway and organism information.

Secondly, our ClusterCAD database is built with RDKit and Django, but
only includes Type I modular PKSs imported from MiBIG. You can use it
online at clustercad.jbei.org, or view the code and launch a docker
install locally from https://github.com/JBEI/clusterCAD. Internally,
it has a RDKit postgresql database, and includes predicted chemical
intermediates at each step of biosynthesis in addition to final
products. It is hand curated, to improve on the automatic AntiSMASH
annotations in MiBIG. I will gradually expand this to support a
greater diversity of natural products. I could send you an example
Jupyter notebook for using it programatically.

Sincerely,
Tyler

On Mon, Nov 27, 2017 at 1:30 PM, James T. Metz via Rdkit-discuss
 wrote:
> RDkit Discussion Group,
>
> My apologies in advance if my request is not appropriate for this
> discussion group.
>
> Given a small molecule that might have some resemblance to natural
> products,
> can someone suggest a free, comprehensive, PYTHON/RDkit searchable database
> of natural products that might be suitable for similarity and substructure
> searching.
>
> I am aware of a few websites that permit searching on the website. If
> possible,
> I would like to programmatically search by running a PYTHON/RDkit script on
> my
> local machine and then return the structures of related molecules to my
> local script.
>
> I would prefer not having to download and store a huge database.
>
> Also, if possible, it would be important to return the organism(s) that
> creates
> the natural product.  Pathway information would be also very, very helpful.
>
> I greatly welcome comments and suggestions.
>
> Thank you.
>
> Regards,
> Jim Metz
> Northwestern University
>
>
>
>
>
> --
> 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
>



-- 
Tyler W. H. Backman
Postdoctoral Fellow
Lawrence Berkeley National Laboratory
Joint BioEnergy Institute

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[Rdkit-discuss] suggestions for comprehensive searchable database of natural products

2017-11-27 Thread James T. Metz via Rdkit-discuss 
RDkit Discussion Group,


My apologies in advance if my request is not appropriate for this 
discussion group.



Given a small molecule that might have some resemblance to natural 
products, 

can someone suggest a free, comprehensive, PYTHON/RDkit searchable database
of natural products that might be suitable for similarity and substructure 
searching.


I am aware of a few websites that permit searching on the website. If 
possible,
I would like to programmatically search by running a PYTHON/RDkit script on my
local machine and then return the structures of related molecules to my local 
script.


I would prefer not having to download and store a huge database.



Also, if possible, it would be important to return the organism(s) that 
creates

the natural product.  Pathway information would be also very, very helpful.


I greatly welcome comments and suggestions.



Thank you.



Regards,

Jim Metz

Northwestern University









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