This presentation combines 2 blog posts explaining the CombiUgi project and the predicted anti-tumor activity of a virtual library of 68,000 compounds

Dan Zaharevitz

Jean-Claude Bradley

Rajarshi Guha

Rikesh Parikh

English

Nature Precedings

  
The CombiUgi Project and Closing 
the Open Science Loop
June 19, 2007 update
http://usefulchem.blogspot.com/2007/05/combiugi-and-closing-open-science-loop.html
Jean-Claude Bradley
includes work from
Rikesh Parikh
Rajarshi Guha
Dan Zaharevitz
http://usefulchem.blogspot.com/2007/06/combiugi-says-order-2-naphthyl.html
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The Ugi Reaction
A few weeks ago I asked my undergraduate student Rikesh Parikh to 
kick off the CombiUgi project: to create lists of commercially available 
boc-protected amino acids, aldehydes, primary amines and isonitriles. 
He is now done and the links to purchase each compound is provided, 
in addition to the SMILES code.
Scheme from http://en.wikipedia.org/wiki/Ugi_reaction
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By indexing these compounds in relevant search engines (I am working 
with Chemspider to make this happen) as UsefulChem molecules 
available upon request (and justification) we have an opportunity to 
close the loop on a practical Open Science project.
By the loop I mean a complete iteration from hypothesis to deciding 
which compounds to make to actually making them and getting testing 
results. These results will confirm or force a modification of the 
hypothesis and the cycle goes through another iteration hopefully closer 
to producing a useful outcome (a good drug lead compound for 
example).
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I imagine that this loop operates in a lot of research groups. But doing 
the work under Open Science conditions lets it evolve in new ways. 
First of all, the direction of progress is determined by the 
collaborators that elect to participate in the process, not 
necessarily scientific objectives. 
An example of that is our recent shift from the testing of our 
compounds as anti-malarial agents to testing them as tumor 
inhibitors simply because Dan Zaharevitz
 from the National Cancer Institute contacted me and suggested that 
we submit our compounds.
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Right after we started to submit our compounds, Dan left this message:
The folks at Indiana have done a lot of cool stuff that is well worth looking at. One 
thing they have running in a preliminary form is a service that 
predicts acompound's activity in cell lines in the screen. This compound is 
predicted to be inactive in the cell lines in the prediction. I actually don't think 
that is a bad result. We probably should put up a place to discuss screens and 
screening strategy, but essentially a prediction tools such as this summarizes 
what is known. A compound that is predicted to be inactive, but turns out to be 
active is much more likely to show you something new and interesting than a 
compound that is predicted to be active and is active.
So that's the last piece that closes the loop. This web service will make a 
prediction about activity of the compounds generated by the CombiUgi algorithm 
and rank them. The flagged compounds will be identifed and synthesized then 
tested via NCI's assays for tumor cell inhibition.N
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My group’ s core expertise is the synthetic component. As far as we are 
concerned the other 2 processes are black boxes. And for scientists involved 
in the computation and testing, our synthesis operation is probably a black 
box. But doing everything in the open, hopefully this will allow other 
researchers to propose other models and create derivative loops of their own.
We'd love to do the same for the anti-malarial assays but we have not found 
an established system in place like NCI that will do substrate screening 
routinely at no cost (except shipping of course).
Is it becoming clearer why I think the scientific process can be 
automated in novel and useful ways with the progressive adoption of 
Open Science? 
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Rajarshi really worked hard on getting an algorithm to create the Ugi product 
SMILE codes and passed them through his tumor cell inhibition program. Out 
of about 68,000 he identified a shortlist of 21 that showed the most activity (
see wiki for details). An example is shown below: 
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C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.OCC%91.Cc1cc(ccc1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCC%91.Oc1ccccc1%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCC%91.Cc1cccc(c1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCC%91.Cc1cc(ccc1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCC%91.Oc1ccccc1%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCC%91.Cc1cccc(c1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCC%91.Cc1cc(ccc1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCCC%91.Oc1ccccc1%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCCC%91.Cc1cccc(c1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCCC%91.Cc1cc(ccc1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCCCC%91.Oc1ccccc1%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCCCC%91.Cc1cccc(c1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.CSCCC(NC(=O)OC(C)(C)C)%90.CCCCCCCC%91.Cc1cc(ccc1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.Oc1ccc(CC(NC(=O)OC(C)(C)C)%90)cc1.CCCCC%91.Oc1ccccc1%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.Oc1ccc(CC(NC(=O)OC(C)(C)C)%90)cc1.CCCCC%91.Cc1cccc(c1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.Oc1ccc(CC(NC(=O)OC(C)(C)C)%90)cc1.CCCCCC%91.Oc1ccccc1%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.Oc1ccc(CC(NC(=O)OC(C)(C)C)%90)cc1.CCCCCC%91.Cc1cccc(c1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.Oc1ccc(CC(NC(=O)OC(C)(C)C)%90)cc1.CCCCCCC%91.Oc1ccccc1%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.Oc1ccc(CC(NC(=O)OC(C)(C)C)%90)cc1.CCCCCCC%91.Cc1cccc(c1O)%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.Oc1ccc(CC(NC(=O)OC(C)(C)C)%90)cc1.CCCCCCCC%91.Oc1ccccc1%92.c%931ccc2ccccc2c1 
C(=O)%90N%91C%92C(=O)N%93.Oc1ccc(CC(NC(=O)OC(C)(C)C)%90)cc1.CCCCCCCC%91.Cc1cccc(c1O)%92.c%931ccc2ccccc2c1 
I find it very interesting that all the top hits involve 2-naphthyl 
isocyanide and over half involve boc-methionine. Is this real or even 
meaningful? We've been discussing these issues privately and I hope 
that Dan, Rajarshi and others continue the discussion openly. 
Top 21 Hits (SMILES format) for predicted anti-tumor activity
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The point of this excercise is not so much to prove that this model is correct or 
that we have found a new anti-tumor lead (though that would be nice) but that 
we can close the scientific loop of hypothesis-synthesis-assay in a completely 
open and collaborative scientific environment.
I welcome suggestions of other compounds from our virtual library that might 
be worth making (for any disease-related target), as long as we have assays 
that someone can run.
We are also working with Tony Williams to see if ChemSpider can serve as a 
database to store and manage the virtual library, the predicted properties and 
the assay results. Hopefully then we could increase the library to several 
million molecules.
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InChI Tags
InChI=1/C11H7N/c1-12-11-7-6-9-4-2-3-5-10(9)8-11/h2-8H
2-naphthyl isocyanide
InChI=1/C5H11NO2S/c1-9-3-2-4(6)5(7)8/h4H,2-3,6H2,1H3,(H,7,8)
methionine
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The CombiUgi Project and Closing the Open Science Loop

Jean-Claude  Bradley

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http://precedings.nature.com/documents/104/version/1

The CombiUgi Project and Closing the Open Science Loop

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