Sections
OpenTox Blog
 
You are here: Home » Data » Blogentries » Public » Knowledge Fair Table B - Drug Discovery Application

Knowledge Fair Table B - Drug Discovery Application

Posted by Roman Affentranger at Sep 13, 2010 09:55 PM |

An example of a predictive toxicology application in drug discovery is given using the data on antimalarial compounds made available at the ChEMBL Neglected Tropical Disease (NTD) archive (http://www.ebi.ac.uk/chemblntd/). The data was imported and made available via a specially installed OpenTox dataset service, to emulate a drug discovery exercise working in a setup separate from public dataset services. OpenTox model services are used for predicting toxicities.

For this workshop activity, we combined all three data sets from the ChEMBL NTD archive in a newly created OpenTox data service: the Tres Cantos Antimalarial TCAMS dataset (>13'000 antimalarials found in a 2-million compound screening library of GlaxoSmithKline), the Novartis-GNF dataset (>5'000 antimalarials) and the St. Jude Children's Research Hospital dataset (>1'100 antimalarials, 172 of which were studied in great detail). More information on these datasets can be found at http://www.ebi.ac.uk/chemblntd/.

Workshop Activity:

 

A) Prioritizing the Antimalarials

Step 1

The antimalarial compounds are prioritized based on a very conservative model for predicting oral toxicity. More specifically, Cramer rules (a model for predicting oral toxicity) are applied to all datasets. Cramer rules is a very conservative model, that is, if it predicts a chemical to be save (class I), there is high probability it will be safe indeed. Food ingredients, for example, are classified as Class I.

Step 2

Experimentally determined cytotoxicities against human cells of the compounds predicted to be safe (Cramer class I) are further examined, and their mutagenicities predicted via Toxtree Benigni Bossa rules.

Step 3

A new dataset is created with compounds that have no mutagenicity alerts, low human cytotoxicity, but high anti-malarial activity. Potential sites of cytochrome P450 metabolism are predicted for for this dataset.

Download detailed instructions for this activity here...

 

B) Additional exercise:

Extract subsets of data to be used to create a model via the OpenTox demo application ToxCreate.

Download detailed instructions for this activity here...


Document Actions