The Joint European Compound Library: boosting precompetitive research.

The Joint European Compound Library (JECL) is a new high-throughput screening collection aimed at driving precompetitive drug discovery and target validation. The JECL has been established with a core of over 321,000 compounds from the proprietary collections of seven pharmaceutical companies and will expand to around 500,000 compounds. Here, we analyse the physicochemical profile and chemical diversity of the core collection, showing that the collection is diverse and has a broad spectrum of predicted biological activity. We also describe a model for sharing compound information from multiple proprietary collections, enabling diversity and quality analysis without disclosing structures. The JECL is available for screening at no cost to European academic laboratories and SMEs through the IMI European Lead Factory (http://www.europeanleadfactory.eu/).

[1]  David Rogers,et al.  Extended-Connectivity Fingerprints , 2010, J. Chem. Inf. Model..

[2]  Peter Willett,et al.  Similarity searching using 2D structural fingerprints. , 2011, Methods in molecular biology.

[3]  Ben Sidders,et al.  Precompetitive activity to address the biological data needs of drug discovery , 2014, Nature Reviews Drug Discovery.

[4]  Marc A. Martí-Renom,et al.  Target Prediction for an Open Access Set of Compounds Active against Mycobacterium tuberculosis , 2013, PLoS Comput. Biol..

[5]  M. Bunnage.  Getting pharmaceutical R&D back on target. , 2011, Nature chemical biology.

[6]  Thierry Kogej,et al.  Big pharma screening collections: more of the same or unique libraries? The AstraZeneca-Bayer Pharma AG case. , 2013, Drug discovery today.

[7]  G. V. Paolini,et al.  Quantifying the chemical beauty of drugs. , 2012, Nature chemistry.

[8]  Joel Cutcher-Gershenfeld,et al.  Precompetitive consortia in biomedicine—how are we doing? , 2013, Nature Biotechnology.

[9]  George Papadatos,et al.  The ChEMBL bioactivity database: an update , 2013, Nucleic Acids Res..

[10]  Dimitris K. Agrafiotis,et al.  A Cluster-Based Strategy for Assessing the Overlap between Large Chemical Libraries and Its Application to a Recent Acquisition , 2006, J. Chem. Inf. Model..

[11]  K. M. Smith,et al.  Novel software tools for chemical diversity , 1998 .

[12]  Meir Glick,et al.  Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases , 2006, J. Chem. Inf. Model..

[13]  John P. Overington,et al.  ChEMBL: a large-scale bioactivity database for drug discovery , 2011, Nucleic Acids Res..

[14]  A. Hillisch,et al.  Rendezvous in chemical space? Comparing the small molecule compound libraries of Bayer and Schering. , 2011, Drug discovery today.