Comparing the chemical spaces of metabolites and available chemicals: models of metabolite-likeness
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The chemical space covered by compounds involved in metabolic reactions was compared with that of a random dataset of purchasable compounds by chemoinformatics techniques. The comparison was based on 3D structure, 2D structure, or descriptors of global properties, by means of self-organizing maps, random forests, and classification trees. The overlap between metabolites and non-metabolites was observed to be the least in the space defined by the global descriptors, the most discriminatory features being the number of OH groups, presence of aromatic systems, and molecular weight. Discrimination between the two datasets was achieved with accuracy up to 97%. Models were built to produce a metabolite-likeness parameter. A relationship between metabolite-likeness and ready biodegradability was observed.
KeywordsChemical diversity Chemoinformatics Computer chemistry Metabolism Neural networks
- CPG NN
Counterpropagation neural network
Japanese Ministry of International Trade and Industry
Radial distribution function
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S. Gupta acknowledges Fundação para a Ciência e Tecnologia (Lisbon, Portugal) for the postdoctoral grant SFRH/BPD/14475/2003 co-funded by the POCI 2010 EU program. Molecular Networks GmbH (Erlangen, Germany) is acknowledged for access to PETRA and CORINA software packages. The authors thank Dr Robert Boethling for assistance with the MITI data.
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