Author(s): Greene N, Judson PN, Langowski JJ, Marchant CA
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Abstract It has long been recognised that the ability to predict the metabolic fate of a chemical substance and the potential toxicity of either the parent compound or its metabolites are important in novel drug design. The popularity of using computer models as an aid in this area has grown considerably in recent years. LHASA Limited has been developing knowledge-based expert systems for toxicity and metabolism prediction in collaboration with industry and regulatory authorities. These systems, DEREK, StAR and METEOR, use rules to describe the relationship between chemical structure and either toxicity in the case of DEREK and StAR, or metabolic fate in the case of METEOR. The rule refinement process for DEREK often involves assessing the predictions for a novel set of compounds and comparing them to their biological assay results as a measure of the system's performance. For example, 266 non-congeneric chemicals from the National Toxicology Program database have been processed through the DEREK mutagenicity knowledge base and the predictions compared to their Salmonella typhimurium mutagenicity data. Initially, 81 of 114 mutagens (71\%) and 117 of 152 non-mutagens (77\%) were correctly identified. Following further knowledge base development, the number of correctly identified mutagens has increased to 96 (84\%). Further work on improving the predictive capabilities of DEREK, StAR and METEOR is in progress.
This article was published in SAR QSAR Environ Res
and referenced in Journal of Petroleum & Environmental Biotechnology