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 com
pound 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 toxici
ty and metabolism prediction in collaboration with industry and regulatory
authorities. These systems, DEREK, StAR and METEOR, use rules to describe t
he 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 predicti
ons for a novel set of compounds and comparing them to their biological ass
ay results as a measure of the system's performance. For example, 266 non-c
ongeneric chemicals from the National Toxicology Program database have been
processed through the DEREK mutagenicity knowledge base and the prediction
s compared to their Salmonella typhimurium mutagenicity data. Initially, 81
of 114 mutagens (71%) and 117 of 152 non-mutagens (77%) were correctly ide
ntified. Following further knowledge base development, the number of correc
tly identified mutagens has increased to 96 (84%). Further work on improvin
g the predictive capabilities of DEREK, StAR and METEOR is in progress.