Computer-modeling-based SARs for analyzing experimental data on biotransformation and toxicity

Over the past decades the description of quantitative structure-activity re lationships (QSARs) has been undertaken in order to find predictive models and/or mechanistic explanations for chemical as well as biological activiti es. This includes QSAR studies in toxicology. In an approach beyond the cla ssical QSAR approaches, attempts have been made to define parameters for th e QSAR studies on the basis of quantum mechanical computer calculations. Th e conversion of relatively small xenobiotics within the active sites of bio transformation enzymes can be expected to follow the general rules of chemi stry. This makes the description of QSARs on the basis of only one paramete r, chosen on the basis of insight in the mechanism, feasible. In contrast, toxicological endpoints can very often be the result of more than one physi co-chemical interaction of the compound with the model system of interest. Therefore the description of quantitative structure-toxicity relationships often does not follow a one-descriptor mechanistic approach but starts from the other end, describing QSARs by multi-parameter approaches. The present paper focuses on the possibilities and restrictions of using computer-base d QSAR modeling for analyzing experimental toxicological data, with emphasi s on examples from the field of biotransformation and toxicity. (C) 2001 El sevier Science Ltd. All rights reserved.