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

Abstract

Over the past decades the description of quantitative structure–activity relationships (QSARs) has been undertaken in order to find predictive models and/or mechanistic explanations for chemical as well as biological activities. This includes QSAR studies in toxicology. In an approach beyond the classical QSAR approaches, attempts have been made to define parameters for the QSAR studies on the basis of quantum mechanical computer calculations. The conversion of relatively small xenobiotics within the active sites of biotransformation enzymes can be expected to follow the general rules of chemistry. This makes the description of QSARs on the basis of only one parameter, chosen on the basis of insight in the mechanism, feasible. In contrast, toxicological endpoints can very often be the result of more than one physico-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-based QSAR modeling for analyzing experimental toxicological data, with emphasis on examples from the field of biotransformation and toxicity.