Integrated Computational Methods for Prediction of the Lowest Observable Adverse Effect Level of Food‐Borne Molecules
Leila Tilaoui, Benoı̂t Schilter, Liên-Anh Tran, Paolo Mazzatorta, Martin Grigorov · QSAR & Combinatorial Science · 2006
Abstract In this work we present an integrated system partly based on the commercially available software TOPKAT, which predicts chronic toxicity through provision of a computational estimation of Lowest Observed Adverse Effect Level (LOAEL) values. We found evidence that the LOAEL correlated with a specific class of molecular descriptors, known as 2D autocorrelation descriptors. The system developed is found to be helpful in supporting – with reasonable confidence – the prioritisation of issues in chemical food research, by establishing levels of safety concern in the absence of sufficient experimental toxicological data.