Integrated Computational Methods for Prediction of the Lowest Observable Adverse Effect Level of Food‐Borne Molecules

Abstract

AbstractIn 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.