Toxicity predictions as risk assessments of food additives by in silico approaches

In silico methodologies, such as quantitative structure-activity relationships (QSARs), allow the prediction of a wide variety of toxicological properties and biological activities for structurally diverse substances. Industrial food production brought along additives such as preservatives, food colors, and low-calorie sweeteners (LCSs). Food preservatives prevent the rotting of perishable food. Dyes are used as food additives and also in various clinical and medical applications. LCSs are increasingly replacing natural sugars as sweeteners. Such food amendments may cause human health effects particularly through their chronic consumption that need to be screened by various toxicological approaches. We used Marvin Sketch to draw the molecular structures and simplified molecular input line entry systems (SMILES) of food additives obtained from the PubChem database to evaluate their mutagenicity and carcinogenicity. The predictive tools LAZAR, pKCSM, Toxtree toxicity were used to assess the mutagenicity and carcinogenicity of selected food colors, preservatives, and LCSs based on literature surveys. The aims of this study were to predict mutagenicity and carcinogenicity of diverse food additives through different chemcomputational tools. In silico methods are among the most suitable tools for initial safety screening of chemicals. QSAR tools can provide useful solutions for risk assessments. They allow predictions for a large amount of structurally characterized, known or not as yet synthesized compounds, in a fast, reproducible, and relatively straightforward manner. Due to their resource- and time-saving characteristics, they are recognized as useful toxicity screening tools.