IN SILICO TOXICITY PREDICTION OF ANTIOXIDANT FOOD ADDITIVES

• Main Author: Setia Permana, Jajat
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/45295
• Institution: Institut Teknologi Bandung

Antioxidant food additives are used to prevent or slowing down the oxidation process in foods. European Food Safety Authority (EFSA) by EC257/2010 regulation set up a programme for reevaluation of approved antioxidant food additives. Safety of the food additive was one of its concern. The aim of the present research was to predict toxicity of antioxidant food additives using in silico toxicity prediction as preliminary evaluation of safety antioxidant food additives. The in silico prediction was conducted for acute toxicity (LD50), mutagenicity, carcinogenicity, reproduction toxicity, chronic toxicity (NOEL), Acceptable Daily Intake (ADI) value and metabolit toxicity. The applied software for the study were Toxtree, TEST, Admet Predictor and OECD QSAR Toolbox. Among 42 antioxidant food additives, the prediction methods predict that 7 compounds as carcinogen (carnosic acid, citric acid, ethylene diamine tetra acetate, isopropyl citrate, octyl gallate, ascorbyl stearate and stearyl citrate); 2 compounds as mutagen (ascorbyl palmitate and 2,4,5-trihydroxybutyrophenone); 6 compounds as reproduction toxic (4 hexyl resorcinol, alpha tocopherol, delta tocopherol, ethoxyquine, gamma tocopherol, tertiary butyl hydroquinone); 2 compounds as carcinogen and reproduction toxic (butylated hydroxy anisole, isomer butylated hydroxy anisole); and 1 compound as mutagen and reproduction toxic, that is norhydroguairetic acid. Acute toxicity prediction was conducted by LD50 prediction. The lowest LD50 value was shown by ethoxyquine, 937.84 mg/kg, while the highest LD50 value was observed of dilauryl thiodipropionate, 13367.79 mg/kg. The comparison between LD50 prediction and LD50 experimental using paired t-test method. Showed that there is no significantly difference between predict LD50 and experimental LD50. Chronic toxicity prediction was conducted by NOEL value predcition, and ADI value was calculated from NOEL value. The compound with lowest ADI value is carnosic acid (0.38 mg/kg bw/day), while the highest ADI value was shown citric acid (1.67 mg/kg bw/day). The camparison between ADI prediction and ADI experimental using paired t-test method showed that there is no significant difference between predicted ADI and experimental ADI. Metabolite prediction was conducted using two software, that were Toxtree and Admet Predictor. The metabolite prediction showed a change in prediction result compared to its parent compound. In concluson, the in silico toxicity prediction method can be used as one supportive method to performe food additive safety evaluation by prediction of carcinogen, genotoxicity, reproduction toxicity, LD50 value and ADI value.