Development of QSARs for Cysteine-containing di- and tripeptides with antioxidant activity. Influence of the cysteine position

Abstract Antioxidants agents play an essential role in the food industry improving the oxidative stability of food products. In the last years, the search for new natural antioxidants has increased due to the potential high toxicity of chemical additives. Therefore, the synthesis and evaluation of the antioxidant activity in peptides is a field of current research. In this study, we performed a Quantitative Structure Activity Relationship analysis (QSAR) of cysteine-containing 19 dipeptides and 19 tripeptides. The main objective is to bring information on the relationship between the structure of peptides and their antioxidant activity. For this purpose, 1D and 2D molecular descriptors were calculated using the PaDEL software, which provide information about the structure, shape, size, charge, polarity, solubility and other aspects of the compounds. Different QSAR model for di- and tripeptides were developed. The statistic parameter for di-peptides model (R2train = 0.947 and R2test = 0.804) and for tripeptide models (R2train = 0.863 and R2test = 0.789) indicate that the generated models have high predictive capacity. Then, the influence of the cysteine position was analyzed predicting the antioxidant activity for new di- and tripeptides, and comparing with glutathione.