Computer-Aided Approaches for Screening Antioxidative Dipeptides and Application to Sorghum Proteins

Abstract

There has been a growing interest in extracting antioxidant peptides from food proteins. This study aimed to develop efficient computer-aided approaches to accelerate the screening efficiency of antioxidative dipeptides. A newly developed quantitative structure–activity relationship model and an improved hydrolysis simulation tool, R-PeptideCutter, were applied to screen high-activity dipeptides in sorghum kafirin. The R2Test and MSETest values were 0.6082, 0.6764 and 0.5302, 0.5467, respectively, for 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonate) (ABTS) radical scavenging capacity and oxygen radical absorbance capacity (ORAC) models. N-terminus residues dominated the antioxidant activity, especially in the ABTS assay, and Y and W at the N-terminus strongly corresponded to higher activity in both assays. The dipeptide YR was predicted as the strongest antioxidant in kafirin (3.352/2.099 μmol Trolox/μmol peptide for ABTS/ORAC activity). Eight kafirin-derived dipeptides were synthesized for model validation. The corresponding ORAC model achieved greater prediction performance, while the ABTS radical scavenging capacity model showed an underestimation in prediction. The improved tool and knowledge can be applied to other proteins and benefit the research and development on antioxidant peptides.