AnOxPePred: using deep learning for the prediction of antioxidative properties of peptides.

ABSTRACT: Dietary antioxidants are an important preservative in food and have been suggested to help in disease prevention. With consumer demands for less synthetic and safer additives in food products, the food industry is searching for antioxidants that can be marketed as natural. Peptides derived from natural proteins show promise, as they are generally regarded as safe and potentially contain other beneficial bioactivities. Antioxidative peptides are usually obtained by testing various peptides derived from hydrolysis of proteins by a selection of proteases. This slow and cumbersome trial-and-error approach to identify antioxidative peptides has increased interest in developing computational approaches for prediction of antioxidant activity and thereby reduce laboratory work. A few antioxidant p

SUBMITTER: Olsen TH 

PROVIDER: S-EPMC7722737 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature