A novel method for exploration and prediction of the bioactive target of rice bran-derived peptide (KF-8) by integrating computational methods and experiments

The investigation into the bioactive peptide's activity and target action poses a significant challenge in the field of food. An active peptide prepared from rice bran, KF-8, was confirmed to possess antioxidant activity in our previous study, but the specific target was unclear. This study used eight target prediction tools based on artificial intelligence and chemoinformatics to preliminarily screen potential antioxidant targets by integrating different computational methods. Then five different types of docking software were comparatively analyzed to further clarify their interaction sites and possible modes of action. The results showed that SIRT1 and CXCR4 are potential antioxidant targets of KF-8. Different docking software suggested that KF-8 interacts with SIRT1 and CXCR4 as major residues. Meanwhile, the results of Immunofluorescence co-localization experiments showed that the co-localization coefficients of KF-8 with SIRT1 and CXCR4 reached 0.5879 and 0.5684. This study provides new alternative means for the discovery of active peptide targets. The diagram of the strategy to explore peptide targets based on model predictions and experiments.