Recent progress in the preparation of bioactive peptides using simulated gastrointestinal digestion processes

Bioactive peptides (BAPs) represent a unique class of peptides known for their extensive physiological functions and their role in enhancing human health. In recent decades, owing to their notable biological attributes such as antioxidant, antihypertensive, antidiabetic, and anti-inflammatory activities, BAPs have received considerable attention. Simulated gastrointestinal digestion (SGD) is a technique designed to mimic physiological conditions by adjusting factors such as digestive enzymes and their concentrations, pH levels, digestion duration, and salt content. Initially established for analyzing the gastrointestinal processing of foods or their constituents, SGD has recently become a preferred method for generating BAPs. The BAPs produced via SGD often exhibit superior biological activity and stability compared with those of BAPs prepared via other methods. This review offers a comprehensive examination of the recent advancements in BAP production from foods via SGD, addressing the challenges of the method and outlining prospective directions for further investigation.

Discovery of potential antidiabetic peptides using deep learning

Antidiabetic peptides (ADPs), peptides with potential antidiabetic activity, hold significant importance in the treatment and control of diabetes. Despite their therapeutic potential, the discovery and prediction of ADPs remain challenging due to limited data, the complex nature of peptide functions, and the expensive and time-consuming nature of traditional wet lab experiments. This study aims to address these challenges by exploring methods for the discovery and prediction of ADPs using advanced deep learning techniques. Specifically, we developed two models: a single-channel CNN and a three-channel neural network (CNN + RNN + Bi-LSTM). ADPs were primarily gathered from the BioDADPep database, alongside thousands of non-ADPs sourced from anticancer, antibacterial, and antiviral peptide datasets. Subsequently, data preprocessing was performed with the evolutionary scale model (ESM-2), followed by model training and evaluation through 10-fold cross-validation. Furthermore, this work collected a series of newly published ADPs as an independent test set through literature review, and found that the CNN model achieved the highest accuracy (90.48 %) in predicting the independent test set, surpassing existing ADP prediction tools. Finally, the application of the model was considered. SeqGAN was used to generate new candidate ADPs, followed by screening with the constructed CNN model. Selected peptides were then evaluated using physicochemical property prediction and structural forecasts for pharmaceutical potential. In summary, this study not only established robust ADP prediction models but also employed these models to screen a batch of potential ADPs, addressing a critical need in the field of peptide-based antidiabetic research.

Antidiabetic effects of protein hydrolysates from Trachinotus ovatus and identification and screening of peptides with α-amylase and DPP-IV inhibitory activities

In the present study, the antidiabetic properties of Trachinotus ovatus protein hydrolysates (TOH) in streptozotocin-induced diabetic mice were investigated, and peptides with α-amylase (AAM) and dipeptidyl peptidase IV (DPP-IV) inhibitory activities were identified and screened. The results showed that TOH alleviated body weight loss, polyphagia, blood glucose elevation and insulin secretion decline in diabetic mice. After 4 weeks of TOH administration, random blood glucose (RBG) decreased significantly. The TOH groups showed a dose-dependent reduction in fasting blood glucose (FBG), especially in the high-dose TOH group, which reduced FBG by 58% versus the effect of metformin. Moreover, TOH exerted a remarkable protective effect on hepatorenal function, as evidenced by increased superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPX) and decreased serum urea levels. Histopathological studies confirmed that TOH can significantly protect the kidney and pancreas from histological changes, which was of great benefit for ensuring the normal secretion of insulin and preventing the occurrence of complications such as diabetic nephropathy. Two fractions with higher inhibitory activity against AAM and DPP-IV, F4 and F6, were obtained from the ultrafiltration of TOH-2 (≤3 kDa). A total of 19 potentially active peptides from F4 and 3 potentially active peptides from F6 were screened by LC‒MS/MS combined with bioinformatic analysis. These peptides are small molecular peptides composed of 2-6 amino acids, rich in characteristic amino acids such as proline, arginine, phenylalanine and asparagine, and contain high proportions of peptides (68% for F4, 67% for F6) with hydrophobicity ≥50%. They offer potent antidiabetic potential and could potentially bind to the active sites in the internal cavities of the target enzymes AAM and DPP-IV. In summary, this study revealed for the first time the antidiabetic effects of protein hydrolysates of Trachinotus ovatus and their derived peptides, which are promising natural ingredients with the potential to be used for the treatment or prevention of diabetes.