Identification of novel α-glucosidase inhibitory peptides in Meretrix meretrix Linnaeus and their inhibitory kinetics using in silico and in vitro analyses

This study aimed to identify novel peptides with α-glucosidase inhibitory activity from Meretrix meretrix Linnaeus hydrolysates (MMLHs) following simulated gastrointestinal digestion (SGD) and to elucidate their inhibitory mechanisms. The molecular weight distribution of MMLHs progressively decreased during SGD, with hydrolysates from the intestinal digestion phase (MMLHs-I) exhibiting the strongest α-glucosidase inhibition (IC50: 0.14 ± 0.02 mg/mL). A total of 127 peptides were identified in MMLHs-I, among which 58 were unique compared to those from the gastric digestion phase. In silico screening and molecular docking identified six novel peptides-FAGDDAPR, VPLF, YRRL, WDH, PPLA, and WSG-with significant α-glucosidase inhibitory activity, displaying IC50 values of 0.90, 1.30, 1.90, 1.20, 1.00, and 1.80 mg/mL, respectively. Among them, FAGDDAPR and PPLA exhibited the highest bioactivity. Kinetic analysis and fluorescence quenching assays demonstrated that both peptides acted as mixed-type inhibitors, forming stable complexes with α-glucosidase. Their inhibitory effects were primarily driven by hydrogen bonding and hydrophobic interactions, which hindered substrate binding and induced conformational changes in the enzyme. These findings suggest that peptides derived from MMLHs through gastrointestinal digestion possess potential antidiabetic properties, highlighting their promise as functional food ingredients for mitigating hyperglycemic damage.

MDPAO1 peptide from human milk enhances brown adipose tissue thermogenesis and mitigates obesity

The regulatory effect of breastfeeding on offspring metabolism has garnered significant attention as an effective strategy in combating childhood obesity. However, the underlying mechanism remains largely unknown. Through integrated analysis of multiple human milk peptide databases and functional screening, MDPAO1 (milk-derived peptide associated with obesity 1) was identified as having potential activity in promoting the expression of thermogenic genes. In lactating mice, intervention with MDPAO1 enhanced the thermogenic phenotype of brown adipose tissue (BAT) and overall metabolic activity. Moreover, MDPAO1 intervention led to reduced body weight gain, increased brown fat mass, and improved glucose tolerance and insulin sensitivity in a mouse model of high-fat diet (HFD)-induced obesity. RNA-seq analysis of BAT post-MDPAO1 intervention revealed close association with mitochondrial oxidative respiratory chain and mitophagy. Subsequent in vitro experiments conducted on primary brown adipocytes confirmed that MDPAO1 inhibited mitophagy, increased mitochondrial mass, and elevated levels of mitochondrial respiratory chain complexes. In conclusion, this study underscores the potential of MDPAO1, a peptide enriched in breast milk, in activating the thermogenic phenotype of brown adipose tissue and mitigating obesity, thus offering novel insights into the mechanisms underlying breastfeeding's role in preventing childhood obesity.

Hybridization Design and High-Throughput Screening of Peptides with Immunomodulatory and Antioxidant Activities

With the increasing recognition of the role of immunomodulation and oxidative stress in various diseases, designing peptides with both immunomodulatory and antioxidant activities has emerged as a promising therapeutic strategy. In this study, a hybridization design was applied as a powerful method to obtain multifunctional peptides. A total of 40 peptides with potential immunomodulatory and antioxidant activities were designed and screened. First, molecular docking was employed to screen peptides with a high binding affinity to MD2, a key receptor protein in the NFκB immune pathway. For the in vitro high-throughput screening, we constructed a reporter gene-based stable cell line, IPEC-J2-Lucia ARE cells, which was subsequently used to screen peptides with antioxidant activity. Furthermore, the biocompatibility, immunomodulatory, and antioxidant activities of these peptides were assessed. Among the candidates, the hybrid peptide VA exhibited the strongest immune-enhancing activity through the activation of the NF-κB pathway and significant antioxidant activity via the Nrf2-ARE pathway. Additionally, VA demonstrated protective effects against H2O2-induced oxidative damage in HepG2 cells. This study not only demonstrates the potential of peptide hybridization, but also develops a screening platform for multifunctional peptides. It provides a new tool for the treatment of autoimmune diseases and oxidative stress-related diseases.

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.