Identification of in vitro angiotensin-converting enzyme and dipeptidyl peptidase IV inhibitory peptides from draft beer by virtual screening and molecular docking

Discovery of novel dipeptidyl peptidase-IV inhibitory peptides derived from walnut protein and their bioactivities in vivo and in vitro

The inhibition of dipeptidyl peptidase IV (DPP-IV) has been regarded as a major target for treating type-2 diabetes (T2D). Food-derived peptides are a great source of DPP-IV inhibitory peptides. In this study, we utilized walnut protein as the raw material and hydrolyzed it using four different proteases. The trypsin hydrolysate exhibited the highest DPP-IV inhibitory activity. A DEAE-52 anion exchange column and a Sephadex G-25 gel filtration column were used to sequentially separate and purify the enzymatic hydrolysates. Mass spectrometry identified 117 peptide sequences, of which LPFA, VPFWA, and WGLP were three highly active DPP-IV inhibitory peptides. Molecular docking results revealed that three peptides primarily bind tightly to DPP-IV through hydrogen bonds and van der Waals forces. The inhibitory activity and absorption transport of the peptides were examined using a Caco-2 cell model. LPFA, VPFWA, and WGLP could cross the Caco-2 cell monolayer intact, with in situ IC50s of 267.9 ± 7.2 μM, 325.0 ± 8.4 μM, and 350.9 ± 8.3 μM, respectively. Oral glucose tolerance tests (OGTT) demonstrated that the three inhibitory peptides significantly improved glucose metabolism in normal ICR mice. This study establishes a theoretical basis for the high-value utilization of walnuts and the therapeutic treatment of T2D.

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.

Preparation, identification, and molecular docking of novel angiotensin-converting enzyme inhibitory peptides derived from rice-based distillers' spent cakes

BACKGROUND

Rice-based distillers' spent cake (RDSC), a by-product of the Chinese liquor (Baijiu) industry, is a potential source of angiotensin-converting enzyme (ACE) inhibitory peptide. Since ACE plays a crucial role in controlling hypertension, inhibition of ACE has been widely emphasized. The ACE inhibitory active peptide derived from by-products of food has been recognized as a safer and cheaper inhibitor.

RESULTS

Aimed to discover ACE-inhibiting active peptides in RDSC. Hydrolysis of RDSC by alcalase for 4 h followed by ultrafiltration yielded low-molecular-weight (< 3 kDa) fractions. Subsequently, a comprehensive method using a combination of liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) and LC-Q-Exactive-MS to identify the novel short peptides (3-5 amino acids residues; n = 7) and medium-sized peptides (more than 6 amino acids residues; n = 6). In vitro activity assay showed that the peptides KPFFPGL, GFPRPLL, GPPGVF, and VGK exhibited the highest activity with inhibitory concentration of 50% (IC50) of 11.63, 12.34, 19.55, and 33.54 μmol L-1. Molecular docking reveal that the active and inactive sites (Glu123, Asp121, Arg522, and Lys118) play important roles in enhancing the ACE inhibitory activity of peptides.

CONCLUSION

Here we report a comprehensive method that effectively extracted and identified the bioactive peptides from RDSC. Four highly active novel peptides may be the most promising candidates for functional foods against hypertension, provide significant information for enhancing value of rice-based distilled by-products. © 2024 Society of Chemical Industry.

Emerging production techniques and potential health promoting properties of plant and animal protein-derived bioactive peptides

Bioactive peptides (BPs) are short amino acid sequences that that are known to exhibit physiological characteristics such as antioxidant, antimicrobial, antihypertensive and antidiabetic properties, suggesting that they could be exploited as functional foods in the nutraceutical industry. These BPs can be derived from a variety of food sources, including milk, meat, marine, and plant proteins. In the past decade, various methods including in silico, in vitro, and in vivo techniques have been explored to unravel underlying mechanisms of BPs. To forecast interactions between peptides and their targets, in silico methods such as BIOPEP, molecular docking and Quantitative Structure-Activity Relationship modeling have been employed. Additionally, in vitro research has examined how BPs affect enzyme activities, protein expressions, and cell cultures. In vivo studies on the contrary have appraised the impact of BPs on animal models and human subjects. Hence, in the light of recent literature, this review examines the multifaceted aspects of BPs production from milk, meat, marine, and plant proteins and their potential bioactivities. We envisage that the various concepts discussed will contribute to a better understanding of the food derived BP production, which could pave a way for their potential applications in the nutraceutical industry.

Kinetic and thermodynamic-based studies on the interaction mechanism of novel R. roxburghii seed peptides against pancreatic lipase and cholesterol esterase

Pancreatic lipase (PL) and cholesterol esterase (CE) are vital digestive enzymes that regulate lipid digestion. Three bioactive peptides (LFCMH, RIPAGSPF, YFRPR), possessing enzyme inhibitory activities, were identified in the seed proteins of R. roxburghii. It is hypothesized that these peptides could inhibit the activities of these enzymes by binding to their active sites or altering their conformation. The results showed that LFCMH exhibited superior inhibitory activity against these enzymes compared to the other peptides. The inhibition mechanisms of the three peptides were identified as either competitive or mixed, according to inhibition models. Further studies have shown that peptides could bind to the active sites of enzymes, thus affecting their spatial conformation and restricting substrate entry into the active site. Molecular simulation further proved that hydrogen bonds and hydrophobic interactions played a vital role in the binding of peptides to enzymes. This study enriches our understanding of interaction mechanisms of peptides on PL and CE.

Health-promoting peptides in fermented beverages

Since ancient times, the consumption of fermented low-alcoholic beverages has enjoyed widespread popularity in various countries, because of their distinct flavors and health benefits. Several studies have demonstrated that light to moderate alcohol consumption is associated with beneficial effects on human health, mainly in cardiovascular disease prevention. Fermented beverages have different non-ethanol components that confer beneficial health effects. These bioactive compounds are mainly peptides that have often been overlooked or poorly explored in numerous fermented beverages. The aim of this review is to provide knowledge and generate interest in the biological activities of peptides that are present and/or released during the fermentation process of widely consumed traditional fermented beverages. Additionally, a brief description of the microorganisms involved in these beverages is provided. Furthermore, this review also explores topics related to the detection, isolation, and identification of peptides, addressing the structure-activity relationships of both antioxidant and angiotensin-converting enzyme inhibitory (ACE-I) activities.

Physiological Mechanisms by Which the Functional Ingredients in Beer Impact Human Health

Nutritional therapy, for example through beer, is the best solution to human chronic diseases. In this article, we demonstrate the physiological mechanisms of the functional ingredients in beer with health-promoting effects, based on the PubMed, Google, CNKI, and ISI Web of Science databases, published from 1997 to 2024. Beer, a complex of barley malt and hops, is rich in functional ingredients. The health effects of beer against 26 chronic diseases are highly similar to those of barley due to the physiological mechanisms of polyphenols (phenolic acids, flavonoids), melatonin, minerals, bitter acids, vitamins, and peptides. Functional beer with low purine and high active ingredients made from pure barley malt, as well as an additional functional food, represents an important development direction, specifically, ginger beer, ginseng beer, and coix-lily beer, as consumed by our ancestors ca. 9000 years ago. Low-purine beer can be produced via enzymatic and biological degradation and adsorption of purines, as well as dandelion addition. Therefore, this review paper not only reveals the physiological mechanisms of beer in overcoming chronic human diseases, but also provides a scientific basis for the development of functional beer with health-promoting effects.

Bioinformatics tools for the study of bioactive peptides from vegetal sources: evolution and future perspectives

Bioactive peptides from vegetal sources have been shown to have functional properties as anti-inflammatory, antioxidant, antihypertensive or antidiabetic capacity. For this reason, they have been proposed as an interesting and promising alternative to improve human health. In recent years, the numerous advances in the bioinformatics field for in silico prediction have speeded up the discovery of bioactive peptides, also reducing the associated costs when using an integrated approach between the classical and bioinformatics discovery. This review aims to provide an overview of the evolution, limitations and latest advances in the field of bioinformatics and computational tools, and specifically make a critical and comprehensive insight into computational techniques used to study the mechanism of interaction that allows the explanation of plant bioactive peptide functionality. In particular, molecular docking is considered key to explain the different functionalities that have been previously identified. The assumptions to simplify such a high complex environment implies a degree of uncertainty that can only be guaranteed and validated by in vitro or in vivo studies, however, the combination of databases, software and bioinformatics applications with the classical approach has become a promising procedure for the study of bioactive peptides.

In Silico Screening of Bioactive Peptides in Stout Beer and Analysis of ACE Inhibitory Activity

Stout beer was selected as the research object to screen angiotensin-converting enzyme (ACE) inhibitory peptides. The peptide sequences of stout beer were identified using ultra-performance liquid chromatography-quadrupole-Orbitrap mass spectrometry with de novo, and 41 peptides were identified with high confidence. Peptide Ranker was used to score the biological activity and six peptides with a score ≥ 0.5 were screened to predict their potential ACE inhibitory (ACEI) activity. The toxicity, hydrophilicity, absorption, and excretion of these peptides were predicted. In addition, molecular docking between the peptides and ACE revealed a significant property of the peptide DLGGFFGFQR. Furthermore, molecular docking conformation and molecular dynamics simulation revealed that DLGGFFGFQR could be tightly bound to ACE through hydrogen bonding and hydrophobic interaction. Lastly, the ACEI activity of DLGGFFGFQR was confirmed using in vitro evaluation and the IC50 value was determined to be 24.45 μM.

Mining Bovine Milk Proteins for DPP-4 Inhibitory Peptides Using Machine Learning and Virtual Proteolysis

Dipeptidyl peptidase-IV (DPP-4) enzyme inhibitors are a promising category of diabetes medications. Bioactive peptides, particularly those derived from bovine milk proteins, play crucial roles in inhibiting the DPP-4 enzyme. This study describes a comprehensive strategy for DPP-4 inhibitory peptide discovery and validation that combines machine learning and virtual proteolysis techniques. Five machine learning models, including GBDT, XGBoost, LightGBM, CatBoost, and RF, were trained. Notably, LightGBM demonstrated superior performance with an AUC value of 0.92 ± 0.01. Subsequently, LightGBM was employed to forecast the DPP-4 inhibitory potential of peptides generated through virtual proteolysis of milk proteins. Through a series of in silico screening process and in vitro experiments, GPVRGPF and HPHPHL were found to exhibit good DPP-4 inhibitory activity. Molecular docking and molecular dynamics simulations further confirmed the inhibitory mechanisms of these peptides. Through retracing the virtual proteolysis steps, it was found that GPVRGPF can be obtained from β-casein through enzymatic hydrolysis by chymotrypsin, while HPHPHL can be obtained from κ-casein through enzymatic hydrolysis by stem bromelain or papain. In summary, the integration of machine learning and virtual proteolysis techniques can aid in the preliminary determination of key hydrolysis parameters and facilitate the efficient screening of bioactive peptides.

A novel ACE inhibitory peptide from Pelodiscus sinensis Wiegmann meat water-soluble protein hydrolysate

Pelodiscus sinensis meat is a nutritional food and tonic with angiotensin-converting enzyme (ACE) inhibitory activities. To identify the bioactive substances responsible, several bioinformatics methods were integrated to enable a virtual screening for bioactive peptides in proteins identified within a water-soluble protein fraction of Pelodiscus sinensis meat by Shotgun proteomics. The peptides were generated from the identified proteins by in silico proteolysis using six proteases. A comparison of the numbers of proteins suitable for digestion with each enzyme and the iBAQ (intensity-based absolute quantification) values for these proteins revealed that bromelain and papain were the most suitable proteases for this sample. Next, the water solubility, toxicity, and ADMET (absorption/distribution/metabolism/excretion/toxicity) properties of these peptides were evaluated in silico. Finally, a novel ACE inhibitory peptide IEWEF with an IC50 value of 41.33 µM was identified. The activity of the synthesized peptide was verified in vitro, and it was shown to be a non-competitive ACE inhibitor. Molecular docking revealed that IEWEF could tightly bind to C-ACE, and N-ACE with energies less than 0 kJ mol-1, and the peptide IEWEF can form hydrogen bonds with C-ACE and N-ACE respectively. These results provide evidence that bioactive peptides in the water-soluble protein fraction account for (at least) some of the ACE inhibitory activities observed in Pelodiscus sinensis meat. Furthermore, our research provides a workflow for the efficient identification of novel ACE inhibitory peptides from complex protein mixtures.

A novel angiotensin I-converting enzyme inhibitory peptide from walnut (Juglans sigillata) protein hydrolysates and its evaluation in Ang II-induced HUVECs and hypertensive rats

This study aims to seek angiotensin-I-converting enzyme inhibitory (ACEi) peptides from walnut using different enzymatic hydrolysis, and further to validate the potent ACEi peptides identified and screened via peptidomics and in silico analysis against hypertension in spontaneously hypertensive rats (SHRs). Results showed that walnut protein hydrolysate (WPH) prepared by combination of alcalase and simulated gastrointestinal digestion exhibited high ACEi activity. WPH was separated via Sephadex-G25, and four peptides were identified, screened and verified based on their PeptideRanker score, structural characteristic and ACE inhibition. Interestingly, FDWLR showed the highest ACEi activity with IC50 value of 8.02 μg/mL, which might be related to its close affinity with ACE observed in molecular docking. Subsequently, high absorption and non-toxicity of FDWLR was predicted via in silico absorption, distribution, metabolism, excretion and toxicity. Furthermore, FDWLR exhibited positively vasoregulation in Ang II-induced human umbilical vein endothelial cells, and great blood pressure lowering effect in SHRs.

Identification of Novel Peptides in Distillers' Grains as Antioxidants, α-Glucosidase Inhibitors, and Insulin Sensitizers: In Silico and In Vitro Evaluation

Distillers' grains are rich in protein and constitute a high-quality source of various bioactive peptides. The purpose of this study is to identify novel bioactive peptides with α-glucosidase inhibitory, antioxidant, and insulin resistance-ameliorating effects from distiller's grains protein hydrolysate. Three novel peptides (YPLPR, AFEPLR, and NDPF) showed good potential bioactivities, and the YPLPR peptide had the strongest bioactivities, whose IC50 values towards α-glucosidase inhibition, radical scavenging rates of 2,2'-azino-bis (3-ethylbenzothiazoline-6- sulfonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) were about 5.31 mmol/L, 6.05 mmol/L, and 7.94 mmol/L, respectively. The glucose consumption of HepG2 cells treated with YPLPR increased significantly under insulin resistance condition. Moreover, the YPLPR peptide also had a good scavenging effect on intracellular reactive oxygen species (ROS) induced by H2O2 (the relative contents: 102.35% vs. 100%). Molecular docking results showed that these peptides could stably combine with α-glucosidase, ABTS, and DPPH free radicals, as well as related targets of the insulin signaling pathway through hydrogen bonding and van der Waals forces. This research presents a potentially valuable natural resource for reducing oxidative stress damage and regulating blood glucose in diabetes, thereby increasing the usage of distillers' grains peptides and boosting their economic worth.

Effect of substrate composition on physicochemical properties of the medium-long-medium structured triacylglycerol

BACKGROUND

Nutritional and functional qualities and applications of structured lipids (SL) depend on the composition and molecular structure of fatty acids in the glycerol backbone of triacylglycerol (TAG). However, the relationship between the substrate composition and physicochemical qualities of SL has not been revealed. The investigation aims to disclose the effect of substrate composition on the physicochemical properties of medium-long-medium structured lipids (MLM-SLs) by enzymatic interesterification of Lipozyme TLIM/RMIM.

RESULTS

The medium-long-chain triacylglycerol (MLCT) yield could reach 70.32%, including 28.98% CaLCa (1,3-dioctonyl-2-linoleoyl glyceride) and 24.34% CaOCa (1,3-didecanoyl-2-oleoyl glyceride). The sn-2 unsaturated fatty acid composition mainly depended on long-chain triacylglycerol (LCT) in the substrate. The increased carbon chain length and double bond in triacylglycerol decreased its melting and crystallization temperature. The balanced substrate composition of MCT/LCT increased the size and finer crystals. Molecular docking simulation revealed that the MLCT molecule mainly interacted with the catalytic triplets of Lipozyme TLIM (Arg81-Ser83-Arg84) and the Lipozyme RMIM (Tyr183-Thr226-Arg262) by OH bond. The oxygen atom of the ester on the MLCT molecule was primarily bound to the hydrogen of hydroxyl and amino groups on the binding sites of Lipozyme TLIM/RMIM. The intermolecular interplay between MLCT and Lipozyme RMIM is more stable than Lipozyme TLIM due to the formation of lower binding affinity energy.

CONCLUSION

This research clarifies the interaction mechanism between MLCT molecules and lipases, and provides an in-depth understanding of the relationship between substrate composition, molecular structure and physicochemical property of MLM-SLs. © 2023 Society of Chemical Industry.

Identification of Novel Umami Peptides in Termitornyces albuminosus (Berk) Heim Soup by In Silico Analyses Combined with Sensory Evaluation: Discovering Potential Mechanism of Umami Taste Formation with Molecular Perspective

In this study, 24 peptides were identified in Termitornyces albuminosus (Berk) Heim soup, 12 of which were predicted to possess an umami taste based on the BIOPEP-UWM or Umami-MRNN databases. Among these 12 peptides, four peptides (i.e., QNDF, QGGDF, EPVTLT, and EVNYDFGGK) exhibited the lowest affinity energy with the umami receptor type 1 member 1 (T1R1) subunit. Molecular docking and molecular dynamics simulation further confirmed the strong binding of these four umami peptides to the umami receptor T1R1/T1R3, with the EVNYDFGGK forming the most stable complex. After synthesizing the four peptides, their umami taste was validated through sensory and electronic tongue analyses with recognition thresholds ranging from 0.0938 to 0.3750 mmol/L. Notably, the EVNYDFGGK peptide displayed the strongest umami taste (recognition threshold, 0.0938 mmol/L). This study may contribute to the industrial development of T. albuminosus by providing a new understanding of the mechanism of its umami formation.

Isolation and Identification of a Novel Anti-Dry Eye Peptide from Tilapia Skin Peptides Based on In Silico, In Vitro, and In Vivo Approaches

Tilapia skin is a great source of collagen. Here, we aimed to isolate and identify the peptides responsible for combating dry eye disease (DED) in tilapia skin peptides (TSP). In vitro cell DED model was used to screen anti-DED peptides from TSP via Sephadex G-25 chromatography, LC/MS/MS, and in silico methods. The anti-DED activity of the screened peptide was further verified in the mice DED model. TSP was divided into five fractions (TSP-I, TSP-II, TSP-III, TSP-IV, and TSP-V), and TSP-II exerted an effective effect for anti-DED. A total of 131 peptides were identified using LC/MS/MS in TSP-II, and NGGPSGPR (NGG) was screened as a potential anti-DED fragment in TSP-II via in silico methods. In vitro, NGG restored cell viability and inhibited the expression level of Cyclooxygenase-2 (COX-2) protein in Human corneal epithelial cells (HCECs) induced by NaCl. In vivo, NGG increased tear production, decreased tear ferning score, prevented corneal epithelial thinning, alleviated conjunctival goblet cell loss, and inhibited the apoptosis of corneal epithelial cells in DED mice. Overall, NGG, as an anti-DED peptide, was successfully identified from TSP, and it may be devoted to functional food ingredients or medicine for DED.

Purification and characterization of the dipeptidyl peptidase-IV inhibitory peptides from eel (Anguilla rostrata) scraps enzymatic hydrolysate for the treatment of type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a serious threat to human health. Owing to the action of dipeptidyl peptidase-IV (DPP-IV), the half-life of entero-insulin hormone after secretion is extremely short, causing insufficient insulin secretion in diabetic patients. Dipeptidyl peptidase-IV inhibitors can be used as a new treatment for T2DM. In this study, the proteins of eel (Anguilla rostrata) scraps hydrolyzed using Protamex protease (EPHs) were found to have strong DPP-IV inhibitory activity. The study also provided research ideas for the development and utilization of A. rostrata scraps.

RESULTS

The median inhibition concentration (IC₅₀ ) value of EPHs was 5.455 ± 0.24 mg mL^-1 . The peptide fractions with the highest DPP-IV inhibitory activity were sequentially separated by ultrafiltration, gel filtration chromatography (GFC), and reversed-phase high performance liquid chromatography (RP-HPLC) in a continuous hierarchical manner and analyzed using matrix-assisted laser desorption/ionization time-of-flight/ time-of-flight mass spectrometry/mass spectrometry (MALDI-TOF/TOF MS/MS). Three peptides that revealed significant inhibitory activity were screened among the identified sequences, with sequences of Phe-Pro-Arg (IC₅₀  = 62.14 ± 1.47 μM), Tyr-Pro-Pro-Ser-Phe-Ser (IC₅₀  = 102.65 ± 4.57 μM), and Tyr-Pro-Tyr-Pro-Ala-Ser (IC₅₀  = 68.30 ± 3.85 μM). Molecular docking simulations revealed that their inhibitory effect was mainly due to the formation of hydrogen bonds with amino acid residues in the active sites of DPP-IV. Analysis of the inhibition patterns of the synthetic peptides displayed that Phe-Pro-Arg and Tyr-Pro-Pro-Ser-Phe-Ser displayed competitive inhibition, whereas Tyr-Pro-Tyr-Pro-Ala-Ser showed mixed competitive/non-competitive inhibition.

CONCLUSIONS

The protein hydrolysates isolated from eel scraps are potential functional food ingredients for the treatment of T2DM. © 2023 Society of Chemical Industry.

BIOPEP-UWM Virtual—A Novel Database of Food-Derived Peptides with In Silico-Predicted Biological Activity

The novel BIOPEP-UWM Virtual database is designed as a repository of peptide sequences whose bioactivity or taste information was the result of in silico predictions. It is a tool complementary to the existing BIOPEP-UWM database summarizing the results of experimental data on bioactive peptides. The layout and organization of the new database are identical to those of the existing BIOPEP-UWM database of bioactive peptides. The peptide data record includes the following information: name; sequence and function information (understood as information about the predicted target biomacromolecule); bibliographic data with the reference paper describing the peptide; additional information, including the peptide structure, annotated using chemical codes as well as the specification of the method used for bioactivity prediction; information about other activities discovered experimentally or predicted using computational methods; peptide taste (if available); and a database reference tab providing information about compound annotations in other databases (if available).