Characterization of structure–antioxidant activity relationship of peptides in free radical systems using QSAR models: Key sequence positions and their amino acid properties

Characterization and relationship analysis of antioxidant and anti-inflammatory peptides in pomelo fruitlet albumin

Several macromolecules from the pomelo fruitlet (PF) have demonstrated functional potential in previous research. In this study, pomelo fruitlet albumin (PFA) was extracted from PF, its anti-inflammatory and antioxidant properties were assessed using enzyme-linked immunosorbent assays, and its capacity to clear free radicals was measured. Meanwhile, we hypothesize that the amino acid sequence may affect the anti-inflammatory and antioxidant properties, and the two may rely on common significant sites within the amino acid sequence. Therefore, we analyzed the amino acid sequence using a quantitative structure-activity relationship model to explore the connection between the antioxidant and anti-inflammatory capacities of PFA. Both capacities were closely associated with six sites within the amino acid sequence. Collectively, this study illustrates that PFA exhibits both anti-inflammatory and antioxidant capacities, with six specific sites identified as significantly affecting both activities.

Potential of Marine Bacterial Metalloprotease A69 in the Preparation of Peanut Peptides with Angiotensin-Converting Enzyme (ACE)-Inhibitory and Antioxidant Properties

Marine bacterial proteases have rarely been used to produce bioactive peptides, although many have been reported. This study aims to evaluate the potential of the marine bacterial metalloprotease A69 from recombinant Bacillus subtilis in the preparation of peanut peptides (PPs) with antioxidant activity and angiotensin-converting enzyme (ACE)-inhibitory activity. Based on the optimization of the hydrolysis parameters of protease A69, a process for PPs preparation was set up in which the peanut protein was hydrolyzed by A69 at 3000 U g-1 and 60 °C, pH 7.0 for 4 h. The prepared PPs exhibited a high content of peptides with molecular weights lower than 1000 Da (>80%) and 3000 Da (>95%) and contained 17 kinds of amino acids. Moreover, the PPs displayed elevated scavenging of hydroxyl radical and 1,1-diphenyl-2-picryl-hydrazyl radical, with IC50 values of 1.50 mg mL-1 and 1.66 mg mL-1, respectively, indicating the good antioxidant activity of the PPs. The PPs also showed remarkable ACE-inhibitory activity, with an IC50 value of 0.71 mg mL-1. By liquid chromatography mass spectrometry analysis, the sequences of 19 ACE inhibitory peptides and 15 antioxidant peptides were identified from the PPs. These results indicate that the prepared PPs have a good nutritional value, as well as good antioxidant and antihypertensive effects, and that the marine bacterial metalloprotease A69 has promising potential in relation to the preparation of bioactive peptides from peanut protein.

Machine learning methods for unveiling the potential of antioxidant short peptides in goat milk-derived proteins during in vitro gastrointestinal digestion

Milk serves as an important dietary source of bioactive peptides, offering notable benefits to individuals. Among the antioxidant short peptides (di- and tripeptides) generated from gastrointestinal digestion are characterized by enhanced bioavailability and bioaccessibility, while assessing them individually presents a labor-intensive and expensive challenge. Based on 4 distinct types of amino acid descriptors (physicochemical, 3D structural, quantum, and topological attributes) and genetic algorithms for feature selection, 1 and 4 machine learning predicted models separately for di- and tripeptides with ABTS radical scavenging capacity exhibited excellent fitting and prediction ability with random forest regression as machine learning algorithm. Intriguingly, the electronic properties of N-terminal amino acid were considered as only factor affecting the antioxidant capacity of dipeptides containing both tyrosine and tryptophan. Four peptides from the potential di- and tripeptides exhibited highly predicted values by the constructed predicted models. Subsequently, a total of 45 dipeptides and 52 tripeptides were screened by a customized workflow in goat milk during in vitro simulated digestion. In addition to 5 known antioxidant dipeptides, 9 peptides were quantified during digestion, falling within the range of 0.04 to 1.78 mg L-1. Particularly noteworthy was the promising in vivo functionality of antioxidant dipeptides with N-terminal tyrosine, supported by in silico assays. Overall, this investigation explored crucial molecular properties influencing antioxidant short peptides and high-throughput screening potential peptides with antioxidant activity from goat milk aided by machine learning, thereby facilitating the identification of novel bioactive peptides from milk-derived proteins and paving the way for understanding their metabolites during digestion.

Collagen derived Gly-Pro-type DPP-IV inhibitory peptides: Structure-activity relationship, inhibition kinetics and inhibition mechanism

Our previous study has demonstrated that both the amino acid at N3 position and peptide length affected the DPP-IV inhibitory activity of Gly-Pro-type peptides. To further elucidate their molecular mechanism, a combined approach of QSAR modeling, enzymatic kinetics and molecular docking was used. Results showed that the QSAR models of Gly-Pro-type tripeptides and Gly-Pro-type peptides containing 3-12 residues were successfully constructed by 5z-scale descriptor with R2 of 0.830 and 0.797, respectively. The lower values of electrophilicity, polarity, and side-chain bulk of amino acid at N3 position caused higher DPP-IV inhibitory activity of Gly-Pro-type peptides. Moreover, an appropriate increase in the length of Gly-Pro-type peptides did not change their competitive inhibition mode, but decreased their inhibition constants (Ki values) and increased interactions with DPP-IV. More importantly, the interactions between the residues at C-terminal of Gly-Pro-type peptides containing 5 ∼ 6 residues with S2 extensive subsites (Ser209, Phe357, Arg358) of DPP-IV increased the interactions of Gly residue at N1 position with the S2 subsites (Glu205, Glu206, Asn710, Arg125, Tyr662) and decreased the acylation level of DPP-IV-peptide complex, and thereby increasing peptides' DPP-IV inhibitory activity.

Advances in Research on the Activity Evaluation, Mechanism and Structure-Activity Relationships of Natural Antioxidant Peptides

Antioxidant peptides are a class of biologically active peptides with low molecular weights and stable antioxidant properties that are isolated from proteins. In this review, the progress in research on the activity evaluation, action mechanism, and structure-activity relationships of natural antioxidant peptides are summarized. The methods used to evaluate antioxidant activity are mainly classified into three categories: in vitro chemical, in vitro cellular, and in vivo animal methods. Also, the biological effects produced by these three methods are listed: the scavenging of free radicals, chelation of metal ions, inhibition of lipid peroxidation, inhibition of oxidative enzyme activities, and activation of antioxidant enzymes and non-enzymatic systems. The antioxidant effects of natural peptides primarily consist of the regulation of redox signaling pathways, which includes activation of the Nrf2 pathway and the inhibition of the NF-κB pathway. The structure-activity relationships of the antioxidant peptides are investigated, including the effects of peptide molecular weight, amino acid composition and sequence, and secondary structure on antioxidant activity. In addition, four computer-assisted methods (molecular docking, molecular dynamics simulation, quantum chemical calculations, and the determination of quantitative structure-activity relationships) for analyzing the structure-activity effects of natural peptides are summarized. Thus, this review lays a theoretical foundation for the development of new antioxidants, nutraceuticals, and cosmetics.

Unlocking the Therapeutic Potential of a Manila Clam-Derived Antioxidant Peptide: Insights into Mechanisms of Action and Cytoprotective Effects against Oxidative Stress

Reactive oxygen species (ROS) are implicated in various pathological conditions due to their ability to induce oxidative damage to cellular components. In this study, we investigated the antioxidant properties of a peptide isolated from the hydrolysate of Manila clam (Ruditapes philippinarum) muscle. Purification steps yielded RPTE2-2-4, exhibiting potent scavenging activities against DPPH•, HO•, and O2•-, akin to Vitamin C. Structural analysis showed that the isolated peptide, LFKKNLLTL, exhibited characteristics associated with antioxidant activity, including a short peptide length and the presence of aromatic and hydrophobic amino acid residues. Moreover, our study demonstrated the cytoprotective effects of the peptide against H2O2-induced oxidative stress in HepG2 cells. Pretreatment with the peptide resulted in a dose-dependent reduction in intracellular ROS levels and elevation of glutathione (GSH) levels, indicating its ability to modulate cellular defense mechanisms against oxidative damage. Furthermore, the peptide stimulated the expression of the cytoprotective enzyme heme oxygenase-1 (HO-1), further reinforcing its antioxidant properties. Overall, our findings highlight the potential of the Manila clam-derived peptide as a natural antioxidant agent with therapeutic implications for oxidative stress-related diseases. Further investigation into its mechanisms of action and in vivo efficacy is warranted to validate its therapeutic potential.

Novel antioxidant peptides from sheep plasma protein hydrolysates: Purification, identification and cytoprotective effects against H2O2-induced oxidative stress

This study sought to purify and identify antioxidant peptides from sheep (Ovis aries) plasma protein hydrolysates and assess their protective impacts on H2O2-induced Caco-2 cells. The purification process involved reversed high-performance liquid chromatography, anion-exchange chromatography, and Sephadex G-25. Three peptides, namely Trp-Glu-Glu-Pro-Ala-Met (WEEPAM), Ser-Leu-His-Phe-Met-Glu (SLHFME), and His-Cys-Thr-Thr-Phe-Met-Ile, with molecular weights of 761.84, 762.87, and 852.03 Da, respectively, were identified by liquid chromatography with tandem mass spectrometry. Among the three antioxidant peptides, superoxide radical (O2 -) radical scavenging capacity of WEEPAM and SLHFME was not significantly different from glutathione (GSH) (p > 0.05), while their 1,1-diphenyl-2-picrylhydrazyl radical scavenging capacity was greater than GSH (p < 0.05). WEEPAM revealed increased antioxidant activity after pepsin and trypsin hydrolysis under an in vitro digestion model. In addition, WEEPAM inhibited oxidative damage in Caco-2 cells by significantly reducing reactive oxygen species accumulation, early apoptosis, malondialdehyde formation, and increasing intracellular superoxide dismutase, glutathione peroxidase, and catalase activities.

New Insights into Antioxidant Peptides: An Overview of Efficient Screening, Evaluation Models, Molecular Mechanisms, and Applications

Antioxidant peptides are currently a hotspot in food science, pharmaceuticals, and cosmetics. In different fields, the screening, activity evaluation, mechanisms, and applications of antioxidant peptides are the pivotal areas of research. Among these topics, the efficient screening of antioxidant peptides stands at the forefront of cutting-edge research. To this end, efficient screening with novel technologies has significantly accelerated the research process, gradually replacing the traditional approach. After the novel antioxidant peptides are screened and identified, a time-consuming activity evaluation is another indispensable procedure, especially in in vivo models. Cellular and rodent models have been widely used for activity evaluation, whilst non-rodent models provide an efficient solution, even with the potential for high-throughput screening. Meanwhile, further research of molecular mechanisms can elucidate the essence underlying the activity, which is related to several signaling pathways, including Keap1-Nrf2/ARE, mitochondria-dependent apoptosis, TGF-β/SMAD, AMPK/SIRT1/PGC-1α, PI3K/Akt/mTOR, and NF-κB. Last but not least, antioxidant peptides have broad applications in food manufacture, therapy, and the cosmetics industry, which requires a systematic review. This review introduces novel technologies for the efficient screening of antioxidant peptides, categorized with a new vision. A wide range of activity evaluation assays, encompassing cellular models, as well as rodent and non-rodent models, are provided in a comprehensive manner. In addition, recent advances in molecular mechanisms are analyzed with specific cases. Finally, the applications of antioxidant peptides in food production, therapy, and cosmetics are systematically reviewed.

Exploring the Potential of Bioactive Peptides: From Natural Sources to Therapeutics

Bioactive peptides, specific protein fragments with positive health effects, are gaining traction in drug development for advantages like enhanced penetration, low toxicity, and rapid clearance. This comprehensive review navigates the intricate landscape of peptide science, covering discovery to functional characterization. Beginning with a peptidomic exploration of natural sources, the review emphasizes the search for novel peptides. Extraction approaches, including enzymatic hydrolysis, microbial fermentation, and specialized methods for disulfide-linked peptides, are extensively covered. Mass spectrometric analysis techniques for data acquisition and identification, such as liquid chromatography, capillary electrophoresis, untargeted peptide analysis, and bioinformatics, are thoroughly outlined. The exploration of peptide bioactivity incorporates various methodologies, from in vitro assays to in silico techniques, including advanced approaches like phage display and cell-based assays. The review also discusses the structure-activity relationship in the context of antimicrobial peptides (AMPs), ACE-inhibitory peptides (ACEs), and antioxidative peptides (AOPs). Concluding with key findings and future research directions, this interdisciplinary review serves as a comprehensive reference, offering a holistic understanding of peptides and their potential therapeutic applications.

Identification, characterization and hypolipidemic effect of novel peptides in protein hydrolysate from Protaetia brevitarsis larvae

The proteins were mainly derived from Protaetia brevitarsis larval extracts obtained using two empty intestine methods (traditional static method: TSM or salt immersion stress method: SISM) and extraction solvents (water: W or 50 % water-ethanol: W:E), and the proteins were used as objects to investigate the effect of emptying intestine methods on hypolipidemic peptides. The results revealed that the F-2 fractions of protein hydrolysate had stronger in vitro hypolipidemic activity, with the peptides obtained by SISM possessing a stronger cholesterol micelle solubility inhibition rate, especially in SISM-W:E-P. Moreover, a total of 106 peptides were tentatively identified, among which SISM identified more peptides with an amino acid number < 8. Meanwhile, five novel peptides (YPPFH, YPGFGK, KYPF, SPLPGPR and VPPP) exhibited good hypolipidemic activity in vitro and in vivo, among which YPPFH, VPPP and KYPF had strong inhibitory activities on pancreatic lipase (PL) and cholesteryl esterase (CE), and KYPF, SPLPGPR and VPPP could significantly reduce the TG content in Caenorhabditis elegans. Thus, P. brevitarsis can be developed as a naturally derived hypolipidemic component for the development and application in functional foods.

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a "user guide" for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure-property relationships in soft materials.

Integration of machine learning in 3D-QSAR CoMSIA models for the identification of lipid antioxidant peptides

The comparative molecular similarity indices analysis (CoMSIA) method is a widely used 3D-quantitative structure-activity relationship (QSAR) approach in the field of medicinal chemistry and drug design. However, relying solely on the Partial Least Square algorithm to build models using numerous CoMSIA indices has, in some cases, led to statistically underperforming models. This issue has also affected 3D-CoMSIA models constructed for the ferric thiocyanate (FTC) dataset from linoleic antioxidant measurements. In this study, a novel modeling routine has been developed incorporating various machine learning (ML) techniques to explore different options for feature selection, model fitting, and tuning algorithms with the ultimate goal of arriving at optimal 3D-CoMSIA models with high predictivity for the FTC activity. Recursive Feature Selection and SelectFromModel techniques were applied for feature selection, resulting in a significant improvement in model fitting and predictivity (R2, RCV2, and R2_test) of 24 estimators. However, these selection methods did not fully address the problem of overfitting and, in some instances, even exacerbated it. On the other hand, hyperparameter tuning for tree-based models resulted in dissimilar levels of model generalization for four tree-based models. GB-RFE coupled with GBR (hyperparameters: learning_rate = 0.01, max_depth = 2, n_estimators = 500, subsample = 0.5) was the only combination that effectively mitigated overfitting and demonstrated superior performance (RCV2 of 0.690, R2_test of 0.759, and R2 of 0.872) compared to the best linear model, PLS (with RCV2 of 0.653, R2_test of 0.575, and R2 of 0.755). Therefore, it was subsequently utilized to screen potential antioxidants among a range of Tryptophyllin L tripeptide fragments, leading to the synthesis and testing of three peptides: F-P-5Htp, F-P-W, and P-5Htp-L. These peptides exhibited promising activity levels, with FTC values of 4.2 ± 0.12, 4.4 ± 0.11, and 1.72 ± 0.15, respectively.

Virtual screening, identification, and potential antioxidant mechanism of novel bioactive peptides during aging by a short-chain peptidomics, quantitative structure-activity relationship analysis, and molecular docking

Antioxidant peptides have received a great deal of attention. However, only a few studies have been conducted on the antioxidant peptides originating from Baijiu. A total of 1490 features deemed potential short-chain peptides (the amino acid number between 2 and 4, SCPs) were screened and analyzed by a customized short-chain peptidomics approach in Feng-flavor Baijiu (FFB) during 14 years of aging, with an obvious discrepancy between FFB aged for 3 years and 6 years being observed. Thirty-nine characteristic SCPs in total were identified and accurately quantified by high-throughput parallel reaction monitoring-based synthetic standards, with the contents ranging from 0.16 to 279.33 μg L-1. Combined with the absorption, distribution, metabolism, excretion, and toxicity analysis model, PGRW, WK, SC, and PAW, four novel antioxidant peptides with high ABTS radical scavenging capacity, were obtained using a customized quantitative structure-activity relationship (QSAR) model based on a two terminal position numbering method, with satisfied coefficients of determination (R2), internal cross-validated R2 (Q2), and external R2 (R2pre) of 0.925, 0.808, and 0.665, respectively. Furthermore, these 4 antioxidant peptides could block the Keap-Nrf2 interaction and promote the accumulation of Nrf2 by molecular docking analysis, and the interaction energy between peptide PGRW and Keap1 was higher than that between epigallocatechin gallate and Keap1 based on CHARMm forced field. Overall, this study facilitated the discovery of functional peptides in Baijiu and the understanding of aging mechanisms.

Contribution of Proteins and Peptides to the Impact of a Soy Protein Isolate on Oxidative Stress and Inflammation-Associated Biomarkers in an Innate Immune Cell Model

The innate and adaptative immune systems are involved in the regulation of inflammatory and oxidative processes and mediators such as reactive oxygen species (ROS) and nitric oxide (NO). The exacerbated action of these players results in an oxidative stress status and chronic inflammation, which is responsible for the development of non-communicable diseases (NCDs). By modulating these mediators, bioactive compounds in food can exert a key role in the prevention of several NCDs. Among these compounds, soybean proteins and peptides such as lunasin have been considered to be among the most promising. The aim of this study was to obtain and characterize a soluble protein-enriched extract from a commercial soybean protein isolate and fractionate it into different fractions through ultrafiltration. Their antioxidant and immunomodulatory properties were then evaluated using biochemical and cell models. A total of 535 proteins (from 282 protein groups) were identified in the extract, in which the presence of the peptide lunasin was confirmed. The enrichment of this peptide was achieved in the 3-10 kDa fraction. The protective effects against the oxidative stress induced by LPS in the macrophage model could have been mediated by the radical scavenging capacity of the peptides present in the soybean samples. Under basal conditions, the extract and its ultrafiltered fractions activated macrophages and induced the release of NO. However, under challenged conditions, the whole extract potentiated the NO-stimulating effects of LPS, whereas the fraction containing 3-10 kDa peptides, including lunasin, counteracted the LPS-induced NO increase. Our findings suggest a promising role of soybean protein as an ingredient for functional foods and nutraceuticals aimed at promoting health and preventing oxidative stress and/or immune-alteration-associated diseases.

Bioactivity of Macronutrients from Chlorella in Physical Exercise

Chlorella is a marine microalga rich in proteins and containing all the essential amino acids. Chlorella also contains fiber and other polysaccharides, as well as polyunsaturated fatty acids such as linoleic acid and alpha-linolenic acid. The proportion of the different macronutrients in Chlorella can be modulated by altering the conditions in which it is cultured. The bioactivities of these macronutrients make Chlorella a good candidate food to include in regular diets or as the basis of dietary supplements in exercise-related nutrition both for recreational exercisers and professional athletes. This paper reviews current knowledge of the effects of the macronutrients in Chlorella on physical exercise, specifically their impact on performance and recovery. In general, consuming Chlorella improves both anaerobic and aerobic exercise performance as well as physical stamina and reduces fatigue. These effects seem to be related to the antioxidant, anti-inflammatory, and metabolic activity of all its macronutrients, while each component of Chlorella contributes its bioactivity via a specific action. Chlorella is an excellent dietary source of high-quality protein in the context of physical exercise, as dietary proteins increase satiety, activation of the anabolic mTOR (mammalian Target of Rapamycin) pathway in skeletal muscle, and the thermic effects of meals. Chlorella proteins also increase intramuscular free amino acid levels and enhance the ability of the muscles to utilize them during exercise. Fiber from Chlorella increases the diversity of the gut microbiota, which helps control body weight and maintain intestinal barrier integrity, and the production of short-chain fatty acids (SCFAs), which improve physical performance. Polyunsaturated fatty acids (PUFAs) from Chlorella contribute to endothelial protection and modulate the fluidity and rigidity of cell membranes, which may improve performance. Ultimately, in contrast to several other nutritional sources, the use of Chlorella to provide high-quality protein, dietary fiber, and bioactive fatty acids may also significantly contribute to a sustainable world through the fixation of carbon dioxide and a reduction of the amount of land used to produce animal feed.

Prediction of antioxidant peptides using a quantitative structure-activity relationship predictor (AnOxPP) based on bidirectional long short-term memory neural network and interpretable amino acid descriptors

Antioxidant peptides can protect against free radical-mediated diseases, especially food-derived antioxidant peptides are considered as potential competitors among synthetic antioxidants due to their safety, high activity and abundant sources. However, wet experimental methods can not meet the need for effectively screening and clearly elucidating the structure-activity relationship of antioxidant peptides. Therefore, it is particularly important to build a reliable prediction platform for antioxidant peptides. In this work, we developed a platform, AnOxPP, for prediction of antioxidant peptides using the bidirectional long short-term memory (BiLSTM) neural network. The sequence characteristics of peptides were converted into feature codes based on amino acid descriptors (AADs). Our results showed that the feature conversion ability of the combined-AADs optimized by the forward feature selection method was more accurate than that of the single-AADs. Especially, the model trained by the optimal descriptor SDPZ27 significantly outperformed the existing predictor on two independent test sets (Accuracy = 0.967 and 0.819, respectively). The SDPZ27-based AnOxPP learned four key structure-activity features of antioxidant peptides, with the following importance as steric properties > hydrophobic properties > electronic properties > hydrogen bond contributions. AnOxPP is a valuable tool for screening and design of peptide drugs, and the web-server is accessible at http://www.cqudfbp.net/AnOxPP/index.jsp.

Comprehensive Evaluation and Comparison of Machine Learning Methods in QSAR Modeling of Antioxidant Tripeptides

Due to their multiple beneficial effects, antioxidant peptides have attracted increasing interest. Currently, the screening and identification of bioactive peptides, including antioxidative peptides based on wet-chemistry methods are time-consuming and highly rely on many advanced instruments and trained personnel. Quantitative structure-activity relationship (QSAR) analysis as an in silico method can be more efficient and cost-effective. However, model performance of QSAR studies on antioxidant peptides was still poor due to limited attempts in model development approaches. The objective of this study was to compare popular machine learning methods for antioxidant activity modeling and screening of tripeptides and identify the critical amino acid features that determine the antioxidant activity. 533 numerical indices of amino acids were adopted to characterize 130 tripeptides with known antioxidant activity from the published literature, and then 7 feature selection strategies plus pairwise correlation were used to screen the most important indices for antioxidant activity and model building. 14 machine learning methods were used to build models based on the feature selection strategies, respectively. Among the 98 models, non-linear regression methods tended to perform better, and the best model with an R ² _Test of 0.847 and RMSE_Test of 0.627 for tripeptide antioxidants was obtained by combining random forest for feature selection and tree-based extreme gradient boost regression for model development. Based on the predicted antioxidant values of 7870 unknown tripeptides, potentially high antioxidant activity tripeptides all have a tyrosine, tryptophan, or cysteine residue at the C-terminal position. Furthermore, the predicted antioxidant activity of six synthesized tripeptides was confirmed through experimental determination, and for the first time, the cysteine or tyrosine residue at the C-terminal was found to be critical to the antioxidant activity based on both QSAR models and experimental observations.

Health-Promoting and Therapeutic Attributes of Milk-Derived Bioactive Peptides

Milk-derived bioactive peptides (BAPs) possess several potential attributes in terms of therapeutic capacity and their nutritional value. BAPs from milk proteins can be liberated by bacterial fermentation, in vitro enzymatic hydrolysis, food processing, and gastrointestinal digestion. Previous evidence suggested that milk protein-derived BAPs have numerous health-beneficial characteristics, including anti-cancerous activity, anti-microbial activity, anti-oxidative, anti-hypertensive, lipid-lowering, anti-diabetic, and anti-osteogenic. In this literature overview, we briefly discussed the production of milk protein-derived BAPs and their mechanisms of action. Milk protein-derived BAPs are gaining much interest worldwide due to their immense potential as health-promoting agents. These BAPs are now used to formulate products sold in the market, which reflects their safety as natural compounds. However, enhanced commercialization of milk protein-derived BAPs depends on knowledge of their particular functions/attributes and safety confirmation using human intervention trials. We have summarized the therapeutic potentials of these BAPs based on data from in vivo and in vitro studies.

Development and sensory test of a dairy product with ACE inhibitory and antioxidant peptides produced at a pilot plant scale

A scale-up process was carried out to obtain potent bioactive peptides from whey protein through a simple hydrolysis process. The scale-up was satisfactory, with results similar to those obtained at lab scale: a fraction of peptides < 1 kDa with ACE inhibitory activity of 18.44 ± 2.47 μg/mL, a DPPH value of 69.40 ± 0.44%, and an ORAC value of 3.37 ± 0.03 μmol TE/mg protein. The peptide sequences responsible for the ACE inhibitory activity were also similar to those identified at lab scale: PM, LL, LF, HFKG and PT. The hydrolysate was used as a functional ingredient in a low-fat yoghurt. The consumer sensory taste panel found no significant difference (p > 0.05) between the bitterness of the control and the functional yoghurt, and about 50% of consumers would buy it. The hydrolysate maintained its bioactivities for 4 months at -20 °C (after thawing and pasteurisation), and for 1 week in yoghurt at 4 °C.

DFBP: A Comprehensive Database of Food-Derived Bioactive Peptides for Peptidomics Research

MOTIVATION

Food-derived bioactive peptides (FBPs) have demonstrated their significance in pharmaceuticals, diets, and nutraceuticals, benefiting public health and global ecology. While significant efforts have been made to discover FBPs and to elucidate the underlying bioactivity mechanisms, there is lack of a systemic study of sequence-structure-activity relationship of FBPs in a large dataset.

RESULTS

Here, we construct a database of food-derived bioactive peptides (DFBP), containing a total of 6276 peptide entries in 31 types from different sources. Further, we develop a series of analysis tools for function discovery/repurposing, traceability, multifunctional bioactive exploration, and physiochemical property assessment of peptides. Finally, we apply this database and data-mining techniques to discover new FBPs as potential drugs for cardiovascular diseases. The DFBP serves as a useful platform for not only the fundamental understanding of sequence-structure-activity of FBPs, but also the design, discovery, and repurposing of peptide-based drugs, vaccines, materials, and food ingredients.

AVAILABILITY AND IMPLEMENTATION

DFBP service can be accessed freely via http://www.cqudfbp.net/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Preparation and Antioxidant Properties of Germinated Soybean Protein Hydrolysates

In this study, soybeans during different germination stages were described and compared with regard to morphology, water content, protein, amino acids, and isoflavones. The optimal conditions for the hydrolysis of proteins obtained from germinated soybeans were determined using the response surface methodology. Gel filtration chromatography was used to separate germinated soybean protein hydrolysates after ultrafiltration, whereas 2,2-Diphenyl-1-picrylhydrazyl (DPPH), ABTS^•+, and FRAP assays were used to assess the antioxidant activity of different fractions. Findings of this study revealed that protein and isoflavone contents were high in soybean at 24 h following germination (the bud was about 0.5–1 cm). The proteins from germinated soybeans were hydrolyzed and separated into five fractions (G1–G5) and evaluated in terms of their molecular weight and antioxidant activity. Interestingly, the antioxidant activity was found to be higher in germinated soybean protein hydrolysates than in other soybean protein hydrolysates derived from soybean meal protein. This suggests that germination can effectively improve the utilization rate of soybean proteins. The antioxidant activity of G3 was best among G1–G5. The results obtained in this study demonstrate that germination for 24 h when the bud length is about 0.5–1 cm can be applied as a special pretreatment of plant seeds in the development of germinated foods. These findings can be used to identify the structure of the potential antioxidative hydrolysates for their possible exploitation in functional foods.

Bioactivities of Mealworm (Alphitobius diaperinus L.) Larvae Hydrolysates Obtained from Artichoke (Cynara scolymus L.) Proteases

In this study, we aimed to obtain hydrolysates with bioactive peptides from mealworm (Alphitobius diaperinus L.) larvae using an artichoke (Cynara scolymus L.) enzyme extract. Two types of substrates were used: the raw larvae flour (LF) and its protein extract (PE). The hydrolysis yield, considering the peptide concentration of the hydrolysates, was higher in PE hydrolysates than in LF hydrolysates (6.39 ± 0.59 vs. 3.02 ± 0.06 mg/mL, respectively). However, LF showed a higher antioxidant activity against the DPPH radical than PE (59.10 ± 1.42 vs. 18.79 ± 0.81 µM Trolox Eq/mg peptides, respectively). Regarding the inhibitory activity of angiotensin-I-converting enzyme (ACE), an IC50 value of 111.33 ± 21.3 µg peptides/mL was observed in the PE. The identification of the peptide sequence of both hydrolysates was conducted, and LF and its PE presented 404 and 116 peptides, respectively, most with low molecular weight (<3 kDa), high percentage of hydrophobic amino acids, and typical characteristics of well-known antioxidant and ACE-inhibitory peptides. Furthermore, the potential bioactivity of the sequences identified was searched in the BIOPEP database. Considering the antioxidant and ACE-inhibitory activities, LF hydrolysates contained a larger number of sequences with potential bioactivity than PE hydrolysates.

Structure-guided discovery of antioxidant peptides bounded to the Keap1 receptor as hunter for potential dietary antioxidants

Human health can be damaged by free radicals, and antioxidant peptides are excellent radical scavengers. Antioxidant tripeptides data set based on 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulofnic acid) (ABTS) assay was created, 9 types of descriptors were integrated and 4 quantitative structure-activity relationship (QSAR) models were constructed in this study. Several structural factors influencing the activity of antioxidant tripeptides and the dominant amino acids at each position of tripeptides were revealed by the optimal model. Ten food-derived tripeptides with higher activity were selected for synthesis and activity determination. Molecular docking results demonstrated that these tripeptides were stably bound to the Keap1 receptor, further elucidating the antioxidant mechanism. It was known from the simulation of gastrointestinal digestion experiments that the model results possessed a guiding effect on the selection of proteins with high antioxidant activity. The performance of the model was proved to be robust after validation.

Peptides derived from the gastrointestinal digestion of amaranth 11S globulin: Structure and antioxidant functionality

The relationship between structural and physicochemical properties and antioxidant activity of peptides from amaranth 11S-globulin was studied. Peptides AWEEREQGSR, TEVWDSNEQ, IYIEQGNGITGM and YLAGKPQQEH had the greatest in vitro activity (ORAC, HORAC). GDRFQDQHQ, HVIKPPSRA and KFNRPETT were the most active ones against Cu⁺²/H₂O₂-induced-LDL oxidation. In a cellular system (H₂O₂-induced-Caco2-TC7), TEVWDSNEQ, IYIEQGNGITGM, GDRFQDQHQ, LAGKPQQEHSGEHQ and KFNRPETT were the most effective in decreasing ROS, while the effects on SOD, GPx, and GSH were variable. To understand the structure-antioxidant activity relationships, the content of aromatic and acidic amino acids, the degree of hydrophobicity and the charge distribution on the accessible surface of peptides structures obtained by molecular dynamics were analysed. The low correlation between in vitro, ex vivo and cellular activities could be explained by the influence of physicochemical and structural properties on the interaction with complex systems (LDL/cells), peptide modifications and/or mechanisms other than direct ROS inhibition in the cells.

Identification of three novel antioxidative peptides from Auxenochlorella pyrenoidosa protein hydrolysates based on a peptidomics strategy

Auxenochlorella pyrenoidosa is recognized as a potential sustainable protein material in food industry, however, its application remains still very limited. Herein, this study aimed to investigate the antioxidative properties of Auxenochlorella pyrenoidosa protein hydrolysates and identify novel antioxidative peptides from protein hydrolysates through a workflow mainly including enzymatic hydrolysis, peptidome quantification, quantitative structure-activity relationship (QSAR) modeling, in silico screening, and validation. Three novel antioxidative peptides including AGWACLVG, IDLAY and YPLDL were identified from protein hydrolysates by papain with the hydrolysis time of 4 h, in which, AGWACLVG showed strong 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging capacity with the IC₅₀ value of 68.88 µM and Trolox equivalent antioxidative capacity of 6.20 ± 0.23 mmol TE/g. This study suggested that Auxenochlorella pyrenoidosa protein hydrolysates could be used as potential antioxidative ingredients in food industry, and the identification of novel antioxidative peptides would contribute to the construction of more robust QSAR models in the future.

Virtual screening and rational design of antioxidant peptides based on tryptophyllin L structures isolated from the Litoria rubella frog

Discovery of natural antioxidants has been carried out for decades relying mainly on experimental approaches that are commonly associated with time and cost demanding biochemical assays. The maturation of quantitative structure activity relationship (QSAR) modelling has provided an alternative approach for searching and designing antioxidant compounds with alleviated costs. As a contribution to this approach, this work aimed to establish a fragment-based 3D-QSAR procedure to discover and design potential antioxidants based on tryptophyllin L structures isolated from the red tree frog Litoria rubella. A force field and a Gaussian 3D-QSAR model were built to screen for potential antioxidants from tripeptide fragments covering all sequences of tryptophyllin L database. Among those, PWY(NH₂ ) corresponding tryptophyllin L 4.1 was predicted to have the highest 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical cation (ABTS⁺ ·) scavenging capability. Two newly designed peptides PYW and PYW(NH₂ ) together with PWY(NH₂ ), tryptophyllin L 4.1, and the reference peptide PWY were synthesized and subjected to two antioxidant assays including ABTS scavenging and ferric reducing antioxidant power assays. Although the experimental TEAC values of the five peptides were roughly similar to those from predictions, the activity order was not in agreement with the predictions. The dissimilarities were accounted by the difference in the experimental procedures, the deviation of modelling regression, and the synergetic effect of structural and experimental features. The ABTS radical scavenging assays revealed that all the tested peptides were strong ABTS⁺ · scavengers with the antioxidant capabilities approximately twice as high as trolox and higher than glutathione. The ferric reducing activities of the peptides were, on the other hand, much weaker than that of trolox suggesting different antioxidant mechanisms inserted by trolox and the peptides. This work was a demonstration that 3D-QSAR methods can be employed in conjunction with experimental methods to effectively detect and design antioxidant peptides.

Computational strategies for the discovery of biological functions of health foods, nutraceuticals and cosmeceuticals: a review

Scientific and consumer interest in healthy foods (also known as functional foods), nutraceuticals and cosmeceuticals has increased in the recent years, leading to an increased presence of these products in the market. However, the regulations across different countries that define the type of claims that may be made, and the degree of evidence required to support these claims, are rather inconsistent. Moreover, there is also controversy on the effectiveness and biological mode of action of many of these products, which should undergo an exhaustive approval process to guarantee the consumer rights. Computational approaches constitute invaluable tools to facilitate the discovery of bioactive molecules and provide biological plausibility on the mode of action of these products. Indeed, methodologies like QSAR, docking or molecular dynamics have been used in drug discovery protocols for decades and can now aid in the discovery of bioactive food components. Thanks to these approaches, it is possible to search for new functions in food constituents, which may be part of our daily diet, and help to prevent disorders like diabetes, hypercholesterolemia or obesity. In the present manuscript, computational studies applied to this field are reviewed to illustrate the potential of these approaches to guide the first screening steps and the mechanistic studies of nutraceutical, cosmeceutical and functional foods.

Protective effect against d-gal-induced aging mice and components of polypeptides and polyphenols in defatted walnut kernel during simulated gastrointestinal digestion

Defatted walnut kernel with pellicle (WKP) is an industrial byproduct during walnut oil extraction, which is rich in protein and polyphenols. WKP was hydrolyzed by simulated gastrointestinal digestion to obtain WKP hydrolysates (WKPHs). Results showed the protein recovery and hydrolysis degree of WKPH were 82.15 and 10.36%. The total phenol contents in WKP and WKPH were 4.90 and 40.70 mg gallic acid equivalent/g, respectively. The antiaging activity of WKPH was evaluated using a d-gal-induced aging mouse model. Results showed that WKPHs could recover the activities of SOD and T-AOC and the content of MDA in tissues and serum of the aging mice. The histological morphology of liver and kidney sections and the immunohistochemistry of TNF-α, IL-1β, and IL-6 in liver were observed. WKPH could effectively protect the tissue structure of the liver and kidney and reduce the inflammatory expression of liver in aging mice. The polypeptides and polyphenols in WKPH were further analyzed. Fifty polypeptides were identified and 12 of these peptides had Leu-Arg at the C-terminal. Forty-two polyphenols were detected, and most phenolic compounds belonged to ellagitannins. This study provided a theoretical basis for the improved processing and high-value utilization of walnut byproducts. PRACTICAL APPLICATION: Defatted walnut kernel with pellicle was hydrolyzed by simulated gastrointestinal digestion to obtain its hydrolysates. The hydrolysates have good antiaging activity in vivo. Fifty polypeptides were identified and 12 of these peptides had Leu-Arg at the C-terminal. Forty-two polyphenols were detected, and most phenolic compounds belonged to ellagitannins. This study could provide a theoretical basis for high-value utilization of walnut byproducts.

FermFooDb: A database of bioactive peptides derived from fermented foods

Globally fermented foods are in demands due to their functional and nutritional benefits. These foods are sources of probiotic organisms and bioactive peptides, various amino acids, enzymes etc. that provides numerous health benefits. FermFooDb (https://webs.iiitd.edu.in/raghava/fermfoodb/) is a manually curated database of bioactive peptides derived from wide range of foods that maintain comprehensive information about peptides and process of fermentation. This database comprises of 2205 entries with following major fields, peptide sequence, Mass and IC50, food source, functional activity, fermentation conditions, starter culture, testing conditions of sequences in vitro or in vivo, type of model and method of analysis. The bioactive peptides in our database have wide range of therapeutic potentials that includes antihypertensive, ACE-inhibitory, antioxidant, antimicrobial, immunomodulatory and cholesterol lowering peptides. These bioactive peptides were derived from different types of fermented foods that include milk, cheese, yogurt, wheat and rice. Numerous, web-based tools have been integrated to retrieve data, peptide mapping of proteins, similarity search and multiple-sequence alignment. This database will be useful for the food industry and researchers to explore full therapeutic potential of fermented foods from specific cultures.

Antioxidant activities of peptides derived from mutton ham, Xuanwei ham and Jinhua ham

The aim of the study was to evaluate antioxidant activity of crude peptides with molecular weight less than 3 KDa extracted from Xuanwei ham, Jinhua ham and mutton ham. UPLC-Q-TOF-MS/MS was used for composition analysis of peptides and homologous protein matching. Further, crude peptide (<3 KDa) was purified using G-15 gel filtration chromatography, and the main antioxidant peptide identified. Analysis showed that mutton ham peptide (MHP) has the highest Fe²⁺ chelating ability, whereas Jinhua ham peptide (JHP) had the highest ABTS and DPPH free radical scavenging ability (P < 0.05). A total of 346, 203 and 296 peptides were identified in JHP, Xuanwei ham peptides (XHP) and MHP, respectively. Most of the peptides were derived from myosin, accounting for 21.97% in JHP, 18.72% in XHP, and 21.96% in MHP. Myosin, actin, myoglobin, troponin, tropomyosin and pyruvate kinase proteins were the main source of peptide differences in the three types of dry cured ham.

Identification of bioactive peptides released from in vitro gastrointestinal digestion of yam proteins (Dioscorea cayennensis)

Bioactive peptides have been broadly studied for their contribution to human health. This study aimed to identify bioactive peptides generated by in vitro gastrointestinal digestion of yam proteins. Yam protein concentrate (YPC) was submitted to simulated digestion. Gastric phase hydrolysate (GPH) and total gastrointestinal phase hydrolysate (GIPH) had their peptides identified by nanoLC-ESI-MS/MS. Peptide sequences were subjected to a database-driven (BIOPEP) bioactivity search. In vitro tests included: Antioxidant activity, DNA damage protection, ACE-inhibitory activity and antibacterial activity against the bacteria Escherichia coli, Salmonella sp. and Lysteria monocytogenes. Simulated digestion generated small peptides (mostly MW < 3500 Da), several of them with potential bioactive sequences predicted in silico. In both GPH and GIPH biological activities were detected, although GIPH displayed stronger DNA damage protection and antibacterial activity against Escherichia coli. The digestion of yam proteins releases promising biologically active peptides which can contribute to the prevention of bacterial infection and chronic degenerative diseases, with beneficial effects to human health.

Research progress on separation of selenoproteins/Se-enriched peptides and their physiological activities

Selenium (Se) is an essential nutrient associated with several physiological processes in humans and has raised interest because of its antioxidant and immune properties. Se deficiency is related to a variety of diseases and dysfunctions in humans. Due to its higher bioavailability and lower toxicity, organic Se is more recommendable than inorganic Se in the frame of a balanced diet. Se is present in 25 identified selenoproteins that commonly occur in human organisms. As part of selenocysteine (SeC), Se becomes co-translationally incorporated into the polypeptide chain and involved in the regulation of oxidative stress, redox mechanisms, and other crucial cellular processes responsible for innate and adaptive immune responses. This review presents the current information regarding the presence of selenoproteins in the human body, and the separation of selenoproteins and selenopeptides from various plants and their physiological roles in the immune and oxidation systems of humans. In general, the application of selenoproteins and Se-enriched peptides are practically important for the clinical arena, whereby it can be used for exploring new healthy foods.

Purification and Identification of Pine Nut (Pinus yunnanensis Franch.) Protein Hydrolysate and Its Antioxidant Activity in Vitro and in Vivo

In this study, the pine nut (Pinus yunnanensis Franch.) protein was hydrolyzed by alkaline protease and trypsin to prepare pine nut protein hydrolysate (PNPH). The chemical, intracellular and in vivo antioxidant capacity of PNPH were evaluated. PNPH owned the ability of scavenging free radicals, and it could protect the HepG2 cells from oxidative damage by preserving cell viability. Moreover, PNPH could reduce the malondialdehyde (MDA) content and improved the superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities in serum, heart and liver of aging mice induced by D-galactose. Further, the PNPH was stepwise purified and identified, and 15 peptides were identified from purified fraction in PNPH. The three-dimension structures of identified peptides were predicted. Among all identified peptides, peptide 3, 7, 8 and 11 were presumed to possess good antioxidant activity. Overall, PNPH and purified peptides isolated from PNPH have potential application prospects in the field of natural antioxidants and anti-aging functional foods.

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

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 predictors exist, however, no tool predicting the antioxidative properties of peptides is, to the best of our knowledge, currently available as a web-server. We here present the AnOxPePred tool and web-server (http://services.bioinformatics.dtu.dk/service.php?AnOxPePred-1.0) that uses deep learning to predict the antioxidant properties of peptides. Our model was trained on a curated dataset consisting of experimentally-tested antioxidant and non-antioxidant peptides. For a variety of metrics our method displays a prediction performance better than a k-NN sequence identity-based approach. Furthermore, the developed tool will be a good benchmark for future predictors of antioxidant peptides.

Ultrasound microwave-assisted enzymatic production and characterisation of antioxidant peptides from sweet potato protein

Herein, we investigated the effects of ultrasound microwave (UM)-assisted hydrolysis using Alcalase (ALC), Flavourzyme (FLA), and their combination (ALC + FLA), on the production of sweet potato protein hydrolysates (SPPH). UM-assisted enzymatic hydrolysis significantly increased the degree of hydrolysis of SPPH compared with untreated (UN) samples. Fractions with differences in molecular weight (MW) of >10, 3-10, and < 3 kDa in SPPH from UM-assisted ALC, FLA, and ALC + FLA hydrolysis displayed higher antioxidant activities than those from UN samples. MW < 3 kDa fractions of SPPH from UM-assisted ALC and ALC + FLA hydrolysis treatments presented much stronger Fe²⁺-chelating activity (98.48% and 98.59%), ·OH scavenging activity (67.11% and 60.06%), and higher ORAC values (110.32 and 106.32 µg TE/mL), from which diverse peptides with potential antioxidant activities were obtained by semi-preparative HPLC and LC-MS/MS. All identified peptide sequences exhibited at least three potential antioxidant amino acids. Additionally, changes in peptide conformational structure and antioxidant amino acid composition were revealed by structure-activity relationship analysis. Thus, ultrasound microwave treatment has great potential in antioxidant peptides production.