Application of quantitative structure-activity relationship to food-derived peptides: Methods, situations, challenges and prospects

Identification and characterization of umami-ACE inhibitory peptides from traditional fermented soybean curds

Fermented soybean curds (FSC) are popular because of its umami taste. Its bioactivities are of interest. Peptides in FSC were identified using nano-HPLC-MS/MS, and 11 candidate peptides showing potential umami and ACE inhibitory activities were screened using various databases. Pharmacophore model analysis showed their high probability of ACE inhibition with fit values >2, which showed the peptides bound to umami receptors and ACE mainly through hydrogen bond, and electrostatic and hydrophobic interactions. Additionally, their docking and interaction energy were independent of the peptide length. Three high umami-ACE inhibitory peptides (VE, FEF, and WEEF) were synthesized. Their umami thresholds were WEEF (0.32 mM) < FEF (0.55 mM) < VE (1.10 mM), while their IC50 were WEEF (85 ± 2 μM) < FEF (170 ± 10 μM) < VE (205 ± 5 μM). NO and ET-1 production were dose-dependent with WEEF showing the best ACE inhibitory activity. The results allowed identification of effective umami agents and ACE inhibitory peptides from fermented soybean products. It could also be useful method for screening potential umami-ACE inhibitory peptides.

Medicine and food homology substances: A review of bioactive ingredients, pharmacological effects and applications

In recent years, the idea of medicine and food homology (MFH), which highlights the intimate relationship between food and medicine, has gained international recognition. Specifically, MFH substances have the ability to serve as both food and medicine. Many foods have been reported to have good nutritional and medical values, not only for satiety but also for nourishing the body and treating diseases pharmacologically. As modern scientific research has progressed, the concept of MFH has been emphasized and developed in a way that has never been seen before. Therefore, in this paper, we reviewed the development history of MFH substances, summarized some typical bioactive ingredients, and recognized pharmacological effects. In addition, we further discussed the application of MFH substances in the food field, with the goal of providing ideas and references for the research and development of MFH in the food industry as well as the progress of related industries.

Antin-diabetic cognitive dysfunction effects and underpinning mechanisms of phytogenic bioactive peptides: a review

Diabetic cognitive dysfunction is one of the important comorbidities and complications of diabetes, which is mainly manifested by loss of learning ability and memory, behavioural disorders, and may even develop into dementia. While traditional anti-diabetic medications are effective in improving cognition and memory, long-term use of these medications can be accompanied by undesirable side effects. Therefore, there is an urgent need to find safe and effective alternative therapies. Accumulating evidence suggests that phytogenic bioactive peptides play an important role in the regulation of cognitive dysfunction in diabetes. In this review, we explored the relationship between diabetes mellitus and cognitive dysfunction, and the potential and underlying mechanisms of plant-derived bioactive peptides to improve diabetic cognitive dysfunction. We found that plant-derived active peptides alleviate diabetic cognitive impairment by inhibiting key enzymes (e.g., α-glucosidase, α-amylase) to improve blood glucose levels and increase antioxidant activity, modulate inflammatory mediators, and address intestinal dysbiosis. In conclusion, plant-derived active peptides show strong potential to improve diabetic cognitive impairment.

Towards a Quantitative Description of Proteolysis: Contribution of Demasking and Hydrolysis Steps to Proteolysis Kinetics of Milk Proteins

The hydrolysis of proteins by proteases (proteolysis) plays a significant role in biology and food science. Despite the importance of proteolysis, a universal quantitative model of this phenomenon has not yet been created. This review considers approaches to modeling proteolysis in a batch reactor that take into account differences in the hydrolysis of the individual peptide bonds, as well as the limited accessibility (masking) for the enzymes of some hydrolysis sites in the protein substrate. Kinetic studies of the proteolysis of β-casein and β-lactoglobulin by various proteolytic enzymes throughout the whole degree of hydrolysis are reviewed. The two-step proteolysis model is regarded, which includes demasking of peptide bonds as a result of opening of the protein structure at the first stage, then hydrolysis of the demasked peptide bonds. To determine the kinetics of demasking, the shift in Trp fluorescence during opening of the protein substrate is analyzed. Two stages of demasking and secondary masking are also considered, explaining the appearance of unhydrolyzed peptide bonds at the end of proteolysis with decreasing enzyme concentrations. Proteolysis of a nanosized substrate is considered for the example of tryptic hydrolysis of β-CN micelles, leading to the formation and degradation of new nanoparticles and non-monotonic changes in the secondary protein structures during proteolysis.

Virtual-screening of xanthine oxidase inhibitory peptides: Inhibition mechanisms and prediction of activity using machine-learning

Xanthine oxidase (XO) inhibitory peptides can prevent XO-mediated hyperuricemia. Currently, QSAR about XO inhibitory peptides with different lengths remains to be enriched. Here, XO inhibitory peptides were obtained from porcine visceral proteins through virtual-screening. A prediction model was established by machine-learning. Virtual-screening retained four lengths of peptides, including 3-6. Molecular-docking recognized their binding sites with XO and showed residues W, F, and G were the key amino acids. Datasets of XO inhibitory peptides therewith were established. The optimal model was used to generalize the peptides reported. Results showed that the R2 of the tripeptide, tetrapeptide, pentapeptide and hexapeptide in the generalisation test were R2 = 0.81, R2 = 0.82, R2 = 0.83 and R2 = 0.83, respectively. Overall, this work can serve as a reference for explaining the activity mechanism of XO inhibitory peptides and predicting the activity of XO inhibitory peptides.

Sequence-Activity Relationship of Angiotensin-Converting Enzyme Inhibitory Peptides Derived from Food Proteins, Based on a New Deep Learning Model

Food-derived peptides are usually safe natural drug candidates that can potentially inhibit the angiotensin-converting enzyme (ACE). The wet experiments used to identify ACE inhibitory peptides (ACEiPs) are time-consuming and costly, making it important and urgent to reduce the scope of experimental validation through bioinformatics methods. Here, we construct an ACE inhibitory peptide predictor (ACEiPP) using optimized amino acid descriptors (AADs) and long- and short-term memory neural networks. Our results show that combined-AAD models exhibit more efficient feature transformation ability than single-AAD models, especially the training model with the optimal descriptors as the feature inputs, which exhibits the highest predictive ability in the independent test (Acc = 0.9479 and AUC = 0.9876), with a significant performance improvement compared to the existing three predictors. The model can effectively characterize the structure-activity relationship of ACEiPs. By combining the model with database mining, we used ACEiPP to screen four ACEiPs with multiple reported functions. We also used ACEiPP to predict peptides from 21,249 food-derived proteins in the Database of Food-derived Bioactive Peptides (DFBP) and construct a library of potential ACEiPs to facilitate the discovery of new anti-ACE peptides.

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 AA descriptors (physicochemical, 3-dimensional structural, quantum, and topological attributes) and genetic algorithms for feature selection, 1 and 4 machine learning-predicted models separately for di- and tripeptides with 2,2-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt radical scavenging capacity exhibited excellent fitting and prediction ability with random forest regression as machine learning algorithm. Intriguingly, the electronic properties of N-terminal AA 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, exhibiting concentrations ranging from 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 discovery of novel functional peptides from milk-derived proteins and paving the way for understanding their metabolites during digestion.

Research Progress on Food-Derived Bioactive Peptides: An Overview of the 3rd International Symposium on Bioactive Peptides

Interest in food-derived bioactive peptides is on the rise. In 2023, the 3rd International Symposium on Bioactive Peptides (ISBP) was held in Niagara Falls, Canada, to provide a platform for knowledge exchange, networking, and collaboration among researchers in this field. This article aims to provide a high-level overview of the key progress and emerging trends in bioactive peptides based on the 3rd ISBP. This review highlights the production of bioactive peptides from sustainable sources through the integration of artificial intelligence and wet-lab research, the emerging roles of bioactive peptides in cognitive function, and the ability of peptides to act as taste modifiers. The emerging research trend in bioactive peptides focuses on utilizing novel processing technologies, understanding peptide-receptor interactions, applying omics in mechanistic studies, conducting clinical trials, and facilitating product development and commercialization.

Novel Antioxidant Peptides from Fermented Whey Protein by Lactobacillus rhamnosus B2-1: Separation and Identification by in Vitro and in Silico Approaches

Whey is a byproduct of the dairy industry and is rich in protein. To enhance the significance of such byproducts and find efficacious antioxidants for combating oxidative stress, this study reported on the preparation, purification, and identification of novel peptides with antioxidant activities from whey protein metabolites following fermentation by Lactobacillus rhamnosus B2-1. The isolation and identification processes involved macroporous adsorption resin column chromatography, gel filtration column chromatography, and liquid chromatography-tandem mass spectrometry. Therein, three novel antioxidant peptides (PKYPVEPF, LEASPEVI, and YPFPGPIHNS) were selected to be synthesized, and they demonstrated remarkable antioxidant activities in vitro chemical assays. PKYPVEPF, LEASPEVI, and YPFPGPIHNS (100 μg/mL) displayed a notable cytoprotective impact on HepG2 cells under oxidative stress induced by H2O2, increasing the cell viability from 49.02 ± 3.05% to 88.59 ± 10.49%, 82.38 ± 19.16%, and 85.15 ± 7.19%, respectively. Moreover, the peptides boosted the activities of catalase and superoxide dismutase in damaged cells and reduced reactive oxygen species levels. The molecular docking studies highlighted that these antioxidant peptides efficiently bound to key amino acids in the Kelch domain of Keap1, thereby preventing the interaction between Keap1 and Nrf2. In conclusion, PKYPVEPF, LEASPEVI, and YPFPGPIHNS demonstrated substantial antioxidant activity, suggesting their potential for widespread application as functional food additives and ingredients.

Recent advances in computational prediction of molecular properties in food chemistry

The combination of food chemistry and computational simulation has brought many impacts to food research, moving from experimental chemistry to computer chemistry. This paper will systematically review in detail the important role played by computational simulations in the development of the molecular structure of food, mainly from the atomic, molecular, and multicomponent dimension. It will also discuss how different computational chemistry models can be constructed and analyzed to obtain reliable conclusions. From the calculation principle to case analysis, this paper focuses on the selection and application of quantum mechanics, molecular mechanics and coarse-grained molecular dynamics in food chemistry research. Finally, experiments and computations of food chemistry are compared and summarized to obtain the best balance between them. The above review and outlook will provide an important reference for the intersection of food chemistry and computational chemistry, and is expected to provide innovative thinking for structural research in food chemistry.

The novel angiotensin-I-converting enzyme inhibitory peptides from Scomber japonicus muscle protein hydrolysates: QSAR-based screening, molecular docking, kinetic and stability studies

Food-derived angiotensin-converting enzyme-inhibitory (ACE-I) peptides have attracted extensive attention. Herein, the ACE-I peptides from Scomber japonicus muscle hydrolysates were screened, and their mechanisms of action and inhibition stability were explored. The quantitative structure-activity relationship (QSAR) model based on 5z-scale metrics was developed to rapidly screen for ACE-I peptides. Two novel potential ACE-I peptides (LTPFT, PLITT) were predicted through this model coupled with in silico screening, of which PLITT had the highest activity (IC50: 48.73 ± 7.59 μM). PLITT inhibited ACE activity with a mixture of non-competitive and competitive mechanisms, and this inhibition mainly contributed to the hydrogen bonding based on molecular docking study. PLITT is stable under high temperatures, pH, glucose, and NaCl. The zinc ions (Zn2+) and copper ions (Cu2+) enhanced ACE-I activity. The study suggests that the QSAR model is effective in rapidly screening for ACE-I inhibitors, and PLITT can be supplemented in foods to lower blood pressure.

Glutamine-derived peptides: Current progress and future directions

Glutamine, the most abundant amino acid in the body, plays a critical role in preserving immune function, nitrogen balance, intestinal integrity, and resistance to infection. However, its limited solubility and instability present challenges for its use a functional nutrient. Consequently, there is a preference for utilizing glutamine-derived peptides as an alternative to achieve enhanced functionality. This article aims to review the applications of glutamine monomers in clinical, sports, and enteral nutrition. It compares the functional effectiveness of monomers and glutamine-derived peptides and provides a comprehensive assessment of glutamine-derived peptides in terms of their classification, preparation, mechanism of absorption, and biological activity. Furthermore, this study explores the potential integration of artificial intelligence (AI)-based peptidomics and synthetic biology in the de novo design and large-scale production of these peptides. The findings reveal that glutamine-derived peptides possess significant structure-related bioactivities, with the smaller molecular weight fraction serving as the primary active ingredient. These peptides possess the ability to promote intestinal homeostasis, exert hypotensive and hypoglycemic effects, and display antioxidant properties. However, our understanding of the structure-function relationships of glutamine-derived peptides remains largely exploratory at current stage. The combination of AI based peptidomics and synthetic biology presents an opportunity to explore the untapped resources of glutamine-derived peptides as functional food ingredients. Additionally, the utilization and bioavailability of these peptides can be enhanced through the use of delivery systems in vivo. This review serves as a valuable reference for future investigations of and developments in the discovery, functional validation, and biomanufacturing of glutamine-derived peptides in food science.

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.

The substitution sites of hydroxyl and galloyl groups determine the inhibitory activity of human pancreatic α-amylase in twelve tea polyphenol monomers

Tea polyphenols have been reported as potential α-amylase inhibitors. However, the quantitative structure-activity relationship (QSAR) between tea polyphenols and human pancreas α-amylase (HPA) is not well understood. Herein, the inhibitory effect of twelve tea polyphenol monomers on HPA was investigated in terms of inhibitory activity, as well as QSAR analysis and interaction mechanism. The results revealed that the HPA inhibitory activity of theaflavins (TFs), especially theaflavin-3'-gallate (TF-3'-G, IC50: 0.313 mg/mL), was much stronger than that of catechins (IC50: 18.387-458.932 mg/mL). The QSAR analysis demonstrated that the determinant for the inhibitory activity of HPA was not the number of hydroxyl and galloyl groups in tea polyphenol monomers, while the substitution sites of these groups potentially might play a more important role in modulating the inhibitory activity. The inhibition kinetics and molecular docking revealed that TF-3'-G as a mixed-type inhibitor had the lowest inhibition constant and bound to the active sites of HPA with the lowest binding energy (-7.74 kcal/mol). These findings could provide valuable insights into the structures-activity relationships between tea polyphenols and the HPA inhibitors.

From microbes to molecules: a review of microbial-driven antioxidant peptide generation

Oxidative stress, arising from excess reactive oxygen species (ROS) or insufficient antioxidant defenses, can damage cellular components, such as lipids, proteins, and nucleic acids, resulting in cellular dysfunction. The relationship between oxidative stress and various health disorders has prompted investigations into potent antioxidants that counteract ROS's detrimental impacts. In this context, antioxidant peptides, composed of two to twenty amino acids, have emerged as a unique group of antioxidants and have found applications in food, nutraceuticals, and pharmaceuticals. Antioxidant peptides are sourced from natural ingredients, mainly proteins derived from foods like milk, eggs, meat, fish, and plants. These peptides can be freed from their precursor proteins through enzymatic hydrolysis, fermentation, or gastrointestinal digestion. Previously published studies focused on the origin and production methods of antioxidant peptides, describing their structure-activity relationship and the mechanisms of food-derived antioxidant peptides. Yet, the role of microorganisms hasn't been sufficiently explored, even though the production of antioxidant peptides frequently employs a variety of microorganisms, such as bacteria, fungi, and yeasts, which are recognized for producing specific proteases. This review aims to provide a comprehensive overview of microorganisms and their proteases participating in enzymatic hydrolysis and microbial fermentation to produce antioxidant peptides. This review also covers endogenous peptides originating from microorganisms. The information obtained from this review might guide the discovery of novel organisms adept at generating antioxidant peptides.

Bioaccessibility of novel antihypertensive short-chain peptides in goat milk using the INFOGEST static digestion model by effect-directed assays

Short-chain peptides (SCPs, 2-4 amino acids) offer potential health benefits. A customized workflow was designed to screen SCPs in goat milk during INFOGEST digestion in vitro and 186 SCPs were preliminarily identified. Based on a two-terminal position numbering method and genetic algorithm combined with a support vector machine, 22 SCPs with predicted IC50 values less than 10 μM were obtained using a quantitative structure-activity relationship (QSAR) model with satisfactory fitting and predictive capacity (R2, RMSE, Q2, and R2pre of 0.93, 0.27, 0.71, and 0.65, respectively). Four novel antihypertensive SCPs were confirmed by testing in vitro and molecular docking analysis, and their quantification results (0.06 to 1.53 mg L-1) suggested distinct metabolic fates. This study facilitated the discovery of unknown potential food-derived antihypertensive peptides and the understanding of bioaccessible peptides during digestion.

Identification of umami peptides from Wuding chicken by Nano-HPLC-MS/MS and insights into the umami taste mechanisms

Wuding chicken is popular with consumers in China because of its umami taste. This study aimed to identify novel umami peptides from Wuding chicken and explore the taste mechanism of umami peptides. The molecular masses and amino acid compositions of peptides in Wuding chicken were identified by nano-scale liquid chromatography-tandem mass spectrometry (Nano-HPLC-MS/MS). The taste characteristics of the peptides synthesized by the solid-phase method were evaluated by sensory evaluation combined with electronic tongue technology. The secondary structure of the peptides was further analyzed by circular dichroism (CD), and the relationship between the structure and taste of the peptides was elucidated by molecular docking. The results showed that eight potential umami peptides were identified, among which FVT (FT-3), LDF (LF-3), and DLAGRDLTDYLMKIL (DL-15) had distinct umami tastes, and FT-3 had the highest umami intensity, followed by LF-3 and DL-15. The relative contents of β-sheets in the three umami peptides were 55.20%, 57.30%, and 47.70%, respectively, which were the key components of Wuding chicken umami peptides. In addition to LF-3 embedded in the cavity-binding domain of the TIR1, both FT-3 and DL-15 were embedded in the venus flytrap domain (VFTD) of the T1R3 to bind the umami receptor T1R1/T1R3. The main binding forces between the umami peptides and the umami receptor T1R1/T1R3 relied on hydrogen bonds and hydrophobic interactions, and the key amino acid residues of the combination of umami peptides and the umami receptor T1R1/T1R3 were Glu292, Asn235, and Tyr262.

Efficient Large-Scale Virtual Screening Based on Heterogeneous Many-Core Supercomputing System

With the rapid growth of virtual drug data- bases, the need for efficient molecular docking tools for large-scale screening is also growing. We have developed Vina@QNLM 2.0, a novel molecular docking system that leverages the logical processing units and computational processing arrays of heterogeneous multicore architecture processors. Compared to Vina@QNLM, the new version optimizes the docking speed without sacrificing accuracy. This greatly improves the scoring capability for large molecules (molecular weight > 500). Simultaneously, the new system provides enhanced support for applications such as reverse target finding through an improved parallel strategy. Vina@QNLM 2.0 achieves a speedup 20 times higher than that, using logical processing units only during a single docking process. Additionally, we successfully scaled the reverse target finding a task to 122,401 kernel groups with a robust scalability of 80.01%. In practice, we completed a reverse target-seeking for nine glycan molecules with 10,094 proteins within 1 hour.

Food-derived bioactive peptides as momentous food components: Can functional peptides passed through the PI3K/Akt/mTOR pathway and NF-κB pathway to repair and protect the skeletal muscle injury?

Muscle injury is defined as an overuse injury or traumatic distraction of a muscle, which is latent in any sport event, from amateur to large events. Based on previous numbers of muscle injuries and time spent to the athletes' recovery, the use of dietary functional factors intervention strategies is essential to enhance the recovery process and health. In recent years, there has been increasing evidence that biologically active peptides played an important role in sports nutrition and muscle injure recovery. Food-derived bioactive peptides were physiologically active peptides mostly derived from proteins following hydrolysis, which could be resorbed in intact form to reduce muscle damage following exercise and induce beneficial adaptions within the connective tissue. However, the complexity of the histoarchitectural considerations for skeletal muscle injuries and the repair mechanism of damaged skeletal muscle were not well known. In the following overview, the potential mechanisms and possible limitations regarding the damaged skeletal muscle metabolism were summarized, which aimed to present an overview of the nutritional strategies and recommendations after a muscular sports injury, emphasizing the use of main bioactive peptides. In addition, this review will provide implications for the studies of dietary bioactive peptides in the future.

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.

Antioxidant peptides: Overview of production, properties, and applications in food systems

In recent years, several studies have reported the beneficial effects of antioxidant peptides in delaying oxidation reactions. Thus, a growing number of food proteins have been investigated as suitable sources for obtaining these antioxidant peptides. In this study, some of the most critical developments in the discovery of peptidic antioxidants are discussed. Initially, the primary methods to release, purify, and identify these antioxidant peptides from various food-derived sources are reviewed. Then, computer-based screening methods of the available peptides are summarized, and methods to interpret their structure-activity relationship are illustrated. Finally, approaches to the large-scale production of these bioactive peptides are described. In addition, the applications of these antioxidants in food systems are discussed, and gaps, future challenges, and opportunities in this field are highlighted. In conclusion, various food items can be considered promising sources to obtain these novel antioxidant peptides, which present various opportunities for food applications in addition to health promotion. The lack of in-depth data on the link between the structure and activity of these antioxidants, which is critical for the prediction of possible bioactive amino acid sequences and their potency in food systems and in vivo conditions (rather than in vitro systems), requires further attention. Consequently, future collaborative research activities between the industry and academia are required to realize the commercialization objectives of these novel antioxidant peptides.

Quantitative Structure-Toxicity Relationship in Bioactive Molecules from a Conceptual DFT Perspective

The preclinical drug discovery stage often requires a large amount of costly and time-consuming experiments using huge sets of chemical compounds. In the last few decades, this process has undergone significant improvements by the introduction of quantitative structure-activity relationship (QSAR) modelling that uses a certain percentage of experimental data to predict the biological activity/property of compounds with similar structural skeleton and/or containing a particular functional group(s). The use of machine learning tools along with it has made life even easier for pharmaceutical researchers. Here, we discuss the toxicity of certain sets of bioactive compounds towards Pimephales promelas and Tetrahymena pyriformis in terms of the global conceptual density functional theory (CDFT)-based descriptor, electrophilicity index (ω). We have compared the results with those obtained by using the commonly used hydrophobicity parameter, logP (where P is the n-octanol/water partition coefficient), considering the greater ease of computing the ω descriptor. The Human African trypanosomiasis (HAT) curing activity of 32 pyridyl benzamide derivatives is also studied against Tryphanosoma brucei. In this review article, we summarize these multiple linear regression (MLR)-based QSAR studies in terms of electrophilicity (ω, ω2) and hydrophobicity (logP, (logP)2) parameters.

Food-derived dipeptidyl peptidase IV inhibitory peptides: Production, identification, structure-activity relationship, and their potential role in glycemic regulation

Dipeptidyl Peptidase IV (DPP-IV) inhibitory peptides are attracting increasing attention, owing to their potential role in glycemic regulation by preventing the inactivation of incretins. However, few reviews have summarized the current understanding of DPP-IV inhibitory peptides and their knowledge gaps. This paper reviews the production, identification and structure-activity relationships (SAR) of DPP-IV inhibitory peptides. Importantly, their bioavailability and hypoglycemic effects are critically discussed. Unlike the traditional method to identifying peptides after separation step by step, the bioinformatics approach identifies peptides via virtual screening that is more convenient and efficient. In addition, the bioinformatics approach was also used to investigate the SAR of peptides. Peptides with proline (Pro) or alanine (Ala) residue at the second position of N-terminal are exhibit strong DPP-IV inhibitory activity. Besides, the bioavailability of DPP-IV inhibitory peptides is related to their gastrointestinal stability and cellular permeability, and in vivo studies showed that the glucose homeostasis has been improved by these peptides. Especially, the intestinal transport of DPP-IV inhibitory peptides and cell biological assays used to evaluate their potential role in glycemic regulation are innovatively summarized. For further successful development of DPP-IV inhibitory peptides in glycemic regulation, future study should elucidate their SAR and in vivo hypoglycemic effects .

Characteristics of antioxidant substances and identification of antioxidant peptides in duck embryo eggs

1. Oxidative stress in duck embryos undergoes dynamic change during incubation. However, the detailed change characteristics has not been studied yet. Here, we explored the dynamic change characteristics of different antioxidant substances in duck embryo eggs during incubation.2. The following trial assayed antioxidant substances, including vitamins E (VE) and C (VC), glutathione (GSH), reduced glutathione (reduced GSH), oxidative glutathione (GSSG), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-px), and malonic dialdehyde (MDA). Five antioxidant peptides (DY1, DY2, DY3, DY4 and DY5) were screened and their protective effect on HepG2 cells and their mechanism of action determined.3. The results showed that antioxidant substances underwent a dynamic change during incubation through various mechanisms. Moreover, the T-AOC of duck embryos at different incubation times, firstly increased and then decreased, reaching the highest level on d 15 during incubation. The peptide DY2 (TVDGPSGKLWRD) exhibited high antioxidant activity in vitro, and is known to regulate the apoptosis pathway in mitochondria.4. The data indicated that duck embryos can be used for the development of related antioxidant products and purification of new bioactive peptides.

Production of Bioactive Peptides from Sea Cucumber and Its Potential Health Benefits: A Comprehensive Review

Bioactive peptides from food have been widely studied due to their potential applications as functional foods and pharmaceuticals. Sea cucumber, a traditional tonic food, is characterized by high protein and low fat, thereby substrates are being studied to release sea cucumber peptides (SCPs). Although recent studies have shown that SCPs have various bioactive functions, there is no literature reviewing the development status of SCPs. In this review, we summarized the production of SCPs, including their purification and identification, then mainly focused on the comprehensive potential health benefits of SCP in vivo and in vitro, and finally discussed the challenge facing the development of SCPs. We found that SCPs have well-documented health benefits due to their antioxidation, anti-diabetes, ACE inhibitory, immunomodulatory, anti-cancer, anti-fatigue, anti-aging, neuroprotection, micromineral-chelating, etc. However, the structure-activity relationships of SCPs and the functional molecular mechanisms underlying their regulation in vivo need further investigation. Research on the safety of SCP and its potential regulation mechanism will contribute to transferring these findings into commercial applications. Hopefully, this review could promote the development and application of SCPs in further investigation and commercialization.

Experimental and computational studies on the mechanism of the β-lactoglobulin-derived peptide inhibiting the antigenicity of β-lactoglobulin

In this study, through a combined simulated enzymolysis-molecular docking-molecular simulation-activity determination-action mechanism strategy, we screened a β-LG-derived peptide (VAGTWYSL) to inhibit the antigenicity of β-LG and explored its mechanism of action. Our results indicate that the inhibitory effect of the peptide on the antigenicity of β-LG is affected by different experimental conditions, including pH, reaction time and concentration. Three factors may contribute to the reduced allergenicity of β-LG. First, there must be sufficient forces between the peptide and β-LG, as a result, hydrophobic forces and hydrogen bonds are the main forces to maintain the structural stability of the complex. Second, the binding of the peptide changes the secondary structure of β-LG, especially with an increase in α-helices and a decrease in β-turns. Third, the peptide binds to the hydrophobic region of β-LG, involving the antigenic epitope region Val41-Lys60, which may reduce the antigenicity.

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.

Caffeoyl malic acid is a potential dual inhibitor targeting TNFα/IL-4 evaluated by a combination strategy of network analysis-deep learning-molecular simulation

Atopic dermatitis (AD) is a common inflammatory skin disease involving multiple signaling pathways. One of the effective treatment strategies of AD is to develop a new drug capable of regulating the key therapeutic targets. Here we report the combination use of network analysis, deep learning, and molecular simulation for the identification of key therapeutic targets for AD and screening of potential multi-target drugs. From the TCM@Taiwan database, we identify a small molecule, namely caffeoyl malic acid (CMA), to inhibit the key therapeutic targets (TNFα and IL-4) for AD. CMA is further identified as a TNFα inhibitor by a deep learning model based on convolutional neural network. Molecular simulations demonstrate that CMA can stably bind to TNFα and IL-4, thereby producing diverse effects on the structural fluctuation, structural flexibility, looseness, and motion strength of each protein. Furthermore, conformation alignments reveal that CMA makes the distance between chain A and C of TNFα become wider and the slit between the two α helices of IL-4 get narrow obviously. CMA leads to the change of protein conformation, which hinders the formation of the protein-receptor complex. Collectively, our findings suggest that CMA is a potential dual TNFα/IL-4 inhibitor for the treatment of AD.

Computational Methods for the Interaction between Cyclodextrins and Natural Compounds: Technology, Benefits, Limitations, and Trends

Cyclodextrins (CDs) have a hollow structure with a hydrophobic interior and hydrophilic exterior. Forming inclusion complexes with CDs will maximize the bioavailability of natural compounds and enable active components to be processed into functional foods, medicines, additives, and so forth. However, experimental methods cannot explain CD-guest binding at the atomic level. Different models have been recently developed to simulate the interaction between CDs and guests to study the binding conformation and analyze noncovalent forces. This review paper summarizes modeling methods of CD-natural compound complexes. The methods include quantitative structure-activity relationships, molecular docking, molecular dynamics simulations, and quantum-chemical calculations. The applications of these methods to enhance the solubility and bioactivities of guest molecules, assist material transportation, and promote compound extraction are also discussed. The purpose of this review is to explore interaction mechanisms of CDs and guests and to help expand new applications of CDs.

Large-Scale Screening of Antifungal Peptides Based on Quantitative Structure-Activity Relationship

Antifungal peptides are effective, biocompatible, and biodegradable, and thus, they are promising to be the next generation of drugs for treating infections caused by fungi. The identification processes of highly active peptides, however, are still time-consuming and labor-intensive. Quantitative structure-activity relationships (QSARs) have dramatically facilitated the discovery of many bioactive drug molecules without a priori knowledge. In this study, we have established an effective QSAR protocol for screening antifungal peptides. The screening protocol integrates an accurate antifungal peptide classification model and four activity prediction models against specified target fungi. A demonstrative application was performed on more than three million candidate peptides, and three outstanding peptides were identified. The whole screening took only a few days, which was much faster than our previous experimental screening works. In conclusion, the protocol is useful and effective for reducing repetitive laboratory efforts in antifungal peptide discovery. The prediction server (antifungal Web server) is freely available at www.chemoinfolab.com/antifungal.