BIOPEP database of sensory peptides and amino acids

Peptide classification landscape: An in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance

Peptides are gaining significant attention in diverse fields such as the pharmaceutical market has seen a steady rise in peptide-based therapeutics over the past six decades. Peptides have been utilized in the development of distinct applications including inhibitors of SARS-COV-2 and treatments for conditions like cancer and diabetes. Distinct types of peptides possess unique characteristics, and development of peptide-specific applications require the discrimination of one peptide type from others. To the best of our knowledge, approximately 230 Artificial Intelligence (AI) driven applications have been developed for 22 distinct types of peptides, yet there remains significant room for development of new predictors. A Comprehensive review addresses the critical gap by providing a consolidated platform for the development of AI-driven peptide classification applications. This paper offers several key contributions, including presenting the biological foundations of 22 unique peptide types and categorizes them into four main classes: Regulatory, Therapeutic, Nutritional, and Delivery Peptides. It offers an in-depth overview of 47 databases that have been used to develop peptide classification benchmark datasets. It summarizes details of 288 benchmark datasets that are used in development of diverse types AI-driven peptide classification applications. It provides a detailed summary of 197 sequence representation learning methods and 94 classifiers that have been used to develop 230 distinct AI-driven peptide classification applications. Across 22 distinct types peptide classification tasks related to 288 benchmark datasets, it demonstrates performance values of 230 AI-driven peptide classification applications. It summarizes experimental settings and various evaluation measures that have been employed to assess the performance of AI-driven peptide classification applications. The primary focus of this manuscript is to consolidate scattered information into a single comprehensive platform. This resource will greatly assist researchers who are interested in developing new AI-driven peptide classification applications.

A novel directed enzymolysis strategy for the preparation of umami peptides in Stropharia rugosoannulata and its mechanism of taste perception

This study aimed to explore the effect of directed enzymolysis on the umami characteristics of S. rugosoannulata, clarify the flavour formation mechanism of umami peptides. We expressed a new aminopeptidase (DNPEP) and obtained the umami peptides of S. rugosoannulata by alkaline protease and DNPEP. The optimal enzymolysis conditions were temperature 55 °C, solid-liquid ratio 1:20 (g/mL), alkaline protease enzymolysis (60 min, 0.5 %, pH 9.0), and DNPEP enzymolysis (80 min, 0.3 %, pH 8.0). The umami peptide components were separated by ultrafiltration and gel filtration chromatography. Six umami peptides (EEAKFN, KAELDLH, LADVEEDK, LKEAHDVA, AHLDYGDGK, and LGKSEDDVSK) were identified by LC-MS/MS and virtual screening, and the umami thresholds of the peptides were 0.15-1.09 mmol/L. Molecular simulations revealed that the amino acid residues Glu301, Ser217, Asp218, and Arg277 were crucial in the binding of the umami peptide to the T1R1/T1R3. Therefore, this study provides a theoretical basis for the development of mushroom condiments.

Effect of Canthaxanthin on Egg Yolk Quality of Huaixiang Laying Hens at Normal and High Temperature

(1) Background: Thermal stress in Guangdong's tropical/subtropical regions significantly compromises yolk quality in Huaixiang chickens. Canthaxanthin (CX), an effective feed additive, has been demonstrated to not only enhance the nutritional composition of egg yolks but also mitigate heat stress. This study systematically evaluates the effects of dietary CX supplementation on egg production rate and yolk nutritional components (e.g., amino acids, lipids, vitamin B2) in Huaixiang hens under both normal and high-temperature environments. (2) Methods: A factorial design was implemented, exposing hens to either thermoneutral (25 ± 2 °C, 65-75% RH) or high-temperature (32 ± 2 °C, 65-75% RH) conditions. Diets were supplemented with graded CX levels (0, 4, 6, 8, or 10 mg/kg) for 9 weeks. Laying performance and yolk nutritional profiles (amino acids, lipids, minerals, vitamin B2) were evaluated at 3-week intervals (3rd, 6th, and 9th weeks. (3) Results: Under normal temperature conditions, the addition of CX significantly enhanced the laying rate, relative yolk weight, yolk color score, lecithin (LEC) content, and it optimized the amino acid profile of the yolk. Under high-temperature conditions, the laying rate, yolk weight, yolk weight ratio, total amino acid content, yolk triglyceride (TG), LEC, and vitamin B2 (VB2) levels in Huaixiang chickens all decreased. However, supplementation with CX under high-temperature conditions effectively mitigated these adverse effects: the laying rate was restored to levels observed under normal temperature conditions, while the relative yolk weight, color score, TG, total cholesterol (TC), LEC, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), calcium (Ca), and VB2 levels were significantly higher than those in the heat-stressed control group. Additionally, the amino acid composition of the yolk was improved. (4) Conclusion: CX enhances the nutrient content of egg yolks under both normal and high-temperature conditions, providing a valuable reference for the production of healthy and high-quality eggs.

The co-fermentation of Actinomucor elegans and Monascus purpureus for the production of meat flavor with soybean protein

This study aimed to prepare meat flavor essence through Monascus purpureus and Actinomucor elegans co-fermentation. The optimal fermentation conditions were determined based on the changes in physicochemical properties during the fermentation process, combined with sensory evaluation. Subsequently, the flavor components of the meat flavor essence were analyzed through solid phase microextraction after undergoing the Maillard reaction from the fermentation broth. Gas chromatography-mass spectrometry analysis identified 62 volatile compounds, among which 25 aroma-active substances were detected by aroma extraction dilution analysis/gas chromatography-olfactometry. By calculating the odor activity values (OAVs), seven aroma-active compounds with OAVs > 1 were identified as the most significant contributors to the aroma. Through aroma reconstitution and omission experiments, the accuracy of these key flavor compounds was verified, elucidating each substance's contribution to the essence's overall aroma. This study serves as a foundation for future investigations into the correlation between the flavor of fermented flavorings and their precursor substances, optimizing the mixed-culture fermentation process and enhancing the quality of meat flavor essences.

Food bioactive peptides: functionality beyond bitterness

Bitter taste is an aversive taste because it is unconsciously associated with toxic compounds. However, a considerable variability in bitter sensitivity exists in those who have the genetic polymorphism for bitter taste receptors (TAS2Rs). Besides the oral cavity, TAS2Rs are present in many body tissues, including the gastrointestinal tract; therefore, they are crucial players both in the gustatory/hedonic system and in the homeostatic system, triggering numerous biological responses, including adipogenesis, carcinogenesis, or immunity. Bitter-tasting compounds are widely distributed in plant and animal foods and belong to many chemical classes. In this study, the evidence was reviewed on bitter peptides, considering the food sources, their formation in food under different processing and storage conditions and in the gastrointestinal tract during digestion, as well as their biological activities. Bitterness associated with peptides is due to the presence of hydrophobic amino acids in the C-terminus. The current literature mainly explores the enzymes and hydrolysis conditions, with the aim of reducing the formation of bitter peptides in hydrolysate preparation or food. Few studies highlight the bioactivity (namely, antihypertensive, antidiabetic, antioxidant, or immunity boosting), besides the bitterness. However, encapsulation of bitter peptides has been tentatively used to develop antihypertensive and antidiabetic supplements. In the era of personalized nutrition and precision medicine, the evidence available suggests the opportunity to use bitter bioactive peptides as functional ingredients in food. Such types of food may modulate a plethora of physiological mechanisms by targeting TAS2Rs in the gastrointestinal tract, thus modulating appetite sensations or gastrointestinal motility and discomfort according to individual nutritional needs and goals. More studies are needed to optimize the technological strategies to target TAS2Rs by bitter bioactive peptides, improve their stability in food, and validate the biological efficacy through well-designed in vivo studies.

Integrative approach to assessing bioactivity from hempseed protein isolate extracted and dehydrated by different methods: Synergising in silico prediction and in vitro validation

This study demonstrated a comprehensive workflow combining in silico screening and prediction with in vitro validation to investigate the bioactivity of hempseed protein isolate (HPI) extracted and dehydrated using different methods. By adopting an in silico approach, 13 major proteins of HPI were hydrolysed by 20 selected enzymes, leading to the prediction of 20 potential bioactivities. With papain hydrolysis, dipeptidyl peptidase-IV (DPP4) and angiotensin-converting enzyme (ACE) inhibitory activities emerged as having the highest potential. In vitro experiments confirmed these predictions, with DPP4 and ACE inhibitory activities displaying IC50 values of 0.32-0.42 mg/mL and 6.8-9.17 μg/mL, respectively. A strong correlation (r2 = 0.96) was observed between in vitro protein inhibitory results and in silico predicted data. This study demonstrated an effective integrative approach for predicting bioactive peptides in food protein, providing valuable guidance on its processing to create value-added products.

Enhancement of nutritional, organoleptic, and umami qualities of chicken soup induced by enzymatic pre-treatment of chicken

To enhance both the quality and cooking efficiency of chicken soup, the effect of enzymatic pre-treatment of chicken on the quality of the chicken soup was investigated in this study. Results indicated that the application of enzymatic pre-treatment markedly enhanced the sensory attributes, physicochemical properties, and nutritional value, compared with the control sample. Specifically, the chicken soup with enzymatic pre-treatment exhibited a significant increase in the concentration of water-soluble proteins, 5'-nucleotides, and umami amino acids (P < 0.05). There were 52 umami peptides identified in enzymatic pre-treatment chicken soup, and eight abundant umami peptides were chosen for molecular docking. The analysis revealed that the primary active sites for interaction between the umami peptide and the T1R1/T1R3 receptor were ASP-30, GLU-27, and MET-342. Therefore, enzymatic pre-treatment of chicken facilitates high-value-added chicken soup products and provides a new approach to improve the quality and efficiency of chicken soup.

Efficient screening and discovery of umami peptides in Douchi enhanced by molecular dynamics simulations

In this study, a partial least squares discriminant analysis (PLS-DA) discriminant model for umami peptides was constructed based on molecular dynamics simulation data, achieving a R 2 value of 0.949 and a Q 2 value of 0.558. Using this novel model and bioinformatics screening methods, five new umami peptides (EALEATAQ, SPPTEE, SEEG, KEE, and FEE, with umami taste thresholds of 0.139, 0.085, 0.096, 0.060, and 0.079 mg/mL, respectively) were identified in Douchi. Molecular docking revealed that the residues ASN150 of T1R1, as well as SER170, GLU301 and GLN389 of T1R3, might be key amino acid residues for the binding of umami peptides to T1R1/T1R3. Molecular dynamics simulations revealed significant differences in the root-mean-square fluctuation (RMSF) values between the two complex systems of umami peptides-T1R1/T1R3 and non-umami peptides-T1R1/T1R3. The newly constructed umami peptide discriminant model can improve the accuracy of umami peptide screening and enhance the efficiency of discovering new umami peptides.

Effects of various supplemental levels of multi-enzyme complex on amino acid profiles in egg yolk, antioxidant capacity, cecal microbial community and metabolites of laying hens

This study aimed to investigate the effects of multi-enzyme (alkaline protease, xylanase, glucanase, β-mannanase, cellulase, acid protease, glucoamylase, and α-galactosidase) on antioxidant capacity, egg quality, amino acid profiles in yolk, cecal microflora and metabolites in laying hens. A total of 384 Jingfen No.6 laying hens aged 65 weeks were randomly divided into 4 treatments groups (6 replicates per group) and fed diets containing 0, 150, 300, or 600 mg kg-1 multi-enzyme over an 8-week feeding duration. Our findings revealed that supplementation with 600 mg kg-1 of multi-enzyme significantly increased the albumen height (P < 0.05) and haugh unit (P < 0.05). Moreover, as the levels of multi-enzyme supplementation in the diet increased, there were significant increases in activities of total antioxidant capacity (T-AOC) in serum (P < 0.05) and glutathione peroxidase (GSH-Px) in the liver (P < 0.05). Different levels of multi-enzyme supplementation significantly affected the composition of amino acid profiles in the yolk. Furthermore, the results from 16S rRNA sequencing and untargeted metabolomics analysis of cecal content revealed that multi-enzyme supplementation altered the cecal microflora and metabolite profiles. We found the relative abundance of the Bacteroidota phyla in T600 group was significantly increased (P < 0.05) compared to CON and T150 groups, but the relative abundance of the Firmicutes phylum in T600 group were significantly lower than T150 group (P < 0.05). At the genus level, the relative abundance of the Parabacteroides genera in T300 group, the Faecalibacterium genera in T300 and T600 groups, the norank_f_Prevotellaceae genera in treatment groups (T150, T300 and T600), the norank_f_Peptococcaceae genera in T600 group, and the Monoglobus genera in T1 group were significantly increased. The KEGG pathway analysis showed that the common enrichment metabolic pathways of each treatment group compared to the CON group were glycine, serine and threonine metabolism, foxo signaling pathway and mTOR signaling pathway, and the enrichment metabolic pathways shared by T300 vs CON and T600 vs CON was galactose metabolism and glycolysis/gluconeogenesis pathways. Correlation analysis identified notable relationships between specific microbes and metabolites with T-AOC in serum, GSH-Px activity in the liver, amino acids in yolk, albumen height, and haugh units. Overall, this study suggests that multi-enzyme supplementation regulated the cecal microbial community and metabolism, potentially influencing amino acid profiles in yolk, antioxidant capacity, and egg quality.

Identification of salty peptides from enzymolysis extract of oyster by peptidomics and virtual screening

Salty peptide as an important sodium substitute, which could reduce the risk of cardiovascular disease caused by excessive sodium intake. In this study, novel salty peptides were prepared and identified from enzymolysis extract of oysters by peptitomic identification, virtual screening and solid phase synthesis. Additionally, molecular simulation was used to study the taste mechanism of salty peptides. 316 peptides were identified in the enzymatic hydrolysates of oysters. 6 peptides, selected through virtual screening, were synthesized using solid-phase synthesis, and EK, LFE, LEY and DR were confirmed to possess a pleasing salty taste through electronic tongue evaluation. Molecular docking results indicated that these 4 peptides could enter the binding pocket within the transmembrane channel-like 4 (TMC4) cavity, wherein salt bridges, hydrogen bonds and attractive charges were the main binding forces. This study provides a rapid screening method for salty peptides in sea food products but possibly applied for other sources.

Novel and efficient techniques in the discovery of antioxidant peptides

As a research hotspot in food science and nutrition, antioxidant peptides can function by scavenging free radicals, inhibiting peroxides, and chelating metal ions. Therefore, how to efficiently discover and screen antioxidant peptides has become a key issue in research and production. Traditional discovery methods are time-consuming and costly, but also challenging to resolve the quantitative structure-activity relationship of antioxidant peptides. Several novel techniques, including artificial intelligence, molecular docking, bioinformatics, quantum chemistry, phage display, switchSENSE, surface plasmon resonance, and fluorescence polarization, are emerging rapidly as solutions. These techniques possess efficient capability for the discovery of antioxidant peptides, even with the potential for high-throughput screening. In addition, the quantitative structure-activity relationship can be resolved. Notably, combining these novel techniques can overcome the drawbacks of a single one, thus improving efficiency and expanding the discovery horizon. This review has summarized eight novel and efficient techniques for discovering antioxidant peptides and the combination of techniques. This review aims to provide scientific evidence and perspectives for antioxidant peptide research.

Quantification- and structural-taste intensity of umami peptides from Agrocybe aegerita through quantitative structure-activity relationship

Agrocybe aegerita, one of the edible mushroom varieties, is popular among consumers for its umami taste. Umami peptides, including EV, EG, EY, ENG, ECG, DEL, DDL, PEG, PEEL, DGPL, and EDCS are the main umami compounds in A. aegerita. In this study, when the concentration of these 11 umami peptides was 5 mg/mL, the corresponding relative umami intensity (measured by MSG concentration) ranged from 4.457 to 5.240 mg/mL, with DDL being the highest. All umami peptides exhibited better umami taste under neutral and weakly acidic conditions (pH 6-7). EY and ENG, with a higher umami intensity at 70 °C, were more suitable for a wide application in thermally processed foods. Additionally, the relationship between the structure and strength of umami peptides was explored using a three-dimensional quantitative structure-activity relationship model with an R2 of 0.987. Overall, umami peptides in A. aegerita possess strong potential for application in food processing.

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

BACKGROUND

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

RESULTS

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

CONCLUSION

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

Decoding of Salty/Saltiness-Enhancing Peptides Derived from Goose Hemoglobin and the Interaction Mechanism with TMC4 Receptor

Amid the growing concern for health-oriented food choices, salt reduction has received widespread attention, particularly in the exploitation of salt alternatives. Peptides with a saltiness-enhancing effect may provide an alternative method for salt reduction. The objective of this study was to isolate and extract novel peptides with salt-reducing effects by fermenting goose blood using a Lactobacillus plantarum strain. Five potential target peptides were screened by a virtual database prediction and molecular docking. Sensory evaluation and E-tongue analysis showed that five peptides (NEALQRM, GDAVKNLD, HAYNLRVD, PEMHAAFDK, and AEEKQLITGL) were identified as target peptides. Particularly, the results of E-tongue showed that GDAVKNLD can increase the saltiness intensity (2.87 ± 0.02) in the complex system. The sensory evaluation results also indicated an increase in saltiness intensity (46.67 ± 4.67 mmol/L NaCl) after adding GDAVKNLD. The results of molecular dynamics simulation indicated that five peptides have good ability to bind tightly to TMC4 receptor, thereby stimulating it to exert an active effect. And these peptides interacted with the TMC4 receptor via hydrogen bonding, hydrophobic interactions, and electrostatic interactions. This research lays a theoretical foundation for discovering novel salty/saltiness-enhancing peptides and provides meaningful contributions to efforts in salt reduction.

UmamiPreDL: Deep learning model for umami taste prediction of peptides using BERT and CNN

Taste is crucial in driving food choice and preference. Umami is one of the basic tastes defined by characteristic deliciousness and mouthfulness that it imparts to foods. Identification of ingredients to enhance umami taste is of significant value to food industry. Various models have been shown to predict umami taste using feature encodings derived from traditional molecular descriptors such as amphiphilic pseudo-amino acid composition, dipeptide composition, and composition-transition-distribution. Highest reported accuracy of 90.5 % was recently achieved through novel model architecture. Here, we propose use of biological sequence transformers such as ProtBert and ESM2, trained on the Uniref databases, as the feature encoders block. With combination of 2 encoders and 2 classifiers, 4 model architectures were developed. Among the 4 models, ProtBert-CNN model outperformed other models with accuracy of 95 % on 5-fold cross validation data and 94 % on independent data.

THPdb2: compilation of FDA approved therapeutic peptides and proteins

During the past 20 years, there has been a significant increase in the number of protein-based drugs approved by the US Food and Drug Administration (FDA). This paper presents THPdb2, an updated version of the THPdb database, which holds information about all types of protein-based drugs, including peptides, antibodies, and biosimilar proteins. THPdb2 contains a total of 6,385 entries, providing comprehensive information about 894 FDA-approved therapeutic proteins, including 354 monoclonal antibodies and 85 peptides or polypeptides. Each entry includes the name of therapeutic molecule, the amino acid sequence, physical and chemical properties, and route of drug administration. The therapeutic molecules that are included in the database target a wide range of biological molecules, such as receptors, factors, and proteins, and have been approved for the treatment of various diseases, including cancers, infectious diseases, and immune disorders.

Understanding the Role of Filamentous Actin in Food Quality: From Structure to Application

Actin, a multifunctional protein highly expressed in eukaryotes, is widely distributed throughout cells and serves as a crucial component of the cytoskeleton. Its presence is integral to maintaining cell morphology and participating in various biological processes. As an irreplaceable component of myofibrillar proteins, actin, including G-actin and F-actin, is highly related to food quality. Up to now, purification of actin at a moderate level remains to be overcome. In this paper, we have reviewed the structures and functions of actin, the methods to obtain actin, and the relationships between actin and food texture, color, and flavor. Moreover, actin finds applications in diverse fields such as food safety, bioengineering, and nanomaterials. Developing an actin preparation method at the industrial level will help promote its further applications in food science, nutrition, and safety.

Bioturbation effect of artificial inoculation on the flavor metabolites and bacterial communities in the Chinese Mao-tofu fermentation

A comparison between artificially inoculated Mao-tofu (CC) and naturally fermented Mao-tofu (MM) indicated that artificially adding Mucor plasmaticus to Mao-tofu dramatically enhanced the essential amino acid (EAA) content, as well as umami and sweet amino acids. Gas chromatography-tandem mass spectrometry (GC-MS/MS) analysis revealed that phenol (3.226 μg/g), 1-octen-3-ol (5.031 μg/g), ethyl heptanoate (1.646 μg/g), and indole (3.422 μg/g) were the key flavor components in Mao-tofu. Unlike MM, CC displayed a substantial increase in esters and a considerable decrease in foul odor substances, including sulfur-containing compounds and indole. Lactococcus raffinolactis, Enterobacter sp. 638, and Streptococcus parauberis KCTC 11537 represented the key bacterial species altering the amino acids and flavor of Mao-tofu according to PacBio single-molecule real-time (SMRT) sequencing and correlation analysis. This study presents the technical feasibility of artificially inoculating Mao-tofu to regulate the core bacterial communities and control the quality of fermented soybean products.

Bioinformatics and bioactive peptides from foods: Do they work together?

We live in the Big Data Era which affects many aspects of science, including research on bioactive peptides derived from foods, which during the last few decades have been a focus of interest for scientists. These two issues, i.e., the development of computer technologies and progress in the discovery of novel peptides with health-beneficial properties, are closely interrelated. This Chapter presents the example applications of bioinformatics for studying biopeptides, focusing on main aspects of peptide analysis as the starting point, including: (i) the role of peptide databases; (ii) aspects of bioactivity prediction; (iii) simulation of peptide release from proteins. Bioinformatics can also be used for predicting other features of peptides, including ADMET, QSAR, structure, and taste. To answer the question asked "bioinformatics and bioactive peptides from foods: do they work together?", currently it is almost impossible to find examples of peptide research with no bioinformatics involved. However, theoretical predictions are not equivalent to experimental work and always require critical scrutiny. The aspects of compatibility of in silico and in vitro results are also summarized herein.

Combining molecular docking and molecular dynamics simulation to discover four novel umami peptides from tuna skeletal myosin with sensory evaluation validation

Umami peptides are an important component of food flavoring agents and have high nutritional value. This work aimed to identify umami peptides from tuna skeletal myosin using a new model method of computer simulation, explore their umami mechanism, and further validate the umami tastes with sensory evaluation. Umami peptides LADW, MEIDD, VAEQE, and EEAEGT were discovered, and all of them bound to taste type 1 receptor 1 and receptor 3 via hydrogen bonds and van der Waals forces to form stable complexes. LADW exhibited the best affinity energy and binding capability. Sensory evaluation and electronic tongue confirmed that all peptides possessed an umami taste, and LADW exhibited the strongest umami intensity. This study not only explored four novel umami peptides to improve the value of tuna skeletal myosin but also provided a new method for the rapid discovery of umami peptides.

Excavation, identification and structure-activity relationship of heat-stable umami peptides in the processing of Wuding chicken

Umami peptides from different stages of Wuding chicken processing were discovered, isolated, and purified using ultrafiltration membrane, gel filtration chromatography, and reversed-phase high-performance liquid chromatography, and the binding mechanism was explored. Twelve umami peptides were found by nano-scale liquid chromatography-tandem mass spectrometry, three of which (HLEEEIK, LDDALR, and ELY) existed throughout the processing step. The umami score and the frequency of active fragments of umami were highest for LEEEL, followed by EEF. The main active sites between umami peptide and receptor T1R1/T1R3 were Tyr262, Glu325, and Glu292, and hydrophobic interaction and hydrogen bonding were the main forces, and bitter amino acids were also important components of umami peptides. It was found for the first time that heat-stable umami peptides exist in Wuding chickens, which provides a basis for the identification and screening of umami peptides in local chickens, and also helps to study the structure-activity relationship of umami peptides.

Fatty acid modification of casein bioactive peptides nano-assemblies, synthesis, characterization and anticarcinogenic effect

In this study, the nano-assemblies of bovine casein hydrolyzed peptides (HP) modified by fatty acids with various alkyl chain lengths (C8, C10, C12 and C14) were synthesized. The physicochemical properties of HP-C8-HP-C14 nano-assemblies were characterized using spectra, laser particle size analyzer, contact angle meter, scanning electron microscope (SEM) and cryo-transmission electron microscope (Cryo-TEM). HP-C8 and HP-C10 self-assembled into a hollow cube cage with an average size of ~500 nm, and the assembly of HP-C12 showed a flower-shaped morphology with more dispersed behavior, and droplet size was observed as ~20 nm. The in vitro cytotoxicity against human breast cancer cells MCF-7 was tested using CCK-8 assay and flow cytometry analysis. HP-C12 showed the highest cytotoxicity for MCF-7 cells with an inhibition rate of 66.03 % ± 0.35 % with an IC50 value of 7.4 μM among HP-Cn. HP-C8, HP-C10 and HP-C12 significantly affected on the migration, invasion and apoptosis of MCF-7 cells. The apoptosis mechanism may depend on the upregulation of anti-apoptotic protein Bcl-2 as well as pro-apoptotic proteins Bax and caspase-8. The dead MCF-7 cells were analyzed with UHPLC-MS/MS using untargeted metabolomics, revealing key metabolic pathways.

Identification, flavor characteristics and molecular docking of umami taste peptides of Xuanwei ham

To better understand the palatable properties of Xuanwei ham, the aqueous extract was isolated, analyzed and combin with sensory evaluation. Of umami-tasting activity and umami-enhancing impact, four new peptides (MDAIKKMQ, RKYEEVAR, YVGDEAQSKRG, and VNVDEVGGEALGR) were extracted and identified by ultrafiltration, gel separation, reverse performance liquid chromatography, and nano-LC-MS / MS. Sensory evaluation results showed that all of them had umami activity and enhanced umami taste, among which VNVDEVGGEALGR had the best effect. These peptides' umami taste thresholds ranged from 0.25 to 0.8 mg/mL. The MSG solution's umami taste threshold ranged from 0.125 to 0.5 mg/mL. Molecular docking results showed that the four umami peptides could be embedded into the binding pocket of the T1R3 cavity of the umami taste receptor T1R1/T1R3, wherein the binding sites Asp219, Asp150, and Thr179 may play crucial roles, and Glu222, Asp108, Glu217 and Glu148 play auxiliary roles. Hydrogen bonding and hydrophobic interactions were the most prominent interaction forces. This study helps to clarify the flavor characteristics of Xuanwei ham and could improve new processing technology.

MFPPDB: a comprehensive multi-functional plant peptide database

Plants produce a wide range of bioactive peptides as part of their innate defense mechanisms. With the explosive growth of plant-derived peptides, verifying the therapeutic function using traditional experimental methods are resources and time consuming. Therefore, it is necessary to predict the therapeutic function of plant-derived peptides more effectively and accurately with reduced waste of resources and thus expedite the development of plant peptides. We herein developed a repository of plant peptides predicted to have multiple therapeutic functions, named as MFPPDB (multi-functional plant peptide database). MFPPDB including 1,482,409 single or multiple functional plant origin therapeutic peptides derived from 121 fundamental plant species. The functional categories of these therapeutic peptides include 41 different features such as anti-bacterial, anti-fungal, anti-HIV, anti-viral, and anti-cancer. The detailed physicochemical information of these peptides was presented in functional search and physicochemical property search module, which can help users easily access the peptide information by the plant peptide species, ID, and functions, or by their peptide ID, isoelectric point, peptide sequence, and molecular weight through web-friendly interface. We further matched the predicted peptides to nine state-of-the-art curated functional peptide databases and found that at least 293,408 of the peptides possess functional potentials. Overall, MFPPDB integrated a massive number of plant peptides have single or multiple therapeutic functions, which will facilitate the comprehensive research in plant peptidomics. MFPPDB can be freely accessed through http://124.223.195.214:9188/mfppdb/index.

Yolk Fatty Acid Profile and Amino Acid Composition in Eggs from Hens Supplemented with ß-Hydroxy-ß-Methylbutyrate

In recent years, a supplementation of livestock animals, including poultry, with β-Hydroxy-β-methylbutyrate (HMB) has gained attention for its effects on protein and fat metabolism. This study investigates the effects of HMB in the laying hen diet on egg quality, focusing on amino acid and fatty acid composition. Laying hens were supplemented with 0.02% HMB, with performance parameters and egg components analyzed. HMB supplementation led to increased albumen weight, influencing egg weight while also reducing feed intake per egg without affecting laying rate, yolk indices, fat, or cholesterol content. Notably, the study revealed significant changes in egg amino acid and fatty acid profiles due to HMB supplementation. Various amino acids, including glycine, serine, and isoleucine, were altered in the yolk, impacting nutritional value and potential health benefits. Regarding fatty acids, the study observed changes in both saturated as well as n-6 and n-3 fatty acids, affecting the overall lipid profile of egg yolks. However, the shifts in fatty acid composition could have implications for cardiovascular health due to altered ratios of n-6/n-3 fatty acids. Further research is required to comprehensively understand the implications of these findings for consumer-oriented egg quality and health benefits.

Identification and In Silico Analysis of ACE-Inhibitory Peptides Derived from Milk Fermented by Lacticaseibacillus paracasei

Inhibition of angiotensin I-converting enzyme (ACE) activity is an effective way to treat hypertension. In the present study, the ability to produce ACE-inhibitory peptides during fermentation of skimmed milk by the Lacticaseibacillus paracasei M3 strain was evaluated, and the inhibitory mechanism and stability were studied by bioinformatics analysis. The results showed that the ACE inhibition activity of fermented milk was 71.94 ± 1.39%. After digestion with gastric juice and pancreatic juice, the ACE inhibitory activities of the fermented milk were 78.40 ± 1.93 and 74.96 ± 1.73%, respectively. After the fermented milk was purified using ultrafiltration and gel chromatography, 11 peptides from milk proteins were identified and sequenced by Nano LC-MS/MS. Molecular docking displayed that peptide PWIQPK had a high affinity, with ACE showing a binding energy of -6.10 kcal/mol. Hydrogen bonds were formed between PWIQPK and Glu384 in the S1 active pocket of ACE and Asp358. In addition, van der Waals forces were observed. In silico proteolysis suggested that PWIQPK could resist the digestion of pepsin and trypsin, indicating that it is relatively stable in the digestive tract. All results indicate that milk fermented by L. paracasei M3 has the potential to be used as a functional food having antihypertensive effects.

In Silico Methodologies to Improve Antioxidants' Characterization from Marine Organisms

Marine organisms have been reported to be valuable sources of bioactive molecules that have found applications in different industrial fields. From organism sampling to the identification and bioactivity characterization of a specific compound, different steps are necessary, which are time- and cost-consuming. Thanks to the advent of the -omic era, numerous genome, metagenome, transcriptome, metatranscriptome, proteome and microbiome data have been reported and deposited in public databases. These advancements have been fundamental for the development of in silico strategies for basic and applied research. In silico studies represent a convenient and efficient approach to the bioactivity prediction of known and newly identified marine molecules, reducing the time and costs of "wet-lab" experiments. This review focuses on in silico approaches applied to bioactive molecule discoveries from marine organisms. When available, validation studies reporting a bioactivity assay to confirm the presence of an antioxidant molecule or enzyme are reported, as well. Overall, this review suggests that in silico approaches can offer a valuable alternative to most expensive approaches and proposes them as a little explored field in which to invest.

Microbiology, flavor formation, and bioactivity of fermented soybean curd (furu): A review

Soybeans are an important plant-based food but its beany flavor and anti-nutritional factors limit its consumption. Fermentation is an effective way to improve its flavor and nutrition. Furu is a popular fermented soybean curd and mainly manufactured in Asia, which has been consumed for thousands of years as an appetizer because of its attractive flavors. This review first classifies furu products on the basis of various factors; then, the microorganisms involved in its fermentation and their various functions are discussed. The mechanisms for the formation of aroma and taste compounds during fermentation are also discussed; and the microbial metabolites and their bioactivities are analyzed. Finally, future prospects and challenges are introduced and further research is proposed. This information is needed to protect the regional characteristics of furu and to regulate its consistent quality. The current information suggests that more in vivo experiments and further clinical trials are needed to confirm its safety and the microbial community needs to be optimized and standardized for each type of furu to improve the production process.

Accurate Prediction of Anti-hypertensive Peptides Based on Convolutional Neural Network and Gated Recurrent unit

Hypertension (HT) is a general disease, and also one of the most ordinary and major causes of cardiovascular disease. Some diseases are caused by high blood pressure, including impairment of heart and kidney function, cerebral hemorrhage and myocardial infarction. Due to the limitations of laboratory methods, bioactive peptides for the treatment of HT need a long time to be identified. Therefore, it is of great immediate significance for the identification of anti-hypertensive peptides (AHTPs). With the prevalence of machine learning, it is suggested to use it as a supplementary method for AHTPs classification. Therefore, we develop a new model to identify AHTPs based on multiple features and deep learning. And the deep model is constructed by combining a convolutional neural network (CNN) and a gated recurrent unit (GRU). The unique convolution structure is used to reduce the feature dimension and running time. The data processed by CNN is input into the recurrent structure GRU, and important information is filtered out through the reset gate and update gate. Finally, the output layer adopts Sigmoid activation function. Firstly, we use Kmer, the deviation between the dipeptide frequency and the expected mean (DDE), encoding based on grouped weight (EBGW), enhanced grouped amino acid composition (EGAAC) and dipeptide binary profile and frequency (DBPF) to extract features. For Kmer, DDE, EBGW and EGAAC, it is widely used in the field of protein research. DBPF is a new feature representation method designed by us. It corresponds dipeptides to binary numbers, and finally obtains a binary coding file and a frequency file. Then these features are spliced together and input into our proposed model for prediction and analysis. After a tenfold cross-validation test, this model has a better competitive advantage than the previous methods, and the accuracy is 96.23% and 99.10%, respectively. From the results, compared with the previous methods, it has been greatly improved. It shows that the combination of convolution calculation and recurrent structure has a positive impact on the classification of AHTPs. The results show that this method is a feasible, efficient and competitive sequence analysis tool for AHTPs. Meanwhile, we design a friendly online prediction tool and it is freely accessible at http://ahtps.zhanglab.site/ .

Fish proteins as potential precursors of taste-active compounds: an in silico study

BACKGROUND

Fish protein is a good source of amino acids and peptides with sensory properties. Theoretically, the type of protein affects the taste quality of the protein hydrolysates. To better use fish protein in the food ingredients industry, an in silico approach was adopted to evaluate the potential of fish protein to release taste-active compounds.

RESULTS

Six types of protein from seven commercial fishes were screened from the Uniprot knowledge base. The results showed that a remarkable number of umami fragments presented in myosin and parvalbumin (PB), such as glutamic acid (Glu), aspartic acid (Asp), and Asp- and Glu- containing peptides, whereas sweet amino acids and bitter peptides (e.g., Pro- and Gly- containing peptides) were mainly found in collagen (CGI) in all fish samples. After the in silico proteolysis by papain, a difference in the profile of taste-active fragments was observed among the six types of proteins. Amino acids were the main hydrolysis products of these proteins, especially umami, sweet, and bitter amino acids, significantly contributing to the taste formation of protein hydrolysates. Besides, the myosin and CGI hydrolysates were abundant in taste active peptides both in types and quantities.

CONCLUSION

Myosin is a promising protein source for producing umami fragments, and CGI seems to be a good precursor of sweet and bitter fragments. Different types of protein have an essential effect on the taste of protein hydrolysates. © 2022 Society of Chemical Industry.

Insights into ultrasonic treatment on the mechanism of proteolysis and taste improvement of defective dry-cured ham

To investigate the effects of ultrasonic treatment on proteolysis and taste development of defective dry-cured ham, sensory attributes, enzyme activities, protein degradation and free amino acids were evaluated after different ultrasonic treatments. The ultrasonic treatment of 1000 W & 50 °C significantly increased the intensities of overall taste, umami, sweetness and richness, and decreased bitterness values compared with other groups. The residual activities of DPP I and cathepsin B + L in 1000 W & 50 °C maintained 48.71% and 24.94% of control group, respectively; the intense degradation of structural proteins was observed by label-free proteomics, accordingly. The contents of total free amino acids from 4522.64 mg/100 g muscles in control group increased to 5838.75 mg/100 g muscles in 1000 W & 50 °C; the largest increase of sweet and umami amino acids observed in 1000 W & 50 °C was responsible for the improvement of taste quality of defective dry-cured ham.

Characteristics of umami peptides identified from porcine bone soup and molecular docking to the taste receptor T1R1/T1R3

To study the umami peptides derived from porcine bone soup, ultrafiltration fractions with molecular weight less than 1 kDa were screened by sensory analysis which showed higher umami intensity. Four potential umami peptides were identified from the screened fractions by Nano-LC-Q-TOF-MS/MS, among which FSGLDGAK, FAGDDAPR and FSGLDGSK were proved to have dominant umami taste by sensory evaluation and electronic tongue. The threshold of the three peptides ranged from 0.1 mM to 0.89 mM. In addition, FSGLDGSK had the highest umami intensity and exhibited a significant umami-enhancing effect in a 0.35% monosodium glutamate solution. The results of molecular docking simulation showed that the key binding sites of taste receptor type 1 member 1 (His71, Asp108 and Glu301) and taste receptor type 1 member 3 (Glu48, Ser104 and His145) were crucial to the interaction with the umami peptides. Besides, electrostatic interaction and hydrogen bond mainly contributed to the mechanism of umami taste.

Antioxidant and immunomodulatory potency of Lacticaseibacillus rhamnosus NCDC24 fermented milk-derived peptides: A computationally guided in-vitro and ex-vivo investigation

Infections of microbial and non-microbial origins have been associated with significant immunological manifestations, thereby underscoring the need for a thorough understanding and investigation of novel immunomodulatory and antioxidant molecules that could prevent these incidences. To this end, we herein aim to identify fermented milk peptides with antioxidant and immunomodulatory properties that could be exploited for specific future applications. Our computational prediction models indicate that these peptides are non-toxic and possess considerable hydrophobicity (19.82-38.96 %) and functionality. Further analyses reveal that two of the four peptides, i.e., Pep 1 (AGWNIPM) and Pep 4 (YLGYLEQLLR), possess higher in-vitro antioxidant activity. The immunomodulatory potential of these two peptides (Pep 1 and Pep 4) is further demonstrated by using a combination of molecular simulation trajectory and ex-vivo approaches. Both peptides demonstrate ability to control the production of pro- inflammatory (TNF-α, IL-1, and IL-6) and anti-inflammatory (IL-10) cytokines as well as nitric oxide release in LPS-stimulated murine peritoneal macrophages. Similarly, peptide interferences also lead to significant (P < 0.05) improvement in macrophage phagocytic capacity. Taken together, these findings highlight the antioxidant and immunomodulatory properties of fermented milk peptides (Pep 1 and Pep 4) within the cellular environment and should facilitate prospective studies exploring such bioactive peptides and related functional molecules mediating the benefits of fermented milk products on human health.

Insight into Ultrasound-Induced Modifications of the Proteome and Flavor-Related Proteins of Unsmoked Bacon by Applying Label-Free Quantitation Technology

The aim of this study was to investigate the modifications of the proteome and flavor-related proteins in unsmoked bacon resulting from ultrasound treatment with the application of label-free quantitation technology together with bioinformatics analysis. Results showed that the expression levels of 137 proteins were markedly affected by ultrasound with most of them being significantly upregulated. The proteins distributed in the cytoplasm and the cytosol, the mitochondrion, and the nucleus were more susceptible to ultrasound treatment. Meanwhile, 20 flavor-related proteins, mostly myofibrillar proteins and metabolic enzymes mainly involved in the metabolic pathways of signaling and cellular processes and environmental information processing, were screened out. In addition, the differential expressions of flavor-related proteins induced by ultrasound were verified by western blotting. This study displayed insightful information from the proteomics perspective for a better understanding of the influential effect of ultrasound treatment on meat flavor.

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

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

A Deep Ensemble Predictor for Identifying Anti-Hypertensive Peptides Using Pretrained Protein Embedding

Hypertension (HT), or high blood pressure is one of the most common and main causes in cardiovascular diseases, which is also related to a series of detrimental diseases in humans. Deficiencies in effective treatment in HT are often associated with a series of diseases including multi-infarct dementia, amputation, and renal failure. Therefore, identifying anti-hypertension peptides has the vital realistic significance. Although many bioactive peptides have been developed to reduce blood pressure, they are time-consuming and laborious. In views of the obstacles of the intrinsic methods in antihypertensive peptide (AHTP) classification, computational methods are suggested as a supplement to identify AHTPs. In this study, we develop a comprehensive feature representation algorithm based on pretrained model and convolutional neural network and apply the deep ensemble model to construct the prediction model. The new predictor is used to identify AHTPs in benchmark and independent datasets. It has been shown in the independent test set that the performance is better than the recent methods. Comparative results indicate that our model can shed some light on hypertension therapy and gains more insights of classifying AHTPs. The implements and codes can be found in https://github.com/yuanying566/AHPred-DE.

Bioactive peptides of whey: obtaining, activity, mechanism of action, and further applications

Bioactive peptides derived from diverse food proteins have been part of diverse investigations. Whey is a rich source of proteins and components related to biological activity. It is known that proteins have effects that promote health benefits. Peptides derived from whey proteins are currently widely studied. These bioactive peptides are amino acid sequences that are encrypted within the first structure of proteins, which required hydrolysis for their release. The hydrolysis could be through in vitro or in vivo enzymatic digestion and using microorganisms in fermented systems. The biological activities associated with bio-peptides include immunomodulatory properties, antibacterial, antihypertensive, antioxidant and opioid, etc. These functions are related to general conditions of health or reduced risk of certain chronic illnesses. To determine the suitability of these peptides/ingredients for applications in food technology, clinical studies are required to evaluate their bioavailability, health claims, and safety of them. This review aimed to describe the biological importance of whey proteins according to the incidence in human health, their role as bioactive peptides source, describing methods, and obtaining technics. In addition, the paper exposes biochemical mechanisms during the activity exerted by biopeptides of whey, and their application trends.

Ensemble-AHTPpred: A Robust Ensemble Machine Learning Model Integrated With a New Composite Feature for Identifying Antihypertensive Peptides

Hypertension or elevated blood pressure is a serious medical condition that significantly increases the risks of cardiovascular disease, heart disease, diabetes, stroke, kidney disease, and other health problems, that affect people worldwide. Thus, hypertension is one of the major global causes of premature death. Regarding the prevention and treatment of hypertension with no or few side effects, antihypertensive peptides (AHTPs) obtained from natural sources might be useful as nutraceuticals. Therefore, the search for alternative/novel AHTPs in food or natural sources has received much attention, as AHTPs may be functional agents for human health. AHTPs have been observed in diverse organisms, although many of them remain underinvestigated. The identification of peptides with antihypertensive activity in the laboratory is time- and resource-consuming. Alternatively, computational methods based on robust machine learning can identify or screen potential AHTP candidates prior to experimental verification. In this paper, we propose Ensemble-AHTPpred, an ensemble machine learning algorithm composed of a random forest (RF), a support vector machine (SVM), and extreme gradient boosting (XGB), with the aim of integrating diverse heterogeneous algorithms to enhance the robustness of the final predictive model. The selected feature set includes various computed features, such as various physicochemical properties, amino acid compositions (AACs), transitions, n-grams, and secondary structure-related information; these features are able to learn more information in terms of analyzing or explaining the characteristics of the predicted peptide. In addition, the tool is integrated with a newly proposed composite feature (generated based on a logistic regression function) that combines various feature aspects to enable improved AHTP characterization. Our tool, Ensemble-AHTPpred, achieved an overall accuracy above 90% on independent test data. Additionally, the approach was applied to novel experimentally validated AHTPs, obtained from recent studies, which did not overlap with the training and test datasets, and the tool could precisely predict these AHTPs.

Exploration of bioactive peptides from various origin as promising nutraceutical treasures: In vitro, in silico and in vivo studies

The current health scenarios describe growing public health problems, such as diabetes, hypertension and cancer. Therefore, researchers focused on studying these health issues are interested in exploring bioactive compounds from different food sources. Among them, bioactive peptides have garnered huge scientific interest because of their multifunctional biological activities such as antioxidative, antimicrobial, antihypertensive, anticancer, antidiabetic, immunomodulatory effect. They can be used as food and pharmaceutical ingredients with a great potential against disease targets. This review covers methods of production in general for several peptides obtained from various food sources including seed, milk and meat, and described their biological activities. Particular focus was given to bioinformatic tools to advance quantification, detection and characterize each peptide sequence obtained from different protein sources with predicted biological activity. Besides, various in vivo studies have been discussed to provide a better understanding of their physiological functions, which altogether could provide valuable information for their commercialization in future foods.

Investigating the Short Peptidome Profile of Italian Dry-Cured Ham at Different Processing Times by High-Resolution Mass Spectrometry and Chemometrics

Short peptides have been spiking interest owing to their significant contribution to the taste and functional properties of dry-cured ham. In this study, a suspect screening approach based on high-resolution mass spectrometry was employed for the comprehensive characterization of the short endogenous peptidome in dry-cured ham samples at different processing stages (14, 22, and 34 months). After careful manual spectra interpretation, a chemometric approach based on principal component analysis was employed for highlighting the differences between the three sets of samples. A total of 236 short peptide sequences was tentatively identified, including 173 natural short peptides and 63 sequences containing non-proteinogenic amino acids, the highest number ever reported for endogenous sequences in dry-cured ham. Samples in the latest processing stages presented a generally higher abundance of dipeptides, indicating residual proteolytic activity. Moreover, the several annotated modified short peptides, mainly pyroglutamination and lactoyl conjugation, allowed hypothesizing several reactions occurring over time. For the first time, several lactoyl-dipeptides were tentatively identified in dry-cured ham samples with maximum concentration in the late processing stage samples. The presented results significantly contribute to the understanding of the reaction involving short peptides that affect the sensory and functional properties of dry-cured ham.

Identification and Quantitation of Bioactive and Taste-Related Dipeptides in Low-Salt Dry-Cured Ham

The reduction of salt in meat products influences the natural mechanisms of proteolysis occurring in their processing, and could affect the final characteristics of the product in terms of texture and flavor due to its effect on the activity of enzymes. In the present study, the quantitation of dipeptides PA, GA, VG, EE, ES, DA, and DG in low-salt Spanish dry-cured ham was carried out using a triple quadrupole mass spectrometry instrument. The developed methodology demonstrated the advantages of hydrophilic interaction liquid chromatography in the removal of salt as a clean-up/separation step before ionization. This resulted in a value of 44.88 μg/g dry-cured ham for GA dipeptide, and values ranging from 2 to 8 μg/g dry-cured ham for VG, EE, ES, DA, and DG dipeptides. PA showed the lowest concentration with a value of 0.18 μg/g dry-cured ham. These outcomes prove the remarkable activity of muscular dipeptidyl peptidases during dry-curing as well as confirming the presence of these dipeptides which are related to certain taste attributes (e.g., ‘bitter’ or ‘umami’). Such dipeptides have also been confirmed as anti-inflammatory and potential cardiovascular protectors using in vitro assays, with the advantage of dipeptides small size increases their chance to resist both gastrointestinal digestion and intestinal/bloodstream transport without being degraded or modified.

A Novel Insight into Screening for Antioxidant Peptides from Hazelnut Protein: Based on the Properties of Amino Acid Residues

This study used the properties of amino acid residues to screen antioxidant peptides from hazelnut protein. It was confirmed that the type and position of amino acid residues, grand average of hydropathy, and molecular weight of a peptide could be comprehensively applied to obtain desirable antioxidants after analyzing the information of synthesized dipeptides and BIOPEP database. As a result, six peptides, FSEY, QIESW, SEGFEW, IDLGTTY, GEGFFEM, and NLNQCQRYM were identified from hazelnut protein hydrolysates with higher antioxidant capacity than reduced Glutathione (GSH) against linoleic acid oxidation. The peptides having Tyr residue at C-terminal were found to prohibit the oxidation of linoleic acid better than others. Among them, peptide FSEY inhibited the rancidity of hazelnut oil very well in an oil-in-water emulsion. Additionally, quantum chemical parameters proved Tyr-residue to act as the active site of FSEY are responsible for its antioxidation. This is the first presentation of a novel approach to excavating desired antioxidant peptides against lipid oxidation from hazelnut protein via the properties of amino acid residues.

The Effect of L-Glutamine on Basal Albumen and Yolk Indices, and Albumen Amino Acids Composition

Simple Summary

At present, with increased consumers’ focus on eating healthy, it is expected that egg protein content and amino acids profile are among the components of eggs that play critical roles in egg selection. Thus, this research investigated the effect dietary L-glutamine supplementation has on basal albumen and yolk indices as well as albumen protein amino acid profile. The study shows a potential role of L-glutamine supplementation for enhancing nutritional values of eggs by the decrease of albumen lipid content and the change of amino acid profile.

Abstract

The current study tested the hypothesis that 1.0% dietary inclusion of L-glutamine (Gln), an non-essential amino acid that influences protein synthesis, can improve internal egg quality, including amino acids profile. Thirty-week-old Bovans Brown laying hens in their middle laying period were assigned to one of the two experimental groups (12 replicate cages, 2 hens/cage) with Gln in the form of alpha-ketoglutarate (10 g/kg) or without Gln inclusion. The experimental period lasted for 30 wks, from the 31st to the 60th week of age of hens, when eggs were collected and selected egg quality indices were determined. Gln supplementation had no effect on albumen and egg yolk share, albumen and yolk basal indices and composition, including yolk cholesterol content. However, Gln decreased the lipid content of the egg albumen (p < 0.001), and influenced albumen amino acid profile, increasing content of asparagine (p < 0.05), phenylalanine (p < 0.05), proline (p < 0.001), tryptophan (p < 0.01), and tyrosine (p < 0.05). In conclusion, the study shows a potential role of Gln supplementation for enhancing nutritional values of eggs by lower lipid content and higher amino acid profile.

Analyses of the response of carbapenem-resistant Pseudomonas aeruginosa against monotherapy and combined therapy using quantum dots and proteomics

Carbapenem-resistant P. aeruginosa (CRPA) has become a serious public health problem and the biofilm formation aggravates this problem. The study aimed to evaluate the occurrence of β-lactamases and quorum sensing (QS) genes in CRPA isolates, analyze production of biofilm, evaluate the response against meropenem (MPM) and∕or polymyxin B (POL B) and its association with azythromicin (AZT) using quantum dots (QDs) and proteomic analysis. Six CRPA isolates were analyzed. β-lactamases and QS genes were search using specific PCRs and were tested for biofilm production by quantitative technique. A CRPA isolate, containing blaKPC gene and biofilm-producing, was selected to assess its response to therapy using QDs and the MALDI-TOF. The β-lactamase detected was blaKPC in 66.7% of the isolates. All isolates were biofilm producers and carriers of the QS genes. QDs-MPM conjugates triggered the formation of biofilm and the association with AZT inhibited this effect. Proteomics analysis showed that treatments with MPM or POL B suppressed the expression of the transglycosylase protein, while combined therapy with AZT induced expression of the RpoN protein. Thus, this study shows that the use of fluorescence combined with the proteomics analysis was promising to understand how a CRPA strain reacts to antimicrobial treatment.