Virtual screening and characteristics of novel umami peptides from porcine type I collagen

This study aimed to rapidly and precisely discover novel umami peptides from porcine type I collagen using virtual screening, sensory evaluation and molecular docking simulation. Porcine type I collagen was hydrolyzed in silico and six umami peptide candidates (CN, SM, CRD, GESMTDGF, MS, DGC) were shortlisted via umami taste, bioactivity, toxicity, allergenicity, solubility and stability predictions. The sensory evaluation confirmed that these peptides exhibited umami taste, with CRD, GESMTDGF and DGC displaying higher umami intensity and significant umami-enhancing effects in 0.35% sodium glutamate solution. Molecular docking predicted that Ser 276/384/385 of T1R1 and Asn68, Val277, Thr305, Ser306, Leu385 of T1R3 may also play critical roles in binding umami peptides. The umami taste of peptides may be perceived mainly through the formation of hydrogen bonds with the hydrophilic amino acids of T1R1/T1R3. This work provided a robust procedure and guidance to develop novel umami peptides from food byproducts.

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.

In Silico Strategies to Predict Anti-aging Features of Whey Peptides

We have analysed the in silico potential of bioactive peptides from cheese whey, the most relevant by-product from the dairy industry, to bind into the active site of collagenase and elastase. The peptides generated from the hydrolysis of bovine β-lactoglobulin with three proteases (trypsin, chymotrypsin, and subtilisin) were docked onto collagenase and elastase by molecular docking. The interaction models were ranked according to their free binding energy using molecular dynamics simulations, which showed that most complexes presented favourable interactions. Interactions with elastase had significantly lower binding energies than those with collagenase. Regarding the interaction site, it was found that four bioactive peptides were positioned in collagenase's active site, while six were found in elastase's active site. Among these, the most we have found one promising collagen-binding peptide produced by chymotrypsin and two for elastase, produced by subtilisin and chymotrypsin. These in silico results can be used as a tool for designing further experiments aiming at testing the in vitro potential of the peptides found in this work.

The identification and characterisation of novel bioactive peptides derived from porcine liver

Bioactive peptides (BAPs) can be derived from a variety of sources; these could be from dietary proteins which are then broken down in the gastrointestinal tract to release BAPs, or they can be isolated from various sources ex vivo. Sources include plant-based proteins such as soy, and chickpeas, and animal proteins from waste from the meat industry and from fish skin. Bioinformatics is also a useful approach to assess the peptides released from digests due to the great number of possible sequences that can be isolated from proteins. Therefore, an in silico analysis of peptides could potentially lead to a more rapid discovery of BAPs. This article investigates a "crude" liver peptide mixture derived from papain hydrolysis of porcine liver and purified peptides derived from the hydrolysates following HPLC fractionation and in silico digestion of the host proteins identified using LC-MS/MS. This allowed the identification of two proteins (cytosol aminopeptidase and haemoglobin subunit alpha) present in the "crude" mixture after LC-MS/MS. In silico hydrolysis of these proteins identified that several peptides were predicted to be both present in the crude mixture using the BIOPEP database and to have potential bioactivity using the Peptide Ranker tool. Peptides (FWG, MFLG and SDPPLVFVG) with the greatest potential bioactivity and which had not previously been reported in the literature were then synthesised. The results indicated that the predicted bioactivity of the synthetic peptides would likely include antioxidant activity. FWG and MFLG derived from the in silico papain hydrolysis of cytosol aminopeptidase showed activity better or comparable to Trolox in the Oxygen Radical Absorbance Capacity (ORAC) assay. The use of these in silico tools, alongside a robust range of biochemical assays which cover a wider range of bioactivities would be a way of improving the discovery of novel bioactive peptides.