The relevance of dipeptides and tripeptides in the bioactivity and taste of dry-cured ham

Gallego, Marta; Mora, Leticia; Toldrá, Fidel

doi:10.1186/s43014-019-0002-7

Cited by 38 publications

(41 citation statements)

References 86 publications

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“…This strategy of research based on searching for biopeptides with known sequences in the protein that so far had not been known as their source is called a positive selection. Such an idea to study biopeptides from foods was applied by several authors [45,46,[49][50][51]. Thus, the next step in our study was to acquire the information about the peptides theoretically found in peptic and/or tryptic hydrolysates of collagens.…”

Section: Source Of Collagenmentioning

confidence: 99%

Characteristics of Biopeptides Released In Silico from Collagens Using Quantitative Parameters

Iwaniak

Minkiewicz

Pliszka

et al. 2020

Foods

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The potential of collagens to release biopeptides was evaluated using the BIOPEP-UWM-implemented quantitative criteria including the frequency of the release of fragments with a given activity by selected enzyme(s) (AE), relative frequency of release of fragments with a given activity by selected enzyme(s) (W), and the theoretical degree of hydrolysis (DHt). Cow, pig, sheep, chicken, duck, horse, salmon, rainbow trout, goat, rabbit, and turkey collagens were theoretically hydrolyzed using: stem bromelain, ficin, papain, pepsin, trypsin, chymotrypsin, pepsin+trypsin, and pepsin+trypsin+chymotrypsin. Peptides released from the collagens having comparable AE and W were estimated for their likelihood to be bioactive using PeptideRanker Score. The collagens tested were the best sources of angiotensin I-converting enzyme (ACE) and dipeptidyl peptidase IV (DPP-IV) inhibitors. AE and W values revealed that pepsin and/or trypsin were effective producers of such peptides from the majority of the collagens examined. Then, the SwissTargetPrediction program was used to estimate the possible interactions of such peptides with enzymes and proteins, whereas ADMETlab was applied to evaluate their safety and drug-likeness properties. Target prediction revealed that the collagen-derived peptides might interact with several human proteins, especially proteinases, but with relatively low probability. In turn, their bioactivity may be limited by their short half-life in the body.

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Section: Source Of Collagenmentioning

confidence: 99%

Characteristics of Biopeptides Released In Silico from Collagens Using Quantitative Parameters

Iwaniak

Minkiewicz

Pliszka

et al. 2020

Foods

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“…These new methods involve also bioinformatic analyses. According to Gallego et al [2019], the bioinformatic-assisted approach affords the opportunity to predict the production of bitter peptides from food sources in a cheaper and faster way. Our idea of employing predictive (i.e.…”

Section: Resultsmentioning

confidence: 99%

“…Thus, in silico studies combined with empirical methodologies enable the complete search for tasting-peptides derived from foods. However, all theoretical predictions of food taste must be confi rmed [Gallego et al, 2019].…”

Section: Resultsmentioning

confidence: 99%

Hybrid Approach in the Analysis of Bovine Milk Protein Hydrolysates as a Source of Peptides Containing Di- and Tripeptide Bitterness Indicators

Iwaniak¹,

Minkiewicz²,

Hrynkiewicz³

et al. 2020

Pol. J. Food Nutr. Sci.

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BSA, bovine serum albumin; B, bromelain; B-MPC, bromelain hydrolysate of milk protein concentrate; F, fi cin; F-MPC, fi cin hydrolysate of milk protein concentrate; MLR, multivariate linear regression; MPC, milk protein concentrate; O-MPC, non-hydrolyzed milk protein concentrate; P, papain; P-MPC, papain hydrolysate of milk protein concentrate; PK, proteinase K; PK-MPC, proteinase K hydrolysate of milk protein concentrate; RP-HPLC, reversed-phase high performance liquid chromatography; RP-HPLC-MS/MS, reversed-phase high performance liquid chromatography and mass spectrometry; Rcaf., the ratio of caffeine (the threshold concentration for 1 mM caffeine solution as a standard (Rcaf. = 1.0); t R predicted , theoretical retention time; t R experimental , experimental retention time; α s1 , casein; α s2-CN, α s2-casein; α-La, α-lactalbumin; β-Lg, βlactoglobulin; β-CN, βcasein; κ-CN, κ-casein; and TFA, trifl uoracetic acid.

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“…This helps understanding some relationships between the structure of a molecule and its activity (e.g., bitter taste). It needs to be noted that although it is possible to prognose the potential of released peptides to taste bitter, such a statement should be confirmed in laboratory conditions [70].…”

Section: Discussionmentioning

confidence: 99%

Soybean (Glycine max) Protein Hydrolysates as Sources of Peptide Bitter-Tasting Indicators: An Analysis Based on Hybrid and Fragmentomic Approaches

et al. 2020

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The aim of this study was to analyze soybean proteins as sources of peptides likely to be bitter using fragmentomic and hybrid approaches involving in silico and in vitro studies. The bitterness of peptides (called parent peptides) was theoretically estimated based on the presence of bitter-tasting motifs, particularly those defined as bitter-tasting indicators. They were selected based on previously published multilinear stepwise regression results. Bioinformatic-assisted analyses covered the hydrolysis of five major soybean-originating protein sequences using bromelain, ficin, papain, and proteinase K. Verification of the results in experimental conditions included soy protein concentrate (SPC) hydrolysis, RP-HPLC (for monitoring the proteolysis), and identification of peptides using RP-HPLC-MS/MS. Discrepancies between in silico and in vitro results were observed when identifying parent peptide SPC hydrolysate samples. However, both analyses revealed that conglycinins were the most abundant sources of parent peptides likely to taste bitter. The compatibility percentage of the in silico and in vitro results was 3%. Nine parent peptides with the following sequences were identified in SPC hydrolysates: LSVISPK, DVLVIPLG, LIVILNG, NPFLFG, ISSTIV, PQMIIV, PFPSIL, DDFFL, and FFEITPEK (indicators are in bold). The fragmentomic idea of research might provide a supportive method for predicting the bitterness of hydrolysates. However, this statement needs to be confirmed experimentally.

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The relevance of dipeptides and tripeptides in the bioactivity and taste of dry-cured ham

Cited by 38 publications

References 86 publications

Characteristics of Biopeptides Released In Silico from Collagens Using Quantitative Parameters

Characteristics of Biopeptides Released In Silico from Collagens Using Quantitative Parameters

Hybrid Approach in the Analysis of Bovine Milk Protein Hydrolysates as a Source of Peptides Containing Di- and Tripeptide Bitterness Indicators

Soybean (Glycine max) Protein Hydrolysates as Sources of Peptide Bitter-Tasting Indicators: An Analysis Based on Hybrid and Fragmentomic Approaches

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