Molecular-level understanding of the hTAS2R1 receptor-bitter tasting tetra-peptide binding: a structural biology study based on computational approaches

Effective computational approaches for bitter-tasting peptides have been developed and analyzed in the present work.

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

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.

Quantitative Structure-Activity Relationship Study of Bitter Di-, Tri- and Tetrapeptides Using Integrated Descriptors

New quantitative structure–activity relationship (QSAR) models for bitter peptides were built with integrated amino acid descriptors. Datasets contained 48 dipeptides, 52 tripeptides and 23 tetrapeptides with their reported bitter taste thresholds. Independent variables consisted of 14 amino acid descriptor sets. A bootstrapping soft shrinkage approach was utilized for variable selection. The importance of a variable was evaluated by both variable selecting frequency and standardized regression coefficient. Results indicated model qualities for di-, tri- and tetrapeptides with R² and Q² at 0.950 ± 0.002, 0.941 ± 0.001; 0.770 ± 0.006, 0.742 ± 0.004; and 0.972 ± 0.002, 0.956 ± 0.002, respectively. The hydrophobic C-terminal amino acid was the key determinant for bitterness in dipeptides, followed by the contribution of bulky hydrophobic N-terminal amino acids. For tripeptides, hydrophobicity of C-terminal amino acids and the electronic properties of the amino acids at the second position were important. For tetrapeptides, bulky hydrophobic amino acids at N-terminus, hydrophobicity and partial specific volume of amino acids at the second position, and the electronic properties of amino acids of the remaining two positions were critical. In summary, this study not only constructs reliable models for predicting the bitterness in different groups of peptides, but also facilitates better understanding of their structure-bitterness relationships and provides insights for their future studies.

Food protein-originating peptides as tastants - Physiological, technological, sensory, and bioinformatic approaches

Taste is one of the factors based on which the organism makes the selection of what to ingest. It also protects humans from ingesting toxic compounds and is one of the main attributes when thinking about food quality. Five basic taste sensations are recognized by humans: bitter, salty, sour, sweet, and umami. The taste of foods is affected by some molecules of some specific chemical nature. One of them are peptides derived from food proteins. Although they are not the major natural compounds originating from food sources that are responsible for the taste, they are in the area of scientific research due to the specific composition of amino acids which are well-known for their sensory properties. Literature data implicate that sweet, bitter, and umami are the tastes attributable to peptides. Moreover, the bitter peptide tastants are the dominant among the other tastes. Additionally, other biological activities like, e.g., inhibiting enzymes that regulate the body functions and acting as preventive food agents of civilization diseases, are also associated with the taste of peptides. The advance in information technologies has contributed to the elaboration of internet archives (databases) as well as in silico tools for the analysis of biological compounds. It also concerns peptides - namely taste carriers originating from foods. Thus, our paper provides a summary of knowledge about peptides as tastants with special attention paid to the following aspects: a) basis of taste perception, b) taste peptides detected in food protein sequences with special emphasis put on the role of bitter peptides, c) peptides that may enhance/suppress the taste of foods, d) databases as well as bioinformatic approaches suitable to study the taste of peptides, e) taste-taste interactions, f) basis of sensory analysis in the evaluation of the taste of molecules, including peptides, and g) the methodology applied to reduce/eliminate the undesired taste of peptides. The list of taste peptides serving some biological functions is presented in the Supplement file. The information provided includes database resources, whereas peptide sequences are given with InChiKeys, which is aimed at facilitating the Google® search. Our collection of data regarding taste peptides may be supportive for the scientists working with the set of peptide data in the context of structure-function activity of peptides.

BIOPEP database of sensory peptides and amino acids

Peptides and amino acids belong to compounds that influence the taste of foods. The aim of this study was to develop a database of sensory peptides and amino acids. Information about the taste of the analyzed compounds was obtained from sensory studies described in the literature. The database of sensory peptides and amino acids has identical structure to the BIOPEP database of biologically active peptides. The information about sensory peptides and amino acids was inserted into the database using standard BIOPEP layouts for bioactive peptides. Information about the biological activity of sensory peptides was obtained from BIOPEP and other databases. The information annotated in the BIOPEP database of sensory peptides and amino acids includes: sequence written in a one-letter code, information about taste, reference, structure written with the use of chemical codes (SMILES, InChI and InChIKey), bioactivity data (mainly inhibition of proteolytic enzymes), if applicable, and ID numbers from other biological and chemical databases. The database contains tools for determining the location of peptides in protein sequences (profiles of potential sensory activity), comparing protein sequences as precursors of sensory peptides based on the frequency of sensory fragments as a quantitative descriptor, simulating proteolysis and calculating novel parameters for quantitative description of simulated proteolysis. The BIOPEP database of sensory peptides and amino acids is available at http://www.uwm.edu.pl/biochemia/index.php/pl/biopep. It is an open access resource that does not require user registration.

Quantitative structure-activity relationship study of bitter peptides

A database consisting of 224 di- to tetradecapeptides and five amino acids was compiled to study quantitative structure-activity relationships of bitter peptides. Partial least-squares regression-1 analysis was conducted using the amino acid three z-scores and/or three parameters (total hydrophobicity, residue number, and log mass values) as X-variables and bitterness values (log 1/T where T is the bitterness threshold) as Y-variables. Using the three parameters only, significant models (p < 0.001) were obtained describing the entire data set as well as data subsets, except that comprised only of octa- to tetradecapeptides. For data sets comprising different peptide lengths, the models were improved by including the three z-scores at the N-terminal and C-terminal positions. Correlation coefficients for bitterness prediction of 48 dipeptides and 12 pentapeptides were 0.75 (RMSEP = 0.53) and 0.90 (RMSEP = 0.48), respectively. Bulky hydrophobic amino acids at the C terminus and bulky basic amino acids at the N terminus were highly correlated to bitterness.

Debittering of protein hydrolyzates

Enzymatic hydrolysis of proteins frequently results in bitter taste, which is due to the formation of low molecular weight peptides composed of mainly hydrophobic amino acids. Methods for debittering of protein hydrolyzates include selective separation such as treatment with activated carbon, extraction with alcohol, isoelectric precipitation, chromatography on silica gel, hydrophobic interaction chromatography, and masking of bitter taste. Bio-based methods include further hydrolysis of bitter peptides with enzymes such as aminopeptidase, alkaline/neutral protease and carboxypeptidase, condensation reactions of bitter peptides using protease, and use of Lactobacillus as a debittering starter adjunct. The causes for the production of bitter peptides in various food protein hydrolyzates and the development of methods for the prevention, reduction, and elimination of bitterness as well as masking of bitter taste in enzymatic protein hydrolyzates are presented.

Bitter taste of enzymic hydrolysates of casein. I. Isolation, structural and sensorial analysis of peptides from tryptic hydrolysates of beta-casein

beta-Casein A2 was isolated from milk of a homozygous cow and hydrolysed with trypsin. The hydrolysate was separated by RP-HPLC into 18 peptides, all but one of which could be attributed to the sequence of beta-casein on the basis of the amino acid composition. Some peptides overlapped. In total, they represented about 97% of the protein sequence. Only three peptides had a bitter taste, namely I49-N68 (recognition threshold 1.0 mg/ml, 0.45 mmol/l), I49-K97 (1.5 mg/ml, 0.28 mmol/l) and G203-V209 (0.175 mg/ml, 0.23 mmol/l). The contribution of the three peptides to the overall bitterness of the beta-casein hydrolysate (2.67 mg/ml) was about 11, 21, and 60%, respectively. Peptide I49-K97 was present in the hydrolysate together with its fragments I49-N68 and S69-K97. Remarkably, the smaller and more hydrophobic fragment I49-N68 was less bitter than I49-K97 on a molar basis, whereas the larger and more hydrophilic fragment S69-K97 had a neutral taste. These results show that in the case of larger peptides neither hydrophobicity nor size are responsible alone for bitter potency, but that conformational parameters must be of great importance. Furthermore, it can be concluded that only a part of the structure is responsible for the contact with the receptor. The bitterness of G203-V209 is discussed in connection with related synthetic peptides in the literature.