Introduction of New Computer Softwares for Classification and Prediction Purposes of Bioactive Peptides: Case Study in Antioxidative Tripeptides

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.

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.

Structure activity relationship modelling of milk protein-derived peptides with dipeptidyl peptidase IV (DPP-IV) inhibitory activity

Quantitative structure activity type models were developed in an attempt to predict the key features of peptide sequences having dipeptidyl peptidase IV (DPP-IV) inhibitory activity. The models were then employed to help predict the potential of peptides, which are currently reported in the literature to be present in the intestinal tract of humans following milk/dairy product ingestion, to act as inhibitors of DPP-IV. Two models (z- and v-scale) for short (2-5 amino acid residues) bovine milk peptides, behaving as competitive inhibitors of DPP-IV, were developed. The z- and the v-scale models (p<0.05, R(2) of 0.829 and 0.815, respectively) were then applied to 56 milk protein-derived peptides previously reported in the literature to be found in the intestinal tract of humans which possessed a structural feature of DPP-IV inhibitory peptides (P at the N2 position). Ten of these peptides were synthetized and tested for their in vitro DPP-IV inhibitory properties. There was no agreement between the predicted and experimentally determined DPP-IV half maximal inhibitory concentrations (IC50) for the competitive peptide inhibitors. However, the ranking for DPP-IV inhibitory potency of the competitive peptide inhibitors was conserved. Furthermore, potent in vitro DPP-IV inhibitory activity was observed with two peptides, LPVPQ (IC50=43.8±8.8μM) and IPM (IC50=69.5±8.7μM). Peptides present within the gastrointestinal tract of human may have promise for the development of natural DPP-IV inhibitors for the management of serum glucose.

Common Amino Acid Subsequences in a Universal Proteome--Relevance for Food Science

A common subsequence is a fragment of the amino acid chain that occurs in more than one protein. Common subsequences may be an object of interest for food scientists as biologically active peptides, epitopes, and/or protein markers that are used in comparative proteomics. An individual bioactive fragment, in particular the shortest fragment containing two or three amino acid residues, may occur in many protein sequences. An individual linear epitope may also be present in multiple sequences of precursor proteins. Although recent recommendations for prediction of allergenicity and cross-reactivity include not only sequence identity, but also similarities in secondary and tertiary structures surrounding the common fragment, local sequence identity may be used to screen protein sequence databases for potential allergens in silico. The main weakness of the screening process is that it overlooks allergens and cross-reactivity cases without identical fragments corresponding to linear epitopes. A single peptide may also serve as a marker of a group of allergens that belong to the same family and, possibly, reveal cross-reactivity. This review article discusses the benefits for food scientists that follow from the common subsequences concept.

Partial characterization of ultrafiltrated soy protein hydrolysates with antioxidant and free radical scavenging activities

Soy protein isolate (SPI) was hydrolyzed with Flavourzyme® (SHF) or chymotrypsin (SHC). Hydrolysates were sequencially fractionated by ultrafiltration using different membrane pore sizes (50, 10, and 3 kDa). The antioxidant ability of each hydrolysate protein fraction was tested in a liposome oxidizing system and their free radical scavenging activity (FRSA) was evaluated with the DPPH method (diphenylpicrilhydrazine radical). Molecular weight (MW) distribution, solubility, surface hydrophobicity, and amino acid composition of each SPI hydrolysate fraction were measured and their effect on antioxidant and scavenging activities was established by multivariate correlation. The most active ultrafiltrated peptide fractions (P < 0.05), from SHF and SHC, had of MW of <3 kDa (F3 and C3, respectively). These fractions decreased liposome oxidation by 83.2% and 84.5%, respectively, and also showed the highest FRSA (F3: 21.3% and C3: 24.4%). In addition to molecular size, the antioxidant activity and FRSA of soy protein fractions were related to their amino acid composition, especially to an increased content of Phe and a lowered content of Lys. Also, hydrophobicity of ultrafiltrated peptide fractions was an important characteristic (P < 0.001) associated with their ability to trap free radicals. Ultrafiltered peptide fractions with low MW have a high potential to be used as natural alternatives to prevent lipid oxidation in foods.