## 4 Discussion  
The study above was divided into two steps: bioinformatic and experimental analyses. According to [PERSON] et al. (2017), bioinformatic analyses help in better understanding biological data and hence their application in food and nutrition increases. Moreover, the fact of the presence of some unique fragments within the primary structures of peptides underlies their different biofunctions. Bioinformatic studies enable minimizing the number of experiments involved to determine the impact of the structure of a peptide on its biological function ([PERSON] and [PERSON], 2017). Moreover, in silico experiments are relatively easy and less costly to carry out, and they do not require reagent and sample preparation ([PERSON] and [PERSON], 2017). Combining the bioinformatics with an experimental verification of the results is, in turn, a kind of methodology called an integrated (i.e., hybrid) approach. This term was introduced by [PERSON] ([PERSON] and [PERSON], 2017), and ever since, many studies on bioactive peptides, including the present one, have implemented procedures to solve a problem using databases of biological information and then involving laboratory analyses ([PERSON] et al., 2018). To the best of our knowledge, the hybrid and fragmentomic approaches have not been applied so far to analyze the potential of soybean proteins as the reservoir of bitter-tasting motifs. Moreover, our protocol of research was partially based on positive selection ([PERSON] and [PERSON], 2017), i.e., finding in the protein the sequential motifs with already known biological function (i.e., provided in a database). [PERSON] et al. (2018) employed this strategy to evaluate the potential of patatin (_Solanum tuberosum_; potato protein) as a source of biopeptides. The biological dataset (peptide sequences) was acquired from the BIOPEP-UWM database. The novel aspect of our research was the use of the positive selection to define bitter-tasting \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parent Peptide** & **Motif 1** & **Bioactivities** \\ \hline LSVISPK & **PK; VI**, SV, SP & DPP IV inhibitor \\ \hline DVLVIPLG & **VL; VI**, LV; IP; PLG & DPP IV inhibitor \\  & **LG; PL; IP; PLG & ACE inhibitor \\  & PLG & Opioid \\  & **VL; LV** & Stimulating glucose uptake \\ \hline LIVILNG & **VI**; LI; IL; LN; NG & DPP IV inhibitor \\  & IL; LN; NG & ACE inhibitor \\  & IV; IL; LI & Stimulating glucose uptake \\ \hline NPFLFG & **FL**; PF; NP & DPP IV inhibitor \\  & **FL**; PF & DPP III inhibitor \\  & **FG; LF** & ACE inhibitor \\ \hline ISSTIV & \begin{tabular}{c} IV \\ ST \\ TI \\ \end{tabular} & \begin{tabular}{c} Stimulating glucose uptake \\ ACE inhibitor \\ DPP IV inhibitor \\ \end{tabular} \\ \hline PQMIIV & \begin{tabular}{c} II; MI; PQ \\ IV; II \\ PQ \\ \end{tabular} & \begin{tabular}{c} DPP IV inhibitor \\ Stimulating glucose uptake \\ ACE inhibitor \\ \end{tabular} \\ \hline PFPSIL & \
\begin{tabular}{c} FP; PF; IL \\ FP; PF; IL; PS; SI \\ IL \\ \end{tabular} &
\begin{tabular}{c} ACE inhibitor \\ DPP IV inhibitor \\ Stimulating glucose uptake \\ DPP III inhibitor \\ \end{tabular} \\ \hline DDFFL & **FL** & DPP IV inhibitor; DPP III inhibitor \\  & FFL; DF & ACE inhibitor \\ \hline
**FFEITPEK** & \
\begin{tabular}{c} **EI**; TP; EK \\ PE \\ \end{tabular} &
\begin{tabular}{c} DPP IV inhibitor; ACE inhibitor \\ DPP III inhibitor \\ \end{tabular} \\ \hline \hline \end{tabular}  
* Bitter-tasting indicators are given in bold, and peptides with no indicator status are given in normal font. Abbreviations: ACE, Angiotensin-converting enzyme (EC 3.4.15.1); DPP III, dipeptidyl peptidase III (EC 3.4.14.4); DPP IV, dipeptidyl peptidase IV (EC 3.4.14.5).  
\end{table} 
Table 4: Additional bioactivity of bitter motifs found in parent peptides identified in SPC (soybean protein concentrate) hydrolysate samples. motifs (especially peptide indicators) in parent sequences potentially released from soybean. According to [PERSON] et al.