## 4 Discussion
[PERSON] and [PERSON] [22] defined the likely reasons that may affect the unsuccessful identification of peptides in a hydrolysate sample. They included no detectable amount of peptide in the sample (e.g., if some peptide bonds likely to be cleaved are actually resistant to hydrolysis) and no detectable fragmentation in an ion trap mass spectrometer. Additionally, peptides identified in SPC hydrolysates are defined as proteotypic peptides, and their identification is dependent on the mass spectrometer used. Finally, there is no method that would serve for the identification of all possible peptides in a protein hydrolysate [22]. The last reason for the discrepancy might be the fact that in silico predictions assume that all peptide bonds are hydrolyzed in a protein chain. Ficin was the most effective enzyme for producing peptides in vitro, whereas bromelain in the theoretical production of parent peptides likely to be bitter. Enzyme rankings were as follows: bromelain > papain > ficin > proteinase K (in silico results) and ficin > bromelin > papain (in vitro results). There was no correlation between the results of RP-HPLC (C parameter from Table 2) and the number of identified peptides with bitterness indicators. Despite the differences between these rankings, the richest source of parent peptides produced by the applied enzymes turned out to be conglycinins. No parent peptides that were identified in all SPH matched the sequences known as bitter themselves. Moreover, none of these peptides were found as bioactive themselves (see Table 4). [PERSON] et al. [9] identified some parent peptides likely to be bitter in milk protein hydrolysates. For example, the PFPIIV peptide matched the bitter-tasting sequence in the BIOPEP-UWM sensory peptide database (peptide ID in the database: 195). PFPIIV was known as bitter itself, contained PFP, PF, IV, **FP, II** bitter motifs, and was identified in bromelain, ficin, and papain hydrolysates of milk protein concentrate. Moreover, two milk protein-derived peptides: TTMPLW (source: papain hydrolysate) and VLPVPQK (source: bromelain hydrolysate), served additional biofunctions. Based on information found in the BIOPEP-UWM bioactive peptide database, the first sequence exhibited opioid, immunomodulating, and ACE inhibitory effects (peptide IDs in the database: 3127, 8172, and 3520, respectively). The second one was reported as an antioxidative agent (peptide ID: 7877) [9]. As was said above, bitterness associated with bioactive peptides may be found as an unwanted property when thinking about the production of food that is health-beneficial and sensorially-attractive [57]. Hence, our concept relying on the fragmentomic idea of research was useful to: (1) find out if the parent peptides were bitter/bioactive themselves or (2) motifs like, e.g., peptidic bitterness indicators that are encrypted in a sequence exhibiting other activities, may \"suggest\" the bioactivity/taste of the parent sequence. This concept shows also the potential of enzymes to produce motifs supposed to be bioactive/bitter. The enzymes' potential to produce unwanted peptides may initially be also an indicative criterion of their \"negative\" selection (i.e., rejection) when considering the production of non- or less bitter hydrolysates. However, according to [PERSON] et al. [39], it needs to be noted that although the theoretical predictions concerning the potential of proteins as sources of peptides and enzymes involved in their production can support further research, such predictions are never 100% consistent with experimental results. This is also true concerning our concept. The discrepancies between in silico and in vitro results may be associated with the specificity of bioinformatic and experimental analyses. Bioinformatic issues are related to the tools used for predictions, especially databases of biological information. Many data on biological peptides are published every year.