## 3 Results and Discussion
Peptides with molecular weight exceeding 500 Da may thus be considered objects of interest as bioactive compounds together with the smaller ones. Comparison of Figures 4 and 7 shows that the prediction of log IC\({}_{50}\) based on a wider variety of descriptors provides better correlation between predicted and observed values than the calculation taking into account predictors associated with molecular weight only. Log IC\({}_{50}\) (ERM) reveals a better correlation with experimental results than log IC\({}_{50}\) (MW). When discussing the results, it is worth mentioning that the SCIGRESS program was applied for the first time to study the SAR of DPP IV-inhibitory peptides. Its advantage is the possibility of refining the models by removing the descriptors which are difficult to interpret in order to produce reliable statistics (see Section 2). Nevertheless, the outputs obtained using SCIGRESS and the implemented descriptors are comparable with the results of [PERSON] et al. [44], who confirmed that some characteristic residues occurred in different locations of peptide DPP IV inhibitors. Dipeptide DPP IV inhibitors were often rich in Trp, which was also confirmed in this study. Additionally, amino acids--like Ala, Leu,  
Figure 7: Plot of the observed and predicted logIC\({}_{50}\) (MW) values for tripeptide DPP IV-inhibitory activity. The numbers in the plot refer to the peptide sequence provided in Table 4. CI—confidence interval. and/or His--were typical for dipeptides capable of DPP IV inhibition [44]. This regularity was also found in the present study, in which the presence of the above-mentioned amino acids in a dipeptide sequence was defined by descriptors related to the number of methyl groups and the number of nitrogens (the higher this number is, the better the impact on bioactivity). The analyses of tripeptide SAR were focused on the impact of their molecular weight on DPP IV inhibition. [PERSON] et al. [44] demonstrated more the diversified composition of tripeptides acting as DPP IV inhibitors, but some specific residues were indicated as well, including, Gly, Ala, Leu, Ile, Gln, Met, Phe, and Pro, which were found in different locations of the sequence. The results achieved using SCIGRESS software showed a more specific focus on the presence of Trp in the tripeptide chain to enhance the DPP IV-inhibiting effect. To summarize, QSAR studies of compounds have been known since 1962 and are still being developed with increasingly sophisticated methods of computation to become a standard approach in drug discovery due to their efficiency in prediction and low cost of analyses [45]. In the area of the QSAR of peptides, particularly those of food origin, studies were undertaken on the sequences showing ACE-inhibitory [46], bitter-tasting [47], and anti-oxidative [11] effects. To date, there has been little research on QSAR of peptide DPP IV inhibitors. This may be due to the fact that although new peptides with such an activity are being identified, it is still not enough to merit creating a dataset for QSAR analysis. The results obtained using SCIGRESS bring more insight into the structural nature of peptides acting as DPP IV inhibitors.