## 4 In Silico Studies on the Biological Activities of Meat Peptides--Practical Approach
CDF shared four H-bond interactions in the S1 pocket of ACE [29]. Bioinformatics is closely related to chemometrics, which is a field of science that uses mathematical and statistical tools to search for useful information from multidimensional measurements. This approach is used to design, or select, the optimal experimental procedures for obtaining maximum information through data analysis, and for acquiring a knowledge of systems and the relationships between them. The described data are primarily the physicochemical parameters that characterize the tested molecules (ligands), which are reduced to their numerical forms. These are known as \"descriptors\". The methods used in chemometric practice to verify the rank of individual descriptors are cluster analysis, artificial neural networks, principal component analysis, the partial least squares method, etc. These methods allow for the determination of the relationship between their structures and functions by using statistical methods [38; 39; 40]. Thus, it is possible to determine which characteristics of the ligands have the most significant influence on their activity. This approach has been used to describe taste peptides [68; 69] or DPP-IV inhibitory peptides [22]. In this approach, target peptides were described in a multidimensional approach by using their descriptors. Using computational methods, a mathematical model was developed for them by combining the structural features (peptide descriptors as independent variables) with the biological activity (as the dependent variable). The in silico analysis, based on the physicochemical properties of molecules (peptides) for discovering their bioactivity, is known as the SAR (the structure-activity relationship). When using chemometry to estimate the SAR, it is assumed that if the structure of a hit is known, on the basis of the data from other similar compounds, the biological effects of this match could be predicted. This is because structurally similar compounds may have similar physical and biological properties and specific mechanisms of action. SAR analysis enables the determination of which chemical groups play an important role in inducing a target effect in the body. Biological activity can also be defined quantitatively as the minimum amount (concentration) of a certain substance that causes a specific biological response (effect). This approach is used in QSAR (the quantitative structure-activity relationship) and QSPR (the quantitative structure-property relationship) analyses. QSAR/QSPR relationship models reduce the time and costs of in vitro tests and enable the rational prediction of the biological, pharmaceutical, physical, and chemical activities/properties. These models are used by experimental scientists as the first stage of their work, and they provide information about the mechanisms of action for biological activities of interest [70]. The general workflow of QSAR/QSPR modeling can be divided into the following stages: (I) Raw data collected from the literature or public databases; (II) Initial data verification and removal of irrelevant information (e.g., by principal component analysis; (III) Definition of relevant descriptors; and (IV) Model construction and evaluation of model performance. The SAR or QSAR approaches have also been used in food research to identify food-derived bioactive peptides. For example, 242 dipeptides acting as DPP-IV inhibitors (as a set of test sequences) were tested using 16 descriptors, and an SAR model was developed for these dipeptides using principal component analysis and multiple regression analysis [22]. [PERSON] et al. [19] showed that the proteins from pork, beef, and poultry are good precursors of ACE-inhibitory peptides (IC\({}_{50}\) < 10 uM) by using a QSAR-aided in silico approach. Thesestudies used the QSAR approach with the SIMCA-P software version +11. In this case, the selected features of the well-known and described peptides and a set of test peptides were compared using statistical models (developed on the basis of reliable datasets).