## 2 In Silico Approach as Part of Food Research Study  
Interventionary studies involving animals or humans, and other studies that require ethical approval, must list the authority that provided approval and the corresponding ethical approval code. The phrase \"in silico\" (lac. literally \"in silicon,\" referring to the mass use of silicon in semiconductor computer circuits) is an expression used for an analysis performed on a computer or by modeling or computer simulation. This expression may be considered as an allusion to the Latin phrases, \"in vivo\", \"in vitro\", and \"in situ\", which are commonly used in biology and refer to experiments conducted on living organisms. The use of computerized methods (in silico) in research is becoming increasingly common and is considered by scientists to be as important as in vitro experimental research. Overall, knowledge obtained from an in silico analysis can be used in in vitro test design. Various fields of science use bioinformatics to better understand processes or phenomena at the molecular level (Figure 1). The approach that uses bioinformatics to assess the relationship between disease/health and food compounds is referred to as \"foodomics.\" Foodomics uses computer software, mathematical algorithms, and statistical tools to archive, retrieve, and analyze data in the field of the biological and natural sciences. In silico analyses rely on a huge amount of data collected, including food peptides (often available online via the Internet), which are useful for empirical research and can also provide a better understanding of the structure-activity relationship of a peptide at the molecular level [18; 19; 20; 21; 22]. Bioinformatics tools present information on the biological and chemical properties of the molecules under study through online tools and databases. For example, databases, such as ATDB, ACEpepDB, BioPepDB, BIOPEP-UWM, EROP-Moscow, FermFooDB, SATPdb, and PepBank, and bioinformatics tools on servers (e.g., PepDraw, Peptide Property Calculator, pI/MW, ProtParam, and GRAVY Calculator) are helpful in searching information for the physicochemical properties of peptide sequences and their sources of origin (proteins), as well as for predicting their bioactivity (e.g., BIOPEP-UWM, iDPPIV-SCM, PeptideLocator, ToxinPred, and OmicTools Peptide prediction) [10; 23]. Examples of the use of databases to search for biologically active peptides, and to evaluate their bioactivity in meat and meat products, are presented in Table 1.  
Computer simulations and molecular docking are also possible using bioinformatics tools. This approach is particularly helpful for assessing the complementarity of a selected peptide sequence to the active site of a molecule, most often an enzyme to inactivate it, as was the case, for example, with the peptide, ACE-I, or DPP-IV inhibitors [24; 25; 26; 27; 28; 29]. By using the molecular model of the enzyme and the peptide molecule, it is possible to evaluate the possibilities of them docking each other without the need for laboratory analyses. Figure 1: Application of bioinformatics in the field of science. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Peptide Sequences and Their** & **Source** & \begin{tabular}{c} **Bioinformatics Tools** \\ **Used in In Silico** \\ **Analysis**\({}^{A}\) \\ \end{tabular}  & \begin{tabular}{c} **Special Conditions of** \\ **Analysis**\({}^{A}\) \\ \end{tabular}  & **References** \\ \hline PPL \({}^{5}\), APPH \({}^{5}\), APPH \({}^{5}\), IPP \({}^{5}\), PPG \({}^{5}\) & \begin{tabular}{c} Meat muscle and \\ byproducts \\ \end{tabular}  & \begin{tabular}{c} BIOPEP, PeptideCutter, \\ ProtParam \\ \end{tabular}  & \begin{tabular}{c} In silico hydrolysis by \\ trypsin, pepsin, papain, \\ bromelain, \\ thermolysin \\ \end{tabular}  & [30] \\ \hline FWG \({}^{2}\), MFLG \({}^{2}\) and SDPPLVFVG \({}^{2}\) & \ \begin{tabular}{c} Cooked beef, pork, \\ chicken, and turkey \\ meat \\ \end{tabular}  &