@article{Sitanggang_Sudarsono_Syah_2018, title={PENDUGAAN PEPTIDA BIOAKTIF DARI SUSU TERHIDROLISIS OLEH PROTEASE TUBUH DENGAN TEKNIK IN SILICO}, volume={29}, url={https://journal.ipb.ac.id/index.php/jtip/article/view/20768}, DOI={10.6066/jtip.2018.29.1.93}, abstractNote={The production of bioactive peptides catalyzed by gastrointestinal system (GIS) enzymes can be predicted in silico. The technique is more preferred than others such as in vivo and in vitro due to its low cost and less tedious procedure. The current study was aimed to predict bioactive peptides resulted from the digestion of bovine milk proteins. The digestion or so-called hydrolysis was simulated by means of a web-based in silico method. Identified bovine milk proteins from the available literatures were αS1-casein, αS2-casein, β-casein, κ-casein, β-lactoglobulin, α-lactalbumin, and lactoferrin. The compositions of amino acids (AAs) or protein sequences were accessed and tabulated from the Universal Protein Resource site (UniProt). Furthermore, the hydrolysis of each protein were simulated using three (3) GIS proteases, i.e., pepsin, trypsin, and chymotrypsin, and their possible combinations. All simulations were performed through web-based procedures using PeptideCutter, Expert Protein Analysis System (ExPASy). The resulted peptides were arranged according to the positions of cleavage sites for each cutting simulation, and compared to the available bioactive peptides data base in the literatures in terms of their AA residues (sequences). The simulation results indicated that β-casein and αS1-casein were the most potent proteins to yield bioactive peptides, of 52 and 48%, respectively. Moreover, each type of the investigated bovine milk proteins could be hydrolyzed by GIS proteases to produce antihypertensive bioactive peptides. This web-based in silico method is conclusively useful to predict bioactive peptides derived from bovine milk, and may also be used for other protein sources.}, number={1}, journal={Jurnal Teknologi dan Industri Pangan}, author={SitanggangAzis Boing and Sudarsono, Sudarsono and Syah, Dahrul}, year={2018}, month={Jun.}, pages={93-101} }