Quantitative Structure Sequence Modeling of Angiotensin-I-Converting Enzyme Peptide Originated from Milk Using Amino Acid Indices based on Quantum Topological Molecular Similarity.

Numerous casein and whey protein-derived angiotensin-I-converting enzyme (ACE) inhibitory peptides/hydrolysates have been identified. Clinical trials in hypertensive animals and humans have shown that these peptides/hydrolysates can bring about a significant reduction in hypertension[1]. In this work, quantum topological molecular similarity (QTMS)amino acids indices [2,3] were utilized in QSAR/ QSAM studies to predict the activity of a set of milk-driven peptides with ACE property. To show the importance of the studied peptides it should be noted that Casokinins and lactokinins which are Casein and Whey Protein-derived ACE inhibitory peptides of milk respectively, have special importance in pharmaceutical industry as the pharmaceutical peptides. Besides they consist of numerous sequences of different lengths and with different IC50 values. In the current project, by combination of QTMS descriptors with Auto cross covariance (ACC) methodology[4] , the QSAM model was built and evaluated to predict the pIC50 value of ACE peptides derived from Bovine Casein and Whey with different number of residues. The model established an acceptable relationship between the selected variables and the pIC50 of the peptides for example for casein data set R2 train, R2 CV and R2 test were obtained equal to 0 .85, 0.81 and 0.82 respectively. For estimating performance of our proposed method and its regression models, different hypertension mammals’ peptides sequences of casein and whey were obtained from human, goat, bovine and sheep. In this regard, each sequences were broken virtually by trypsin and chymotrypsin enzyme. After ACC preparation, pIC50 value of each peptide was estimated by using the suggested QSAM models to predict and synthesize new peptides to control hypertension disease as pharmaceutical targets.