Modeling of short polypeptide chains to identify Essential Amino Acids by calculating Nuclear Magnetic Resonance spectrum

Since reducing or increasing proteins could be the signs of diseases in the body, they could be used as biomarkers for diagnosing some diseases. This study investigated small protein strings by computing the magnetic resonance spectrum of the nucleus. Amino acids are the building blocks of protein in the body, and the body does not produce the essential amino acids. They must reach the body through the food chain. Because essential amino acids are required for vital processes such as protein production and hormone synthesis, they are of great importance and are studied in this study. First, strings of two to six amino chains with the same monomers were modeled using Gauss View software, and their magnetic resonance spectrum was calculated using Gaussian09w software. These structures are modeled to investigate factors such as the type and length of the amino acid chain on the amplitude and location of the maximum peak in the magnetic resonance spectrum of the nucleus. The results show each amino acid has a unique own magnetic resonance spectrum and these amino acids in a polypeptide chain affect magnetic resonance spectrum. The ability of the nuclear magnetic resonance method to diagnose and identify a variety of diseases, its non-invasive nature, as well as the possibility of repeatability of experiments, in addition to reducing the cost of experiments, make this method as one of the novel and advanced diagnosis.