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Computational design of Phe-Tyr dipeptide and preparation, characterization, cytotoxicity studies of Phe-Tyr dipeptide loaded PLGA nanoparticles for the treatment of hypertension

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posted on 2017-09-11, 11:15 authored by Serda Kecel-Gündüz, Yasemin Budama-Kilinc, Rabia Cakir Koc, Yagmur Kökcü, Bilge Bicak, Bahar Aslan, Aysen E. Özel

Phe-Tyr dipeptide which was investigated in Wakame food with greatest ACE-inhibitory activity is used as a pharmaceutical drug for the treatment of hypertension, cardiovascular diseases, and diabetic nephropathy. To improve the bioavailability of Phe-Tyr, a delivery system based on poly (lactic-co-glycolic acid) (PLGA) nanoparticles loaded with Phe-Tyr (Phe-Tyr-PLGA NPs) for treating hypertension and cardiovascular diseases was prepared in this study. In the experiments, poly(lactic-co-glycolic acid) (PLGA) and Phe-Tyr dipeptide-loaded PLGA nanoparticles were prepared using the double emulsion (w/o/w) method. The characterizations of the nanoparticles were performed with a UV–vis spectrometer, the Zeta-sizer system, and FTIR spectrometer. The optimum size of the Phe-Tyr dipeptide-loaded PLGA nanoparticle was obtained with a 213.8 nm average particle size, and a 0.061 polydispersity index, −19.5 mV zeta potential, 34% of loaded and 90.09% of encapsulation efficiency. From TEM analysis, it was clearly seen that the dipeptide loaded nanoparticles had the spherical and non-aggregated morphology and Phe-Tyr dipeptide loaded-PLGA nanoparticles were obtained successfully. Cell toxicity of nanoparticles at different concentrations was assayed with XTT methods on L929 fibroblast cells. This study determined that the nanoparticles have low toxicity at lower concentration and toxicity augmented with increasing concentration of dipeptide. To analyze the effect of solvents on structure of Phe-Tyr, Molecular dynamics simulation was performed with GROMACS program and molecular orbital calculations were carried out to obtain structural and electronic properties of dipeptide. Moreover, molecular docking calculations were also employed to model and predict protein–drug interactions.

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