Publication: Evaluation of Anti-Cancer and Anti-Covid-19 Properties of Cationic Pentapeptide Glu-Gln-Arg-Pro-Arg, From Rice Bran Protein and Its D-Isomer Analogs Through Molecular Docking Simulations
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Science Inc.
Abstract
Bioactive peptides derived from food proteins are becoming increasingly popular due to the growing awareness of their health-promoting properties. The structure and mechanism of anti-cancer action of pentapeptide GluGln-Arg-Pro-Arg (EQRPR) derived from a rice bran protein are not known. Theoretical and experimental methods were employed to fill this gap. The conformation analysis of the EQRPR pentapeptide was performed first and the obtained lowest energy conformer was optimized. The experimental structural data obtained by FTIR and CD spectroscopies agree well with the theoretical results. D-isomer introduced one-by-one to each position and all D-isomers of the peptide were also examined for its possible anti-proteolytic and activity enhancement properties. The molecular docking revealed avid binding of the pentapeptide to the integrins alpha(5)beta(1) and alpha(IIb)beta(3), with K-d values of 90 nM and 180 nM, respectively. Moreover, the EQRPR and its D-isomers showed strong binding affinities to apo-and holo-forms of M-pro, spike glycoprotein, ACE2, and dACE2. The predicted results indicate that the pentapeptide may significantly inhibit SARS-CoV-2 infection. Thus, the peptide has the potential to be the leading molecule in the drug discovery process as having multifunctional with diverse biological activities.
Description
Keywords
Anti-cancer Peptides, Molecular Modeling, Molecular Docking, FTIR, Circular Dichroism, Cationic Peptides
Citation
Gasymov, O. K., Celik, S., Agaeva, G., Akyuz, S., Kecel-Gunduz, S., Qocayev, N. M., ... & Aliyev, J. A. (2021). Evaluation of anti-cancer and anti-covid-19 properties of cationic pentapeptide Glu-Gln-Arg-Pro-Arg, from rice bran protein and its d-isomer analogs through molecular docking simulations. Journal of Molecular Graphics and Modelling, 108, 107999.