Shahrzad Shahbazi - Department of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran
Somayeh Reiisi - Department of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran

Background: Antimicrobial peptides are short amino acid sequences, involved in diverse functions. Theyhave anti-cancer properties, probably due to controlling mutagenic compounds by direct binding tocarcinogens or inhibition of microbes that produce these agents. Azurin is a copper-comprising redox proteinsecreted by Pseudomonas aeruginosa. Azurin and its derived peptide can selectively enter into different typesof cancer cells and induce cell cycle arrest or apoptosis. The use of computational methods for drug designinghas been considered a powerful technique in recent decades. Thus, the aim of the current study is to improvethe approach for the identification of possible peptide drug molecules for gastric cancer targeting throughbioinformatics analysis.Materials and Methods: Azurin peptide sequence submits to AntiCP server for predict and design of newlyanticancer peptides. The ۲D and ۳D structures of these peptides were drawn with Protean (DNAstar software)and Phyre۲ respectively. The ۳D structures of peptides were docked with the VEGFR using docking serverswissdock and the peptide with the maximum binding energy value was identified. As well, anticanceractivity for each peptide was estimated with iACP software.Results: AntiCP server predicts >۲۰۰ peptides with the anticancer property. Anticancer activity of newlydesigned peptides showed ۹۸-۹۹% anticancer specificity. Results of this study indicated that among ۲۰۰peptides that were virtually screened, ۱۸ peptides showed the high anticancer property and among thesepeptides, DSRVIEHTKLIGSGEKDSVTFDVSK was identified as a potential sequence for VEGFR ligand.Conclusion: Our results revealed the possibility of a successful design of a new anticancer peptide derivedfrom the Azurin peptide. Therefore, the newly designed peptide can be proposed as a potential inhibitor agentagainst gastric cancer.

Anti-cancer peptides; Azurin peptide; Gastric cancer; In Silico