In <i>Silico s</i>tudy of anticancer and antimicrobial peptides derived from Cycloviolacin O2 (CyO2)

Cancer is considered a global threat to public health as one of the leading causes of premature deaths in most countries worldwide. Chemotherapy in cancer has reached a therapeutic plateau caused by high cost, low specificity, long development time, and severe side effects. Currently, peptide-based targeted therapeutics are being extensively studied to be utilized for cancer treatment due to their small size, high specificity, and selectivity. In this study, we utilized several in silico methods to design more potent dual anticancer and antimicrobial activities using Cycloviolacin O2 (CyO2), a natural antimicrobial peptide from a plant. The dual activity of these peptides also helps address the intersection between cancer and infections, where chronic infections and their treatment can lead to the induction of cancer progression, and inversely, the weakened immune system from cancer treatments herald opportunistic infections. In the present study, the fifteen amino acid length fragment of CyO2 (Uniprot ID: P58434) was mutated with lysine residues, resulting in increased helical propensity and stability. Our results showed that a novel fragment T2.2 (double lysine substitution) peptide had the most stable physicochemical properties (amphipathicity, charge, hydrophobicity, half-life, and molecular weight) and highest biological activities (anticancer and antimicrobial) among the CyO2-derived peptides. This highlighted the importance of lysine residue in developing stable therapeutic peptides with low hemolytic activity. The molecular docking study indicated the potential of T2.2 to induce extrinsic apoptosis by binding to the death domain of the Fas receptor. Our results indicated that the short T2.2 peptide derived from CyO2 could be considered a potential therapeutic agent in anticancer and antimicrobial treatments. Furthermore, in vitro and in vivo studies are essential to confirm the predictions obtained by the in silico analysis.