In silico identification and functional validation of linear cationic α-helical antimicrobial peptides in the ascidian Ciona intestinalis

We developed a computing method to identify linear cationic α-helical antimicrobial peptides (LCAMPs) in the genome of Ciona intestinalis based on its structural and physicochemical features. Using this method, 22 candidates of Ciona LCAMPs, including well-known antimicrobial peptides, were identified from 21,975 non-redundant amino acid sequences in Ciona genome database, Ghost database. We also experimentally confirmed the antimicrobial activities of five LCAMP candidates, and three of them were found to be active in the presence of 500 mM NaCl, nearly equivalent to the salt concentration of seawater. Membrane topology prediction suggested that salt resistance of Ciona LCAMPs might be influenced by hydrophobic interactions between the peptide and membrane. Further, we applied our method to Xenopus tropicalis genome and found 11 LCAMP candidates. Thus, our method may serve as an effective and powerful tool for searching LCAMPs that are difficult to find using conventional homology-based methods.