Database-aided prediction and design of novel antimicrobial peptides.

The isolation and characterization of potent antimicrobial peptides from natural sources has opened a new avenue to the development of future antimicrobials. To further expand the peptide space, new antimicrobial peptides can be predicted or designed based on natural peptide templates. By using the knowledge derived from mature peptides, propeptides, or both (i.e. precursor proteins), a variety of peptide prediction tools have been developed. Furthermore, bacteriocins are predicted under the genomic context by considering not only the peptide itself, but also the accompanying genes for its expression, processing and export. This chapter also discusses database-aided peptide design based on database screening, sequence shuffl ing, grammar-based design and de novo design. Finally, major strategies for improving peptide selectivity and stability are highlighted.