The problem of multidrug resistance requires the efficient and accurate identification of new classes of antimicrobial agents. Endogenous antimicrobial peptides produced by most organisms are a promising source of such molecules. We have exploited the high conservation of signal sequences in teleost and anuran antimicrobial peptides to search cDNA (expressed sequence tag) databases for likely candidates. Subject sequences were then analysed for the presence of potential antimicrobial peptides based on physicochemical properties (amphipathic helical structure, cationicity) and use of the D-descriptor model to predict the therapeutic index (relation between the minimum inhibitory concentration and the concentration giving 50% haemolysis). This analysis also suggested mutations to probe the role of the primary structure in determining potency and selectivity. Selected sequences were chemically synthesized and the antimicrobial activity of the peptides was confirmed. In particular, a short (21-residue) sequence, likely of sticklefish origin, showed potent activity and it was possible to tune the spectrum of action and/or selectivity by combining three directed mutations. Membrane permeabilization studies on both bacterial and host cells indicate that the mode of action was prevalently membranolytic. This method opens up the possibility for more effective searching of the vast and continuously growing expressed sequence tag databases for novel antimicrobial peptides, which are likely abundant, and the efficient identification of the most promising candidates among them.
Conservation of signal sequences in teleost and anuran antimicrobial peptides allowed identification of new potential AMPs in EST databases, which were then subjected to therapeutics index prediction. A sticklefish peptide showed a potent activity which could be tuned by combining three directed mutations. The mode of action was prevalently membranolytic. The method thus allows effective mining of EST databases for novel AMPs.