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Antibacterial peptides are researched mainly for the potential benefit they have in a variety of socially relevant diseases, used by the host to protect itself from different types of pathogenic bacteria. We used the mathematical-computational method known as Hidden Markov models (HMMs) in targeting a subset of antibacterial peptides named Selective Cationic Amphipatic Antibacterial Peptides (SCAAPs). The main difference in the implementation of HMMs was focused on the detection of SCAAP using principally five physical-chemical properties for each candidate SCAAPs, instead of using the statistical information about the amino acids which form a peptide. By this method a cluster of antibacterial peptides was detected and as a result the following were found: 9 SCAAPs, 6 synthetic antibacterial peptides that belong to a subregion of Cecropin A and Magainin 2, and 19 peptides from the Cecropin A family. A scoring function was developed using HMMs as its core, uniquely employing information accessible from the databases.
 Antimicrobial peptides occupy a prominent place in the production of pharmaceuticals, because of their effective contribution to the protection of the immune system against almost all types of pathogens. These peptides are thoroughly studied by computational methods designed to shed light on their main functions. In this paper, we propose a computational approach, named the Polarity Profile method that represents an improvement to the former Polarity Index method. The Polarity Profile method is very effective in detecting the subgroup of antibacterial peptides called selective cationic amphipathic antibacterial peptides (SCAAP) that show high toxicity towards bacterial membranes and exhibit almost zero toxicity towards mammalian cells. Our study was restricted to the peptides listed in the antimicrobial peptides database (APD2) of December 19, 2012. Performance of the Polarity Profile method is demonstrated through a comparison to the former Polarity Index method by using the same sets of peptides. The efficiency of the Polarity Profile method exceeds 85% taking into account the false positive and/or false negative peptides.
 A novel antibacterial protein with a molecular mass of 44 kDa has been isolated from dried fruiting bodies of the wild mushroom Clitocybe sinopica. Sodium dodecyl sulfate/polyacrylamide gel electrophoresis showed that the protein was composed of two subunits each with a molecular mass of 22 kDa. Its N-terminal amino-acid sequence, SVQATVNGDKML, has not been reported for other antimicrobial proteins. The purification protocol included ion exchange chromatography on DEAE-cellulose, CM-cellulose and Q-Sepharose, and gel filtration by fast protein liquid chromatography on Superdex 75. The antibacterial protein was adsorbed on all three ion exchangers. The antimicrobial activity profile of the protein against tested bacterial and fungal strains disclosed that it possessed potent antibacterial activity against Agrobacterium rhizogenes, A. tumefaciens, A. vitis, Xanthomonas oryzae and X. malvacearum with a minimum inhibitory concentration mostly below 0.6 μM. However, it had no antibacterial activity against Pseudomonas batatae, Erwinia herbicola, Escherichia coli, and Staphylococcus aureus, and no antifungal activity against Setosphaeria turcica, Fusarium oxysporum, Verticillium dahliae, Bipolaris maydis, and B. sativum. The antibacterial antivity against A. tumefaciens was stable after exposure to 20-60°C for 30 min and to pH 4-9 for 1 h.
The work describes purification and biochemical characterization of two inducible antimicrobial peptides from the hemolymph of Galleria mellonella. The peptides were isolated by a sequence of reversed-phase chromatography steps from the hemolymph of larvae immunized with viable bacteria. The first peptide is a member of the cecropin family while the second one is rich in proline residues and has a unique se­quence.
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