Antimicrobial Peptides (AMPs) for Antibiotics

Antimicrobial Peptides (AMPs) for Antibiotics Dhayalini Yoginthran Antibiotic resistance is something that has been growing in the world, some might even say that we are entering or have already entered a post antibiotic world. It is currently one of the superior concerns in the 21 st century, especially in regards to pathogenic microorganisms. Throughout the years, research had allowed for the development of first line antibiotics that were efficacious against infections plaguing the population. Due to resistance build up towards first line agents, second line agents were then used to treat infections, which usually have a broad spectrum in treatment. In some cases pathogens have also acquired resistance towards multiple drugs, one such example would be Staphylococcus aureus (Zainnudin and Dale, 1990) . Antimicrobial peptides (AMPs) are substances produced by animals, bacteria and plants. They are also known as host defence peptides and are a part of the non-specific immune system. Differences between eukaryotes and pro karyotes show the potential of targeted therapy with the use of AMPs . They are dynamic and are of broad spectrum and have shown plausible evidence that they may be used as a new therapeutic agent. AMPs are quite small, have various sequences and lengths. They are also known to be cationic and amphipathic (Hultmark, 2003). They have shown considerable bactericidal activity against both Gram positive and Gram negative strains of bacteria, Mycobacterium tuberculosis , malignant cells as well as viruses that are enveloped (Reddy et al., 2004). AMPs work by the interaction with the membrane of the potential pathogen thus leads to the perturbation of said membrane. The peptide is then inserted into the bilayer of the membrane that causes the displacement of the lipids. The perturbation and the displacement actions render it easy for the peptide to be translocation into the intracellular target of the pathogen. AMPs are usually derived from coding sequences in a gene, databases of known AMPs have been curated to hold information of AMPs as well as to provide tools to predict possible AMPs that are found in genomes (Fjell et al., 2007). The Antimicrobial Peptide database (APD) is one of the major resource for antimicrobial peptide sequences that have been curated. AMPs from various phylogenetic kingdoms are available, making the prediction of models based on qualitative and quantitative activity easier. In order to bring the development of AMPs into light, certain objectives are to be met. An AMP must be active against the pathogen in which it is targeted against and must have a high therapeutic index. In order to look for a suitable AMP that can act as a broad spectrum antibiotic. A method will be explained to show the screening process to look for one such AMP. The method would be to employ template based studies. A template AMP will be used to look for peptides that have better antimicrobial activity and also is reduced in toxicity by altering amino acid sequence s. In order to elucidate positions of amino acids that are important in antimicrobial activity, a single amino acid in the peptide will be changed, and hence the changes will be studied. Template AMPs that could be used for this would be lactoferrin or magainin. The variety of peptides are designed based on the amphiphilicity and charge of the AMPs and their role in antimicrobial activity. It will be possible to synthesis peptides using a high throughput approach of arrays that is done together with a speedy luminescence assay to portray bactericidal activity. This would lead to us being able to perform a complete substitution method to study the amino acid changes in the desired peptide. Several substitution studies that have been performed have shown that the activity shown by the substituted amino acids differ with regards to the template AMP utilised (Schneider et al., 1995). A linguistic model shall be used to pinpoint patterns in natural peptides (Loose et al., 2006). It is po ssible that the novel peptide that is constructed based on this will show superiority against models that are generated based on the random shuffling of amino acid sequences. Functionally important patterns of amino acids will be found using this linguistic model. In a previous study conducted by Loose et al (2006), 4 out of 40 designed peptides showcased activity against E. coli and B. cereus at an acceptable concentration.