In summary peptide engineering could help, in a near future, to find the essential Pg-AMP1 regions involved on antimicrobial activity. Once that this regions have being found, it will be possible to enhance the bactericidal activity by switching amino acid residues and also reduce the costs by reducing Pg-AMP1 length, leading to a possible application on industrial drug
development. This work was supported by CNPq, FAPEMIG, CAPES, UCB, UFJF and FAPDF. “
“The growing number of the selleck screening library pathogen’s resistance mechanisms to conventional drugs significantly increased in the last decade, in part because of the increase of the immune-compromised patients [5]. In some cases due to the resistance problem, only few drugs present the potency necessary to treat these opportunistic infections. Unfortunately, click here some of these drugs, such as amphotericin B, have the disadvantage of excessive toxicity, which could limit its use by patients
receiving other therapies with toxic drugs, i.e. anticancer therapy [16]. The development of alternative antibiotic therapies able to circumvent this problem is one of the intriguing challenges of the modern medicine. For this purpose, antimicrobial peptides represent a promise to be used as antifungal and bactericidal agents since episodes of natural resistance to these peptides are not frequent [2], [18] and [23]. Antimicrobial peptides can be found in all forms of life, from bacteria and fungi to plants, invertebrates and vertebrates [23]. They can be produced from secondary metabolites or, as most of them, encoded by genes conserved throughout evolution [3] and [44]. Despite some exceptions [32], usually, these peptides have the common features of being present on a cationic surface and also forming amphipathic structures [34] and [37].
Gemcitabine datasheet Among the strategies used to identify these peptides, the technique to predict peptide sequences directly from genomic or transcriptome databases is currently used [19]. The genomic and transcriptome databases are valuable sources to identify gene sequences involved in the biosynthesis of antibiotics [4]. The in silico analysis of protein sequences or direct into the genes databases are strategies used to predict peptides of therapeutic interest [31]. The search for peptides using this strategy is performed by using sophisticated computational programs that scans the databases, correlating the antimicrobial peptide features previously described in the literature on the amino acid sequences. Since the main characteristics of antimicrobial peptides are already known, the pursuit of these similarities in silico in these databases is a tool to shorten the identification and selection of new antibiotics [14] and [17]. In order to certify the in silico identified peptides, the selected sequences must be synthesized by chemical synthesis and evaluated in vitro against selected microorganisms aiming to explore the antimicrobial potential [4] and [23].
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