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Computational Screening and Characterization of Novel Bacteriocins through Peptidome Mining of Pathogenic Bacteria

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Document pages: 25 pages

Abstract: Antibiotic resistance is a major clinical and public health issue. One solution to resolving this issue is the use of bacteriocin. Bacteriocins are formed by bacteria, and the growth of similar or closely related bacterial strains is inhibited. Staphylococcus, Streptococcus, Klebsiella, and Shigella species are among the few pathogenic organisms that have developed resistance to drugs available. Such pathogens cause pneumonia, meningitis, pharyngitis, media otitis, sinusitis, bacteremia, pericarditis, infections with arthritis, etc. The present study adopted the different new bioinformatics approaches to predict novel putative bacteriocins from the proteome of these identified Multi-Drug resistant (MDR) pathogens. The current study revealed that 16 proteins of 7 pathogens & 2 probiotics were capable of binding the expected Bacteriocins. The study also revealed that some experimentally identified bacteriocins and cyclotides are capable of binding to selected organisms with few MDR proteins and essential proteins.

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