Mohammed Walid Chemao-Elfihri, Mohammed Hakmi, Hanane Abbou, Souad Kartti, Elmostafa El Fahime, Lahcen Belyamani, Saber Boutayeb
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Staphylococcus hominis as a source of antimicrobial peptides: identification of a new peptide with potential antimicrobial properties using in silico approach
The rapid progression of antimicrobial resistance, fueled by the excessive use of antibiotics, has become a major public health concern. Among the pathogens contributing to this crisis, Staphylococcus aureus stands out as a significant therapeutic challenge, especially with the rise of resistant strains like Methicillin-Resistant S. aureus (MRSA). In this context, antimicrobial peptides (AMPs) emerge as a promising alternative, thanks to their unique mechanisms of action. Exploring the genomes of species such as Staphylococcus hominis, known for producing AMPs effective against S. aureus, offers promising opportunities for discovering novel therapeutic agents. In this study, Average Nucleotide Identity (ANI) combined with phylogenetic analysis identified a potential emerging subspecies of Staphylococcus hominis. The core genome analysis led to the identification of a potential antimicrobial peptide. The peptide model simulated with the S. aureus membrane model in molecular dynamics revealed that it interacts primarily with the lipids head groups, leading to an overall rigidification of the bacterial membrane.
期刊介绍:
Research papers must make a significant and original contribution to
microbiology and be of interest to a broad readership. The results of any
experimental approach that meets these objectives are welcome, particularly
biochemical, molecular genetic, physiological, and/or physical investigations into
microbial cells and their interactions with their environments, including their eukaryotic hosts.
Mini-reviews in areas of special topical interest and papers on medical microbiology, ecology and systematics, including description of novel taxa, are also published.
Theoretical papers and those that report on the analysis or ''mining'' of data are
acceptable in principle if new information, interpretations, or hypotheses
emerge.