AUTHOR=Okella Hedmon , Georrge John J. , Ochwo Sylvester , Ndekezi Christian , Koffi Kevin Tindo , Aber Jacqueline , Ajayi Clement Olusoji , Fofana Fatoumata Gnine , Ikiriza Hilda , Mtewa Andrew G. , Nkamwesiga Joseph , Bassogog Christian Bernard Bakwo , Kato Charles Drago , Ogwang Patrick Engeu TITLE=New Putative Antimicrobial Candidates: In silico Design of Fish-Derived Antibacterial Peptide-Motifs JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=8 YEAR=2020 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2020.604041 DOI=10.3389/fbioe.2020.604041 ISSN=2296-4185 ABSTRACT=
Antimicrobial resistance remains a great threat to global health. In response to the World Health Organizations’ global call for action, nature has been explored for novel and safe antimicrobial candidates. To date, fish have gained recognition as potential source of safe, broad spectrum and effective antimicrobial therapeutics. The use of computational methods to design antimicrobial candidates of industrial application has however, been lagging behind. To fill the gap and contribute to the current fish-derived antimicrobial peptide repertoire, this study used Support Vector Machines algorithm to fish out fish-antimicrobial peptide-motif candidates encrypted in 127 peptides submitted at the Antimicrobial Peptide Database (APD3), steered by their physico-chemical characteristics (i.e., positive net charge, hydrophobicity, stability, molecular weight and sequence length). The best two novel antimicrobial peptide-motifs (A15_B, A15_E) with the lowest instability index (−28.25, −22.49, respectively) and highest isoelectric point (p