Antimicrobial peptides (AMPs) have been identified as a potentially new class of antibiotics. There is a lot of computational methods of AMP prediction. Although most of them can predict antimicrobial potency against any microbe (microbe is not identified) with rather high accuracy, prediction quality of these tools against particular bacterial strains is low (Bioinformatics, 2018, in press; Journal of Chemical Information and Modeling 58, 1141-1151). Special prediction is a tool for the prediction of antimicrobial potency of peptides against particular target species with high accuracy. This tool is included into the Database of Antimicrobial Activity and Structure of Peptides (DBAASP, https://dbaasp.org, Nucleic acids research 44 (D1), D1104-D1112). In this presentation we describe this tool and predictive models for some Gram+ bacterial strains (Staphylococcus aureus ATCC 25923 and Bacillus subtilis) and a model for the prediction of hemolytic activity. Predictive model for Gram- Escherichia coli ATCC 25922 was presented earlier (Journal of Chemical Information and Modeling 58, 1141-1151, In 2nd Int. Electron. Conf. Med. Chem. 01-30 November 2016; Sciforum, 2016, A031). Special prediction tool can be used for the design of peptides being active against particular strain. To demonstrate the capability of the tool, peptides predicted as active against E. coli ATCC 25922 and S. aureus ATCC 25923 have been synthesized, and tested in vitro. The results have shown the justification of using special prediction tool for the design of new AMPs.
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DBAASP Special prediction as a tool for the prediction of antimicrobial potency against particular target species
Published: 31 October 2018 by MDPI in 4th International Electronic Conference on Medicinal Chemistry session ECMC-4
Keywords: Antimicrobial peptides; AMP prediction; Design of AMPs