Novel active Trp- and Arg-rich antimicrobial peptides with high solubility and low red blood cell toxicity designed using machine learning tools.

Autor: Henson BAB; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Li F; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Álvarez-Huerta JA; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Wedamulla PG; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Palacios AV; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Scott MRM; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Lim DTE; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Scott WMH; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Villanueva MTL; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Ye E; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada., Straus SK; Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC, V6T 1Z1, Canada. Electronic address: sstraus@chem.ubc.ca.
Jazyk: angličtina
Zdroj: International journal of antimicrobial agents [Int J Antimicrob Agents] 2024 Dec 05, pp. 107399. Date of Electronic Publication: 2024 Dec 05.
DOI: 10.1016/j.ijantimicag.2024.107399
Abstrakt: Given the rising number of multidrug-resistant (MDR) bacteria, there is a need to design synthetic antimicrobial peptides (AMPs) that are highly active, non-hemolytic, and highly soluble to act as alternatives to antibiotics that are either no longer effective or used as drugs of last resort. Machine learning tools allow the straightforward in silico identification of non-hemolytic antimicrobial peptides. Here, we utilized a number of these tools to rank the best peptides from two libraries: 1) 8192 peptides with sequence bhxxbhbGAL, where b is the basic amino acid R or K, h is a hydrophobic amino acid, i.e. G, A, L, F, I, V, Y, or W and x is Q, S, A, or V; and 2) 512 peptides with sequence RWhxbhRGWL, where b and h are as for the first library and x is Q, S, A, or G. The top 100 sequences from each library, as well as 10 peptides predicted to be active but hemolytic (for a total of 220 peptides), were SPOT synthesized and their IC 50 values were determined against S. aureus USA 300 (MRSA). Of these, 6 AMPs with low IC 50 's were characterized further in terms of: MICs against MRSA, E. faecalis, K. pneumoniae, E.coli and P. aeruginosa; RBC lysis; secondary structure in mammalian and bacterial model membranes; and activity against cancer cell lines HepG2, CHO, and PC-3. Overall, the approach yielded a large family of active antimicrobial peptides with high solubility and low red blood cell toxicity. It also provides a framework for future designs and improved machine learning tools.
Competing Interests: Competing Interests All authors declare no competing interests.
(Copyright © 2024. Published by Elsevier Ltd.)
Databáze: MEDLINE
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