In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Name
s41467-018-03746-3.pdf
Description
Published version
Size
1.59 MB
Format
Adobe PDF
Checksum (MD5)
22f5db72ec76f5fe61ed63688759a568
Author(s)
Porto, William F
Irazazabal, Luz
Alves, Eliane SF
Ribeiro, Suzana M
Matos, Carolina O
Pires, Állan S
Fensterseifer, Isabel CM
Miranda, Vivian J
Haney, Evan F
Humblot, Vincent
Date Issued
2018
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Version
Final published version
Abstract
© 2018 The Author(s). Plants are extensively used in traditional medicine, and several plant antimicrobial peptides have been described as potential alternatives to conventional antibiotics. However, after more than four decades of research no plant antimicrobial peptide is currently used for treating bacterial infections, due to their length, post-translational modifications or high dose requirement for a therapeutic effect. Here we report the design of antimicrobial peptides derived from a guava glycine-rich peptide using a genetic algorithm. This approach yields guavanin peptides, arginine-rich α-helical peptides that possess an unusual hydrophobic counterpart mainly composed of tyrosine residues. Guavanin 2 is characterized as a prototype peptide in terms of structure and activity. Nuclear magnetic resonance analysis indicates that the peptide adopts an α-helical structure in hydrophobic environments. Guavanin 2 is bactericidal at low concentrations, causing membrane disruption and triggering hyperpolarization. This computational approach for the exploration of natural products could be used to design effective peptide antibiotics.
MIT Department
Massachusetts Institute of Technology. Synthetic Biology Center
Massachusetts Institute of Technology. Center for Microbiome Informatics and Therapeutics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/S41467-018-03746-3
