In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design

• DOI: 10.1038/s41467-018-03746-3
• Publication Date: 2018-04-11T14:11:11Z
• Authors: William F. Porto; Luz Irazazabal; Eliane S. F. Alves; Suzana M. Ribeiro; Carolina O. Matos; Állan S. Pires; Isabel C. M. Fens...; Vivian J. Miranda; Evan F. Haney; Vincent Humblot; Marcelo D. T. Torres; Robert E. W. Hancock; Luciano M. Liao; Ali Ladram; Timothy K. Lu; Cesar de la Fuent...; Octavio L. Franco
• Keywords: Models, Molecular; Science; Article; Protein Structure, Secondary; Mice; Structure-Activity Relationship; 03 medical and health sciences; [CHIM] Chemical Sciences; Escherichia coli; [CHIM]Chemical Sciences; Animals; Combinatorial Chemistry Techniques; Pseudomonas Infections; Amino Acid Sequence; Nuclear Magnetic Resonance, Biomolecular; Plant Proteins; Skin; 0303 health sciences; Psidium; Q; Cell Membrane; Anti-Bacterial Agents; 3. Good health; Drug Design; Pseudomonas aeruginosa; Hydrophobic and Hydrophilic Interactions; Algorithms; Antimicrobial Cationic Peptides

AbstractPlants 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.