Molecular Design and Genetic Optimization of Antimicrobial Peptides Containing Unnatural Amino Acids Against Antibiotic-Resistant Bacterial Infections

Antimicrobial peptides (AMPs) have been the focus of intense research towards the finding of a viable alternative to current small-molecule antibiotics, owing to their commonly observed and naturally occurring resistance against pathogens. However, natural peptides have many problems such as low bioavailability and high allergenicity that largely limit the clinical applications of AMPs. In the present study, an integrative protocol that combined chemoinformatics modeling, molecular dynamics simulations, and in vitro susceptibility test was described to design AMPs containing unnatural amino acids (AMP-UAAs). To fulfill this, a large panel of synthetic AMPs with determined activity was collected and used to perform quantitative structure-activity relationship (QSAR) modeling. The obtained QSAR predictors were then employed to direct genetic algorithm (GA)-based optimization of AMP-UAA population, to which a number of commercially available, structurally diverse unnatural amino acids were introduced during the optimization process. Subsequently, several designed AMP-UAAs were confirmed to have high antibacterial potency against two antibiotic-resistant strains, i.e. multidrug-resistant Pseudomonas aeruginosa (MDRPA) and methicillin-resistant Staphylococcus aureus (MRSA), with minimum inhibitory concentration (MIC)< 10 mu g/ml. Structural dynamics characterizations revealed that the most potent AMPUAA peptide is an amphipathic helix that can spontaneously embed into an artificial lipid bilayer and exhibits a strong destructuring tendency associated with the embedding process. (C) 2016 Wiley Periodicals, Inc. Biopolymers