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.
The blockage of the hERG K+ channels is closely associated with lethal cardiac arrhythmia. The notorious ligand promiscuity of this channel earmarked hERG as one of the most important antitargets to be considered in early stages of drug development process. Herein we report on the development of an innovative and freely accessible web server for early identification of putative hERG blockers and non-blockers in chemical libraries. We have collected the largest publicly available curated hERG dataset of 5,984 compounds. We succeed in developing robust and externally predictive binary (CCR ≈0.8) and multiclass models (accuracy ≈0.7). These models are available as a web-service freely available for public at http://labmol.farma-cia.ufg.br/predherg/. Three following outcomes are available for the users: prediction by binary model, prediction by multi-class model, and the probability maps of atomic contribution. The Pred-hERG will be continuously updated and upgraded as new information became available.
Novel antibiotics are urgently needed to combat multidrug-resistant pathogens. Venoms represent previously untapped sources of novel drugs. Here we repurposed mastoparan-L, the toxic active principle derived from the venom of the wasp Vespula lewisii, into synthetic antimicrobials. We engineered within its N terminus a motif conserved among natural peptides with potent immunomodulatory and antimicrobial activities. The resulting peptide, mast-MO, adopted an α-helical structure as determined by NMR, exhibited increased antibacterial properties comparable to standard-of-care antibiotics both in vitro and in vivo, and potentiated the activity of different classes of antibiotics. Mechanism-of-action studies revealed that mast-MO targets bacteria by rapidly permeabilizing their outer membrane. In animal models, the peptide displayed direct antimicrobial activity, led to enhanced ability to attract leukocytes to the infection site, and was able to control inflammation. Permutation studies depleted the remaining toxicity of mast-MO toward human cells, yielding derivatives with antiinfective activity in animals. We demonstrate a rational design strategy for repurposing venoms into promising antimicrobials.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.