The increasing rate in antibiotic-resistant bacterial strains has become an imperative health issue. Thus, pharmaceutical industries have focussed their efforts to find new potent, non-toxic compounds to treat bacterial infections. Antimicrobial peptides (AMPs) are promising candidates in the fight against antibiotic-resistant pathogens due to their low toxicity, broad range of activity and unspecific mechanism of action. In this context, bioinformatics' strategies can inspire the design of new peptide leads with enhanced activity. Here, we describe an artificial neural network approach, based on the AMP's physicochemical characteristics, that is able not only to identify active peptides but also to assess its antimicrobial potency. The physicochemical properties considered are directly derived from the peptide sequence and comprise a complete set of parameters that accurately describe AMPs. Most interesting, the results obtained dovetail with a model for the AMP's mechanism of action that takes into account new concepts such as peptide aggregation. Moreover, this classification system displays high accuracy and is well correlated with the experimentally reported data. All together, these results suggest that the physicochemical properties of AMPs determine its action. In addition, we conclude that sequence derived parameters are enough to characterize antimicrobial peptides.

The ribonuclease A superfamily is a vertebrate-specific family of proteins that encompasses eight functional members in humans. The proteins are secreted by diverse innate immune cells, from blood cells to epithelial cells and their levels in our body fluids correlate with infection and inflammation processes. Recent studies ascribe a prominent role to secretory RNases in the extracellular space. Extracellular RNases endowed with immuno-modulatory and antimicrobial properties can participate in a wide variety of host defense tasks, from performing cellular housekeeping to maintaining body fluid sterility. Their expression and secretion are induced in response to a variety of injury stimuli. The secreted proteins can target damaged cells and facilitate their removal from the focus of infection or inflammation. Following tissue damage, RNases can participate in clearing RNA from cellular debris or work as signaling molecules to regulate the host response and contribute to tissue remodeling and repair. We provide here an overall perspective on the current knowledge of human RNases’ biological properties and their role in health and disease. The review also includes a brief description of other vertebrate family members and unrelated extracellular RNases that share common mechanisms of action. A better knowledge of RNase mechanism of actions and an understanding of their physiological roles should facilitate the development of novel therapeutics.

Summary: AMPA is a web application for assessing the antimicrobial domains of proteins, with a focus on the design on new antimicrobial drugs. The application provides fast discovery of antimicrobial patterns in proteins that can be used to develop new peptide-based drugs against pathogens. Results are shown in a user-friendly graphical interface and can be downloaded as raw data for later examination. Availability: AMPA is freely available on the web at http://tcoffee.crg.cat/apps/ampa. The source code is also available in the web. Contact:marc.torrent@upf.edu; david.andreu@upf.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Antimicrobial proteins and peptides (AMPs) are important effectors of the innate immune system that play a vital role in the prevention of infections. Recent advances have highlighted the similarity between AMPs and amyloid proteins. Using the Eosinophil Cationic Protein as a model, we have rationalized the structure-activity relationships between amyloid aggregation and antimicrobial activity. Our results show how protein aggregation can induce bacteria agglutination and cell death. Using confocal and total internal reflection fluorescence microscopy we have tracked the formation in situ of protein amyloid-like aggregates at the bacteria surface and on membrane models. In both cases, fibrillar aggregates able to bind to amyloid diagnostic dyes were detected. Additionally, a single point mutation (Ile13 to Ala) can suppress the protein amyloid behavior, abolishing the agglutinating activity and impairing the antimicrobial action. The mutant is also defective in triggering both leakage and lipid vesicle aggregation. We conclude that ECP aggregation at the bacterial surface is essential for its cytotoxicity. Hence, we propose here a new prospective biological function for amyloid-like aggregates with potential biological relevance. Microbial infections are reported among the worst human diseases and cause millions of deaths per year over the world. Antibiotics are used to treat infections and have saved more lives than any other drug in human history. However, due to extended use, many strains are becoming refractive to common antibiotics. In this light, new promising compounds, like antimicrobial proteins and peptides (AMPs) are being investigated. Some AMPs also show agglutinating activity; this is the ability to clump bacteria after treatment. This feature is particularly appealing because agglutinating peptides could be used to keep bacteria to the infection focus, helping microbe clearance by host immune cells. In this study, we propose a novel mechanism to explain agglutinating activity at a molecular level using Eosinophil Cationic Protein. We show that the agglutinating mechanism is driven by the protein amyloid-like aggregation at the bacteria cell surface. Accordingly, elimination of the amyloid behavior abolishes both the agglutinating and the antimicrobial activities. This study provides a new concept on how Nature could exploit amyloid-like aggregates to fight bacterial infections. Moreover, these results could also add new insights in understanding the relation between infection and inflammation with dementia and amyloid-related diseases like Alzheimer.