Characterization of an RNase with two catalytic centers. Human RNase6 catalytic and phosphate-binding site arrangement favors the endonuclease cleavage of polymeric substrates.

BACKGROUND: Human RNase6 is a small cationic antimicrobial protein that belongs to the vertebrate RNaseA superfamily. All members share a common catalytic mechanism, which involves a conserved catalytic triad, constituted by two histidines and a lysine (His15/His122/Lys38 in RNase6 corresponding to His12/His119/Lys41 in RNaseA). Recently, our first crystal structure of human RNase6 identified an additional His pair (His36/His39) and suggested the presence of a secondary active site. METHODS: In this work we have explored RNase6 and RNaseA subsite architecture by X-ray crystallography, site-directed mutagenesis and kinetic characterization. RESULTS: The analysis of two novel crystal structures of RNase6 in complex with phosphate anions at atomic resolution locates a total of nine binding sites and reveals the contribution of Lys87 to phosphate-binding at the secondary active center. Contribution of the second catalytic triad residues to the enzyme activity is confirmed by mutagenesis. RNase6 catalytic site architecture has been compared with an RNaseA engineered variant where a phosphate-binding subsite is converted into a secondary catalytic center (RNaseA-K7H/R10H). CONCLUSIONS: We have identified the residues that participate in RNase6 second catalytic triad (His36/His39/Lys87) and secondary phosphate-binding sites. To note, residues His39 and Lys87 are unique within higher primates. The RNaseA/RNase6 side-by-side comparison correlates the presence of a dual active site in RNase6 with a favored endonuclease-type cleavage pattern. GENERAL SIGNIFICANCE: An RNase dual catalytic and extended binding site arrangement facilitates the cleavage of polymeric substrates. This is the first report of the presence of two catalytic centers in a single monomer within the RNaseA superfamily.

Connecting peptide physicochemical and antimicrobial properties by a rational prediction model.

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.

A theoretical approach to spot active regions in antimicrobial proteins.

BACKGROUND: Much effort goes into identifying new antimicrobial compounds able to evade the increasing resistance of microorganisms to antibiotics. One strategy relies on antimicrobial peptides, either derived from fragments released by proteolytic cleavage of proteins or designed from known antimicrobial protein regions. RESULTS: To identify these antimicrobial determinants, we developed a theoretical approach that predicts antimicrobial proteins from their amino acid sequence in addition to determining their antimicrobial regions. A bactericidal propensity index has been calculated for each amino acid, using the experimental data reported from a high-throughput screening assay as reference. Scanning profiles were performed for protein sequences and potentially active stretches were identified by the best selected threshold parameters. The method was corroborated against positive and negative datasets. This successful approach means that we can spot active sequences previously reported in the literature from experimental data for most of the antimicrobial proteins examined. CONCLUSION: The method presented can correctly identify antimicrobial proteins with an accuracy of 85% and a sensitivity of 90%. The method can also predict their key active regions, making this a tool for the design of new antimicrobial drugs.

Bactericidal and membrane disruption activities of the eosinophil cationic protein are largely retained in an N-terminal fragment.

ECP (eosinophil cationic protein) is an eosinophil secretion protein with antipathogen activities involved in the host immune defence system. The bactericidal capacity of ECP relies on its action on both the plasma membrane and the bacterial wall. In a search for the structural determinants of ECP antimicrobial activity, we have identified an N-terminal domain (residues 1-45) that retains most of ECP's membrane-destabilizing and antimicrobial activities. Two sections of this domain, ECP-(1-19) and ECP-(24-45), have also been evaluated. All three peptides bind and partially insert into lipid bilayers, inducing aggregation of lipid vesicles and leakage of their aqueous content. In such an environment, the peptides undergo conformational change, significantly increasing their alpha-helix content. The bactericidal activity of the three peptides against Escherichia coli and Staphylococcus aureus has been assessed at both the cytoplasmic membrane and the bacterial envelope levels. ECP-(1-45) and ECP-(24-45) partially retain the native proteins ability to bind LPS (lipopolysaccharides), and electron microscopy reveals cell damage by both peptides. Interestingly, in the E. coli cells agglutination activity of ECP is only retained by the longest segment ECP-(1-45). Comparative results suggest a task distribution, whereby residues 1-19 would contribute to membrane association and destabilization, while the 24-45 region would be essential for bactericidal action. Results also indicate that ECP cytotoxicity is not uniquely dependant on its membrane disruption capacity, and that specific interactions at the bacteria wall are also involved.