Peptide cyclization and cyclodimerization by Cu(I)-mediated azide-alkyne cycloaddition.

Head-to-tail cyclodimerization of resin-bound oligopeptides bearing azide and alkyne groups occurs readily by 1,3-dipolar cycloaddition upon treatment with Cu(I). The process was found to be independent of peptide sequence, sensitive to the proximity of the alkyne to the resin, sensitive to solvent composition, facile for alpha- and beta-peptides but not for gamma-peptides, and inhibited by the inclusion of tertiary amide linkages. Peptides shorter than hexamers were predominantly converted to cyclic monomers. Oligoglycine and oligo(beta-alanine) chains underwent oligomerization by 1,3-dipolar cycloaddition in the absence of a copper catalyst. These results suggest that cyclodimerization depends on the ability of the azido-alkyne peptide to form in-frame hydrogen bonds between chains in order to place the reacting groups in close proximity and lower the entropic penalty for dimerization. The properties of the resin and solvent are crucial, giving rise to a productive balance between swelling and interstrand H-bonding. These findings allow for the design of optimal substrates for triazole-forming ring closure and for the course of the reaction to be controlled by the choice of conditions.

Infection control by antibody disruption of bacterial quorum sensing signaling.

Quorum sensing (QS) is the process through which bacteria communicate utilizing small diffusible molecules termed autoinducers. It has been demonstrated that QS controls a plethora of microbial processes including the expression of virulence factors. Here we report an immunopharmacotherapeutic approach for the attenuation of QS in the Gram-positive human pathogen Staphylococcus aureus. An anti-autoinducer monoclonal antibody, AP4-24H11, was elicited against a rationally designed hapten, and efficiently inhibited QS in vitro through the sequestration of the autoinducing peptide (AIP)-4 produced by S. aureus RN4850. Importantly, AP4-24H11 suppressed S. aureus pathogenicity in an abscess formation mouse model in vivo and provided complete protection against a lethal S. aureus challenge. These findings provide a strong foundation for further investigations of immunopharmacotherapy for the treatment of bacterial infections in which QS controls the expression of virulence factors.

Design of a directed molecular network.

An ability to rationally design complex networks from the bottom up can offer valuable quantitative model systems for use in gaining a deeper appreciation for the principles governing the self-organization and functional characteristics of complex systems. We report herein the de novo design, graph prediction, experimental analysis, and characterization of simple self-organized, nonlinear molecular networks. Our approach makes use of the sequence-dependent auto- and cross-catalytic functional characteristics of template-directed peptide fragment condensation reactions in neutral aqueous solutions. Starting with an array of 81 sequence similar 32-residue coiled-coil peptides, we estimated the relative stability difference between all plausible A(2)B-type coiled-coil ensembles and used this information to predict the auto- and cross-catalysis pathways and the resulting plausible network motif and connectivities. Similar to most complex systems, the generated graph displays clustered nodes with an overall hierarchical architecture. To test the validity of the design principles used, nine nodes composing a main segment of the graph were experimentally analyzed for their capacity in establishing the predicted network connectivity. The resulting self-organized chemical network is shown to display 25 directed edges in good agreement with the graph analysis estimations. Moreover, we show that by varying the system parameters (presence or absence of certain substrates or templates), its operating network motif can be altered, even to the extremes of turning pathways on or off. We suggest that this approach can be expanded for the construction of large-scale networks, offering a means to study and to understand better the emergent, collective behaviors of networks.