Development of a rotamer library for use in beta-peptide foldamer computational design

Quest for New Generation Biocompatible Materials: Tailoring β-Peptide Structure and Interactions via Synergy of Experiments and Modelling

Peptide-based self-assembly has been used to produce a wide range of nanostructures. While most of these systems involve self-assembly of α-peptides, more recently β-peptides have also been shown to undergo supramolecular self-assembly, and have been used to produce materials for applications in tissue engineering, cell culture and drug delivery. In order to engineer new materials with specific structure and function, theoretical molecular modelling can provide significant insights into the collective balance of non-covalent interactions that drive the self-assembly and determine the structure of the resultant supramolecular materials under different conditions. However, this approach has only recently become feasible for peptide-based self-assembled nanomaterials, particularly those that incorporate non α-amino acids. This perspective provides an overview of the challenges associated with computational modelling of the self-assembly of β-peptides and the recent success using a combination of experimental and computational techniques to provide insights into the self-assembly mechanisms and fully atomistic models of these new biocompatible materials.

Conformational landscapes of artificial peptides predicted by various force fields: are we ready to simulate β-amino acids?

With the introduction of artificial peptides as antimicrobial agents and organic catalysts, numerous efforts have been made to design foldamers with desirable structures and functions. Computational tools are a helpful proxy for revealing the dynamic structures at atomic resolution and understanding foldamer's complex structure-function relationships. However, the performance of conventional force fields in predicting the structures of artificial peptides has not been systematically evaluated. In this study, we critically assessed three popular force fields, AMBER ff14SB, CHARMM36m, and OPLS-AA/L, in predicting conformational propensities of a β-peptide foldamer at monomer and hexamer levels. Simulation results were compared to those obtained from quantum chemistry calculations and experimental data. We also utilised replica exchange molecular dynamics simulations to investigate the energy landscape of each force field and assess the similarities and differences between force fields. We compared different solvent systems in the AMBER ff14SB and CHARMM36m frameworks and confirmed the unanimous role of hydrogen bonds in shaping energy landscapes. We anticipate that our data will pave the way for further improvements to force fields and for understanding the role of solvents in peptide folding, crystallisation, and engineering.

Metal Cation-Binding Mechanisms of Q-Proline Peptoid Macrocycles in Solution

The rational design of foldable and functionalizable peptidomimetic scaffolds requires the concerted application of both computational and experimental methods. Recently, a new class of designed peptoid macrocycle incorporating spiroligomer proline mimics (Q-prolines) has been found to preorganize when bound by monovalent metal cations. To determine the solution-state structure of these cation-bound macrocycles, we employ a Bayesian inference method (BICePs) to reconcile enhanced-sampling molecular simulations with sparse ROESY correlations from experimental NMR studies to predict and design conformational and binding properties of macrocycles as functional scaffolds for peptidomimetics. Conformations predicted to be most populated in solution were then simulated in the presence of explicit cations to yield trajectories with observed binding events, revealing a highly preorganized all-trans amide conformation, whose formation is likely limited by the slow rate of cis/trans isomerization. Interestingly, this conformation differs from a racemic crystal structure solved in the absence of cation. Free energies of cation binding computed from distance-dependent potentials of mean force suggest Na⁺ has a higher affinity to the macrocycle than K⁺, with both cations binding much more strongly in acetonitrile than water. The simulated affinities are able to correctly rank the extent to which different macrocycle sequences exhibit preorganization in the presence of different metal cations and solvents, suggesting our approach is suitable for solution-state computational design.

De novo protein design, a retrospective

Proteins are molecular machines whose function depends on their ability to achieve complex folds with precisely defined structural and dynamic properties. The rational design of proteins from first-principles, or de novo, was once considered to be impossible, but today proteins with a variety of folds and functions have been realized. We review the evolution of the field from its earliest days, placing particular emphasis on how this endeavor has illuminated our understanding of the principles underlying the folding and function of natural proteins, and is informing the design of macromolecules with unprecedented structures and properties. An initial set of milestones in de novo protein design focused on the construction of sequences that folded in water and membranes to adopt folded conformations. The first proteins were designed from first-principles using very simple physical models. As computers became more powerful, the use of the rotamer approximation allowed one to discover amino acid sequences that stabilize the desired fold. As the crystallographic database of protein structures expanded in subsequent years, it became possible to construct proteins by assembling short backbone fragments that frequently recur in Nature. The second set of milestones in de novo design involves the discovery of complex functions. Proteins have been designed to bind a variety of metals, porphyrins, and other cofactors. The design of proteins that catalyze hydrolysis and oxygen-dependent reactions has progressed significantly. However, de novo design of catalysts for energetically demanding reactions, or even proteins that bind with high affinity and specificity to highly functionalized complex polar molecules remains an importnant challenge that is now being achieved. Finally, the protein design contributed significantly to our understanding of membrane protein folding and transport of ions across membranes. The area of membrane protein design, or more generally of biomimetic polymers that function in mixed or non-aqueous environments, is now becoming increasingly possible.

Peptide science: A "rule model" for new generations of peptidomimetics

Peptides have been heavily investigated for their biocompatible and bioactive properties. Though a wide array of functionalities can be introduced by varying the amino acid sequence or by structural constraints, properties such as proteolytic stability, catalytic activity, and phase behavior in solution are difficult or impossible to impart upon naturally occurring α-L-peptides. To this end, sequence-controlled peptidomimetics exhibit new folds, morphologies, and chemical modifications that create new structures and functions. The study of these new classes of polymers, especially α-peptoids, has been highly influenced by the analysis, computational, and design techniques developed for peptides. This review examines techniques to determine primary, secondary, and tertiary structure of peptides, and how they have been adapted to investigate peptoid structure. Computational models developed for peptides have been modified to predict the morphologies of peptoids and have increased in accuracy in recent years. The combination of in vitro and in silico techniques have led to secondary and tertiary structure design principles that mirror those for peptides. We then examine several important developments in peptoid applications inspired by peptides such as pharmaceuticals, catalysis, and protein-binding. A brief survey of alternative backbone structures and research investigating these peptidomimetics shows how the advancement of peptide and peptoid science has influenced the growth of numerous fields of study. As peptide, peptoid, and other peptidomimetic studies continue to advance, we will expect to see higher throughput structural analyses, greater computational accuracy and functionality, and wider application space that can improve human health, solve environmental challenges, and meet industrial needs. STATEMENT OF SIGNIFICANCE: Many historical, chemical, and functional relations draw a thread connecting peptides to their recent cognates, the "peptidomimetics". This review presents a comprehensive survey of this field by highlighting the width and relevance of these familial connections. In the first section, we examine the experimental and computational techniques originally developed for peptides and their morphing into a broader analytical and predictive toolbox. The second section presents an excursus of the structures and properties of prominent peptidomimetics, and how the expansion of the chemical and structural diversity has returned new exciting properties. The third section presents an overview of technological applications and new families of peptidomimetics. As the field grows, new compounds emerge with clear potential in medicine and advanced manufacturing.

Addressing Antimicrobial Resistance through New Medicinal and Synthetic Chemistry Strategies

Over the past century, a multitude of derivatives of structural scaffolds with established antimicrobial potential have been prepared and tested, and a variety of new scaffolds have emerged. The effectiveness of antibiotics, however, is in sharp decline because of the emergence of drug-resistant microorganisms. The prevalence of drug resistance, both in clinical and community settings, is a consequence of bacterial ingenuity in altering pathways and/or cell morphology, making it a persistent threat to human health. The fundamental ability of pathogens to survive in a multitude of habitats can be triggered by recognition of chemical signals that warn organisms of exposure to a potentially harmful environment. Host immune defenses, including reactive oxygen intermediates and antibacterial substances, are among the multitude of chemical signals that can subsequently trigger expression of phenotypes better adapted for survival in that hostile environment. Thus, resistance development appears to be unavoidable, which leads to the conclusion that developing an alternative perspective for treatment options is vital. This review will discuss emerging medicinal chemistry approaches for addressing the global multidrug resistance in the 21st century.

Identifying the Coiled-Coil Triple Helix Structure of β-Peptide Nanofibers at Atomic Resolution

Peptide self-assembly represents a powerful bottom-up approach to the fabrication of nanomaterials. β³-Peptides are non-natural peptides composed entirely of β-amino acids, which have an extra methylene in the backbone, and we reported fibers derived from the self-assembly of β³-peptides that adopt 14-helical structures. β³-Peptide assemblies represent a class of stable nanomaterials that can be used to generate bio- and magneto-responsive materials with proteolytic stability. However, the three-dimensional structure of many of these materials remains unknown. To develop structure-based criteria for the design of β³-peptide-based biomaterials with tailored function, we investigated the structure of a tri-β³-peptide nanoassembly by molecular dynamics simulations and X-ray fiber diffraction analysis. Diffraction data was collected from aligned fibrils formed by Ac-β³[LIA] in water and used to inform and validate the model structure. Models with 3-fold radial symmetry resulted in stable fibers with a triple-helical coiled-coil motif and measurable helical pitch and periodicity. The fiber models revealed a hydrophobic core and twist along the fiber axis arising from a maximization of contacts between hydrophobic groups of adjacent tripeptides on the solvent-exposed fiber surface. These atomic structures of macroscale fibers derived from β³-peptide-based materials provide valuable insight into the effects of the geometric placement of the side chains and the influence of solvent on the core fiber structure which is perpetuated in the superstructure morphology.

Rotamer Libraries for the High-Resolution Design of β-Amino Acid Foldamers

β-Amino acids offer attractive opportunities to develop biologically active peptidomimetics, either employed alone or in conjunction with natural α-amino acids. Owing to their potential for unique conformational preferences that deviate considerably from α-peptide geometries, β-amino acids greatly expand the possible chemistries and physical properties available to polyamide foldamers. Complete in silico support for designing new molecules incorporating non-natural amino acids typically requires representing their side-chain conformations as sets of discrete rotamers for model refinement and sequence optimization. Such rotamer libraries are key components of several state-of-the-art design frameworks. Here we report the development, incorporation in to the Rosetta macromolecular modeling suite, and validation of rotamer libraries for β3-amino acids.

β-Peptide bundles: Design. Build. Analyze. Biosynthesize

Peptides containing β-amino acids are unique non-natural polymers known to assemble into protein-like tertiary and quaternary structures. When composed solely of β-amino acids, the structures formed, defined assemblies of 14-helices called β-peptide bundles, fold cooperatively in water solvent into unique and discrete quaternary assemblies that are highly thermostable, bind complex substrates and metal ion cofactors, and, in certain cases, catalyze chemical reactions. In this Perspective, we recount the design and elaboration of β-peptide bundles and provide an outlook on recent, unexpected discoveries that could influence research on β-peptides and β-peptide bundles (and β-amino acid-containing proteins) for decades to come.

SDRL: a sequence-dependent protein side-chain rotamer library

Since the introduction of the first protein side-chain rotamer library (RL) almost half a century ago, RLs have been components of many programs and algorithms in structural bioinformatics. Based on the dependence of side-chain dihedral angles on the local backbone, three types of RLs have been identified: backbone-independent, secondary-structure-dependent and backbone-dependent. In all previous studies, the effect of sequence specificity on side-chain conformational preferences was neglected. In the effort to develop a new class of RLs, we considered that the side-chain conformation of the central residue in each triplet on a protein backbone depends on the sequence of the triplet; therefore, we developed a sequence-dependent rotamer library (SDRL). To accomplish this, 400 possible triplet sequences for 18 natural amino acids as the central residue, which corresponds to 7200 triplet sequences in total, were considered. Searching the set of 11 546 selected PDB entries for the 7200 triplet sequences resulted in 2 364 541 instances occurring for 18 amino acids. Our results show that Leu and Val experience minimal impact from the adjacent residues in adopting side-chain conformations. Cys, Ile, Trp, His, Asp, Met, Glu, Gln, Arg and Lys, on the other hand, adopt their side-chain conformations mostly based on the adjacent residues on the backbone. The remaining residue types were moderately dependent on the adjacent residues. Using the new library, side-chain repacking algorithms can find preferred conformations of each residue more easily than with other backbone-independent RLs.

Realistic sampling of amino acid geometries for a multipolar polarizable force field

The Quantum Chemical Topological Force Field (QCTFF) uses the machine learning method kriging to map atomic multipole moments to the coordinates of all atoms in the molecular system. It is important that kriging operates on relevant and realistic training sets of molecular geometries. Therefore, we sampled single amino acid geometries directly from protein crystal structures stored in the Protein Databank (PDB). This sampling enhances the conformational realism (in terms of dihedral angles) of the training geometries. However, these geometries can be fraught with inaccurate bond lengths and valence angles due to artefacts of the refinement process of the X-ray diffraction patterns, combined with experimentally invisible hydrogen atoms. This is why we developed a hybrid PDB/nonstationary normal modes (NM) sampling approach called PDB/NM. This method is superior over standard NM sampling, which captures only geometries optimized from the stationary points of single amino acids in the gas phase. Indeed, PDB/NM combines the sampling of relevant dihedral angles with chemically correct local geometries. Geometries sampled using PDB/NM were used to build kriging models for alanine and lysine, and their prediction accuracy was compared to models built from geometries sampled from three other sampling approaches. Bond length variation, as opposed to variation in dihedral angles, puts pressure on prediction accuracy, potentially lowering it. Hence, the larger coverage of dihedral angles of the PDB/NM method does not deteriorate the predictive accuracy of kriging models, compared to the NM sampling around local energetic minima used so far in the development of QCTFF.

Conformational properties of 1,4- and 1,5-substituted 1,2,3-triazole amino acids – building units for peptidic foldamers

Peptidic foldamers have recently emerged as a novel class of artificial oligomers with properties and structural diversity similar to that of natural peptides, but possessing additional interesting features granting them great potential for applications in fields from nanotechnology to pharmaceuticals. Among these, foldamers containing 1,4- and 1,5-substitued triazole amino acids are easily prepared via the Cu- and Ru-catalyzed click reactions and may offer increased side chain variation, but their structural capabilities have not yet been widely explored. We here describe a systematic analysis of the conformational space of the two most important basic units, the 1,4-substitued (4Tzl) and the 1,5-substitued (5Tzl) 1,2,3-triazole amino acids, using quantum chemical calculations and NMR spectroscopy. Possible conformations of the two triazoles were scanned and their potential minima were located using several theoretical approaches (B3LYP/6-311++G(2d,2p), ωB97X-D/6-311++G(2d,2p), M06-2X/6-311++G(2d,2p) and MP2/6-311++G(2d,2p)) in different solvents. BOC-protected versions of 4Tzl and 5Tzl were also prepared via one step transformations and analyzed by 2D NOESY NMR. Theoretical results show 9 conformers for 5Tzl derivatives with relative energies lying close to each other, which may lead to a great structural diversity. NMR analysis also indicates that conformers preferring turn, helix and zig-zag secondary structures may coexist in solution. In contrast, 4Tzl has a much lower number of conformers, only 4, and these lack strong intraresidual interactions. This is again supported by NMR suggesting the presence of both extended and bent conformers. The structural information provided on these building units could be employed in future design of triazole foldamers.

A rotamer library to enable modeling and design of peptoid foldamers

Peptoids are a family of synthetic oligomers composed of N-substituted glycine units. Along with other "foldamer" systems, peptoid oligomer sequences can be predictably designed to form a variety of stable secondary structures. It is not yet evident if foldamer design can be extended to reliably create tertiary structure features that mimic more complex biomolecular folds and functions. Computational modeling and prediction of peptoid conformations will likely play a critical role in enabling complex biomimetic designs. We introduce a computational approach to provide accurate conformational and energetic parameters for peptoid side chains needed for successful modeling and design. We find that peptoids can be described by a "rotamer" treatment, similar to that established for proteins, in which the peptoid side chains display rotational isomerism to populate discrete regions of the conformational landscape. Because of the insufficient number of solved peptoid structures, we have calculated the relative energies of side-chain conformational states to provide a backbone-dependent (BBD) rotamer library for a set of 54 different peptoid side chains. We evaluated two rotamer library development methods that employ quantum mechanics (QM) and/or molecular mechanics (MM) energy calculations to identify side-chain rotamers. We show by comparison to experimental peptoid structures that both methods provide an accurate prediction of peptoid side chain placements in folded peptoid oligomers and at protein interfaces. We have incorporated our peptoid rotamer libraries into ROSETTA, a molecular design package previously validated in the context of protein design and structure prediction.

Comparative mechanistic studies of brilacidin, daptomycin, and the antimicrobial peptide LL16

Brilacidin (PMX30063) has shown potent bactericidal activity against drug-resistant and -susceptible strains of multiple Gram-negative and Gram-positive pathogens. In this study, we demonstrate that brilacidin causes membrane depolarization in the Gram-positive bacterium Staphylococcus aureus, to an extent comparable to that caused by the lipopeptidic drug daptomycin. Transcriptional profiling of Staphylococcus aureus by deep sequencing shows that the global response to brilacidin treatment is well correlated to those of treatment with daptomycin and the cationic antimicrobial peptide LL37 and mostly indicates abrogation of cell wall and membrane functions. Furthermore, the upregulation of various chaperones and proteases by brilacidin and daptomycin indicates that cytoplasmic protein misfolding stress may be a contributor to the mechanism of action of these drugs. These stress responses were orchestrated mainly by three two-component systems, GraSR, VraSR, and NsaSR, which have been implicated in virulence and drug resistance against other clinically available antibiotics.

Computational screening and selection of cyclic peptide hairpin mimetics by molecular simulation and kinetic network models

Designing peptidomimetic compounds to have a preorganized structure in solution is highly nontrivial. To show how simulation-based approaches can help speed this process, we performed an extensive simulation study of designed cyclic peptide mimics of a β-hairpin from bacterial protein LapD involved in a protein-protein interaction (PPI) pertinent to bacterial biofilm formation. We used replica exchange molecular dynamics (REMD) simulation to screen 20 covalently cross-linked designs with varying stereochemistry and selected the most favorable of these for massively parallel simulation on Folding@home in explicit solvent. Markov state models (MSMs) built from the trajectory data reveal how subtle chemical modifications can have a significant effect on conformational populations, leading to the overall stabilization of the target structure. In particular, we identify a key steric interaction between a methyl substituent and a valine side chain that acts to allosterically shift population between native and near-native states, which could be exploited in future designs. Visualization of this mechanism is aided considerably by the tICA method, which identifies degrees of freedom most important in slow conformational transitions. The combination of quantitative detail and human comprehension provided by MSMs suggests such approaches will be increasingly useful for design.

Adding diverse noncanonical backbones to rosetta: enabling peptidomimetic design

Peptidomimetics are classes of molecules that mimic structural and functional attributes of polypeptides. Peptidomimetic oligomers can frequently be synthesized using efficient solid phase synthesis procedures similar to peptide synthesis. Conformationally ordered peptidomimetic oligomers are finding broad applications for molecular recognition and for inhibiting protein-protein interactions. One critical limitation is the limited set of design tools for identifying oligomer sequences that can adopt desired conformations. Here, we present expansions to the ROSETTA platform that enable structure prediction and design of five non-peptidic oligomer scaffolds (noncanonical backbones), oligooxopiperazines, oligo-peptoids, [Formula: see text]-peptides, hydrogen bond surrogate helices and oligosaccharides. This work is complementary to prior additions to model noncanonical protein side chains in ROSETTA. The main purpose of our manuscript is to give a detailed description to current and future developers of how each of these noncanonical backbones was implemented. Furthermore, we provide a general outline for implementation of new backbone types not discussed here. To illustrate the utility of this approach, we describe the first tests of the ROSETTA molecular mechanics energy function in the context of oligooxopiperazines, using quantum mechanical calculations as comparison points, scanning through backbone and side chain torsion angles for a model peptidomimetic. Finally, as an example of a novel design application, we describe the automated design of an oligooxopiperazine that inhibits the p53-MDM2 protein-protein interaction. For the general biological and bioengineering community, several noncanonical backbones have been incorporated into web applications that allow users to freely and rapidly test the presented protocols (http://rosie.rosettacommons.org). This work helps address the peptidomimetic community's need for an automated and expandable modeling tool for noncanonical backbones.

Serverification of molecular modeling applications: the Rosetta Online Server that Includes Everyone (ROSIE)

The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code's difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step 'serverification' protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org.

Secondary structure of short β-peptides as the chiral expression of monomeric building units: a rational and predictive model

Chirality of the monomeric residues controls and determines the prevalent folding of small oligopeptides (from di- to tetramers) composed of 2-aminocyclobutane-1-carboxylic acid (ACBA) derivatives with the same or different absolute and relative configuration. The cis-form of the monomeric ACBA gives rise to two conformers, namely, Z6 and Z8, while the trans-form manifests uniquely as an H8 structure. By combining these subunits in oligo- and polypeptides, their local structural preference remains, thus allowing the rational design of new short foldamers. A lego-type molecular architecture evolves; the overall look depends only on the conformational properties of the structural building units. A versatile and efficient method to predict the backbone folds of designed cyclobutane β-peptides is based on QM calculations. Predictions are corroborated by high-resolution NMR studies on selected stereoisomers, most of them being new foldamers that have been synthesized and characterized for the first time. Thus, the chiral expression of monomeric building units results in the defined secondary structures of small oligomers. As a result of this study, a new set of chirality controlled foldamers is provided to probe as biocompatible biopolymers.

Relationship between side-chain branching and stoichiometry in β(3)-peptide bundles

The stability and stoichiometry of β(3)-peptide bundles is influenced by side-chain identity. β(3)-peptides containing β(3)-homoleucine on one helical face assemble into octamers, whereas those containing β(3)-homovaline form tetramers. From a structural perspective, the side chains of β(3)-homoleucine and β(3)-homovaline differ in terms of both side-chain length and γ-carbon branching. To evaluate the extent to which these two parameters control β(3)-peptide bundle stoichiometry, we synthesized the β(3)-peptide Acid-3Y, which contains β(3)-homoisoleucine in place of β(3)-homoleucine or β(3)-homovaline. Acid-3Y assembles into a stable tetramer whose stability resembles that of the previously characterized Acid-VY tetramer. These results suggest that β(3)-peptide bundle stoichiometry is dominated by the presence or absence of γ-carbon branching on core side chains.

The power of hard-sphere models: explaining side-chain dihedral angle distributions of Thr and Val

The energy functions used to predict protein structures typically include both molecular-mechanics and knowledge-based terms. In contrast, our approach is to develop robust physics- and geometry-based methods. Here, we investigate to what extent simple hard-sphere models can be used to predict side-chain conformations. The distributions of the side-chain dihedral angle χ(1) of Val and Thr in proteins of known structure show distinctive features: Val side chains predominantly adopt χ(1) = 180°, whereas Thr side chains typically adopt χ(1) = 60° and 300° (i.e., χ(1) = ±60° or g- and g(+) configurations). Several hypotheses have been proposed to explain these differences, including interresidue steric clashes and hydrogen-bonding interactions. In contrast, we show that the observed side-chain dihedral angle distributions for both Val and Thr can be explained using only local steric interactions in a dipeptide mimetic. Our results emphasize the power of simple physical approaches and their importance for future advances in protein engineering and design.

Antibacterial mechanism of action of arylamide foldamers

Small arylamide foldamers designed to mimic the amphiphilic nature of antimicrobial peptides (AMPs) have shown potent bactericidal activity against both Gram-negative and Gram-positive strains without many of the drawbacks of natural AMPs. These foldamers were shown to cause large changes in the permeability of the outer membrane of Escherichia coli. They cause more limited permeabilization of the inner membrane which reaches critical levels corresponding with the time required to bring about bacterial cell death. Transcriptional profiling of E. coli treated with sublethal concentrations of the arylamides showed induction of genes related to membrane and oxidative stresses, with some overlap with the effects observed for polymyxin B. Protein secretion into the periplasm and the outer membrane is also compromised, possibly contributing to the lethality of the arylamide compounds. The induction of membrane stress response regulons such as rcs coupled with morphological changes at the membrane observed by electron microscopy suggests that the activity of the arylamides at the membrane represents a significant contribution to their mechanism of action.

Computational design of a self-assembling β-peptide oligomer

The first computationally designed self-assembling oligomer consisting of exclusively β-amino acids (βAAs) is presented. The packing of a β-3(14) helix into coiled-coils of varying stoichiometries as a function of amino acid sequence is examined. β-Peptides with hVal repeating every third residue in the sequence appeared to have a strong propensity to pack into hexameric bundles. The designed sequence was synthesized and characterized with CD spectroscopy, NMR, and analytical ultracentrifugation, suggesting that the peptide adopts a well-folded hexameric structure.