Conformational preferences of peptide-peptoid hybrid oligomers

The emerging role of computational design in peptide macrocycle drug discovery

Drug discovery is a laborious process with rising cost per new drug. Peptide macrocycles are promising therapeutics, though conformational flexibility can reduce target affinity and specificity. Recent computational advancements address this problem by enabling rational design of rigidly folded peptide macrocycles.

AREAS COVERED

This review summarizes currently approved peptide macrocycle therapeutics and discusses advantages of mesoscale drugs over small molecules or protein therapeutics. It describes the history, rationale, and state of the art of computational tools, such as Rosetta, that allow the design of rigidly structured peptide macrocycles. The emerging pipeline for designing peptide macrocycle drugs is described, including current challenges in designing permeable molecules that can emulate the chameleonic behavior of natural macrocycles. Prospects for reducing computational cost and improving accuracy with emerging computational technologies are also discussed.

EXPERT OPINION

To embrace computational design of peptide macrocycle drugs, we must shift current attitudes regarding the role of computation in drug discovery, and move beyond Lipinski's rules. This technology has the potential to shift failures to earlier in silico stages of the drug discovery process, improving success rates in costly clinical trials. Given the available tools, now is the time for drug developers to incorporate peptide macrocycle design into drug discovery pipelines.

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.

Unconstrained peptoid tetramer exhibits a predominant conformation in aqueous solution

Conformational control in peptoids, N-substituted glycines, is crucial for the design and synthesis of biologically-active compounds and atomically-defined nanomaterials. While there are a growing number of structural studies in solution, most have been performed with conformationally-constrained short sequences (e.g., sterically-hindered sidechains or macrocyclization). Thus, the inherent degree of heterogeneity of unconstrained peptoids in solution remains largely unstudied. Here, we explored the folding landscape of a series of simple peptoid tetramers in aqueous solution by NMR spectroscopy. By incorporating specific ¹³ C-probes into the backbone using bromoacetic acid-2-¹³ C as a submonomer, we developed a new technique for sequential backbone assignment of peptoids based on the 1,n-Adequate pulse sequence. Unexpectedly, two of the tetramers, containing an N-(2-aminoethyl)glycine residue (Nae), had preferred conformations. NMR and molecular dynamics studies on one of the tetramers showed that the preferred conformer (52%) had a trans-cis-trans configuration about the three amide bonds. Moreover, >80% of the ensemble contained a cis amide bond at the central amide. The backbone dihedral angles observed fall directly within the expected minima in the peptoid Ramachandran plot. Analysis of this compound against similar peptoid analogs suggests that the commonly used Nae monomer plays a key role in the stabilization of peptoid structure via a side-chain-to-main-chain interaction. This discovery may offer a simple, synthetically high-yielding approach to control peptoid structure, and suggests that peptoids have strong intrinsic conformational preferences in solution. These findings should facilitate the predictive design of folded peptoid structures, and accelerate application in areas ranging from drug discovery to biomimetic nanoscience.

Self-assembly of bioactive peptides, peptide conjugates, and peptide mimetic materials

Molecular self-assembly is a multi-disciplinary field of research, with potential chemical and biological applications. One of the main driving forces of self-assembly is molecular amphiphilicity, which can drive formation of complex and stable nanostructures. Self-assembling peptide and peptide conjugates have attracted great attention due to their biocompatibility, biodegradability and biofunctionality. Understanding assembly enables the better design of peptide amphiphiles which may form useful and functional nanostructures. This review covers self-assembly of amphiphilic peptides and peptide mimetic materials, as well as their potential applications.

Protocols for Molecular Modeling with Rosetta3 and RosettaScripts

Previously, we published an article providing an overview of the Rosetta suite of biomacromolecular modeling software and a series of step-by-step tutorials [Kaufmann, K. W., et al. (2010) Biochemistry 49, 2987–2998]. The overwhelming positive response to this publication we received motivates us to here share the next iteration of these tutorials that feature de novo folding, comparative modeling, loop construction, protein docking, small molecule docking, and protein design. This updated and expanded set of tutorials is needed, as since 2010 Rosetta has been fully redesigned into an object-oriented protein modeling program Rosetta3. Notable improvements include a substantially improved energy function, an XML-like language termed “RosettaScripts” for flexibly specifying modeling task, new analysis tools, the addition of the TopologyBroker to control conformational sampling, and support for multiple templates in comparative modeling. Rosetta’s ability to model systems with symmetric proteins, membrane proteins, noncanonical amino acids, and RNA has also been greatly expanded and improved.

Peptide to Peptoid Substitutions Increase Cell Permeability in Cyclic Hexapeptides

The effect of peptide-to-peptoid substitutions on the passive membrane permeability of an N-methylated cyclic hexapeptide is examined. In general, substitutions maintained permeability but increased conformational heterogeneity. Diversification with nonproteinogenic side chains increased permeability up to 3-fold. Additionally, the conformational impact of peptoid substitutions within a β-turn are explored. Based on these results, the strategic incorporation of peptoid residues into cyclic peptides can maintain or improve cell permeability, while increasing access to diverse side-chain functionality.

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.