Targeting RNA with cysteine-constrained peptides

RNA-Binding Macrocyclic Peptides

Being able to effectively target RNA with potent ligands will open up a large number of potential therapeutic options. The knowledge on how to achieve this is ever expanding but an important question that remains open is what chemical matter is suitable to achieve this goal. The high flexibility of an RNA as well as its more limited chemical diversity and featureless binding sites can be difficult to target selectively but can be addressed by well-designed cyclic peptides. In this review we will provide an overview of reported cyclic peptide ligands for therapeutically relevant RNA targets and discuss the methods used to discover them. We will also provide critical insights into the properties required for potent and selective interaction and suggestions on how to assess these parameters. The use of cyclic peptides to target RNA is still in its infancy but the lessons learned from past examples can be adopted for the development of novel potent and selective ligands.

Photoinduced reconfiguration to control the protein-binding affinity of azobenzene-cyclized peptides

The impact of next-generation biorecognition elements (ligands) will be determined by the ability to remotely control their binding activity for a target biomolecule in complex environments. Compared to conventional mechanisms for regulating binding affinity (pH, ionic strength, or chaotropic agents), light provides higher accuracy and rapidity, and is particularly suited for labile targets. In this study, we demonstrate a general method to develop azobenzene-cyclized peptide ligands with light-controlled affinity for target proteins. Light triggers a cis/trans isomerization of the azobenzene, which results in a major structural rearrangement of the cyclic peptide from a non-binding to a binding configuration. Critical to this goal are the ability to achieve efficient photo-isomerization under low light dosage and the temporal stability of both cis and trans isomers. We demonstrated our method by designing photo-switchable peptides targeting vascular cell adhesion marker 1 (VCAM1), a cell marker implicated in stem cell function. Starting from a known VCAM1-binding linear peptide, an ensemble of azobenzene-cyclized variants with selective light-controlled binding were identified by combining in silico design with experimental characterization via spectroscopy and surface plasmon resonance. Variant cycloAZOB[G-VHAKQHRN-K] featured rapid, light-controlled binding of VCAM1 (KD,trans/KD,cis ∼ 130). Biotin-cycloAZOB[G-VHAKQHRN-K] was utilized to label brain microvascular endothelial cells (BMECs), showing co-localization with anti-VCAM1 antibodies in cis configuration and negligible binding in trans configuration.

Computational Opportunities and Challenges in Finding Cyclic Peptide Modulators of Protein-Protein Interactions

Peptide cyclization can improve stability, conformational constraint, and compactness. However, apart from beta-turn structures, which are well incorporated into cyclic peptides (CPs), many primary peptide structures and functions are markedly altered by cyclization. Accordingly, to mimic linear peptide interfaces with cyclic peptides, it can be beneficial to screen combinatorial cyclic peptide libraries. Computational methods have been developed to screen CPs, but face a number of challenges. Here, we review methods to develop in silico computational libraries, and the potential for screening naturally occurring libraries of CPs. The simplest and most rapid computational pharmacophore methods that estimate peptide three-dimensional structures to be screened versus targets are relatively easy to implement, and while the constraint on structure imposed by cyclization makes them more effective than the same approaches with linear peptides, there are a large number of limiting assumptions. In contrast, full molecular dynamics simulations of cyclic peptide structures not only are costly to implement, but also require careful attention to interpretation, so that not only is the computation time rate limiting, but the interpretation time is also rate limiting due to the analysis of the typically complex underlying conformational space of CPs. A challenge for the field of computational cyclic peptide screening is to bridge this gap effectively. Natural compound libraries of short cyclic peptides, and short cyclized regions of proteins, encoded in the genomes of many organisms present a potential treasure trove of novel functionality which may be screened via combined computational and experimental screening approaches.

Computational approaches to developing short cyclic peptide modulators of protein-protein interactions

Cyclic peptides are a promising class of bioactive molecules potentially capable of modulating "difficult" targets, such as protein-protein interactions. Cyclic peptides have long been used as therapeutics derived from natural product derivatives, but remain an underexplored class of compounds from the perspective of rational drug design, possibly due to the known weaknesses of peptide drugs in general. While cyclic peptides are non"druglike" by the accepted empirical rules, their unique structure may lend itself to both membrane permeability and proteolytic resistance-the main barriers to oral delivery. The constrained shape of cyclic peptides also lends itself better to virtual screening approaches, and new tools and successes in this area have been recently noted. An increasing number of strategies are available, both to generate and screen cyclic peptide libraries, and best practises and current successes are described within. This chapter will describe various computational strategies for virtual screening cyclic peptides, along with known implementations and applications. We will explore the generation and screening of diverse combinatorial virtual libraries, incorporating a range of cyclization strategies and structural modifications. More advanced approaches covered include evolutionary algorithms designed to aid in screening large structural libraries, machine learning approaches, and harnessing bioinformatics resources to bias cyclic peptide virtual libraries towards known bioactive structures.

The interactions and recognition of cyclic peptide mimetics of Tat with HIV-1 TAR RNA: a molecular dynamics simulation study

The interaction of HIV-1 trans-activator protein Tat with its cognate trans-activation response element (TAR) RNA is critical for viral transcription and replication. Therefore, it has long been considered as an attractive target for the development of antiviral compounds. Recently, the conformationally constrained cyclic peptide mimetics of Tat have been tested to be a promising family of lead peptides. Here, we focused on two representative cyclic peptides termed as L-22 and KP-Z-41, both of which exhibit excellent inhibitory potency against Tat and TAR interaction. By means of molecular dynamics simulations, we obtained a detailed picture of the interactions between them and HIV-1 TAR RNA. In results, it is found that the binding modes of the two cyclic peptides to TAR RNA are almost identical at or near the bulge regions, whereas the binding interfaces at the apical loop exhibit large conformational heterogeneity. In addition, it is revealed that electrostatic interaction energy contributes much more to KP-Z-41 complex formation than to L-22 complex, which is the main source of energy that results in a higher binding affinity of KP-Z-41 over-22 for TAR RNA. Furthermore, we identified a conserved motif RRK (Arg-Arg-Lys) that is shown to be essential for specific binding of this class of cyclic peptides to TAR RNA. This work can provide a useful insight into the design and modification of cyclic peptide inhibitors targeting the association of HIV-1 Tat and TAR RNA.

CycloPs: generating virtual libraries of cyclized and constrained peptides including nonnatural amino acids

We introduce CycloPs, software for the generation of virtual libraries of constrained peptides including natural and nonnatural commercially available amino acids. The software is written in the cross-platform Python programming language, and features include generating virtual libraries in one-dimensional SMILES and three-dimensional SDF formats, suitable for virtual screening. The stand-alone software is capable of filtering the virtual libraries using empirical measurements, including peptide synthesizability by standard peptide synthesis techniques, stability, and the druglike properties of the peptide. The software and accompanying Web interface is designed to enable the rapid generation of large, structurally diverse, synthesizable virtual libraries of constrained peptides quickly and conveniently, for use in virtual screening experiments. The stand-alone software, and the Web interface for evaluating these empirical properties of a single peptide, are available at http://bioware.ucd.ie .

Essential structural requirements for specific recognition of HIV TAR RNA by peptide mimetics of Tat protein

The pharmacological disruption of the interaction between the HIV Tat protein and its cognate transactivation response RNA (TAR) would generate novel anti-viral drugs with a low susceptibility to drug resistance, but efforts to discover ligands with sufficient potency to warrant pharmaceutical development have been unsuccessful. We have previously described a family of structurally constrained β-hairpin peptides that potently inhibits viral growth in HIV-infected cells. The nuclear magnetic resonance (NMR) structure of an inhibitory complex revealed that the peptide makes intimate contacts with the 3-nt bulge and the upper helix of the RNA hairpin, but that a single residue contacts the apical loop where recruitment of the essential cellular co-factor cyclin T₁ occurs. Attempting to extend the peptide to form more interactions with the RNA loop, we examined a library of longer peptides and achieved >6-fold improvement in affinity. The structure of TAR bound to one of the extended peptides reveals that the peptide slides down the major groove of the RNA, relative to our design, in order to maintain critical interactions with TAR. These conserved contacts involve three amino acid side chains and identify critical interaction points required for potent and specific binding to TAR RNA. They constitute a template of essential interactions required for inhibition of this RNA.