Mixed-chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to date, but there is currently no way to systematically search the structural space spanned by such compounds. Natural proteins do not provide a useful guide: Peptide macrocycles lack regular secondary structures and hydrophobic cores, and can contain local structures not accessible with L-amino acids. Here, we enumerate the stable structures that can be adopted by macrocyclic peptides composed of L- and D-amino acids by near-exhaustive backbone sampling followed by sequence design and energy landscape calculations. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. Nuclear magnetic resonance structures of 9 of 12 designed 7- to 10-residue macrocycles, and three 11- to 14-residue bicyclic designs, are close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide macrocycles and vastly increase the available starting scaffolds for both rational drug design and library selection methods.

Many of today's drug discovery programs utilize high-throughput screening methods that rely on quick evaluations of protein activity to rank potential chemical leads. By monitoring biologically relevant protein-ligand interactions, NMR can provide a means to validate these discovery leads and to optimize the drug discovery process. NMR-based screens typically use a change in chemical shift or linewidth to detect a protein-ligand interaction. However, the relatively low throughput of current NMR screens and their high demand on sample requirements generally makes it impractical to collect complete binding curves to measure the affinity for each compound in a large and diverse chemical library. As a result, NMR ligand screens are typically limited to identifying candidates that bind to a protein and do not give any estimate of the binding affinity. To address this issue, a methodology has been developed to rank binding affinities for ligands based on NMR-based screens that use 1D 1 H NMR line-broadening experiments. This method was demonstrated by using it to estimate the dissociation equilibrium constants for twelve ligands with the protein human serum albumin (HSA). The results were found to give good agreement with previous affinities that have been reported for these same ligands with HSA.

MicroRNAs (miRNAs) help orchestrate cellular growth and survival through post-transcriptional mechanisms. The dysregulation of miRNA biogenesis can lead to cellular growth defects, chemotherapeutic resistance and plays a direct role in the development of many chronic diseases. Among these RNAs, miR-21 is consistently overexpressed in most human cancers leading to the down regulation of key tumor suppressing and pro-apoptotic factors; suggesting that inhibition of miR-21 biogenesis could reverse these negative effects. However, targeted inhibition of miR-21 using small molecules has had limited success. To overcome difficulties in targeting RNA secondary structure with small molecules, we developed a class of cyclic β-hairpin peptidomimetics which binds to RNA stem loop structures, such as miRNA precursors, with potent affinity and specificity. We screened an existing cyclic peptide library and discovered a lead structure which binds to pre-miR21 with a KD=200nM and prefers it over other pre-miRNAs. The NMR structure of the complex shows the peptide recognizes the Dicer cleavage site and alters processing of the precursor to the mature miRNA in vitro and in cultured cells. The structure provides a rational for the peptide binding activity and clear guidance for further improvements in affinity and targeting.

The increasing appreciation of the central role of non-coding RNAs (miRNAs and long non coding RNAs) in chronic and degenerative human disease makes them attractive therapeutic targets. This would not be unprecedented: the bacterial ribosomal RNA is a mainstay for antibacterial treatment, while the conservation and functional importance of viral RNA regulatory elements has long suggested they would constitute attractive targets for new antivirals. Oligonucleotide-based chemistry has obvious appeals but also considerable pharmacological limitations that are yet to be addressed satisfactorily. Recent studies identifying small molecules targeting non-coding RNAs may provide an alternative approach to oligonucleotide methods. Here we review recent work investigating new structural and chemical principles for targeting RNA with small molecules.

Small molecules that bind to RNA potently and specifically are relatively rare. The study of molecules that bind to the HIV-1 transactivation response (TAR) hairpin, a cis-acting HIV genomic element, has long been an important model system for the chemistry of targeting RNA. Here we report the synthesis, biochemical and structural evaluation of a series of molecules that bind to HIV-1 TAR RNA. A promising analog, 15, retained the TAR binding affinity of the initial hit and displaced a Tat-derived peptide with an IC50 of 40 >M. NMR characterization of a soluble analog, 2, revealed a non-canonical binding mode for this class of compounds. Finally, evaluation of 2 and 15 by Selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) indicates specificity in binding to TAR within the context of an in vitro-synthesized 365-nt HIV-1 5′-untranslated region (UTR). Thus, these compounds exhibit a novel and specific mode of interaction with TAR, providing important implications for RNA ligand design.

Large amounts of data from high throughput metabolomic experiments are commonly visualized using a principal component analysis (PCA) 2D scores plot. The question of the similarity or difference between multiple metabolic states then becomes a question of the degree of overlap between their respective data point clusters in PC scores space. A qualitative visual inspection of the clustering pattern in PCA score plots is a common protocol. This report describes the application of tree diagrams and bootstrapping techniques for an improved quantitative analysis of metabolic PCA data clustering. Our PCAtoTree program creates a distance matrix with 100 bootstrap steps that describes the separation of all clusters in a metabolic dataset. Using accepted phylogenetic software, the distance matrix resulting from the various metabolic states is organized into a phylogenetic-like tree format, where bootstrap values ≥ 50 indicate a statistically relevant branch separation. PCAtoTree analysis of two previously published data sets demonstrates the improved resolution of metabolic state differences using tree diagrams. In addition, for metabolomic studies of large numbers of different metabolic states, the tree format provides a better description of similarities and differences between each metabolic state. The approach is also tolerant of sample size variations between different metabolic states.

A multi-step NMR based screening assay is described for identifying and evaluating chemical leads for their ability to bind a target protein. The multi-step NMR assay provides structure-related information while being an integral part of a structure based drug discovery and design program. The fundamental principle of the multi-step NMR assay is to combine distinct 1D and 2D NMR techniques, in such a manner, that the inherent strengths and weakness associated with each technique is complementary to each other in the screen. By taking advantage of the combined strengths of 1D and 2D NMR experiments, it is possible to minimize protein requirements and experiment time and differentiate between non-specific and stoichiometric binders while being able to verify ligand binding, determine a semi-quantitative dissociation constant, identify the ligand binding site and rapidly determine a protein-ligand co-structure. Furthermore, the quality and physical behavior of the ligand is readily evaluated to determine its appropriateness as a chemical lead. The utility of the multi-step NMR assay is demonstrated with the use of PrgI from Salmonella typhimurium and human serum albumin (HSA) as target proteins.

BackgroundFunctional similarity is challenging to identify when global sequence and structure similarity is low. Active-sites or functionally relevant regions are evolutionarily more stable relative to the remainder of a protein structure and provide an alternative means to identify potential functional similarity between proteins. We recently developed the FAST-NMR methodology to discover biochemical functions or functional hypotheses of proteins of unknown function by experimentally identifying ligand binding sites. FAST-NMR utilizes our CPASS software and database to assign a function based on a similarity in the structure and sequence of ligand binding sites between proteins of known and unknown function.Methodology/Principal FindingsThe PrgI protein from Salmonella typhimurium forms the needle complex in the type III secretion system (T3SS). A FAST-NMR screen identified a similarity between the ligand binding sites of PrgI and the Bcl-2 apoptosis protein Bcl-xL. These ligand binding sites correlate with known protein-protein binding interfaces required for oligomerization. Both proteins form membrane pores through this oligomerization to release effector proteins to stimulate cell death. Structural analysis indicates an overlap between the PrgI structure and the pore forming motif of Bcl-xL. A sequence alignment indicates conservation between the PrgI and Bcl-xL ligand binding sites and pore formation regions. This active-site similarity was then used to verify that chelerythrine, a known Bcl-xL inhibitor, also binds PrgI.Conclusions/SignificanceA structural and functional relationship between the bacterial T3SS and eukaryotic apoptosis was identified using our FAST-NMR ligand affinity screen in combination with a bioinformatic analysis based on our CPASS program. A similarity between PrgI and Bcl-xL is not readily apparent using traditional global sequence and structure analysis, but was only identified because of conservation in ligand binding sites. These results demonstrate the unique opportunity that ligand-binding sites provide for the identification of functional relationships when global sequence and structural information is limited.