Rational design of inhibitors of HIV-1 TAR RNA through the stabilisation of electrostatic "hot spots"

Small molecules targeting microRNAs: new opportunities and challenges in precision cancer therapy

Noncoding RNAs, especially miRNAs, play a pivotal role in cancer initiation and metastasis, underscoring their susceptibility to precise modulation via small molecule inhibitors. This review examines the innovative strategy of targeting oncogenic miRNAs with small drug-like molecules, an approach that can reshape the cancer treatment landscape. We review the current understanding of the multifaceted roles of miRNAs in oncogenesis, highlighting emerging therapeutic paradigms that have the potential to expand cancer treatment options. As research on small molecule inhibitors of miRNA is still in its early stages, ongoing investigative efforts and the development of new technologies and chemical matter are essential to fulfill the significant potential of this innovative approach to cancer treatment.

Small molecule approaches to targeting RNA

The development of innovative methodologies to identify RNA binders has attracted enormous attention in chemical biology and drug discovery. Although antibiotics targeting bacterial ribosomal RNA have been on the market for decades, the renewed interest in RNA targeting reflects the need to better understand complex intracellular processes involving RNA. In this context, small molecules are privileged tools used to explore the biological functions of RNA and to validate RNAs as therapeutic targets, and they eventually are to become new drugs. Despite recent progress, the rational design of specific RNA binders requires a better understanding of the interactions which occur with the RNA target to reach the desired biological response. In this Review, we discuss the challenges to approaching this underexplored chemical space, together with recent strategies to bind, interact and affect biologically relevant RNAs.

Structural and computational studies of HIV-1 RNA

Viruses remain a global threat to animals, plants, and humans. The type 1 human immunodeficiency virus (HIV-1) is a member of the retrovirus family and carries an RNA genome, which is reverse transcribed into viral DNA and further integrated into the host-cell DNA for viral replication and proliferation. The RNA structures from the HIV-1 genome provide valuable insights into the mechanisms underlying the viral replication cycle. Moreover, these structures serve as models for designing novel therapeutic approaches. Here, we review structural data on RNA from the HIV-1 genome as well as computational studies based on these structural data. The review is organized according to the type of structured RNA element which contributes to different steps in the viral replication cycle. This is followed by an overview of the HIV-1 transactivation response element (TAR) RNA as a model system for understanding dynamics and interactions in the viral RNA systems. The review concludes with a description of computational studies, highlighting the impact of biomolecular simulations in elucidating the mechanistic details of various steps in the HIV-1's replication cycle.

Thermal titration molecular dynamics (TTMD): shedding light on the stability of RNA-small molecule complexes

Ribonucleic acids are gradually becoming relevant players among putative drug targets, thanks to the increasing amount of structural data exploitable for the rational design of selective and potent binders that can modulate their activity. Mainly, this information allows employing different computational techniques for predicting how well would a ribonucleic-targeting agent fit within the active site of its target macromolecule. Due to some intrinsic peculiarities of complexes involving nucleic acids, such as structural plasticity, surface charge distribution, and solvent-mediated interactions, the application of routinely adopted methodologies like molecular docking is challenged by scoring inaccuracies, while more physically rigorous methods such as molecular dynamics require long simulation times which hamper their conformational sampling capabilities. In the present work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of unbinding kinetics, to characterize RNA-ligand complexes. In this article, we explored its applicability as a post-docking refinement tool on RNA in complex with small molecules, highlighting the capability of this method to identify the native binding mode among a set of decoys across various pharmaceutically relevant test cases.

Drug-Like Small Molecules That Inhibit Expression of the Oncogenic MicroRNA-21

We report the discovery of drug-like small molecules that bind specifically to the precursor of the oncogenic and pro-inflammatory microRNA-21 with mid-nanomolar affinity. The small molecules target a local structure at the Dicer cleavage site and induce distinctive structural changes in the RNA, which correlate with specific inhibition of miRNA processing. Structurally conservative single nucleotide substitutions eliminate the conformational change induced by the small molecules, which is also not observed in other miRNA precursors. The most potent of these compounds reduces cellular proliferation and miR-21 levels in cancer cell lines without inhibiting kinases or classical receptors, while closely related compounds without this specific binding activity are inactive in cells. These molecules are highly ligand-efficient (MW < 330) and display specific biochemical and cellular activity by suppressing the maturation of miR-21, thereby providing an avenue toward therapeutic development in multiple diseases where miR-21 is abnormally expressed.

RLBind: a deep learning method to predict RNA-ligand binding sites

Identification of RNA-small molecule binding sites plays an essential role in RNA-targeted drug discovery and development. These small molecules are expected to be leading compounds to guide the development of new types of RNA-targeted therapeutics compared with regular therapeutics targeting proteins. RNAs can provide many potential drug targets with diverse structures and functions. However, up to now, only a few methods have been proposed. Predicting RNA-small molecule binding sites still remains a big challenge. New computational model is required to better extract the features and predict RNA-small molecule binding sites more accurately. In this paper, a deep learning model, RLBind, was proposed to predict RNA-small molecule binding sites from sequence-dependent and structure-dependent properties by combining global RNA sequence channel and local neighbor nucleotides channel. To our best knowledge, this research was the first to develop a convolutional neural network for RNA-small molecule binding sites prediction. Furthermore, RLBind also can be used as a potential tool when the RNA experimental tertiary structure is not available. The experimental results show that RLBind outperforms other state-of-the-art methods in predicting binding sites. Therefore, our study demonstrates that the combination of global information for full-length sequences and local information for limited local neighbor nucleotides in RNAs can improve the model's predictive performance for binding sites prediction. All datasets and resource codes are available at https://github.com/KailiWang1/RLBind.

SILCS-RNA: Toward a Structure-Based Drug Design Approach for Targeting RNAs with Small Molecules

RNA molecules can act as potential drug targets in different diseases, as their dysregulated expression or misfolding can alter various cellular processes. Noncoding RNAs account for ∼70% of the human genome, and these molecules can have complex tertiary structures that present a great opportunity for targeting by small molecules. In the present study, the site identification by ligand competitive saturation (SILCS) computational approach is extended to target RNA, termed SILCS-RNA. Extensions to the method include an enhanced oscillating excess chemical potential protocol for the grand canonical Monte Carlo calculations and individual simulations of the neutral and charged solutes from which the SILCS functional group affinity maps (FragMaps) are calculated for subsequent binding site identification and docking calculations. The method is developed and evaluated against seven RNA targets and their reported small molecule ligands. SILCS-RNA provides a detailed characterization of the functional group affinity pattern in the small molecule binding sites, recapitulating the types of functional groups present in the ligands. The developed method is also shown to be useful for identification of new potential binding sites and identifying ligand moieties that contribute to binding, granular information that can facilitate ligand design. However, limitations in the method are evident including the ability to map the regions of binding sites occupied by ligand phosphate moieties and to fully account for the wide range of conformational heterogeneity in RNA associated with binding of different small molecules, emphasizing inherent challenges associated with applying computer-aided drug design methods to RNA. While limitations are present, the current study indicates how the SILCS-RNA approach may enhance drug discovery efforts targeting RNAs with small molecules.

Protein-Based Virtual Screening Tools Applied for RNA-Ligand Docking Identify New Binders of the preQ1-Riboswitch

Targeting RNA with small molecules is an emerging field. While several ligands for different RNA targets are reported, structure-based virtual screenings (VSs) against RNAs are still rare. Here, we elucidated the general capabilities of protein-based docking programs to reproduce native binding modes of small-molecule RNA ligands and to discriminate known binders from decoys by the scoring function. The programs were found to perform similar compared to the RNA-based docking tool rDOCK, and the challenges faced during docking, namely, protomer and tautomer selection, target dynamics, and explicit solvent, do not largely differ from challenges in conventional protein-ligand docking. A prospective VS with the Bacillus subtilis preQ₁-riboswitch aptamer domain performed with FRED, HYBRID, and FlexX followed by microscale thermophoresis assays identified six active compounds out of 23 tested VS hits with potencies between 29.5 nM and 11.0 μM. The hits were selected not solely based on their docking score but for resembling key interactions of the native ligand. Therefore, this study demonstrates the general feasibility to perform structure-based VSs against RNA targets, while at the same time it highlights pitfalls and their potential solutions when executing RNA-ligand docking.

Gaussian Accelerated Molecular Dynamics in OpenMM

Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.

fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions

Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt—a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt)—a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction fingerprint-based similarity as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of interaction fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties. The fingeRNAt software is freely available at https://github.com/n-szulc/fingeRNAt.

Structure-based design and synthesis of copper(ii) complexes as antivirus drug candidates targeting SARS CoV-2 and HIV

This paper describes the structure-based design and synthesis of two novel square-planar trans-N2O2 Cu(ii) complexes [Cu(L1)2] (1) and [Cu(L2)2] (2) of 2-((Z)-(4-methoxyphenylimino)methyl)-4,6-dichlorophenol (L1H) and 2-((Z)-(2,4-dibromophenylimino)methyl)-4-bromophenol (L2H) as potential inhibitors against the main protease of the SARS-CoV-2 and HIV viruses.

Structure-based deep learning for binding site detection in nucleic acid macromolecules

Structure-based drug design (SBDD) targeting nucleic acid macromolecules, particularly RNA, is a gaining momentum research direction that already resulted in several FDA-approved compounds. Similar to proteins, one of the critical components in SBDD for RNA is the correct identification of the binding sites for putative drug candidates. RNAs share a common structural organization that, together with the dynamic nature of these molecules, makes it challenging to recognize binding sites for small molecules. Moreover, there is a need for structure-based approaches, as sequence information only does not consider conformation plasticity of nucleic acid macromolecules. Deep learning holds a great promise to resolve binding site detection problem, but requires a large amount of structural data, which is very limited for nucleic acids, compared to proteins. In this study we composed a set of ∼2000 nucleic acid-small molecule structures comprising ∼2500 binding sites, which is ∼40-times larger than previously used one, and demonstrated the first structure-based deep learning approach, BiteNet_N, to detect binding sites in nucleic acid structures. BiteNet_N operates with arbitrary nucleic acid complexes, shows the state-of-the-art performance, and can be helpful in the analysis of different conformations and mutant variants, as we demonstrated for HIV-1 TAR RNA and ATP-aptamer case studies.

Conformational dynamics and energetics of viral RNA recognition by lab-evolved proteins

The conserved and structured elements in viral RNA genomes interact with proteins to regulate various events in the viral life cycle and have become key targets for developing novel therapeutic approaches. We probe physical interactions between lab-evolved proteins and a viral RNA element from the HIV-1 genome. Specifically, we study the role of an arginine-rich loop in recognition of designed proteins by the viral RNA element. We report free energy calculations to quantitatively estimate the protein/RNA binding energetics, focusing on the mutations of arginine residues involved in recognition of the major groove of RNA by proteins.

Efficient NMR Screening Approach to Discover Small Molecule Fragments Binding Structured RNA

We describe a scalable nuclear magnetic resonance (NMR) screening approach to identify and prioritize small molecule fragments that bind to structured RNAs. This approach is target agnostic and, therefore, amenable to many RNA structures and libraries, and it provides initial hits for further synthetic elaboration and structure-based drug discovery efforts. We demonstrate the approach on the pre-miR-21 stem-loop, which is of significant interest in oncology and metabolic diseases. We screened the pre-miR-21 hairpin using a small (420 compounds) commercially available fragment library and identified 18 hits in the first round of triage screening. This was further refined to four fragments which passed all screening cascade filters. Among these four hits, a thiadiazole fragment was demonstrated to bind the Dicer cleavage site of pre-miR-21 by target-detected NMR experiments and through the observation of clear intermolecular NOEs.

Role of conformational heterogeneity in ligand recognition by viral RNA molecules

Ribonucleic acid (RNA) molecules are known to undergo conformational changes in response to various environmental stimuli including temperature, pH, and ligands. In particular, viral RNA molecules are a key example of conformationally adapting molecules that have evolved to switch between many functional conformations. The transactivation response element (TAR) RNA from the type-1 human immunodeficiency virus (HIV-1) is a viral RNA molecule that is being increasingly explored as a potential therapeutic target due to its role in the viral replication process. In this work, we have studied the dynamics in TAR RNA in apo and liganded states by performing explicit-solvent molecular dynamics (MD) simulations initiated with 27 distinct structures. We determined that the TAR RNA structure is significantly stabilized on ligand binding with especially decreased fluctuations in its two helices. This rigidity is further coupled with the decreased flipping of bulge nucleotides, which were observed to flip more frequently in the absence of ligands. We found that initially-distinct structures of TAR RNA converged to similar conformations on removing ligands. We also report that conformational dynamics in unliganded TAR structures leads to the formation of binding pockets capable of accommodating ligands of various sizes.

Role and Perspective of Molecular Simulation-Based Investigation of RNA-Ligand Interaction: From Small Molecules and Peptides to Photoswitchable RNA Binding

Aberrant RNA–protein complexes are formed in a variety of diseases. Identifying the ligands that interfere with their formation is a valuable therapeutic strategy. Molecular simulation, validated against experimental data, has recently emerged as a powerful tool to predict both the pose and energetics of such ligands. Thus, the use of molecular simulation may provide insight into aberrant molecular interactions in diseases and, from a drug design perspective, may allow for the employment of less wet lab resources than traditional in vitro compound screening approaches. With regard to basic research questions, molecular simulation can support the understanding of the exact molecular interaction and binding mode. Here, we focus on examples targeting RNA–protein complexes in neurodegenerative diseases and viral infections. These examples illustrate that the strategy is rather general and could be applied to different pharmacologically relevant approaches. We close this study by outlining one of these approaches, namely the light-controllable association of small molecules with RNA, as an emerging approach in RNA-targeting therapy.

Targeting structural features of viral genomes with a nano-sized supramolecular drug

RNA targeting is an exciting frontier for drug design. Intriguing targets include functional RNA structures in structurally-conserved untranslated regions (UTRs) of many lethal viruses. However, computational docking screens, valuable in protein structure targeting, fail for inherently flexible RNA. Herein we harness MD simulations with Markov state modeling to enable nanosize metallo-supramolecular cylinders to explore the dynamic RNA conformational landscape of HIV-1 TAR untranslated region RNA (representative for many viruses) replicating experimental observations. These cylinders are exciting as they have unprecedented nucleic acid binding and are the first supramolecular helicates shown to have anti-viral activity in cellulo: the approach developed in this study provides additional new insight about how such viral UTR structures might be targeted with the cylinder binding into the heart of an RNA-bulge cavity, how that reduces the conformational flexibility of the RNA and molecular details of the insertion mechanism. The approach and understanding developed represents a new roadmap for design of supramolecular drugs to target RNA structural motifs across biology and nucleic acid nanoscience.

The Perturbed Free-Energy Landscape: Linking Ligand Binding to Biomolecular Folding

The effects of ligand binding on biomolecular conformation are crucial in drug design, enzyme mechanisms, the regulation of gene expression, and other biological processes. Descriptive models such as "lock and key", "induced fit", and "conformation selection" are common ways to interpret such interactions. Another historical model, linked equilibria, proposes that the free-energy landscape (FEL) is perturbed by the addition of ligand binding energy for the bound population of biomolecules. This principle leads to a unified, quantitative theory of ligand-induced conformation change, building upon the FEL concept. We call the map of binding free energy over biomolecular conformational space the "binding affinity landscape" (BAL). The perturbed FEL predicts/explains ligand-induced conformational changes conforming to all common descriptive models. We review recent experimental and computational studies that exemplify the perturbed FEL, with emphasis on RNA. This way of understanding ligand-induced conformation dynamics motivates new experimental and theoretical approaches to ligand design, structural biology and systems biology.

Understanding the characteristics of nonspecific binding of drug-like compounds to canonical stem-loop RNAs and their implications for functional cellular assays

Identifying small molecules that selectively bind an RNA target while discriminating against all other cellular RNAs is an important challenge in RNA-targeted drug discovery. Much effort has been directed toward identifying drug-like small molecules that minimize electrostatic and stacking interactions that lead to nonspecific binding of aminoglycosides and intercalators to many stem-loop RNAs. Many such compounds have been reported to bind RNAs and inhibit their cellular activities. However, target engagement and cellular selectivity assays are not routinely performed, and it is often unclear whether functional activity directly results from specific binding to the target RNA. Here, we examined the propensities of three drug-like compounds, previously shown to bind and inhibit the cellular activities of distinct stem-loop RNAs, to bind and inhibit the cellular activities of two unrelated HIV-1 stem-loop RNAs: the transactivation response element (TAR) and the rev response element stem IIB (RREIIB). All compounds bound TAR and RREIIB in vitro, and two inhibited TAR-dependent transactivation and RRE-dependent viral export in cell-based assays while also exhibiting off-target interactions consistent with nonspecific activity. A survey of X-ray and NMR structures of RNA-small molecule complexes revealed that aminoglycosides and drug-like molecules form hydrogen bonds with functional groups commonly accessible in canonical stem-loop RNA motifs, in contrast to ligands that specifically bind riboswitches. Our results demonstrate that drug-like molecules can nonspecifically bind stem-loop RNAs most likely through hydrogen bonding and electrostatic interactions and reinforce the importance of assaying for off-target interactions and RNA selectivity in vitro and in cells when assessing novel RNA-binders.

Co-crystal structures of HIV TAR RNA bound to lab-evolved proteins show key roles for arginine relevant to the design of cyclic peptide TAR inhibitors

RNA-protein interfaces control key replication events during the HIV-1 life cycle. The viral trans-activator of transcription (Tat) protein uses an archetypal arginine-rich motif (ARM) to recruit the host positive transcription elongation factor b (pTEFb) complex onto the viral trans-activation response (TAR) RNA, leading to activation of HIV transcription. Efforts to block this interaction have stimulated production of biologics designed to disrupt this essential RNA-protein interface. Here, we present four co-crystal structures of lab-evolved TAR-binding proteins (TBPs) in complex with HIV-1 TAR. Our results reveal that high-affinity binding requires a distinct sequence and spacing of arginines within a specific β2-β3 hairpin loop that arose during selection. Although loops with as many as five arginines were analyzed, only three arginines could bind simultaneously with major-groove guanines. Amino acids that promote backbone interactions within the β2-β3 loop were also observed to be important for high-affinity interactions. Based on structural and affinity analyses, we designed two cyclic peptide mimics of the TAR-binding β2-β3 loop sequences present in two high-affinity TBPs (KD values of 4.2 ± 0.3 and 3.0 ± 0.3 nm). Our efforts yielded low-molecular weight compounds that bind TAR with low micromolar affinity (KD values ranging from 3.6 to 22 μm). Significantly, one cyclic compound within this series blocked binding of the Tat-ARM peptide to TAR in solution assays, whereas its linear counterpart did not. Overall, this work provides insight into protein-mediated TAR recognition and lays the ground for the development of cyclic peptide inhibitors of a vital HIV-1 RNA-protein interaction.

Advances in RNA 3D Structure Modeling Using Experimental Data

RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.

Regulation of MALAT1 triple helix stability and in vitro degradation by diphenylfurans

Small molecule-based modulation of a triple helix in the long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) has been proposed as an attractive avenue for cancer treatment and a model system for understanding small molecule:RNA recognition. To elucidate fundamental recognition principles and structure-function relationships, we designed and synthesized nine novel analogs of a diphenylfuran-based small molecule DPFp8, a previously identified lead binder of MALAT1. We investigated the role of recognition modalities in binding and in silico studies along with the relationship between affinity, stability and in vitro enzymatic degradation of the triple helix. Specifically, molecular docking studies identified patterns driving affinity and selectivity, including limited ligand flexibility, as observed by ligand preorganization and 3D shape complementarity for the binding pocket. The use of differential scanning fluorimetry allowed rapid evaluation of ligand-induced thermal stabilization of the triple helix, which correlated with decreased in vitro degradation of this structure by the RNase R exonuclease. The magnitude of stabilization was related to binding mode and selectivity between the triple helix and its precursor stem loop structure. Together, this work demonstrates the value of scaffold-based libraries in revealing recognition principles and of raising broadly applicable strategies, including functional assays, for small molecule-RNA targeting.

Exposing Hidden High-Affinity RNA Conformational States

RNA recognition frequently results in conformational changes that optimize intermolecular binding. As a consequence, the overall binding affinity of RNA to its binding partners depends not only on the intermolecular interactions formed in the bound state but also on the energy cost associated with changing the RNA conformational distribution. Measuring these "conformational penalties" is, however, challenging because bound RNA conformations tend to have equilibrium populations in the absence of the binding partner that fall outside detection by conventional biophysical methods. In this study we employ as a model system HIV-1 TAR RNA and its interaction with the ligand argininamide (ARG), a mimic of TAR's cognate protein binding partner, the transactivator Tat. We use NMR chemical shift perturbations and relaxation dispersion in combination with Bayesian inference to develop a detailed thermodynamic model of coupled conformational change and ligand binding. Starting from a comprehensive 12-state model of the equilibrium, we estimate the energies of six distinct detectable thermodynamic states that are not accessible by currently available methods. Our approach identifies a minimum of four RNA intermediates that differ in terms of the TAR conformation and ARG occupancy. The dominant bound TAR conformation features two bound ARG ligands and has an equilibrium population in the absence of ARG that is below detection limit. Consequently, even though ARG binds to TAR with an apparent overall weak affinity (Kdapp ≈ 0.2 mM), it binds the prefolded conformation with a Kd in the nM range. Our results show that conformational penalties can be major determinants of RNA-ligand binding affinity as well as a source of binding cooperativity, with important implications for a predictive understanding of how RNA is recognized and for RNA-targeted drug discovery.

An ultra-high affinity ligand of HIV-1 TAR reveals the RNA structure recognized by P-TEFb

The HIV-1 trans-activator protein Tat binds the trans-activation response element (TAR) to facilitate recruitment of the super elongation complex (SEC) to enhance transcription of the integrated pro-viral genome. The Tat–TAR interaction is critical for viral replication and the emergence of the virus from the latent state, therefore, inhibiting this interaction has long been pursued to discover new anti-viral or latency reversal agents. However, discovering active compounds that directly target RNA with high affinity and selectivity remains a significant challenge; limiting pre-clinical development. Here, we report the rational design of a macrocyclic peptide mimic of the arginine rich motif of Tat, which binds to TAR with low pM affinity and 100-fold selectivity against closely homologous RNAs. Despite these unprecedented binding properties, the new ligand (JB181) only moderately inhibits Tat-dependent reactivation in cells and recruitment of positive transcription elongation factor (P-TEFb) to TAR. The NMR structure of the JB181–TAR complex revealed that the ligand induces a structure in the TAR loop that closely mimics the P-TEFb/Tat1:57/AFF4/TAR complex. These results strongly suggest that high-affinity ligands which bind the UCU bulge are not likely to inhibit recruitment of the SEC and suggest that targeting of the TAR loop will be an essential feature of effective Tat inhibitors.

Design of RNA-targeting macrocyclic peptides

RNA structures play a pivotal role in many biological processes and the progression of human disease, making them an attractive target for therapeutic development. Often RNA structures operate through the formation of complexes with RNA-binding proteins, however, much like protein-protein interactions, RNA-protein interactions span large surface areas and often lack traditional druggable properties, making it challenging to target them with small molecules. Peptides provide much greater surface areas and therefore greater potential for forming specific and high affinity interactions with RNA. In this chapter, we discuss our approach for engineering peptides that bind to structured RNAs by highlighting methods and design strategies from previous successful projects aimed at inhibiting the HIV Tat-TAR interaction and the biogenesis of oncogenic microRNAs.

NMR characterization of RNA small molecule interactions

Exciting discoveries of naturally occurring ligand-sensing and disease-linked noncoding RNAs have promoted significant interests in understanding RNA-small molecule interactions. NMR spectroscopy is a powerful tool for characterizing intermolecular interactions. In this review, we describe protocols and approaches for applying NMR spectroscopy to investigate interactions between RNA and small molecules. We review protocols for RNA sample preparation, methods for identifying RNA-binding small molecules, approaches for mapping RNA-small molecule interactions, determining complex structures, and characterizing binding kinetics. We hope this review will provide a guideline to streamline NMR applications in studying RNA-small molecule interactions, facilitating both basic mechanistic understandings of RNA functions and translational efforts in developing RNA-targeted therapeutics.

Face-time with TAR: Portraits of an HIV-1 RNA with diverse modes of effector recognition relevant for drug discovery

Small molecules and short peptides that potently and selectively bind RNA are rare, making the molecular structures of these complexes highly exceptional. Accordingly, several recent investigations have provided unprecedented structural insights into how peptides and proteins recognize the HIV-1 transactivation response (TAR) element, a 59-nucleotide-long, noncoding RNA segment in the 5' long terminal repeat region of viral transcripts. Here, we offer an integrated perspective on these advances by describing earlier progress on TAR binding to small molecules, and by drawing parallels to recent successes in the identification of compounds that target the hepatitis C virus internal ribosome entry site (IRES) and the flavin-mononucleotide riboswitch. We relate this work to recent progress that pinpoints specific determinants of TAR recognition by: (i) viral Tat proteins, (ii) an innovative lab-evolved TAR-binding protein, and (iii) an ultrahigh-affinity cyclic peptide. New structural details are used to model the TAR-Tat-super-elongation complex (SEC) that is essential for efficient viral transcription and represents a focal point for antiviral drug design. A key prediction is that the Tat transactivation domain makes modest contacts with the TAR apical loop, whereas its arginine-rich motif spans the entire length of the TAR major groove. This expansive interface has significant implications for drug discovery and design, and it further suggests that future lab-evolved proteins could be deployed to discover steric restriction points that block Tat-mediated recruitment of the host SEC to HIV-1 TAR.

Biosensor-surface plasmon resonance: A strategy to help establish a new generation RNA-specific small molecules

Biosensor surface plasmon resonance (SPR) is a highly sensitive technique and is most commonly used to decipher the interactions of biological systems including proteins and nucleic acids. Throughout the years, there have been significant efforts to develop SPR assays for studying protein-protein interactions, protein-DNA interactions, as well as small molecules to target DNAs that are of therapeutic interest. With the explosion of discovery of new RNA structures and functions, it is time to review the applications of SPR to RNA interaction studies, which have actually extended over a long time period. The primary advantage of SPR is its ability to measure affinities and kinetics in real time, along with being a label-free technique and utilizing relatively small quantities of materials. Recently, developments that use SPR to analyze the interactions of different RNA sequences with proteins and small molecules demonstrate the versatility of SPR as a powerful method in the analysis of the structure-function relationships, not only for biological macromolecules but also for potential drug candidates. This chapter will guide the reader through some background material followed by an extensive assay development to dissect the interactions of small molecules and RNA sequences using SPR as the critical method. The protocol includes (i) fundamental concepts of SPR, (ii) experimental design and execution, (iii) the immobilization of RNA using the streptavidin-biotin capturing method, and (iv) affinities and kinetics analyses of the interactions using specific example samples. The chapter also contains useful notes to address situations that might arise during the process. This assay demonstrates SPR as a valuable quantitative method used in the search for potential therapeutic agents that selectively target RNA.

Computational modeling of RNA 3D structure based on experimental data

RNA molecules are master regulators of cells. They are involved in a variety of molecular processes: they transmit genetic information, sense cellular signals and communicate responses, and even catalyze chemical reactions. As in the case of proteins, RNA function is dictated by its structure and by its ability to adopt different conformations, which in turn is encoded in the sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore the majority of known RNAs remain structurally uncharacterized. To address this problem, predictive computational methods were developed based on the accumulated knowledge of RNA structures determined so far, the physical basis of the RNA folding, and taking into account evolutionary considerations, such as conservation of functionally important motifs. However, all theoretical methods suffer from various limitations, and they are generally unable to accurately predict structures for RNA sequences longer than 100-nt residues unless aided by additional experimental data. In this article, we review experimental methods that can generate data usable by computational methods, as well as computational approaches for RNA structure prediction that can utilize data from experimental analyses. We outline methods and data types that can be potentially useful for RNA 3D structure modeling but are not commonly used by the existing software, suggesting directions for future development.

Increasing the length of poly-pyrimidine bulges broadens RNA conformational ensembles with minimal impact on stacking energetics

Helical elements separated by bulges frequently undergo transitions between unstacked and coaxially stacked conformations during the folding and function of noncoding RNAs. Here, we examine the dynamic properties of poly-pyrimidine bulges of varying length (n = 1-4, 7) across a range of Mg²⁺ concentrations using HIV-1 TAR RNA as a model system and solution NMR spectroscopy. In the absence of Mg²⁺, helices linked by bulges with n ≥ 3 residues adopt predominantly unstacked conformations (stacked population <15%), whereas one-bulge and two-bulge motifs adopt predominantly stacked conformations (stacked population >74%). In the presence of 3 mM Mg²⁺, the helices predominantly coaxially stack (stacked population >84%), regardless of bulge length, and the midpoint for the Mg²⁺-dependent stacking transition is within threefold regardless of bulge length. In the absence of Mg²⁺, the difference between free energy of interhelical coaxial stacking across the bulge variants is estimated to be ∼2.9 kcal/mol, based on an NMR chemical shift mapping with stacking being more energetically disfavored for the longer bulges. This difference decreases to ∼0.4 kcal/mol in the presence of Mg²⁺ NMR RDCs and resonance intensity data show increased dynamics in the stacked state with increasing bulge length in the presence of Mg²⁺ We propose that Mg²⁺ helps to neutralize the growing electrostatic repulsion in the stacked state with increasing bulge length thereby increasing the number of coaxial conformations that are sampled. Energetically compensated interhelical stacking dynamics may help to maximize the conformational adaptability of RNA and allow a wide range of conformations to be optimally stabilized by proteins and ligands.

Non-Natural Linker Configuration in 2,6-Dipeptidyl-Anthraquinones Enhances the Inhibition of TAR RNA Binding/Annealing Activities by HIV-1 NC and Tat Proteins

The HIV-1 nucleocapsid (NC) protein represents an excellent molecular target for the development of anti-retrovirals by virtue of its well-characterized chaperone activities, which play pivotal roles in essential steps of the viral life cycle. Our ongoing search for candidates able to impair NC binding/annealing activities led to the identification of peptidyl-anthraquinones as a promising class of nucleic acid ligands. Seeking to elucidate the inhibition determinants and increase the potency of this class of compounds, we have now explored the effects of chirality in the linker connecting the planar nucleus to the basic side chains. We show here that the non-natural linker configuration imparted unexpected TAR RNA targeting properties to the 2,6-peptidyl-anthraquinones and significantly enhanced their potency. Even if the new compounds were able to interact directly with the NC protein, they manifested a consistently higher affinity for the TAR RNA substrate and their TAR-binding properties mirrored their ability to interfere with NC-TAR interactions. Based on these findings, we propose that the viral Tat protein, sharing the same RNA substrate but acting in distinct phases of the viral life cycle, constitutes an additional druggable target for this class of peptidyl-anthraquinones. The inhibition of Tat-TAR interaction for the test compounds correlated again with their TAR-binding properties, while simultaneously failing to demonstrate any direct Tat-binding capabilities. These considerations highlighted the importance of TAR RNA in the elucidation of their inhibition mechanism, rather than direct protein inhibition. We have therefore identified anti-TAR compounds with dual in vitro inhibitory activity on different viral proteins, demonstrating that it is possible to develop multitarget compounds capable of interfering with processes mediated by the interactions of this essential RNA domain of HIV-1 genome with NC and Tat proteins.

High-performance virtual screening by targeting a high-resolution RNA dynamic ensemble

Dynamic ensembles hold great promise in advancing RNA-targeted drug discovery. Here we subjected the transactivation response element (TAR) RNA from human immunodeficiency virus type-1 to experimental high-throughput screening against ~100,000 drug-like small molecules. Results were augmented with 170 known TAR-binding molecules and used to generate sublibraries optimized for evaluating enrichment when virtually screening a dynamic ensemble of TAR determined by combining NMR spectroscopy data and molecular dynamics simulations. Ensemble-based virtual screening scores molecules with an area under the receiver operator characteristic curve of ~0.85-0.94 and with ~40-75% of all hits falling within the top 2% of scored molecules. The enrichment decreased significantly for ensembles generated from the same molecular dynamics simulations without input NMR data and for other control ensembles. The results demonstrate that experimentally determined RNA ensembles can significantly enrich libraries with true hits and that the degree of enrichment is dependent on the accuracy of the ensemble.

Superior HIV-1 TAR Binders with Conformationally Constrained R52 Arginine Mimics in the Tat(48-57) Peptide

We report a 100-fold increase in binding affinity of the Tat(48-57) peptide to HIV-1 transcriptional activator-responsive element (TAR) RNA by replacing Arg52, an essential and critical residue for Tat's specific binding, with (2S,4S)-4-guanidinoproline. The resulting αTat1M peptide is a far superior binder than γTat1M, a peptide containing another conformationally constrained arginine mimic, (2S,4S)-4-amino-N-(3-guanidinopropyl)proline, or even the control Tat peptide (CtrlTat) itself. Our observations are supported by circular dichroism (CD), isothermal titration calorimetry (ITC), gel electrophoresis and UV spectroscopy studies. Molecular dynamics simulations suggest increased interactions between the more compact αTat1M and TAR RNA, relative to CtrlTat. The CD signature of the RNA itself remains largely unchanged upon binding of the peptides. The Tat mimetics further have better cell uptake properties than the control Tat peptide, thus increasing their potential application as specific TAR-binding molecules.

Halogen Bonding in Nucleic Acid Complexes

Halogen bonding (X-bonding) has attracted notable attention among noncovalent interactions. This highly directional attraction between a halogen atom and an electron donor has been exploited in knowledge-based drug design. A great deal of information has been gathered about X-bonds in protein-ligand complexes, as opposed to nucleic acid complexes. Here we provide a thorough analysis of nucleic acid complexes containing either halogenated building blocks or halogenated ligands. We analyzed close contacts between halogens and electron-rich moieties. The phosphate backbone oxygen is clearly the most common halogen acceptor. We identified 21 X-bonds within known structures of nucleic acid complexes. A vast majority of the X-bonds is formed by halogenated nucleobases, such as bromouridine, and feature excellent geometries. Noncovalent ligands have been found to form only interactions with suboptimal interaction geometries. Hence, the first X-bonded nucleic acid binder remains to be discovered.

Amiloride as a new RNA-binding scaffold with activity against HIV-1 TAR

Diversification of RNA-targeted scaffolds offers great promise in the search for selective ligands of therapeutically relevant RNA such as HIV-1 TAR. We herein report the establishment of amiloride as a novel RNA-binding scaffold along with synthetic routes for combinatorial C(5)- and C(6)-diversification. Iterative modifications at the C(5)- and C(6)- positions yielded derivative 24, which demonstrated a 100-fold increase in activity over the parent dimethylamiloride in peptide displacement assays. NMR chemical shift mapping was performed using the 2D SOFAST- [1H-13C] HMQC NMR method, which allowed for facile and rapid evaluation of binding modes for all library members. Cheminformatic analysis revealed distinct differences between selective and non-selective ligands. In this study, we evolved dimethylamiloride from a weak TAR ligand to one of the tightest binding selective TAR ligands reported to date through a novel combination of synthetic methods and analytical techniques. We expect these methods to allow for rapid library expansion and tuning of the amiloride scaffold for a range of RNA targets and for SOFAST NMR to allow unprecedented evaluation of small molecule:RNA interactions.

Molecular dynamics and MM/GBSA-integrated protocol probing the correlation between biological activities and binding free energies of HIV-1 TAR RNA inhibitors

The interaction of HIV-1 transactivator protein Tat with its cognate transactivation response (TAR) RNA has emerged as a promising target for developing antiviral compounds and treating HIV infection, since it is a crucial step for efficient transcription and replication. In the present study, molecular dynamics (MD) simulations and MM/GBSA calculations have been performed on a series of neamine derivatives in order to estimate appropriate MD simulation time for acceptable correlation between ΔG_bind and experimental pIC₅₀ values. Initially, all inhibitors were docked into the active site of HIV-1 TAR RNA. Later to explore various conformations and examine the docking results, MD simulations were carried out. Finally, binding free energies were calculated using MM/GBSA method and were correlated with experimental pIC₅₀ values at different time scales (0-1 to 0-10 ns). From this study, it is clear that in case of neamine derivatives as simulation time increased the correlation between binding free energy and experimental pIC₅₀ values increased correspondingly. Therefore, the binding energies which can be interpreted at longer simulation times can be used to predict the bioactivity of new neamine derivatives. Moreover, in this work, we have identified some plausible critical nucleotide interactions with neamine derivatives that are responsible for potent inhibitory activity. Furthermore, we also provide some insights into a new class of oxadiazole-based back bone cyclic peptides designed by incorporating the structural features of neamine derivatives. On the whole, this approach can provide a valuable guidance for designing new potent inhibitors and modify the existing compounds targeting HIV-1 TAR RNA.

Shortening the HIV-1 TAR RNA Bulge by a Single Nucleotide Preserves Motional Modes over a Broad Range of Time Scales

Helix-junction-helix (HJH) motifs are flexible building blocks of RNA architecture that help define the orientation and dynamics of helical domains. They are also frequently involved in adaptive recognition of proteins and small molecules and in the formation of tertiary contacts. Here, we use a battery of nuclear magnetic resonance techniques to examine how deleting a single bulge residue (C24) from the human immunodeficiency virus type 1 (HIV-1) transactivation response element (TAR) trinucleotide bulge (U23-C24-U25) affects dynamics over a broad range of time scales. Shortening the bulge has an effect on picosecond-to-nanosecond interhelical and local bulge dynamics similar to that casued by increasing the Mg(2+) and Na(+) concentration, whereby a preexisting two-state equilibrium in TAR is shifted away from a bent flexible conformation toward a coaxial conformation, in which all three bulge residues are flipped out and flexible. Surprisingly, the point deletion minimally affects microsecond-to-millisecond conformational exchange directed toward two low-populated and short-lived excited conformational states that form through reshuffling of bases pairs throughout TAR. The mutant does, however, adopt a slightly different excited conformational state on the millisecond time scale, in which U23 is intrahelical, mimicking the expected conformation of residue C24 in the excited conformational state of wild-type TAR. Thus, minor changes in HJH topology preserve motional modes in RNA occurring over the picosecond-to-millisecond time scales but alter the relative populations of the sampled states or cause subtle changes in their conformational features.

Improving combination antiretroviral therapy by targeting HIV-1 gene transcription

INTRODUCTION

Combination Antiretroviral Therapy (cART) has not allowed the cure of HIV. The main obstacle to HIV eradication is the existence of quiescent reservoirs. Several other limitations of cART have been described, such as strict life-long treatment and high costs, restricting it to Western countries, as well as the development of multidrug resistance. Given these limitations and the impetus to find a cure, the development of new treatments is necessary. Areas covered: In this review, we discuss the current status of several efficient molecules able to suppress HIV gene transcription, including NF-kB and Tat inhibitors. We also assess the potential of new proteins belonging to the intriguing DING family, which have been reported to have potential anti-HIV-1 activity by inhibiting HIV gene transcription. Expert opinion: Targeting HIV-1 gene transcription is an alternative approach, which could overcome cART-related issues, such as the emergence of multidrug resistance. Improving cART will rely on the identification and characterization of new actors inhibiting HIV-1 transcription. Combining such efforts with the use of new technologies, the development of new models for preclinical studies, and improvement in drug delivery will considerably reduce drug toxicity and thus increase patient adherence.

Modulating RNA Alignment Using Directional Dynamic Kinks: Application in Determining an Atomic-Resolution Ensemble for a Hairpin using NMR Residual Dipolar Couplings

Approaches that combine experimental data and computational molecular dynamics (MD) to determine atomic resolution ensembles of biomolecules require the measurement of abundant experimental data. NMR residual dipolar couplings (RDCs) carry rich dynamics information, however, difficulties in modulating overall alignment of nucleic acids have limited the ability to fully extract this information. We present a strategy for modulating RNA alignment that is based on introducing variable dynamic kinks in terminal helices. With this strategy, we measured seven sets of RDCs in a cUUCGg apical loop and used this rich data set to test the accuracy of an 0.8 μs MD simulation computed using the Amber ff10 force field as well as to determine an atomic resolution ensemble. The MD-generated ensemble quantitatively reproduces the measured RDCs, but selection of a sub-ensemble was required to satisfy the RDCs within error. The largest discrepancies between the RDC-selected and MD-generated ensembles are observed for the most flexible loop residues and backbone angles connecting the loop to the helix, with the RDC-selected ensemble resulting in more uniform dynamics. Comparison of the RDC-selected ensemble with NMR spin relaxation data suggests that the dynamics occurs on the ps-ns time scales as verified by measurements of R(1ρ) relaxation-dispersion data. The RDC-satisfying ensemble samples many conformations adopted by the hairpin in crystal structures indicating that intrinsic plasticity may play important roles in conformational adaptation. The approach presented here can be applied to test nucleic acid force fields and to characterize dynamics in diverse RNA motifs at atomic resolution.

HIV-1 drug discovery: targeting folded RNA structures with branched peptides

Human immunodeficiency virus type 1 (HIV-1) is an RNA virus that is prone to high rates of mutation. While the disease is managed with current antiretroviral therapies, drugs with a new mode of action are needed. A strategy towards this goal is aimed at targeting the native three-dimensional fold of conserved RNA structures. This perspective highlights medium-sized peptides and peptidomimetics used to target two conserved RNA structures of HIV-1. In particular, branched peptides have the capacity to bind in a multivalent fashion, utilizing a large surface area to achieve the necessary affinity and selectivity toward the target RNA.

Substrate recognition and modification by the nosiheptide resistance methyltransferase

Background

The proliferation of antibiotic resistant pathogens is an increasing threat to the general public. Resistance may be conferred by a number of mechanisms including covalent or mutational modification of the antibiotic binding site, covalent modification of the drug, or the over-expression of efflux pumps. The nosiheptide resistance methyltransferase (NHR) confers resistance to the thiazole antibiotic nosiheptide in the nosiheptide producer organism Streptomyces actuosus through 2ʹO-methylation of 23S rRNA at the nucleotide A1067. Although the crystal structures of NHR and the closely related thiostrepton-resistance methyltransferase (TSR) in complex with the cofactor S-Adenosyl-L-methionine (SAM) are available, the principles behind NHR substrate recognition and catalysis remain unclear.

Methodology/Principal Findings

We have analyzed the binding interactions between NHR and model 58 and 29 nucleotide substrate RNAs by gel electrophoresis mobility shift assays (EMSA) and fluorescence anisotropy. We show that the enzyme binds to RNA as a dimer. By constructing a hetero-dimer complex composed of one wild-type subunit and one inactive mutant NHR-R135A subunit, we show that only one functional subunit of the NHR homodimer is required for its enzymatic activity. Mutational analysis suggests that the interactions between neighbouring bases (G1068 and U1066) and A1067 have an important role in methyltransfer activity, such that the substitution of a deoxy sugar spacer (5ʹ) to the target nucleotide achieved near wild-type levels of methylation. A series of atomic substitutions at specific positions on the substrate adenine show that local base-base interactions between neighbouring bases are important for methylation.

Conclusion/Significance

Taken together these data suggest that local base-base interactions play an important role in aligning the substrate 2’ hydroxyl group of A1067 for methyl group transfer. Methylation of nucleic acids is playing an increasingly important role in fundamental biological processes and we anticipate that the approach outlined in this manuscript may be useful for investigating other classes of nucleic acid methyltransferases.

Structure based approaches for targeting non-coding RNAs with small molecules

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.

Molecular dynamics simulations identify time scale of conformational changes responsible for conformational selection in molecular recognition of HIV-1 transactivation responsive RNA

The HIV-1 Tat protein and several small molecules bind to HIV-1 transactivation responsive RNA (TAR) by selecting sparsely populated but pre-existing conformations. Thus, a complete characterization of TAR conformational ensemble and dynamics is crucial to understand this paradigmatic system and could facilitate the discovery of new antivirals targeting this essential regulatory element. We show here that molecular dynamics simulations can be effectively used toward this goal by bridging the gap between functionally relevant time scales that are inaccessible to current experimental techniques. Specifically, we have performed several independent microsecond long molecular simulations of TAR based on one of the most advanced force fields available for RNA, the parmbsc0 AMBER. Our simulations are first validated against available experimental data, yielding an excellent agreement with measured residual dipolar couplings and order parameter S(2). This contrast with previous molecular dynamics simulations (Salmon et al., J. Am. Chem. Soc. 2013 135, 5457-5466) based on the CHARMM36 force field, which could achieve only modest accord with the experimental RDC values. Next, we direct the computation toward characterizing the internal dynamics of TAR over the microsecond time scale. We show that the conformational fluctuations observed over this previously elusive time scale have a strong functionally oriented character in that they are primed to sustain and assist ligand binding.

Efficient in silico exploration of RNA interhelical conformations using Euler angles and WExplore

HIV-1 TAR RNA is a two-helix bulge motif that plays a critical role in HIV viral replication and is an important drug target. However, efforts at designing TAR inhibitors have been challenged by its high degree of structural flexibility, which includes slow large-amplitude reorientations of its helices with respect to one another. Here, we use the recently introduced algorithm WExplore in combination with Euler angles to achieve unprecedented sampling of the TAR conformational ensemble. Our ensemble achieves similar agreement with experimental NMR data when compared with previous TAR computational studies, and is generated at a fraction of the computational cost. It clearly emerges from configuration space network analysis that the intermittent formation of the A22-U40 base pair acts as a reversible switch that enables sampling of interhelical conformations that would otherwise be topologically disallowed. We find that most previously determined ligand-bound structures are found in similar location in the network, and we use a sample-and-select approach to guide the construction of a set of novel conformations which can serve as the basis for future drug development efforts. Collectively, our findings demonstrate the utility of WExplore in combination with suitable order parameters as a method for exploring RNA conformational space.

Triptolide inhibits human immunodeficiency virus type 1 replication by promoting proteasomal degradation of Tat protein

Background

Plants remain an important source of new drugs, new leads and new chemical entities. Triptolide is a diterpenoid epoxide isolated from Tripterygium wilfordii Hook F that possesses a broad range of bioactivities, including anti-inflammatory, immunosuppressive and anti-tumor properties. The antiviral activity of triptolide against human immunodeficiency virus type 1 (HIV-1) has not been reported.

Results

In this study, nanomolar concentrations of triptolide were shown to potently inhibit HIV-1 replication in vitro. To identify the step(s) of the HIV-1 replication cycle affected by triptolide, time-of-addition studies, PCR analysis and direct transfection of viral genomic DNA were performed. The results of these experiments indicated that triptolide acts at the stage of viral gene transcription. In addition, a luciferase-based reporter assay that allows quantitative analysis of long terminal repeat (LTR)-driven transcription showed that Tat-induced LTR activation was impaired in the presence of triptolide. Moreover, Western blot analysis of exogenous gene expression (driven by the human elongation factor 1 α subunit promoter) in transiently transfected cells revealed that triptolide specifically reduces the steady-state level of Tat protein, without suppressing global gene expression. Further studies showed that triptolide accelerates Tat protein degradation, which can be rescued by administration of the proteasome inhibitor MG132. Mutation analysis revealed that N-terminal domains of Tat protein and nuclear localization are required for triptolide to reduce steady-state level of Tat.

Conclusion

This study suggests for the first time that triptolide exerts its anti-HIV-1 activity by specifically prompting the degradation of the virally encoded Tat protein, which is a novel mechanism of action for an anti-HIV-1 compound. This compound may serve as a starting point for developing a novel HIV-1 therapeutic approach or as a basic research tool for interrogating events during viral replication.

Multivalent Amino Sugars to Recognize Different TAR RNA Conformations

Neomycin dimers synthesized using "click chemistry" with varying functionality and length in the linker region have been shown to be effective in targeting the HIV-1 TAR RNA region of the HIV virus. TAR (Transactivation Response) RNA region, a 59 base pair stem loop structure located at the 5'-end of all nascent viral transcripts interacts with its target, a key regulatory protein, Tat, and necessitates the replication of HIV-1 virus. Ethidium bromide displacement and FRET competition assays have revealed nanomolar binding affinity between neomycin dimers and wildtype TAR RNA while in case of neomycin, only a weak binding was detected. Here, NMR and FID-based comparisons reveal an extended binding interface for neomycin dimers involving the upper stem of the TAR RNA thereby offering an explanation for increased affinities. To further explore the potential of these modified aminosugars we have extended binding studies to include four TAR RNA mutants that display conformational differences with minimal sequence variation. The differences in binding between neomycin and neomycin dimers is characterized with TAR RNA mutants that include mutations to the bulge region, hairpin region, and both the bulge and hairpin regions. Our results demonstrate the effect of these mutations on neomycin binding and our results show that linker functionalities between dimeric units of neomycin can distinguish between the conformational differences of mutant TAR RNA structures.