Structure of TAR RNA complexed with a Tat-TAR interaction nanomolar inhibitor that was identified by computational screening

SRI-30827, a novel allosteric modulator of the dopamine transporter, alleviates HIV-1 Tat-induced potentiation of cocaine conditioned place preference in mice

Objectives

HIV-1 Tat (transactivator of transcription) protein disrupts dopaminergic transmission and potentiates the rewarding effects of cocaine. Allosteric modulators of the dopamine transporter (DAT) have been shown to reverse Tat-induced DAT dysfunction. We hypothesized that a novel DAT allosteric modulator, SRI-30827, would counteract Tat-induced potentiation of cocaine reward.

Methods

Doxycycline (Dox)-inducible Tat transgenic (iTat-tg) mice and their G-tg (Tat-null) counterparts were tested in a cocaine conditioned place preference (CPP) paradigm. Mice were treated 14 days with saline, or Dox (100 mg/kg/day, i.p.) to induce Tat protein. Upon induction, mice were place conditioned two days with cocaine (10 mg/kg/day) after a 1-h daily intracerebroventricular (i.c.v.) pretreatment with SRI-30827 (1 nmol) or a vehicle control, and final place preference assessed as a measure of cocaine reward.

Results

Dox-treatment significantly potentiated cocaine-CPP in iTat-tg mice over the response of saline-treated control littermates. SRI-30827 treatment eliminated Tat-induced potentiation without altering normal cocaine-CPP in saline-treated mice. Likewise, SRI-30827 did not alter cocaine-CPP in both saline- and Dox-treated G-tg mice incapable of expressing Tat protein.

Conclusions

These findings add to a growing body of evidence that allosteric modulation of DAT could provide a promising therapeutic intervention for patients with comorbid HIV-1 and cocaine use disorder (CUD).

PERFUMES: pipeline to extract RNA functional motifs and exposed structures

MOTIVATION

Up to 75% of the human genome encodes RNAs. The function of many non-coding RNAs relies on their ability to fold into 3D structures. Specifically, nucleotides inside secondary structure loops form non-canonical base pairs that help stabilize complex local 3D structures. These RNA 3D motifs can promote specific interactions with other molecules or serve as catalytic sites.

RESULTS

We introduce PERFUMES, a computational pipeline to identify 3D motifs that can be associated with observable features. Given a set of RNA sequences with associated binary experimental measurements, PERFUMES searches for RNA 3D motifs using BayesPairing2 and extracts those that are over-represented in the set of positive sequences. It also conducts a thermodynamics analysis of the structural context that can support the interpretation of the predictions. We illustrate PERFUMES' usage on the SNRPA protein binding site, for which the tool retrieved both previously known binder motifs and new ones.

AVAILABILITY AND IMPLEMENTATION

PERFUMES is an open-source Python package (https://jwgitlab.cs.mcgill.ca/arnaud_chol/perfumes).

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.

Kinetic Resolution of the Atomic 3D Structures Formed by Ground and Excited Conformational States in an RNA Dynamic Ensemble

Knowing the 3D structures formed by the various conformations populating the RNA free-energy landscape, their relative abundance, and kinetic interconversion rates is required to obtain a quantitative and predictive understanding of how RNAs fold and function at the atomic level. While methods integrating ensemble-averaged experimental data with computational modeling are helping define the most abundant conformations in RNA ensembles, elucidating their kinetic rates of interconversion and determining the 3D structures of sparsely populated short-lived RNA excited conformational states (ESs) remains challenging. Here, we developed an approach integrating Rosetta-FARFAR RNA structure prediction with NMR residual dipolar couplings and relaxation dispersion that simultaneously determines the 3D structures formed by the ground-state (GS) and ES subensembles, their relative abundance, and kinetic rates of interconversion. The approach is demonstrated on HIV-1 TAR, whose six-nucleotide apical loop was previously shown to form a sparsely populated (∼13%) short-lived (lifetime ∼ 45 μs) ES. In the GS, the apical loop forms a broad distribution of open conformations interconverting on the pico-to-nanosecond time scale. Most residues are unpaired and preorganized to bind the Tat-superelongation protein complex. The apical loop zips up in the ES, forming a narrow distribution of closed conformations, which sequester critical residues required for protein recognition. Our work introduces an approach for determining the 3D ensemble models formed by sparsely populated RNA conformational states, provides a rare atomic view of an RNA ES, and kinetically resolves the atomic 3D structures of RNA conformational substates, interchanging on time scales spanning 6 orders of magnitude, from picoseconds to microseconds.

Small Molecules Targeting Viral RNA

The majority of antivirals available target viral proteins; however, RNA is emerging as a new and promising antiviral target due to the presence of highly structured RNA in viral genomes fundamental for their replication cycle. Here, we discuss methods for the identification of RNA-targeting compounds, starting from the determination of RNA structures either from purified RNA or in living cells, followed by in silico screening on RNA and phenotypic assays to evaluate viral inhibition. Moreover, we review the small molecules known to target the programmed ribosomal frameshifting element of SARS-CoV-2, the internal ribosomal entry site of different viruses, and RNA elements of HIV.

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.

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 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.

Targeting Tat-TAR RNA Interaction for HIV-1 Inhibition

The HIV-1 Tat protein interacts with TAR RNA and recruits CDK9/cyclin T1 and other host factors to induce HIV-1 transcription. Thus, Tat–TAR RNA interaction, which is unique for HIV-1, represents an attractive target for anti-HIV-1 therapeutics. To target Tat–TAR RNA interaction, we used a crystal structure of acetylpromazine bound to the bulge of TAR RNA, to dock compounds from the Enamine database containing over two million individual compounds. The docking procedure identified 173 compounds that were further analyzed for the inhibition of HIV-1 infection. The top ten inhibitory compounds with IC₅₀ ≤ 6 µM were selected and the three least toxic compounds, T6780107 (IC₅₀ = 2.97 μM), T0516-4834 (IC₅₀ = 0.2 μM) and T5628834 (IC₅₀ = 3.46 μM), were further tested for HIV-1 transcription inhibition. Only the T0516-4834 compound showed selective inhibition of Tat-induced HIV-1 transcription, whereas the T6780107 compound inhibited equally basal and Tat-induced transcription and the T5628834 compound only inhibited basal HIV-1 transcription. The compounds were tested for the inhibition of translation and showed minimal (<25%) effect. The T0516-4834 compound also showed the strongest inhibition of HIV-1 RNA expression and p24 production in CEM T cells and peripheral blood mononuclear cells infected with HIV-1 IIIB. Of the three compounds, only the T0516-4834 compound significantly disrupted Tat–TAR RNA interaction. Additionally, of the three tested compounds, T5628834 and, to a lesser extent, T0516-4834 disrupted Tat–CDK9/cyclin T1 interaction. None of the three compounds showed significant inhibition of the cellular CDK9 and cyclin T1 levels. In silico modelling showed that the T0516-4834 compound interacted with TAR RNA by binding to the bulge formed by U23, U25, C39, G26,C39 and U40 residues. Taken together, our study identified a novel benzoxazole compound that disrupted Tat–TAR RNA interaction and inhibited Tat-induced transcription and HIV-1 infection, suggesting that this compound might serve as a new lead for anti-HIV-1 therapeutics.

RPocket: an intuitive database of RNA pocket topology information with RNA-ligand data resources

Background

RNA regulates a variety of biological functions by interacting with other molecules. The ligand often binds in the RNA pocket to trigger structural changes or functions. Thus, it is essential to explore and visualize the RNA pocket to elucidate the structural and recognition mechanism for the RNA-ligand complex formation.

Results

In this work, we developed one user-friendly bioinformatics tool, RPocket. This database provides geometrical size, centroid, shape, secondary structure element for RNA pocket, RNA-ligand interaction information, and functional sites. We extracted 240 RNA pockets from 94 non-redundant RNA-ligand complex structures. We developed RPDescriptor to calculate the pocket geometrical property quantitatively. The geometrical information was then subjected to RNA-ligand binding analysis by incorporating the sequence, secondary structure, and geometrical combinations. This new approach takes advantage of both the atom-level precision of the structure and the nucleotide-level tertiary interactions. The results show that the higher-level topological pattern indeed improves the tertiary structure prediction. We also proposed a potential mechanism for RNA-ligand complex formation. The electrostatic interactions are responsible for long-range recognition, while the Van der Waals and hydrophobic contacts for short-range binding and optimization. These interaction pairs can be considered as distance constraints to guide complex structural modeling and drug design.

Conclusion

RPocket database would facilitate RNA-ligand engineering to regulate the complex formation for biological or medical applications. RPocket is available at http://zhaoserver.com.cn/RPocket/RPocket.html.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04349-4.

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.

A New Approach to 3D Modeling of Inhomogeneous Populations of Viral Regulatory RNA

Tertiary structure (3D) is the physical context of RNA regulatory activity. Retroviruses are RNA viruses that replicate through the proviral DNA intermediate transcribed by hosts. Proviral transcripts form inhomogeneous populations due to variable structural ensembles of overlapping regulatory RNA motifs in the 5′-untranslated region (UTR), which drive RNAs to be spliced or translated, and/or dimerized and packaged into virions. Genetic studies and structural techniques have provided fundamental input constraints to begin predicting HIV 3D conformations in silico. Using SimRNA and sets of experimentally-determined input constraints of HIV^NL4-3 trans-activation responsive sequence (TAR) and pairings of unique-5′ (U5) with dimerization (DIS) or AUG motifs, we calculated a series of 3D models that differ in proximity of 5′-Cap and the junction of TAR and PolyA helices; configuration of primer binding site (PBS)-segment; and two host cofactors binding sites. Input constraints on U5-AUG pairings were most compatible with intramolecular folding of 5′-UTR motifs in energetic minima. Introducing theoretical constraints predicted metastable PolyA region drives orientation of 5′-Cap with TAR, U5 and PBS-segment helices. SimRNA and the workflow developed herein provides viable options to predict 3D conformations of inhomogeneous populations of large RNAs that have been intractable to conventional ensemble methods.

Ligand Recognition in Viral RNA Necessitates Rare Conformational Transitions

Ribonucleic acids (RNAs) are conformationally flexible molecules that fold into three-dimensional structures and play an important role in different cellular processes as well as in the development of many diseases. RNA has therefore become an important target for developing novel therapeutic approaches. The biophysical processes underlying RNA function are often associated with rare structural transitions that play a key role in ligand recognition. In this work, we probe these rarely occurring transitions using nonequilibrium simulations by characterizing the dissociation of a ligand molecule from an HIV-1 viral RNA element. Specifically, we observed base-flipping rare events that are coupled with ligand binding/unbinding and also provided mechanistic details underlying these transitions.

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.

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.

In silico Analyses of Subtype Specific HIV-1 Tat-TAR RNA Interaction Reveals the Structural Determinants for Viral Activity

HIV-1 Tat transactivates viral genes through strong interaction with TAR RNA. The stem-loop bulged region of TAR consisting of three nucleotides at the position 23–25 and the loop region consisting of six nucleotides at the position 30–35 are essential for viral transactivation. The arginine motif of Tat (five arginine residues on subtype TatC) is critically important for TAR interaction. Any mutations in this motif could lead to reduce transactivation ability and pathogenesis. Here, we identified structurally important residues (arginine and lysine residues) of Tat in this motif could bind to TAR via hydrogen bond interactions which is critical for transactivation. Natural mutant Ser46Phe in the core motif could likely led to conformational change resulting in more hydrogen bond interactions than the wild type Tat making it highly potent transactivator. Importantly, we report the possible probabilities of number of hydrogen bond interactions in the wild type Tat and the mutants with TAR complexes. This study revealed the differential transactivation of subtype B and C Tat could likely be due to the varying number of hydrogen bonds with TAR. Our data support that the N-terminal and the C-terminal domains of Tat is involved in the TAR interactions through hydrogen bonds which is important for transactivation. This study highlights the evolving pattern of structurally important determinants of Tat in the arginine motif for viral transactivation.

Inhibition of Bacterial RNase P RNA by Phenothiazine Derivatives

There is a need to identify novel scaffolds and targets to develop new antibiotics. Methylene blue is a phenothiazine derivative, and it has been shown to possess anti-malarial and anti-trypanosomal activities. Here, we show that different phenothiazine derivatives and pyronine G inhibited the activities of three structurally different bacterial RNase P RNAs (RPRs), including that from Mycobacterium tuberculosis, with Ki values in the lower μM range. Interestingly, three antipsychotic phenothiazines (chlorpromazine, thioridazine, and trifluoperazine), which are known to have antibacterial activities, also inhibited the activity of bacterial RPRs, albeit with higher Ki values than methylene blue. Phenothiazines also affected lead(II)-induced cleavage of bacterial RPR and inhibited yeast tRNA(Phe), indicating binding of these drugs to functionally important regions. Collectively, our findings provide the first experimental data showing that long, noncoding RNAs could be targeted by different phenothiazine derivatives.

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.

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.

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.

Identification of biologically active, HIV TAR RNA-binding small molecules using small molecule microarrays

Identifying small molecules that selectively bind to structured RNA motifs remains an important challenge in developing potent and specific therapeutics. Most strategies to find RNA-binding molecules have identified highly charged compounds or aminoglycosides that commonly have modest selectivity. Here we demonstrate a strategy to screen a large unbiased library of druglike small molecules in a microarray format against an RNA target. This approach has enabled the identification of a novel chemotype that selectively targets the HIV transactivation response (TAR) RNA hairpin in a manner not dependent on cationic charge. Thienopyridine 4 binds to and stabilizes the TAR hairpin with a Kd of 2.4 μM. Structure-activity relationships demonstrate that this compound achieves activity through hydrophobic and aromatic substituents on a heterocyclic core, rather than cationic groups typically required. Selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) analysis was performed on a 365-nucleotide sequence derived from the 5' untranslated region (UTR) of the HIV-1 genome to determine global structural changes in the presence of the molecule. Importantly, the interaction of compound 4 can be mapped to the TAR hairpin without broadly disrupting any other structured elements of the 5' UTR. Cell-based anti-HIV assays indicated that 4 inhibits HIV-induced cytopathicity in T lymphocytes with an EC50 of 28 μM, while cytotoxicity was not observed at concentrations approaching 1 mM.

Coarse grained models reveal essential contributions of topological constraints to the conformational free energy of RNA bulges

Recent studies have shown that simple stereochemical constraints encoded at the RNA secondary structure level significantly restrict the orientation of RNA helices across two-way junctions and yield physically reasonable distributions of RNA 3D conformations. Here we develop a new coarse-grain model, TOPRNA, that is optimized for exploring detailed aspects of these topological constraints in complex RNA systems. Unlike prior models, TOPRNA effectively treats RNAs as collections of semirigid helices linked by freely rotatable single strands, allowing us to isolate the effects of secondary structure connectivity and sterics on 3D structure. Simulations of bulge junctions show that TOPRNA captures new aspects of topological constraints, including variations arising from deviations in local A-form structure, translational displacements of the helices, and stereochemical constraints imposed by bulge-linker nucleotides. Notably, these aspects of topological constraints define free energy landscapes that coincide with the distribution of bulge conformations in the PDB. Our simulations also quantitatively reproduce NMR RDC measurements made on HIV-1 TAR at low salt concentrations, although not for different TAR mutants or at high salt concentrations. Our results confirm that topological constraints are an important determinant of bulge conformation and dynamics and demonstrate the utility of TOPRNA for studying the topological constraints of complex RNAs.

NMR studies of nucleic acid dynamics

Nucleic acid structures have to satisfy two diametrically opposite requirements; on one hand they have to adopt well-defined 3D structures that can be specifically recognized by proteins; on the other hand, their structures must be sufficiently flexible to undergo very large conformational changes that are required during key biochemical processes, including replication, transcription, and translation. How do nucleic acids introduce flexibility into their 3D structure without losing biological specificity? Here, I describe the development and application of NMR spectroscopic techniques in my laboratory for characterizing the dynamic properties of nucleic acids that tightly integrate a broad set of NMR measurements, including residual dipolar couplings, spin relaxation, and relaxation dispersion with sample engineering and computational approaches. This approach allowed us to obtain fundamental new insights into directional flexibility in nucleic acids that enable their structures to change in a very specific functional manner.

Enhanced sampling and overfitting analyses in structural refinement of nucleic acids into electron microscopy maps

Flexible fitting computational algorithms are often useful to interpret low-resolution maps of many macromolecular complexes generated by electron microscopy (EM) imaging. One such atomistic simulation technique is molecular dynamics flexible fitting (MDFF), which has been widely applied to generate structural models of large ribonucleoprotein assemblies such as the ribosome. We have previously shown that MDFF simulations of globular proteins are sensitive to the resolution of the target EM map and the strength of restraints used to preserve the secondary structure elements during fitting (Vashisth, H.; et al. Structure 2012, 20, 1453-1462). In this work, we aim to systematically examine the quality of structural models of various nucleic acids obtained via MDFF by varying the map resolution and the strength of structural restraints. We also demonstrate how an enhanced conformational sampling technique for proteins, temperature-accelerated molecular dynamics (TAMD), can be combined with MDFF for the structural refinement of nucleic acids in EM maps. Finally, we also demonstrate application of TAMD-assisted MDFF (TAMDFF) on a RNA/protein complex and suggest that TAMDFF is a viable strategy for enhanced conformational fitting in target maps of ribonucleoprotein complexes.

Novel insights of structure-based modeling for RNA-targeted drug discovery

Substantial progress in RNA biology highlights the importance of RNAs (e.g., microRNAs) in diseases and the potential of targeting RNAs for drug discovery. However, the lack of RNA-specific modeling techniques demands the development of new tools for RNA-targeted rational drug design. Herein, we implemented integrated approaches of accurate RNA modeling and virtual screening for RNA inhibitor discovery with the most comprehensive evaluation to date of five docking and 11 scoring methods. For the first time, statistical analysis was heavily employed to assess the significance of our predictions. We found that GOLD:GOLD Fitness and rDock:rDock_solv could accurately predict the RNA ligand poses, and ASP rescoring further improved the ranking of ligand binding poses. Due to the weak correlations (R(2) < 0.3) of existing scoring with experimental binding affinities, we implemented two new RNA-specific scoring functions, iMDLScore1 and iMDLScore2, and obtained better correlations with R(2) = 0.70 and 0.79, respectively. We also proposed a multistep virtual screening approach and demonstrated that rDock:rDock_solv together with iMDLScore2 rescoring obtained the best enrichment on the flexible RNA targets, whereas GOLD:GOLD Fitness combined with rDock_solv rescoring outperformed other methods for rigid RNAs. This study provided practical strategies for RNA modeling and offered new insights into RNA-small molecule interactions for drug discovery.

A small-molecule probe induces a conformation in HIV TAR RNA capable of binding drug-like fragments

The HIV-1 transactivation response (TAR) element-Tat interaction is a potentially valuable target for treating HIV infection, but efforts to develop TAR-binding antiviral drugs have not yet yielded a successful candidate for clinical development. In this work, we describe a novel approach toward screening fragments against RNA that uses a chemical probe to target the Tat-binding region of TAR. This probe fulfills two critical roles in the screen: by locking the RNA into a conformation capable of binding other fragments, it simultaneously allows the identification of proximal binding fragments by ligand-based NMR. Using this approach, we have discovered six novel TAR-binding fragments, three of which were docked relative to the probe-RNA structure using experimental NMR restraints. The consistent orientations of functional groups in our data-driven docked structures and common electrostatic properties across all fragment leads reveal a surprising level of selectivity by our fragment-sized screening hits. These models further suggest linking strategies for the development of higher-affinity lead compounds for the inhibition of the TAR-Tat interaction.

Dynamic ensemble view of the conformational landscape of HIV-1 TAR RNA and allosteric recognition

RNA conformational dynamics and the resulting structural heterogeneity play an important role in RNA functions, e.g., recognition. Recognition of HIV-1 TAR RNA has been proposed to occur via a conformational capture mechanism. Here, using ultrafast time-resolved fluorescence spectroscopy, we have probed the complexity of the conformational landscape of HIV-1 TAR RNA and monitored the position-dependent changes in the landscape upon binding of a Tat protein-derived peptide and neomycin B. In the ligand-free state, the TAR RNA samples multiple families of conformations with various degrees of base stacking around the three-nucleotide bulge region. Some subpopulations partially resemble those ligand-bound states, but the coaxially stacked state is below the detection limit. When Tat or neomycin B binds, the bulge region as an ensemble undergoes a conformational transition in a position-dependent manner. Tat and neomycin B induce mutually exclusive changes in the TAR RNA underlying the mechanism of allosteric inhibition at an ensemble level with residue-specific details. Time-resolved anisotropy decay measurements revealed picosecond motions of bases in both ligand-free and ligand-bound states. Mutation of a base pair at the bulge--stem junction has differential effects on the conformational distributions of the bulge bases. A dynamic model of the ensemble view of the conformational landscape for HIV-1 TAR RNA is proposed, and the implication of the general mechanism of RNA recognition and its impact on RNA-based therapeutics are discussed.

HIV-1 TAR RNA spontaneously undergoes relevant apo-to-holo conformational transitions in molecular dynamics and constrained geometrical simulations

We report all-atom molecular dynamics and replica exchange molecular dynamics simulations on the unbound human immunodeficiency virus type-1 (HIV-1) transactivation responsive region (TAR) RNA structure and three TAR RNA structures in bound conformations of, in total, approximately 250 ns length. We compare the extent of observed conformational sampling with that of the conceptually simpler and computationally much cheaper constrained geometrical simulation approach framework rigidity optimized dynamic algorithm (FRODA). Atomic fluctuations obtained by replica-exchange molecular dynamics (REMD) simulations agree quantitatively with those obtained by molecular dynamics (MD) and FRODA simulations for the unbound TAR structure. Regarding the stereochemical quality of the generated conformations, backbone torsion angles and puckering modes of the sugar-phosphate backbone were reproduced equally well by MD and REMD simulations, but further improvement is needed in the case of FRODA simulations. Essential dynamics analysis reveals that all three simulation approaches show a tendency to sample bound conformations when starting from the unbound TAR structure, with MD and REMD simulations being superior with respect to FRODA. These results are consistent with the experimental view that bound TAR RNA conformations are transiently sampled in the free ensemble, following a conformation selection model. The simulation-generated TAR RNA conformations have been successfully used as receptor structures for docking. This finding has important implications for RNA-ligand docking in that docking into an ensemble of simulation-generated RNA structures is shown to be a valuable means to cope with large apo-to-holo conformational transitions of the receptor structure.

Base pairs and pseudo pairs observed in RNA-ligand complexes

Previously, a geometric nomenclature was proposed in which RNA base pairs were classified by their interaction edges (Watson-Crick, Hoogsteen or sugar-edge) and the glycosidic bond orientations relative to the hydrogen bonds formed (cis or trans). Here, base pairs and pseudo pairs observed in RNA-ligand complexes are classified in a similar manner. Twenty-one basic geometric families are geometrically possible (18 for base pairs formed between a nucleic acid base and a ligand containing heterocycle and 3 families for pseudo pairs). Of those, 16 of them have been observed in X-ray and/or NMR structures.

Domain-elongation NMR spectroscopy yields new insights into RNA dynamics and adaptive recognition

By simplifying the interpretation of nuclear magnetic resonance spin relaxation and residual dipolar couplings data, recent developments involving the elongation of RNA helices are providing new atomic insights into the dynamical properties that allow RNA structures to change functionally and adaptively. Domain elongation, in concert with spin relaxation measurements, has allowed the detailed characterization of a hierarchical network of local and collective motional modes occurring at nanosecond timescale that mirror the structural rearrangements that take place following adaptive recognition. The combination of domain elongation with residual dipolar coupling measurements has allowed the experimental three-dimensional visualization of very large amplitude rigid-body helix motions in HIV-1 transactivation response element (TAR) that trace out a highly choreographed trajectory in which the helices twist and bend in a correlated manner. The dynamic trajectory allows unbound TAR to sample many of its ligand bound conformations, indicating that adaptive recognition occurs by "conformational selection" rather than "induced fit." These studies suggest that intrinsic flexibility plays essential roles directing RNA conformational changes along specific pathways.

Constructing RNA dynamical ensembles by combining MD and motionally decoupled NMR RDCs: new insights into RNA dynamics and adaptive ligand recognition

We describe a strategy for constructing atomic resolution dynamical ensembles of RNA molecules, spanning up to millisecond timescales, that combines molecular dynamics (MD) simulations with NMR residual dipolar couplings (RDC) measured in elongated RNA. The ensembles are generated via a Monte Carlo procedure by selecting snap-shot from an MD trajectory that reproduce experimentally measured RDCs. Using this approach, we construct ensembles for two variants of the transactivation response element (TAR) containing three (HIV-1) and two (HIV-2) nucleotide bulges. The HIV-1 TAR ensemble reveals significant mobility in bulge residues C24 and U25 and to a lesser extent U23 and neighboring helical residue A22 that give rise to large amplitude spatially correlated twisting and bending helical motions. Omission of bulge residue C24 in HIV-2 TAR leads to a significant reduction in both the local mobility in and around the bulge and amplitude of inter-helical bending motions. In contrast, twisting motions of the helices remain comparable in amplitude to HIV-1 TAR and spatial correlations between them increase significantly. Comparison of the HIV-1 TAR dynamical ensemble and ligand bound TAR conformations reveals that several features of the binding pocket and global conformation are dynamically preformed, providing support for adaptive recognition via a ‘conformational selection’ type mechanism.

Discovery of ligands for a novel target, the human telomerase RNA, based on flexible-target virtual screening and NMR

The human ribonucleoprotein telomerase is a validated anticancer drug target, and hTR-P2b is a part of the human telomerase RNA (hTR) essential for its activity. Interesting ligands that bind hTR-P2b were identified by iteratively using a tandem structure-based approach: docking of potential ligands from small databases to hTR-P2b via the program MORDOR, which permits flexibility in both ligand and target, with subsequent NMR screening of high-ranking compounds. A high percentage of the compounds tested experimentally were found via NMR to bind to the U-rich region of hTR-P2b; most have MW < 500 Da and are from different compound classes, and several possess a charge of 0 or +1. Of the 48 ligands identified, 24 exhibit a decided preference to bind hTR-P2b RNA rather than A-site rRNA and 10 do not bind A-site rRNA at all. Binding affinity was measured by monitoring RNA imino proton resonances for some of the compounds that showed hTR binding preference.

Insight into the mechanisms of aminoglycoside derivatives interaction with HIV-1 entry steps and viral gene transcription

In recent years, based on peptide models of HIV-1 RNA binding, NMR structures of Tat-responsive element-ligand complexes and aminoglycoside-RNA interactions, and HIV-1 Tat structure, we have designed and synthesized aminoglycoside-arginine conjugates (AACs) and aminoglycoside poly-arginine conjugates (APACs), to serve as Tat mimetics. These novel molecules inhibit HIV-1 infectivity with 50% effective concentration values in the low micromolar range, the most potent compounds being the hexa-arginine-neomycin B and nona-D-arginine-neomycin conjugates. Importantly, these compounds, in addition to acting as Tat antagonists, inhibit HIV-1 infectivity by blocking several steps in HIV-1 cell entry. The AACs and APACs inhibit HIV-1 cell entry by interacting with gp120 at the CD4-binding site, by interacting with CXCR4 at the binding site of the CXCR4 mAb 12G5, and apparently by interacting with transient structures of the ectodomain of gp41. In the current review, we discuss the mechanisms of anti-HIV-1 activities of these AACs, APACs and other aminoglycoside derivatives in detail. Targeting several key processes in the viral life cycle by the same compound not only may increase its antiviral efficacy, but more importantly, may reduce the capacity of the virus to develop resistance to the compound. AACs and APACs may thus serve as leading compounds for the development of multitargeting novel HIV-1 inhibitors.

Characterizing complex dynamics in the transactivation response element apical loop and motional correlations with the bulge by NMR, molecular dynamics, and mutagenesis

The HIV-1 transactivation response element (TAR) RNA binds a variety of proteins and is a target for developing anti-HIV therapies. TAR has two primary binding sites: a UCU bulge and a CUGGGA apical loop. We used NMR residual dipolar couplings, carbon spin relaxation (R(1) and R(2)), and relaxation dispersion (R(1rho)) in conjunction with molecular dynamics and mutagenesis to characterize the dynamics of the TAR apical loop and investigate previously proposed long-range interactions with the distant bulge. Replacement of the wild-type apical loop with a UUCG loop did not significantly affect the structural dynamics at the bulge, indicating that the apical loop and the bulge act largely as independent dynamical recognition centers. The apical loop undergoes complex dynamics at multiple timescales that are likely important for adaptive recognition: U31 and G33 undergo limited motions, G32 is highly flexible at picosecond-nanosecond timescales, and G34 and C30 form a dynamic Watson-Crick basepair in which G34 and A35 undergo a slow (approximately 30 mus) likely concerted looping in and out motion, with A35 also undergoing large amplitude motions at picosecond-nanosecond timescales. Our study highlights the power of combining NMR, molecular dynamics, and mutagenesis in characterizing RNA dynamics.

Tripeptides from synthetic amino acids block the Tat-TAR association and slow down HIV spread in cell cultures

Non-natural amino acids with aromatic or heteroaromatic side chains were incorporated into tripeptides of the general structure Arg-X-Arg and tested as ligands of the HIV RNA element TAR. Some of these compounds could compete efficiently with the association of TAR and Tat and downregulated a TAR-controlled reporter gene in HeLa cells. Peptide 7, which contains a 2-pyrimidinyl-alkyl chain, also inhibited the spread of HIV-1 in cell cultures. NMR studies of 7 bound to HIV-2-TAR gave evidence for contacts in the bulge region.

Visualizing spatially correlated dynamics that directs RNA conformational transitions

RNAs fold into three-dimensional (3D) structures that subsequently undergo large, functionally important, conformational transitions in response to a variety of cellular signals. RNA structures are believed to encode spatially tuned flexibility that can direct transitions along specific conformational pathways. However, this hypothesis has proved difficult to examine directly because atomic movements in complex biomolecules cannot be visualized in 3D by using current experimental methods. Here we report the successful implementation of a strategy using NMR that has allowed us to visualize, with complete 3D rotational sensitivity, the dynamics between two RNA helices that are linked by a functionally important trinucleotide bulge over timescales extending up to milliseconds. The key to our approach is to anchor NMR frames of reference onto each helix and thereby directly measure their dynamics, one relative to the other, using 'relativistic' sets of residual dipolar couplings (RDCs). Using this approach, we uncovered super-large amplitude helix motions that trace out a surprisingly structured and spatially correlated 3D dynamic trajectory. The two helices twist around their individual axes by approximately 53 degrees and 110 degrees in a highly correlated manner (R = 0.97) while simultaneously (R = 0.81-0.92) bending by about 94 degrees. Remarkably, the 3D dynamic trajectory is dotted at various positions by seven distinct ligand-bound conformations of the RNA. Thus even partly unstructured RNAs can undergo structured dynamics that directs ligand-induced transitions along specific predefined conformational pathways.

The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA

Principles of fragment-based molecular design are presented and discussed in the context of de novo drug design. The underlying idea is to dissect known drug molecules in fragments by straightforward pseudo-retro-synthesis. The resulting building blocks are then used for automated assembly of new molecules. A particular question has been whether this approach is actually able to perform scaffold-hopping. A prospective case study illustrates the usefulness of fragment-based de novo design for finding new scaffolds. We were able to identify a novel ligand disrupting the interaction between the Tat peptide and TAR RNA, which is part of the human immunodeficiency virus (HIV-1) mRNA. Using a single template structure (acetylpromazine) as reference molecule and a topological pharmacophore descriptor (CATS), new chemotypes were automatically generated by our de novo design software Flux. Flux features an evolutionary algorithm for fragment-based compound assembly and optimization. Pharmacophore superimposition and docking into the target RNA suggest perfect matching between the template molecule and the designed compound. Chemical synthesis was straightforward, and bioactivity of the designed molecule was confirmed in a FRET assay. This study demonstrates the practicability of de novo design to generating RNA ligands containing novel molecular scaffolds.

NMR studies of RNA dynamics and structural plasticity using NMR residual dipolar couplings

An increasing number of RNAs are being discovered that perform their functions by undergoing large changes in conformation in response to a variety of cellular signals, including recognition of proteins and small molecular targets, changes in temperature, and RNA synthesis itself. The measurement of NMR residual dipolar couplings (RDCs) in partially aligned systems is providing new insights into the structural plasticity of RNA through combined characterization of large-amplitude collective helix motions and local flexibility in noncanonical regions over a wide window of biologically relevant timescales (<milliseconds). Here, we review RDC methodology for studying RNA structural dynamics and survey what has been learnt thus far from application of these methods. Future methodological challenges are also identified.

Characterizing the relative orientation and dynamics of RNA A-form helices using NMR residual dipolar couplings

We present a protocol for determining the relative orientation and dynamics of A-form helices in 13C/15N isotopically enriched RNA samples using NMR residual dipolar couplings (RDCs). Non-terminal Watson-Crick base pairs in helical stems are experimentally identified using NOE and trans-hydrogen bond connectivity and modeled using the idealized A-form helix geometry. RDCs measured in the partially aligned RNA are used to compute order tensors describing average alignment of each helix relative to the applied magnetic field. The order tensors are translated into Euler angles defining the average relative orientation of helices and order parameters describing the amplitude and asymmetry of interhelix motions. The protocol does not require complete resonance assignments and therefore can be implemented rapidly to RNAs much larger than those for which complete high-resolution NMR structure determination is feasible. The protocol is particularly valuable for exploring adaptive changes in RNA conformation that occur in response to biologically relevant signals. Following resonance assignments, the procedure is expected to take no more than 2 weeks of acquisition and data analysis time.

Probing Na(+)-induced changes in the HIV-1 TAR conformational dynamics using NMR residual dipolar couplings: new insights into the role of counterions and electrostatic interactions in adaptive recognition

Many regulatory RNAs undergo large changes in structure upon recognition of proteins and ligands, but the mechanism by which this occurs remains poorly understood. Using NMR residual dipolar coupling (RDCs), we characterized Na+-induced changes in the structure and dynamics of the bulge-containing HIV-1 transactivation response element (TAR) RNA that mirrors changes induced by small molecules bearing a different number of cationic groups. Increasing the Na+ concentration from 25 to 320 mM led to a continuous reduction in the average inter-helical bend angle (from 46 degrees to 22 degrees ), inter-helical twist angle (from 66 degrees to -18 degrees ), and inter-helix flexibility (as measured by an increase in the internal generalized degree of order from 0.56 to 0.74). Similar conformational changes were observed with Mg2+, indicating that nonspecific electrostatic interactions drive the conformational transition, although results also suggest that Na+ and Mg2+ may associate with TAR in distinct modes. The transition can be rationalized on the basis of a population-weighted average of two ensembles comprising an electrostatically relaxed bent and flexible TAR conformation that is weakly associated with counterions and a globally rigid coaxial conformation that has stronger electrostatic potential and association with counterions. The TAR inter-helical orientations that are stabilized by small molecules fall around the metal-induced conformational pathway, indicating that counterions may help predispose the TAR conformation for target recognition. Our results underscore the intricate sensitivity of RNA conformational dynamics to environmental conditions and demonstrate the ability to detect subtle conformational changes using NMR RDCs.