Conformation of the TAR RNA-arginine complex by NMR spectroscopy

Decoding the enigma of RNA-protein recognition: quantum chemical insights into arginine fork motifs

Arginine (Arg) forks are noncovalent recognition motifs wherein an Arg interacts with the phosphates and guanine nucleobases of RNA, providing extraordinary specific RNA:protein recognition. In this work, we carried out an in-depth DFT based quantum mechanical investigation on all known classes of Arg forks to estimate their intrinsic structural stabilities and interaction energies. The optimized structures closely mimic the structural characteristics of Arg forks and this close match between experimental and optimized geometries suggests that Arg forks are intrinsically stable and do not require additional support from other RNA or protein components. Both hydrogen-bonding and cation-π interactions are important for the intrinsic stability of Arg forks, providing an average interaction energy of -36.7 kcal mol-1. Furthermore, we found a direct correlation between Arg forks' interaction energies and the number of phosphates involved, which is more delicately modulated by other factors, like the types of hydrogen bonds and cation-π interactions that constitute the Arg fork. Additionally, we observed a positive correlation between the average interaction energies of Arg forks and the frequency of their occurrence in available crystal structures. At the broader level, this work establishes the groundwork for more precise modeling and understanding of RNA-protein interfaces, which could have potential implications in advancing the knowledge of biomolecular recognition patterns.

Design of deep-red emissive forced intercalation-induced light-up peptide as an indicator for the HIV-1 TAR RNA-ligand assay: integration of benzo[c,d]indole-quinoline (BIQ) cyanine dye into Tat peptide

We report on a deep-red emissive fluorogenic peptide probe for human immunodeficiency virus-1 (HIV-1) trans-activation responsive (TAR) RNA as an indicator for fluorescence indicator displacement (FID) assay. The probe design is based on the concept of the forced intercalation of thiazole orange (TO) dyes (FIT) on the peptide backbone, as recently proposed by our group, where the Q (glutamic acid) residue in the Tat peptide (RKKRR-Q-RRR) is replaced with TO as if it were an amino acid surrogate. Here, instead of green emissive TO, we utilized a deep-red emissive benzo[c,d]indole-quinoline (BIQ) cyanine dye developed previously by our group for imaging of nucleolar RNA in living cells. The developed 9-mer FIT peptide (RKKRR-BIQ-RRR; named BIQ-FiLuP) exhibits a significant off-on signaling ability for TAR RNA (λem = 660 nm, I/I0 = 130-fold, Φfree = 0.0009, Φbound = 0.052), and the dissociation constant Kd reaches ca. 1 nM. When used in FID assay, BIQ-FiLuP, like TO-based FiLuP, is able to distinguish between competitive and noncompetitive inhibitors, which has never been demonstrated with all previous indicators for TAR RNA. Deep-red emissive BIQ-FiLuP facilitates the evaluation of green to yellow emissive ligands without suffering from optical interference. The combination use with green emissive TO-based FiLuP (λem = 541 nm) would cover the examination of a wide range of fluorescent test compounds.

Forced intercalation-induced light-up peptides as fluorogenic indicators for the HIV-1 TAR RNA-ligand assay

Fluorescence indicators capable of binding to human immunodeficiency virus-1 (HIV-1) trans-activation responsive (TAR) RNA are powerful tools for the exploratory studies of the identification of anti-HIV drug candidates. This work presents a new design strategy for fluorogenic indicators with a transactivator of transcription (Tat)-derived peptide based on the forced intercalation of thiazole orange (TO) dyes (FIT). The developed 9-mer FIT peptide (RKKRR-TO-RRR: named FiLuP) features the TO unit integrated onto a Dap (2,3-diaminopropionic acid) residue in the middle of the Tat peptide sequence; the Q (glutamic acid) residue in the Tat peptide (RKKRR-Q-RRR) is replaced with TO as if it were an amino acid surrogate. This facilitates a significant light-up response (450-fold at λem = 541 nm, Φfree = 0.0057, and Φbound = 0.61) upon binding to TAR RNA. The response of FiLuP is highly selective to TAR RNA over other non-cognate RNAs, and FiLuP maintains strong binding affinity (Kd = 1.0 ± 0.6 nM). Significantly, in contrast to previously developed Tat peptide-based FRET probes, FiLuP is able to discriminate between "competitive" and "noncompetitive" inhibitors when used in the fluorescence indicator displacement (FID) assay. The FID assay under stringent screening conditions is also possible, enabling super-strong competitive binders toward TAR RNA to be sieved out.

RNA's Dynamic Conformational Selection and Entropic Allosteric Mechanism in Controlling Cascade Protein Binding Events

In the TAR RNA of immunodeficiency viruses, an allosteric communication exists between a distant loop and a bulge. The bulge interacts with the TAT protein vital for transactivating viral RNA, while the loop interacts with cyclin-T1, contingent on TAT binding. Through extensive atomistic and free energy simulations, we investigate TAR-TAT binding in nonpathogenic bovine immunodeficiency virus (BIV) and pathogenic human immunodeficiency virus (HIV). Thermodynamic analysis reveals enthalpically driven binding in BIV and entropically favored binding in HIV. The broader global basin in HIV is attributed to binding-induced loop fluctuation, corroborated by nuclear magnetic resonance (NMR), indicating classical entropic allostery onset. While this loop fluctuation affects the TAT binding affinity, it generates a binding-competent conformation that aids subsequent effector (cyclin-T1) binding. This study underscores how two structurally similar apo-RNA scaffolds adopt distinct conformational selection mechanisms to drive enthalpic and entropic allostery, influencing protein affinity in the signaling cascade.

Molecular insights into the interaction between a disordered protein and a folded RNA

Intrinsically disordered protein regions (IDRs) are well-established as contributors to intermolecular interactions and the formation of biomolecular condensates. In particular, RNA-binding proteins (RBPs) often harbor IDRs in addition to folded RNA-binding domains that contribute to RBP function. To understand the dynamic interactions of an IDR-RNA complex, we characterized the RNA-binding features of a small (68 residues), positively charged IDR-containing protein, SERF. At high concentrations, SERF and RNA undergo charge-driven associative phase separation to form a protein- and RNA-rich dense phase. A key advantage of this model system is that this threshold for demixing is sufficiently high that we could use solution-state biophysical methods to interrogate the stoichiometric complexes of SERF with RNA in the one-phase regime. Herein, we describe our comprehensive characterization of SERF alone and in complex with a small fragment of the HIV-1 TAR RNA (TAR) with complementary biophysical methods and molecular simulations. We find that this binding event is not accompanied by the acquisition of structure by either molecule; however, we see evidence for a modest global compaction of the SERF ensemble when bound to RNA. This behavior likely reflects attenuated charge repulsion within SERF via binding to the polyanionic RNA and provides a rationale for the higher-order assembly of SERF in the context of RNA. We envision that the SERF-RNA system will lower the barrier to accessing the details that support IDR-RNA interactions and likewise deepen our understanding of the role of IDR-RNA contacts in complex formation and liquid-liquid phase separation.

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.

Structural interaction fingerprints and machine learning for predicting and explaining binding of small molecule ligands to RNA

Ribonucleic acids (RNAs) play crucial roles in living organisms and some of them, such as bacterial ribosomes and precursor messenger RNA, are targets of small molecule drugs, whereas others, e.g. bacterial riboswitches or viral RNA motifs are considered as potential therapeutic targets. Thus, the continuous discovery of new functional RNA increases the demand for developing compounds targeting them and for methods for analyzing RNA-small molecule interactions. We recently developed fingeRNAt-a software for detecting non-covalent bonds formed within complexes of nucleic acids with different types of ligands. The program detects several non-covalent interactions and encodes them as structural interaction fingerprint (SIFt). Here, we present the application of SIFts accompanied by machine learning methods for binding prediction of small molecules to RNA. We show that SIFt-based models outperform the classic, general-purpose scoring functions in virtual screening. We also employed Explainable Artificial Intelligence (XAI)-the SHapley Additive exPlanations, Local Interpretable Model-agnostic Explanations and other methods to help understand the decision-making process behind the predictive models. We conducted a case study in which we applied XAI on a predictive model of ligand binding to human immunodeficiency virus type 1 trans-activation response element RNA to distinguish between residues and interaction types important for binding. We also used XAI to indicate whether an interaction has a positive or negative effect on binding prediction and to quantify its impact. Our results obtained using all XAI methods were consistent with the literature data, demonstrating the utility and importance of XAI in medicinal chemistry and bioinformatics.

Plumbing mysterious RNAs in "dark genome" for the conquest of human diseases

Next-generation sequencing has revealed that less than 2% of transcribed genes are translated into proteins, with a large portion transcribed into noncoding RNAs (ncRNAs). Among these, long noncoding RNAs (lncRNAs) represent the largest group and are pervasively transcribed throughout the genome. Dysfunctions in lncRNAs have been found in various diseases, highlighting their potential as therapeutic, diagnostic, and prognostic targets. However, challenges, such as unknown molecular mechanisms and nonspecific immune responses, and issues of drug specificity and delivery present obstacles in translating lncRNAs into clinical applications. In this review, we summarize recent publications that have explored lncRNA functions in human diseases. We also discuss challenges and future directions for developing lncRNA treatments, aiming to bridge the gap between functional studies and clinical potential and inspire further exploration in the field.

Structural basis of tRNAPro acceptor stem recognition by a bacterial trans-editing domain

High fidelity tRNA aminoacylation by aminoacyl-tRNA synthetases is essential for cell viability. ProXp-ala is a trans-editing protein that is present in all three domains of life and is responsible for hydrolyzing mischarged Ala-tRNAPro and preventing mistranslation of proline codons. Previous studies have shown that, like bacterial prolyl-tRNA synthetase, Caulobacter crescentus ProXp-ala recognizes the unique C1:G72 terminal base pair of the tRNAPro acceptor stem, helping to ensure deacylation of Ala-tRNAPro but not Ala-tRNAAla. The structural basis for C1:G72 recognition by ProXp-ala is still unknown and was investigated here. NMR spectroscopy, binding, and activity assays revealed two conserved residues, K50 and R80, that likely interact with the first base pair, stabilizing the initial protein-RNA encounter complex. Modeling studies are consistent with direct interaction between R80 and the major groove of G72. A third key contact between A76 of tRNAPro and K45 of ProXp-ala was essential for binding and accommodating the CCA-3' end in the active site. We also demonstrated the essential role that the 2'OH of A76 plays in catalysis. Eukaryotic ProXp-ala proteins recognize the same acceptor stem positions as their bacterial counterparts, albeit with different nucleotide base identities. ProXp-ala is encoded in some human pathogens; thus, these results have the potential to inform new antibiotic drug design.

RNA conformational propensities determine cellular activity

Cellular processes are the product of interactions between biomolecules, which associate to form biologically active complexes1. These interactions are mediated by intermolecular contacts, which if disrupted, lead to alterations in cell physiology. Nevertheless, the formation of intermolecular contacts nearly universally requires changes in the conformations of the interacting biomolecules. As a result, binding affinity and cellular activity crucially depend both on the strength of the contacts and on the inherent propensities to form binding-competent conformational states2,3. Thus, conformational penalties are ubiquitous in biology and must be known in order to quantitatively model binding energetics for protein and nucleic acid interactions4,5. However, conceptual and technological limitations have hindered our ability to dissect and quantitatively measure how conformational propensities affect cellular activity. Here we systematically altered and determined the propensities for forming the protein-bound conformation of HIV-1 TAR RNA. These propensities quantitatively predicted the binding affinities of TAR to the RNA-binding region of the Tat protein and predicted the extent of HIV-1 Tat-dependent transactivation in cells. Our results establish the role of ensemble-based conformational propensities in cellular activity and reveal an example of a cellular process driven by an exceptionally rare and short-lived RNA conformational state.

The HIV-1 Integrase C-Terminal Domain Induces TAR RNA Structural Changes Promoting Tat Binding

Recent evidence indicates that the HIV-1 Integrase (IN) binds the viral genomic RNA (gRNA), playing a critical role in the morphogenesis of the viral particle and in the stability of the gRNA once in the host cell. By combining biophysical, molecular biology, and biochemical approaches, we found that the 18-residues flexible C-terminal tail of IN acts as a sensor of the peculiar apical structure of the trans-activation response element RNA (TAR), interacting with its hexaloop. We show that the binding of the whole IN C-terminal domain modifies TAR structure, exposing critical nucleotides. These modifications favour the subsequent binding of the HIV transcriptional trans-activator Tat to TAR, finally displacing IN from TAR. Based on these results, we propose that IN assists the binding of Tat to TAR RNA. This working model provides a mechanistic sketch accounting for the emerging role of IN in the early stages of proviral transcription and could help in the design of anti-HIV-1 therapeutics against this new target of the viral infectious cycle.

A structure-based mechanism for displacement of the HEXIM adapter from 7SK small nuclear RNA

Productive transcriptional elongation of many cellular and viral mRNAs requires transcriptional factors to extract pTEFb from the 7SK snRNP by modulating the association between HEXIM and 7SK snRNA. In HIV-1, Tat binds to 7SK by displacing HEXIM. However, without the structure of the 7SK-HEXIM complex, the constraints that must be overcome for displacement remain unknown. Furthermore, while structure details of the TatNL4-3-7SK complex have been elucidated, it is unclear how subtypes with more HEXIM-like Tat sequences accomplish displacement. Here we report the structures of HEXIM, TatG, and TatFin arginine rich motifs in complex with the apical stemloop-1 of 7SK. While most interactions between 7SK with HEXIM and Tat are similar, critical differences exist that guide function. First, the conformational plasticity of 7SK enables the formation of three different base pair configurations at a critical remodeling site, which allows for the modulation required for HEXIM binding and its subsequent displacement by Tat. Furthermore, the specific sequence variations observed in various Tat subtypes all converge on remodeling 7SK at this region. Second, we show that HEXIM primes its own displacement by causing specific local destabilization upon binding - a feature that is then exploited by Tat to bind 7SK more efficiently.

Hidden intermediates in Mango III RNA aptamer folding revealed by pressure perturbation

Fluorescent RNA aptamers have the potential to enable routine quantitation and localization of RNA molecules and serve as models for understanding biologically active aptamers. In recent years, several fluorescent aptamers have been selected and modified to improve their properties, revealing that small changes to the RNA or the ligands can modify significantly their fluorescent properties. Although structural biology approaches have revealed the bound, ground state of several fluorescent aptamers, characterization of low-abundance, excited states in these systems is crucial to understanding their folding pathways. Here we use pressure as an alternative variable to probe the suboptimal states of the Mango III aptamer with both fluorescence and NMR spectroscopy approaches. At moderate KCl concentrations, increasing pressure disrupted the G-quadruplex structure of the Mango III RNA and led to an intermediate with lower fluorescence. These observations indicate the existence of suboptimal RNA structural states that still bind the TO1-biotin fluorophore and moderately enhance fluorescence. At higher KCl concentration as well, the intermediate fluorescence state was populated at high pressure, but the G-quadruplex remained stable at high pressure, supporting the notion of parallel folding and/or binding pathways. These results demonstrate the usefulness of pressure for characterizing RNA folding intermediates.

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. In addition, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. The capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

Correlation in Domain Fluctuations Navigates Target Search of a Viral Peptide along RNA

Biological macromolecules often exhibit correlations in fluctuations involving distinct domains. This study decodes their functional implications in RNA-protein recognition and target-specific binding. The target search of a peptide along RNA in a viral TAR-Tat complex is closely monitored using atomistic simulations, steered molecular dynamics simulations, free energy calculations, and a machine-learning-based clustering technique. An anticorrelated domain fluctuation is identified between the tetraloop and the bulge region in the apo form of TAR RNA that sets a hierarchy in the domain-specific fluctuations at each binding event and that directs the succeeding binding footsteps. Thus, at each binding footstep, the dynamic partner selects an RNA location for binding where it senses a higher fluctuation, which is conventionally reduced upon binding. This event stimulates an alternate domain fluctuation, which then dictates sequential binding footstep/s and thus the search progresses. Our cross-correlation maps show that the fluctuations relay from one domain to another specific domain until the anticorrelation between those interdomain fluctuations sustains. Artificial attenuation of that hierarchical domain fluctuation inhibits specific RNA binding. The binding is completed with the arrival of a few long-lived water molecules that mediate slightly distant RNA-protein sites and finally stabilize the overall complex. The study underscores the functional importance of naturally designed fluctuating RNA motifs (bulge, tetraloop) and their interplay in dictating the directionality of the search in a highly dynamic environment.

Probing RNA Conformational Equilibria within the Functional Cellular Context

Low-abundance short-lived non-native conformations referred to as excited states (ESs) are increasingly observed in vitro and implicated in the folding and biological activities of regulatory RNAs. We developed an approach for assessing the relative abundance of RNA ESs within the functional cellular context. Nuclear magnetic resonance (NMR) spectroscopy was used to estimate the degree to which substitution mutations bias conformational equilibria toward the inactive ES in vitro. The cellular activity of the ES-stabilizing mutants was used as an indirect measure of the conformational equilibria within the functional cellular context. Compensatory mutations that restore the ground-state conformation were used to control for changes in sequence. Using this approach, we show that the ESs of two regulatory RNAs from HIV-1, the transactivation response element (TAR) and the Rev response element (RRE), likely form in cells with abundances comparable to those measured in vitro, and their targeted stabilization may provide an avenue for developing anti-HIV therapeutics.

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.

2'-O-Methylation can increase the abundance and lifetime of alternative RNA conformational states

2'-O-Methyl (Nm) is a highly abundant post-transcriptional RNA modification that plays important biological roles through mechanisms that are not entirely understood. There is evidence that Nm can alter the biological activities of RNAs by biasing the ribose sugar pucker equilibrium toward the C3'-endo conformation formed in canonical duplexes. However, little is known about how Nm might more broadly alter the dynamic ensembles of flexible RNAs containing bulges and internal loops. Here, using NMR and the HIV-1 transactivation response (TAR) element as a model system, we show that Nm preferentially stabilizes alternative secondary structures in which the Nm-modified nucleotides are paired, increasing both the abundance and lifetime of low-populated short-lived excited states by up to 10-fold. The extent of stabilization increased with number of Nm modifications and was also dependent on Mg2+. Through phi-value analysis, the Nm modification also provided rare insights into the structure of the transition state for conformational exchange. Our results suggest that Nm could alter the biological activities of Nm-modified RNAs by modulating their secondary structural ensembles as well as establish the utility of Nm as a tool for the discovery and characterization of RNA excited state conformations.

Rapid and accurate determination of atomistic RNA dynamic ensemble models using NMR and structure prediction

Biomolecules form dynamic ensembles of many inter-converting conformations which are key for understanding how they fold and function. However, determining ensembles is challenging because the information required to specify atomic structures for thousands of conformations far exceeds that of experimental measurements. We addressed this data gap and dramatically simplified and accelerated RNA ensemble determination by using structure prediction tools that leverage the growing database of RNA structures to generate a conformation library. Refinement of this library with NMR residual dipolar couplings provided an atomistic ensemble model for HIV-1 TAR, and the model accuracy was independently supported by comparisons to quantum-mechanical calculations of NMR chemical shifts, comparison to a crystal structure of a substate, and through designed ensemble redistribution via atomic mutagenesis. Applications to TAR bulge variants and more complex tertiary RNAs support the generality of this approach and the potential to make the determination of atomic-resolution RNA ensembles routine.

Determining dynamic ensembles of biomolecules is still challenging. Here the authors present an approach for rapid RNA ensemble determination that combines RNA structure prediction tools and NMR residual dipolar coupling data and use it to determine atomistic ensemble models for a variety of RNAs.

NMR Studies of Retroviral Genome Packaging

Nearly all retroviruses selectively package two copies of their unspliced RNA genomes from a cellular milieu that contains a substantial excess of non-viral and spliced viral RNAs. Over the past four decades, combinations of genetic experiments, phylogenetic analyses, nucleotide accessibility mapping, in silico RNA structure predictions, and biophysical experiments were employed to understand how retroviral genomes are selected for packaging. Genetic studies provided early clues regarding the protein and RNA elements required for packaging, and nucleotide accessibility mapping experiments provided insights into the secondary structures of functionally important elements in the genome. Three-dimensional structural determinants of packaging were primarily derived by nuclear magnetic resonance (NMR) spectroscopy. A key advantage of NMR, relative to other methods for determining biomolecular structure (such as X-ray crystallography), is that it is well suited for studies of conformationally dynamic and heterogeneous systems—a hallmark of the retrovirus packaging machinery. Here, we review advances in understanding of the structures, dynamics, and interactions of the proteins and RNA elements involved in retroviral genome selection and packaging that are facilitated by NMR.

Different views of the dynamic landscape covered by the 5'-hairpin of the 7SK small nuclear RNA

The 7SK small nuclear RNA (7SKsnRNA) plays a key role in the regulation of RNA polymerase II by sequestrating and inhibiting the positive transcription elongation factor b (P-TEFb) in the 7SK ribonucleoprotein complex (7SKsnRNP), a process mediated by interaction with the protein HEXIM. P-TEFb is also an essential cellular factor recruited by the viral protein Tat to ensure the replication of the viral RNA in the infection cycle of the human immunodeficiency virus (HIV-1). Tat promotes the release of P-TEFb from the 7SKsnRNP and subsequent activation of transcription, by displacing HEXIM from the 5'-hairpin of the 7SKsnRNA. This hairpin (HP1), comprising the signature sequence of the 7SKsnRNA, has been the subject of three independent structural studies aimed at identifying the structural features that could drive the recognition by the two proteins, both depending on arginine-rich motifs (ARM). Interestingly, four distinct structures were determined. In an attempt to provide a comprehensive view of the structure-function relationship of this versatile RNA, we present here a structural analysis of the models, highlighting how HP1 is able to adopt distinct conformations with significant impact on the compactness of the molecule. Since these models are solved under different conditions by nuclear magnetic resonance (NMR) and crystallography, the impact of the buffer composition on the conformational variation was investigated by complementary biophysical approaches. Finally, using isothermal titration calorimetry, we determined the thermodynamic signatures of the Tat-ARM and HEXIM-ARM peptide interactions with the RNA, showing that they are associated with distinct binding mechanisms.

The roles of structural dynamics in the cellular functions of RNAs

RNAs fold into 3D structures that range from simple helical elements to complex tertiary structures and quaternary ribonucleoprotein assemblies. The functions of many regulatory RNAs depend on how their 3D structure changes in response to a diverse array of cellular conditions. In this Review, we examine how the structural characterization of RNA as dynamic ensembles of conformations, which form with different probabilities and at different timescales, is improving our understanding of RNA function in cells. We discuss the mechanisms of gene regulation by microRNAs, riboswitches, ribozymes, post-transcriptional RNA modifications and RNA-binding proteins, and how the cellular environment and processes such as liquid-liquid phase separation may affect RNA folding and activity. The emerging RNA-ensemble-function paradigm is changing our perspective and understanding of RNA regulation, from in vitro to in vivo and from descriptive to predictive.

From parts lists to functional significance-RNA-protein interactions in gene regulation

Hundreds of canonical RNA binding proteins facilitate diverse and essential RNA processing steps in cells forming a central regulatory point in gene expression. However, recent discoveries including the identification of a large number of noncanonical proteins bound to RNA have changed our view on RNA-protein interactions merely as necessary steps in RNA biogenesis. As the list of proteins interacting with RNA has expanded, so has the scope of regulation through RNA-protein interactions. In addition to facilitating RNA metabolism, RNA binding proteins help to form subcellular structures and membraneless organelles, and provide means to recruit components of macromolecular complexes to their sites of action. Moreover, RNA-protein interactions are not static in cells but the ribonucleoprotein (RNP) complexes are highly dynamic in response to cellular cues. The identification of novel proteins in complex with RNA and ways cells use these interactions to control cellular functions continues to broaden the scope of RNA regulation in cells and the current challenge is to move from cataloguing the components of RNPs into assigning them functions. This will not only facilitate our understanding of cellular homeostasis but may bring in key insights into human disease conditions where RNP components play a central role. This review brings together the classical view of regulation accomplished through RNA-protein interactions with the novel insights gained from the identification of RNA binding interactomes. We discuss the challenges in combining molecular mechanism with cellular functions on the journey towards a comprehensive understanding of the regulatory functions of RNA-protein interactions in cells. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications aRNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition.

Demonstration that Small Molecules can Bind and Stabilize Low-abundance Short-lived RNA Excited Conformational States

Many promising RNA drug targets have functions that require the formation of RNA-protein complexes, but inhibiting RNA-protein interactions can prove difficult using small molecules. Regulatory RNAs have been shown to transiently form excited conformational states (ESs) that remodel local aspects of secondary structure. In some cases, the ES conformation has been shown to be inactive and to be poorly recognized by protein binding partners. In these cases, specifically targeting and stabilizing the RNA ES using a small molecule provides a rational structure-based strategy for inhibiting RNA activity. However, this requires that a small molecule discriminates between two conformations of the same RNA to preferentially bind and stabilize the short-lived low-abundance ES relative to the long-lived more abundant ground state (GS). Here, we tested the feasibility of this approach by designing a mutant that inverts the conformational equilibrium of the HIV-1 transactivation response element (TAR) RNA, such that the native GS conformation becomes a low-abundance ES. Using this mutant and NMR chemical shift mapping experiments, we show that argininamide, a ligand mimic of TAR's cognate protein binding partner Tat, is able to restore a native-like conformation by preferentially binding and stabilizing the transient and low-populated ES. A synthetic small molecule optimized to bind the TAR GS also partially stabilized the ES, whereas an aminoglycoside molecule that binds RNAs nonspecifically did not preferentially stabilize the ES to a similar extent. These results support the feasibility of inhibiting RNA activity using small molecules that preferentially bind and stabilize the ES.

Identification and Characterization of New RNA Tetraloop Sequence Families

There is an abundance of RNA sequence information available due to the efforts of sequencing projects. However, current techniques implemented to solve the tertiary structures of RNA, such as NMR and X-ray crystallography, are difficult and time-consuming. Therefore, biophysical techniques are not able to keep pace with the abundance of sequence information available. Because of this, there is a need to develop quick and efficient ways to predict RNA tertiary structure from sequence. One promising approach is to identify structural patterns within previously solved 3D structures and apply these patterns to new sequences. RNA tetraloops are one of the most common naturally occurring secondary structure motifs. Here, we use RNA Characterization of Secondary Structure Motifs (CoSSMos), Dissecting the Spatial Structure of RNA (DSSR), and a bioinformatic approach to search for and characterize tertiary structure patterns among tetraloops. Not surprising, we identified the well-known GNRA and UNCG tetraloops, as well as the previously identified RNYA tetraloop. However, some previously identified characteristics of these families were not observed in this data set, and some new characteristics were identified. In addition, we also identified and characterized three new tetraloop sequence families: YGAR, UGGU, and RMSA. This new structural information sheds light on the tertiary structure of tetraloops and contributes to the efforts of RNA tertiary structure prediction from sequence.

Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions

The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to determine RNA-protein interactions in multiple aspects. However, due to the facts that RNA-protein interactions are tissuespecific and condition-specific, as well as these interactions are weak and frequently compete with each other, those experimental techniques can not be made full use of to discover the complete spectrum of RNA-protein interactions. To moderate these issues, continuous efforts have been devoted to developing high quality computational techniques to study the interactions between RNAs and proteins. Many important progresses have been achieved with the application of novel techniques and strategies, such as machine learning techniques. Especially, with the development and application of CLIP techniques, more and more experimental data on RNA-protein interaction under specific biological conditions are available. These CLIP data altogether provide a rich source for developing advanced machine learning predictors. In this review, recent progresses on computational predictors for RNA-protein interaction were summarized in the following aspects: dataset, prediction strategies, and input features. Possible future developments were also discussed at the end of the review.

3D structure stability of the HIV-1 TAR RNA in ion solutions: A coarse-grained model study

As an extremely common structural motif, RNA hairpins with bulge loops [e.g., the human immunodeficiency virus type 1 (HIV-1) transactivation response (TAR) RNA] can play essential roles in normal cellular processes by binding to proteins and small ligands, which could be very dependent on their three-dimensional (3D) structures and stability. Although the structures and conformational dynamics of the HIV-1 TAR RNA have been extensively studied, there are few investigations on the thermodynamic stability of the TAR RNA, especially in ion solutions, and the existing studies also have some divergence on the unfolding process of the RNA. Here, we employed our previously developed coarse-grained model with implicit salt to predict the 3D structure, stability, and unfolding pathway for the HIV-1 TAR RNA over a wide range of ion concentrations. As compared with the extensive experimental/theoretical results, the present model can give reliable predictions on the 3D structure stability of the TAR RNA from the sequence. Based on the predictions, our further comprehensive analyses on the stability of the TAR RNA as well as its variants revealed that the unfolding pathway of an RNA hairpin with a bulge loop is mainly determined by the relative stability between different states (folded state, intermediate state, and unfolded state) and the strength of the coaxial stacking between two stems in folded structures, both of which can be apparently modulated by the ion concentrations as well as the sequences.

Incorporating G-C Pair-Recognizing Guanidinium into PNAs for Sequence and Structure Specific Recognition of dsRNAs over dsDNAs and ssRNAs

Recognition of RNAs under physiological conditions is important for the development of chemical probes and therapeutic ligands. Nucleobase-modified dsRNA-binding PNAs (dbPNAs) are promising for the recognition of dsRNAs in a sequence and structure specific manner under near-physiological conditions. Guanidinium is often present in proteins and small molecules for the recognition of G bases in nucleic acids, in cell-penetrating carriers, and in bioactive drug molecules, which might be due to the fact that guanidinium is amphiphilic and has unique hydrogen bonding and stacking properties. We hypothesized that a simple guanidinium moiety can be directly incorporated into PNAs to facilitate enhanced molecular recognition of G-C pairs in dsRNAs and improved bioactivity. We grafted a guanidinium moiety directly into a PNA monomer (designated as R) using a two-carbon linker as guided by computational modeling studies. The synthetic scheme of the PNA R monomer is relatively simple compared to that of the previously reported L monomer. We incorporated the R residue into various dbPNAs for binding studies. dbPNAs incorporated with R residues are excellent in sequence specifically recognizing G-C pairs in dsRNAs over dsDNA and ssRNAs. We demonstrated that the R residue is compatible with unmodified T and C and previously developed modified L and Q residues in dbPNAs for targeting model dsRNAs, the influenza A viral panhandle duplex structure, and the HIV-1 frameshift site RNA hairpin. Furthermore, R residues enhance the cellular uptake of PNAs.

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.

Targeting RNA with Small Molecules To Capture Opportunities at the Intersection of Chemistry, Biology, and Medicine

The biology of healthy and disease-affected cells is often mediated by RNA structures, desirable targets for small molecule chemical probes and lead medicines. Although structured regions are found throughout the transcriptome, some even with demonstrated functionality, human RNAs are considered recalcitrant to small molecule targeting. However, targeting structured regions with small molecules provides an important alternative to oligonucleotides that target sequence. In this Perspective, we describe challenges and progress in developing small molecules interacting with RNA (SMIRNAs) to capture their significant opportunities at the intersection of chemistry, biology, and medicine. Key to establishing a new paradigm in chemical biology and medicine is the development of methods to obtain, preferably by design, bioactive compounds that modulate RNA targets and companion methods that validate their direct effects in cells and pre-clinical models. While difficult, demonstration of direct target engagement in the complex cellular milieu, along with methods to establish modes of action, is required to push this field forward. We also describe frameworks for accelerated advancements in this burgeoning area, their implications, key new technologies for development of SMIRNAs, and milestones that have led to broader acceptance of RNA as a small molecule druggable target.

HIV-1 Tat interactions with cellular 7SK and viral TAR RNAs identifies dual structural mimicry

The HIV Tat protein competes with the 7SK:HEXIM interaction to hijack pTEFb from 7SK snRNP and recruit it to the TAR motif on stalled viral transcripts. Here we solve structures of 7SK stemloop-1 and TAR in complex with Tat’s RNA binding domain (RBD) to gain insights into this process. We find that 7SK is peppered with arginine sandwich motifs (ASM)—three classical and one with a pseudo configuration. Despite having similar RBDs, the presence of an additional arginine, R52, confers Tat the ability to remodel the pseudo configuration, required for HEXIM binding, into a classical sandwich, thus displacing HEXIM. Tat also uses R52 to remodel the TAR bulge into an ASM whose structure is identical to that of the remodeled ASM in 7SK. Together, our structures reveal a dual structural mimicry wherein viral Tat and TAR have co-opted structural motifs present in cellular HEXIM and 7SK for productive transcription of its genome.

The HIV Tat protein recruits a host elongation factor from the cellular 7SK complex to the viral TAR RNA to ensure transcriptional elongation. Here, Pham et al. solve the structures of both 7SK and TAR RNAs in complex with Tat’s RNA binding domain and gain mechanistic insights into the process.

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.

Unconventional RNA-binding proteins step into the virus-host battlefront

The crucial participation of cellular RNA‐binding proteins (RBPs) in virtually all steps of virus infection has been known for decades. However, most of the studies characterizing this phenomenon have focused on well‐established RBPs harboring classical RNA‐binding domains (RBDs). Recent proteome‐wide approaches have greatly expanded the census of RBPs, discovering hundreds of proteins that interact with RNA through unconventional RBDs. These domains include protein–protein interaction platforms, enzymatic cores, and intrinsically disordered regions. Here, we compared the experimentally determined census of RBPs to gene ontology terms and literature, finding that 472 proteins have previous links with viruses. We discuss what these proteins are and what their roles in infection might be. We also review some of the pioneering examples of unorthodox RBPs whose RNA‐binding activity has been shown to be critical for virus infection. Finally, we highlight the potential of these proteins for host‐based therapies against viruses.

This article is categorized under:

RNA Interactions with Proteins and Other Molecules > Protein–RNA Interactions: Functional Implications

RNA in Disease and Development > RNA in Disease

RNA Interactions with Proteins and Other Molecules > RNA–Protein Complexes

Structure of HIV TAR in complex with a Lab-Evolved RRM provides insight into duplex RNA recognition and synthesis of a constrained peptide that impairs transcription

Natural and lab-evolved proteins often recognize their RNA partners with exquisite affinity. Structural analysis of such complexes can offer valuable insight into sequence-selective recognition that can be exploited to alter biological function. Here, we describe the structure of a lab-evolved RNA recognition motif (RRM) bound to the HIV-1 trans-activation response (TAR) RNA element at 1.80 Å-resolution. The complex reveals a trio of arginines in an evolved β2-β3 loop penetrating deeply into the major groove to read conserved guanines while simultaneously forming cation-π and salt-bridge contacts. The observation that the evolved RRM engages TAR within a double-stranded stem is atypical compared to most RRMs. Mutagenesis, thermodynamic analysis and molecular dynamics validate the atypical binding mode and quantify molecular contributions that support the exceptionally tight binding of the TAR-protein complex (KD,App of 2.5 ± 0.1 nM). These findings led to the hypothesis that the β2-β3 loop can function as a standalone TAR-recognition module. Indeed, short constrained peptides comprising the β2-β3 loop still bind TAR (KD,App of 1.8 ± 0.5 μM) and significantly weaken TAR-dependent transcription. Our results provide a detailed understanding of TAR molecular recognition and reveal that a lab-evolved protein can be reduced to a minimal RNA-binding peptide.

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.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Long Noncoding RNA in Cancer: Wiring Signaling Circuitry

Long noncoding RNAs (lncRNAs), which are encoded by a vast less explored region of the human genome, may hold missing drivers of cancer and have gained attention recently as a potentially crucial layer of cancer cell regulation. lncRNAs are aberrantly expressed in a broad spectrum of cancers, and they play key roles in promoting and maintaining tumor initiation and progression, demonstrating their clinical potential as biomarkers and therapeutic targets. Recent discoveries have revealed that lncRNAs act as key signal transduction mediators in cancer signaling pathways by interacting with proteins, RNA, and lipids. Here, we review the mechanisms by which lncRNAs regulate cellular responses to extracellular signals and discuss their clinical potential as diagnostic indicators, stratification markers, and therapeutic targets of combinatorial treatments.

Using Genome Sequence to Enable the Design of Medicines and Chemical Probes

Rapid progress in genome sequencing technology has put us firmly into a postgenomic era. A key challenge in biomedical research is harnessing genome sequence to fulfill the promise of personalized medicine. This Review describes how genome sequencing has enabled the identification of disease-causing biomolecules and how these data have been converted into chemical probes of function, preclinical lead modalities, and ultimately U.S. Food and Drug Administration (FDA)-approved drugs. In particular, we focus on the use of oligonucleotide-based modalities to target disease-causing RNAs; small molecules that target DNA, RNA, or protein; the rational repurposing of known therapeutic modalities; and the advantages of pharmacogenetics. Lastly, we discuss the remaining challenges and opportunities in the direct utilization of genome sequence to enable design of medicines.

The crystal structure of the 5΄ functional domain of the transcription riboregulator 7SK

In vertebrates, the 7SK RNA forms the scaffold of a complex, which regulates transcription pausing of RNA-polymerase II. By binding to the HEXIM protein, the complex comprising proteins LARP7 and MePCE captures the positive transcription elongation factor P-TEFb and prevents phosphorylation of pausing factors. The HEXIM-binding site embedded in the 5΄-hairpin of 7SK (HP1) encompasses a short signature sequence, a GAUC repeat framed by single-stranded uridines. The present crystal structure of HP1 shows a remarkably straight helical stack involving several unexpected triples formed at a central region. Surprisingly, two uridines of the signature sequence make triple interactions in the major groove of the (GAUC)₂. The third uridine is turned outwards or inward, wedging between the other uridines, thus filling the major groove. A molecular dynamics simulation indicates that these two conformations of the signature sequence represent stable alternatives. Analyses of the interaction with the HEXIM protein confirm the importance of the triple interactions at the signature sequence. Altogether, the present structural analysis of 7SK HP1 highlights an original mechanism of swapping bases, which could represent a possible ‘7SK signature’ and provides new insight into the functional importance of the plasticity of RNA.

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.

The Genetic Code and RNA-Amino Acid Affinities

A significant part of the genetic code likely originated via a chemical interaction, which should be experimentally verifiable. One possible verification relates bound amino acids (or perhaps their activated congeners) and ribonucleotide sequences within cognate RNA binding sites. To introduce this interaction, I first summarize how amino acids function as targets for RNA binding. Then the experimental method for selecting relevant RNA binding sites is characterized. The selection method’s characteristics are related to the investigation of the RNA binding site model treated at the outset. Finally, real binding sites from selection and also from extant natural RNAs (for example, the Sulfobacillus guanidinium riboswitch) are connected to the genetic code, and by extension, to the evolutionary progression that produced the code. During this process, peptides may have been produced directly on an instructive amino acid binding RNA (a DRT; Direct RNA Template). Combination of observed stereochemical selectivity with adaptation and co-evolutionary refinement is logically required, and also potentially sufficient, to create the striking order conserved throughout the present coding table.

Ultraslow Domain Motions in HIV-1 TAR RNA Revealed by Solid-State Deuterium NMR

Intrinsic motions may allow HIV-1 transactivation response (TAR) RNA to change its conformation to form a functional complex with the Tat protein, which is essential for viral replication. Understanding the dynamic properties of TAR necessitates determining motion on the intermediate nanosecond-to-microsecond time scale. To this end, we performed solid-state deuterium NMR line-shape and T_1Z relaxation-time experiments to measure intermediate motions for two uridine residues, U40 and U42, within the lower helix of TAR. We infer global motions at rates of ∼10⁵ s^-1 in the lower helix, which are much slower than those in the upper helix (∼10⁶ s^-1), indicating that the two helical domains reorient independently of one another in the solid-state sample. These results contribute to the aim of fully describing the properties of functional motions in TAR RNA.

Development of Small Molecules with a Noncanonical Binding Mode to HIV-1 Trans Activation Response (TAR) RNA

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

Insights into HIV-1 proviral transcription from integrative structure and dynamics of the Tat:AFF4:P-TEFb:TAR complex

HIV-1 Tat hijacks the human superelongation complex (SEC) to promote proviral transcription. Here we report the 5.9 Å structure of HIV-1 TAR in complex with HIV-1 Tat and human AFF4, CDK9, and CycT1. The TAR central loop contacts the CycT1 Tat-TAR recognition motif (TRM) and the second Tat Zn²⁺-binding loop. Hydrogen-deuterium exchange (HDX) shows that AFF4 helix 2 is stabilized in the TAR complex despite not touching the RNA, explaining how it enhances TAR binding to the SEC 50-fold. RNA SHAPE and SAXS data were used to help model the extended (Tat Arginine-Rich Motif) ARM, which enters the TAR major groove between the bulge and the central loop. The structure and functional assays collectively support an integrative structure and a bipartite binding model, wherein the TAR central loop engages the CycT1 TRM and compact core of Tat, while the TAR major groove interacts with the extended Tat ARM.

DOI:http://dx.doi.org/10.7554/eLife.15910.001

Kinetic and thermodynamic framework for P4-P6 RNA reveals tertiary motif modularity and modulation of the folding preferred pathway

The past decade has seen a wealth of 3D structural information about complex structured RNAs and identification of functional intermediates. Nevertheless, developing a complete and predictive understanding of the folding and function of these RNAs in biology will require connection of individual rate and equilibrium constants to structural changes that occur in individual folding steps and further relating these steps to the properties and behavior of isolated, simplified systems. To accomplish these goals we used the considerable structural knowledge of the folded, unfolded, and intermediate states of P4-P6 RNA. We enumerated structural states and possible folding transitions and determined rate and equilibrium constants for the transitions between these states using single-molecule FRET with a series of mutant P4-P6 variants. Comparisons with simplified constructs containing an isolated tertiary contact suggest that a given tertiary interaction has a stereotyped rate for breaking that may help identify structural transitions within complex RNAs and simplify the prediction of folding kinetics and thermodynamics for structured RNAs from their parts. The preferred folding pathway involves initial formation of the proximal tertiary contact. However, this preference was only ∼10 fold and could be reversed by a single point mutation, indicating that a model akin to a protein-folding contact order model will not suffice to describe RNA folding. Instead, our results suggest a strong analogy with a modified RNA diffusion-collision model in which tertiary elements within preformed secondary structures collide, with the success of these collisions dependent on whether the tertiary elements are in their rare binding-competent conformations.

A review on architecture of the gag-pol ribosomal frameshifting RNA in human immunodeficiency virus: a variability survey of virus genotypes

Programmed '-1' ribosomal frameshifting is necessary for expressing the pol gene overlapped from a gag of human immunodeficiency virus. A viral RNA structure that requires base pairing across the overlapping sequence region suggests a mechanism of regulating ribosome and helicase traffic during expression. To get precise roles of an element around the frameshift site, a review on architecture of the frameshifting RNA is performed in combination of reported information with augments of a representative set of 19 viral samples. In spite of a different length for the viral RNAs, a canonical comparison on the element sequence allocation is performed for viewing variability associations between virus genotypes. Additionally, recent and historical insights recognized in frameshifting regulation are looked back as for indel and single nucleotide polymorphism of RNA. As specially noted, structural changes at a frameshift site, the spacer sequence, and a three-helix junction element, as well as two Watson-Crick base pairs near a bulge and a C-G pair close a loop, are the most vital strategies for the virus frameshifting regulations. All of structural changes, which are dependent upon specific sequence variations, facilitate an elucidation about the RNA element conformation-dependent mechanism for frameshifting. These facts on disrupting base pair interactions also allow solving the problem of competition between ribosome and helicase on a same RNA template, common to single-stranded RNA viruses. In a broad perspective, each new insight of frameshifting regulation in the competition systems introduced by the RNA element construct changes will offer a compelling target for antiviral therapy.