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The discovery and design of biologically important RNA molecules is outpacing three-dimensional structural characterization. Here, we demonstrate that cryo-electron microscopy can routinely resolve maps of RNA-only systems and that these maps enable subnanometer-resolution coordinate estimation when complemented with multidimensional chemical mapping and Rosetta DRRAFTER computational modeling. This hybrid 'Ribosolve' pipeline detects and falsifies homologies and conformational rearrangements in 11 previously unknown 119- to 338-nucleotide protein-free RNA structures: full-length Tetrahymena ribozyme, hc16 ligase with and without substrate, full-length Vibrio cholerae and Fusobacterium nucleatum glycine riboswitch aptamers with and without glycine, Mycobacterium SAM-IV riboswitch with and without S-adenosylmethionine, and the computer-designed ATP-TTR-3 aptamer with and without AMP. Simulation benchmarks, blind challenges, compensatory mutagenesis, cross-RNA homologies and internal controls demonstrate that Ribosolve can accurately resolve the global architectures of RNA molecules but does not resolve atomic details. These tests offer guidelines for making inferences in future RNA structural studies with similarly accelerated throughput.

Specimens below 50 kDa have generally been considered too small to be analyzed by single-particle cryo-electron microscopy (cryo-EM). The high flexibility of pure RNAs makes it difficult to obtain high-resolution structures by cryo-EM. In bacteria, riboswitches regulate sulfur metabolism through binding to the S-adenosylmethionine (SAM) ligand and offer compelling targets for new antibiotics. SAM-I, SAM-I/IV, and SAM-IV are the three most commonly found SAM riboswitches, but the structure of SAM-IV is still unknown. Here, we report the structures of apo and SAM-bound SAM-IV riboswitches (119-nt, ~40 kDa) to 3.7 Å and 4.1 Å resolution, respectively, using cryo-EM. The structures illustrate homologies in the ligand-binding core but distinct peripheral tertiary contacts in SAM-IV compared to SAM-I and SAM-I/IV. Our results demonstrate the feasibility of resolving small RNAs with enough detail to enable detection of their ligand-binding pockets and suggest that cryo-EM could play a role in structure-assisted drug design for RNA., The conformational heterogeneity of RNA molecules makes their structure determination by X-ray crystallography and NMR challenging. Here the authors show that RNA structures can be solved by cryo-EM and present the structures of a 40 kDa SAM-IV riboswitch in the apo form and bound to its ligand S-adenosylmethionine.

Single-particle cryogenic electron microscopy (cryo-EM) has become a standard technique for determining protein structures at atomic resolution1–3. However, cryo-EM studies of protein-free RNA are in their early days. The Tetrahymena thermophila group I self-splicing intron was the first ribozyme to be discovered and has been a prominent model system for the study of RNA catalysis and structure–function relationships4, but its full structure remains unknown. Here we report cryo-EM structures of the full-length Tetrahymena ribozyme in substrate-free and bound states at a resolution of 3.1 A. Newly resolved peripheral regions form two coaxially stacked helices; these are interconnected by two kissing loop pseudoknots that wrap around the catalytic core and include two previously unforeseen (to our knowledge) tertiary interactions. The global architecture is nearly identical in both states; only the internal guide sequence and guanosine binding site undergo a large conformational change and a localized shift, respectively, upon binding of RNA substrates. These results provide a long-sought structural view of a paradigmatic RNA enzyme and signal a new era for the cryo-EM-based study of structure–function relationships in ribozymes. Cryo-electron microscopy has been used to determine the structure of the Tetrahymena ribozyme (a catalytic RNA) at sufficiently high resolution to model side chains and metal ions.

A hallmark of the initiation step of HIV-1 reverse transcription, in which viral RNA genome is converted into double-stranded DNA, is that it is slow and non-processive. Biochemical studies have identified specific sites along the viral RNA genomic template in which reverse transcriptase (RT) stalls. These stalling points, which occur after the addition of three and five template dNTPs, may serve as checkpoints to regulate the precise timing of HIV-1 reverse transcription following viral entry. Structural studies of reverse transcriptase initiation complexes (RTICs) have revealed unique conformations that may explain the slow rate of incorporation; however, questions remain about the temporal evolution of the complex and features that contribute to strong pausing during initiation. Here we present cryo-electron microscopy and single-molecule characterization of an RTIC after three rounds of dNTP incorporation (+3), the first major pausing point during reverse transcription initiation. Cryo-electron microscopy structures of a +3 extended RTIC reveal conformational heterogeneity within the RTIC core. Three distinct conformations were identified, two of which adopt unique, likely off-pathway, intermediates in the canonical polymerization cycle. Single-molecule Forster resonance energy transfer experiments confirm that the +3 RTIC is more structurally dynamic than earlier-stage RTICs. These alternative conformations were selectively disrupted through structure-guided point mutations to shift single-molecule Forster resonance energy transfer populations back toward the on-pathway conformation. Our results support the hypothesis that conformational heterogeneity within the HIV-1 RTIC during pausing serves as an additional means of regulating HIV-1 replication.

Reverse transcription of the HIV-1 RNA genome into double-stranded DNA is a central step in viral infection1 and a common target of antiretroviral drugs2. The reaction is catalysed by viral reverse transcriptase (RT)3,4 that is packaged in an infectious virion with two copies of viral genomic RNA5 each bound to host lysine 3 transfer RNA (tRNALys3), which acts as a primer for initiation of reverse transcription6,7. Upon viral entry into cells, initiation is slow and non-processive compared to elongation8,9. Despite extensive efforts, the structural basis of RT function during initiation has remained a mystery. Here we use cryo-electron microscopy to determine a three-dimensional structure of an HIV-1 RT initiation complex. In our structure, RT is in an inactive polymerase conformation with open fingers and thumb and with the nucleic acid primer–template complex shifted away from the active site. The primer binding site (PBS) helix formed between tRNALys3 and HIV-1 RNA lies in the cleft of RT and is extended by additional pairing interactions. The 5′ end of the tRNA refolds and stacks on the PBS to create a long helical structure, while the remaining viral RNA forms two helical stems positioned above the RT active site, with a linker that connects these helices to the RNase H region of the PBS. Our results illustrate how RNA structure in the initiation complex alters RT conformation to decrease activity, highlighting a potential target for drug action. A cryo-EM structure of an initiation complex of HIV-1 reverse transcriptase sheds light on the initiation of reverse transcription of viral RNA.

Adenosine-to-inosine (A-to-I) RNA editing catalyzed by ADAR enzymes occurs in double-stranded RNAs. Despite a compelling need towards predictive understanding of natural and engineered editing events, how the RNA sequence and structure determine the editing efficiency and specificity (i.e., cis-regulation) is poorly understood. We apply a CRISPR/Cas9-mediated saturation mutagenesis approach to generate libraries of mutations near three natural editing substrates at their endogenous genomic loci. We use machine learning to integrate diverse RNA sequence and structure features to model editing levels measured by deep sequencing. We confirm known features and identify new features important for RNA editing. Training and testing XGBoost algorithm within the same substrate yield models that explain 68 to 86 percent of substrate-specific variation in editing levels. However, the models do not generalize across substrates, suggesting complex and context-dependent regulation patterns. Our integrative approach can be applied to larger scale experiments towards deciphering the RNA editing code., The RNA sequence and secondary structure regulate RNA editing by ADAR. Here the authors employ a CRISPR/Cas9-mediated saturation mutagenesis and machine learning to predict RNA editing efficiency of specific substrates.

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at ., This Perspective reviews tools developed over the past five years in the macromolecular modeling, docking and design software Rosetta.

The molecular mechanisms of exon definition and back-splicing are fundamental unanswered questions in pre-mRNA splicing. Here we report cryo-electron microscopy structures of the yeast spliceosomal E complex assembled on introns, providing a view of the earliest event in the splicing cycle that commits pre-mRNAs to splicing. The E complex architecture suggests that the same spliceosome can assemble across an exon, and that it either remodels to span an intron for canonical linear splicing (typically on short exons) or catalyses back-splicing to generate circular RNA (on long exons). The model is supported by our experiments, which show that an E complex assembled on the middle exon of yeast EFM5 or HMRA1 can be chased into circular RNA when the exon is sufficiently long. This simple model unifies intron definition, exon definition, and back-splicing through the same spliceosome in all eukaryotes and should inspire experiments in many other systems to understand the mechanism and regulation of these processes.

Maintenance of telomeres by telomerase permits continuous proliferation of rapidly dividing cells, including the majority of human cancers. Despite its direct biomedical significance, the architecture of the human telomerase complex remains unknown. Generating homogeneous telomerase samples has presented a significant barrier to developing improved structural models. Here we pair single-molecule Förster resonance energy transfer (smFRET) measurements with Rosetta modeling to map the conformations of the essential telomerase RNA core domain within the active ribonucleoprotein. FRET-guided modeling places the essential pseudoknot fold distal to the active site on a protein surface comprising the C-terminal element, a domain that shares structural homology with canonical polymerase thumb domains. An independently solved medium-resolution structure of Tetrahymena telomerase provides a blind test of our modeling methodology and sheds light on the structural homology of this domain across diverse organisms. Our smFRET-Rosetta models reveal nanometer-scale rearrangements within the RNA core domain during catalysis. Taken together, our FRET data and pseudoatomic molecular models permit us to propose a possible mechanism for how RNA core domain rearrangement is coupled to template hybrid elongation.

SummaryHigh-throughput methodologies have enabled routine generation of RNA target sets and sequence motifs for RNA-binding proteins (RBPs). Nevertheless, quantitative approaches are needed to capture the landscape of RNA/RBP interactions responsible for cellular regulation. We have used the RNA-MaP platform to directly measure equilibrium binding for thousands of designed RNAs and to construct a predictive model for RNA recognition by the human Pumilio proteins PUM1 and PUM2. Despite prior findings of linear sequence motifs, our measurements revealed widespread residue flipping and instances of positional coupling. Application of our thermodynamic model to published in vivo crosslinking data reveals quantitative agreement between predicted affinities and in vivo occupancies. Our analyses suggest a thermodynamically driven, continuous Pumilio binding landscape that is negligibly affected by RNA structure or kinetic factors, such as displacement by ribosomes. This work provides a quantitative foundation for dissecting the cellular behavior of RBPs and cellular features that impact their occupancies.

RNA-protein assemblies carry out many critical biological functions including translation, RNA splicing, and telomere extension. Increasingly, cryo-electron microscopy (cryoEM) is used to determine the structures of these complexes, but nearly all maps determined with this method have regions in which the local resolution does not permit manual coordinate tracing. Because RNA coordinates typically cannot be determined by docking crystal structures of separate components and existing structure prediction algorithms cannot yet model RNA-protein complexes, RNA coordinates are frequently omitted from final models despite their biological importance. To address these omissions, we have developed a new framework for De novo Ribonucleoprotein modeling in Real-space through Assembly of Fragments Together with Electron density in Rosetta (DRRAFTER). We show that DRRAFTER recovers near-native models for a diverse benchmark set of small RNA-protein complexes, as well as for large RNA-protein machines, including the spliceosome, mitochondrial ribosome, and CRISPR-Cas9-sgRNA complexes where the availability of both high and low resolution maps enable rigorous tests. Blind tests on yeast U1 snRNP and spliceosomal P complex maps demonstrate that the method can successfully build RNA coordinates in real-world modeling scenarios. Additionally, to aid in final model interpretation, we present a method for reliable in situ estimation of DRRAFTER model accuracy. Finally, we apply this method to recently determined maps of telomerase, the HIV-1 reverse transcriptase initiation complex, and the packaged MS2 genome, demonstrating that DRRAFTER can be used to accelerate accurate model building in challenging cases.

RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment. The riboswitch structures include biological binding sites for small molecules (S-adenosyl methionine, cyclic diadenosine monophosphate, 5-amino 4-imidazole carboxamide riboside 5′-triphosphate, glutamine) and proteins (YbxF), and one set describes large conformational changes between ligand-free and ligand-bound states. The Varkud satellite ribozyme is the most recently solved structure of a known large ribozyme. All puzzles have established biological functions and require structural understanding to appreciate their molecular mechanisms. Through the use of fast-track experimental data, including multidimensional chemical mapping, and accurate prediction of RNA secondary structure, a large portion of the contacts in 3D have been predicted correctly leading to similar topologies for the top ranking predictions. Template-based and homology-derived predictions could predict structures to particularly high accuracies. However, achieving biological insights from de novo prediction of RNA 3D structures still depends on the size and complexity of the RNA. Blind computational predictions of RNA structures already appear to provide useful structural information in many cases. Similar to the previous RNA-Puzzles Round II experiment, the prediction of non-Watson–Crick interactions and the observed high atomic clash scores reveal a notable need for an algorithm of improvement. All prediction models and assessment results are available at http://ahsoka.u-strasbg.fr/rnapuzzles/.

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta’s success is the energy function: amodel parameterized from small molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, beta_nov15. Applying these concepts,we explain how to use Rosetta energies to identify and analyze the features of biomolecular models.Finally, we discuss the latest advances in the energy function that extend capabilities from soluble proteins to also include membrane proteins, peptides containing non-canonical amino acids, carbohydrates, nucleic acids, and other macromolecules.

Elucidating the detailed process of ligand binding to a receptor is pharmaceutically important for identifying druggable binding sites. With the ability to provide atomistic detail, computational methods are well poised to study these processes. Here, accelerated molecular dynamics (aMD) is proposed to simulate processes of ligand binding to a G-protein-coupled receptor (GPCR), in this case the M3 muscarinic receptor, which is a target for treating many human diseases, including cancer, diabetes and obesity. Long-timescale aMD simulations were performed to observe the binding of three chemically diverse ligand molecules: antagonist tiotropium (TTP), partial agonist arecoline (ARc) and full agonist acetylcholine (ACh). In comparison with earlier microsecond-timescale conventional MD simulations, aMD greatly accelerated the binding of ACh to the receptor orthosteric ligand-binding site and the binding of TTP to an extracellular vestibule. Further aMD simulations also captured binding of ARc to the receptor orthosteric site. Additionally, all three ligands were observed to bind in the extracellular vestibule during their binding pathways, suggesting that it is a metastable binding site. This study demonstrates the applicability of aMD to protein–ligand binding, especially the drug recognition of GPCRs.