Automated and assisted RNA resonance assignment using NMR chemical shift statistics

NMR structures of small molecules bound to a model of a CUG RNA repeat expansion

Trinucleotide repeat expansions fold into long, stable hairpins and cause a variety of incurable RNA gain-of-function diseases such as Huntington's disease, the myotonic dystrophies, and spinocerebellar ataxias. One approach for treating these diseases is to bind small molecules to these structured RNAs. Both Huntington's disease-like 2 (HDL2) and myotonic dystrophy type 1 (DM1) are caused by a r(CUG) repeat expansion, or r(CUG)exp. The RNA folds into a hairpin structure with a periodic array of 1 × 1 nucleotide UU loops (5'CUG/3'GUC; where the underlined nucleotides indicate the Us in the internal loop) that sequester various RNA-binding proteins (RBPs) and hence the source of its gain-of-function. Here, we report nuclear magnetic resonance (NMR)-refined structures of single 5'CUG/3'GUC motifs in complex with three different small molecules, a di-guandinobenzoate (1), a derivative of 1 where the guanidino groups have been exchanged for imidazole (2), and a quinoline with improved drug-like properties (3). These structures were determined using NMR spectroscopy and simulated annealing with restrained molecular dynamics (MD). Compounds 1, 2, and 3 formed stacking and hydrogen bonding interactions with the 5'CUG/3'GUC motif. Compound 3 also formed van der Waals interactions with the internal loop. The global structure of each RNA-small molecule complexes retains an A-form conformation, while the internal loops are still dynamic but to a lesser extent compared to the unbound form. These results aid our understanding of ligand-RNA interactions and enable structure-based design of small molecules with improved binding affinity for and biological activity against r(CUG)exp. As the first ever reported structures of a r(CUG) repeat bound to ligands, these structures can enable virtual screening campaigns combined with machine learning assisted de novo design.

The 5'-terminal stem-loop RNA element of SARS-CoV-2 features highly dynamic structural elements that are sensitive to differences in cellular pH

We present the nuclear magnetic resonance spectroscopy (NMR) solution structure of the 5'-terminal stem loop 5_SL1 (SL1) of the SARS-CoV-2 genome. SL1 contains two A-form helical elements and two regions with non-canonical structure, namely an apical pyrimidine-rich loop and an asymmetric internal loop with one and two nucleotides at the 5'- and 3'-terminal part of the sequence, respectively. The conformational ensemble representing the averaged solution structure of SL1 was validated using NMR residual dipolar coupling (RDC) and small-angle X-ray scattering (SAXS) data. We show that the internal loop is the major binding site for fragments of low molecular weight. This internal loop of SL1 can be stabilized by an A12-C28 interaction that promotes the transient formation of an A+•C base pair. As a consequence, the pKa of the internal loop adenosine A12 is shifted to 5.8, compared to a pKa of 3.63 of free adenosine. Furthermore, applying a recently developed pH-differential mutational profiling (PD-MaP) approach, we not only recapitulated our NMR findings of SL1 but also unveiled multiple sites potentially sensitive to pH across the 5'-UTR of SARS-CoV-2.

NMR structures of small molecules bound to a model of an RNA CUG repeat expansion

Trinucleotide repeat expansions fold into long, stable hairpins and cause a variety of incurable RNA gain-of-function diseases such as Huntington's disease, the myotonic dystrophies, and spinocerebellar ataxias. One approach for treating these diseases is to bind small molecules to the structured RNAs. Both Huntington's disease-like 2 (HDL2) and myotonic dystrophy type 1 (DM1) are caused by a r(CUG) repeat expansion, or r(CUG)exp. The RNA folds into a hairpin structure with a periodic array of 1×1 nucleotide UU loops (5'CUG/3'GUC; where the underlined nucleotides indicate the Us in the internal loop) that sequester various RNA-binding proteins (RBP) and hence the source of its gain-of-function. Here, we report NMR-refined structures of single 5'CUG/3'GUC motifs in complex with three different small molecules, a di-guandinobenzoate (1), a derivative of 1 where the guanidino groups have been exchanged for imidazole (2), and a quinoline with improved drug-like properties (3). These structures were determined using nuclear magnetic resonance (NMR) spectroscopy and simulated annealing with restrained molecular dynamics (MD). Compounds 1, 2, and 3 formed stacking and hydrogen bonding interactions with the 5'CUG/3'GUC motif. Compound 3 also formed van der Waals interactions with the internal loop. The global structure of each RNA-small molecule complexes retains an A-form conformation, while the internal loops are still dynamic but to a lesser extent compared to the unbound form. These results aid our understanding of ligand-RNA interactions and enable structure-based design of small molecules with improved binding affinity for and biological activity against r(CUG)exp. As the first ever reported structures of RNA r(CUG) repeats bound to ligands, these structures can enable virtual screening campaigns combined with machine learning assisted de novo design.

Integrative solution structure of PTBP1-IRES complex reveals strong compaction and ordering with residual conformational flexibility

RNA-binding proteins (RBPs) are crucial regulators of gene expression, often composed of defined domains interspersed with flexible, intrinsically disordered regions. Determining the structure of ribonucleoprotein (RNP) complexes involving such RBPs necessitates integrative structural modeling due to their lack of a single stable state. In this study, we integrate magnetic resonance, mass spectrometry, and small-angle scattering data to determine the solution structure of the polypyrimidine-tract binding protein 1 (PTBP1/hnRNP I) bound to an RNA fragment from the internal ribosome entry site (IRES) of the encephalomyocarditis virus (EMCV). This binding, essential for enhancing the translation of viral RNA, leads to a complex structure that demonstrates RNA and protein compaction, while maintaining pronounced conformational flexibility. Acting as an RNA chaperone, PTBP1 orchestrates the IRES RNA into a few distinct conformations, exposing the RNA stems outward. This conformational diversity is likely common among RNP structures and functionally important. Our approach enables atomic-level characterization of heterogeneous RNP structures.

Chemical shift transfer: an effective strategy for protein NMR assignment with ARTINA

Chemical shift transfer (CST) is a well-established technique in NMR spectroscopy that utilizes the chemical shift assignment of one protein (source) to identify chemical shifts of another (target). Given similarity between source and target systems (e.g., using homologs), CST allows the chemical shifts of the target system to be assigned using a limited amount of experimental data. In this study, we propose a deep-learning based workflow, ARTINA-CST, that automates this procedure, allowing CST to be carried out within minutes or hours of computational time and strictly without any human supervision. We characterize the efficacy of our method using three distinct synthetic and experimental datasets, demonstrating its effectiveness and robustness even when substantial differences exist between the source and target proteins. With its potential applications spanning a wide range of NMR projects, including drug discovery and protein interaction studies, ARTINA-CST is anticipated to be a valuable method that facilitates research in the field.

Dynamically regulated two-site interaction of viral RNA to capture host translation initiation factor

Many RNA viruses employ internal ribosome entry sites (IRESs) in their genomic RNA to commandeer the host's translational machinery for replication. The IRES from encephalomyocarditis virus (EMCV) interacts with eukaryotic translation initiation factor 4 G (eIF4G), recruiting the ribosomal subunit for translation. Here, we analyze the three-dimensional structure of the complex composed of EMCV IRES, the HEAT1 domain fragment of eIF4G, and eIF4A, by cryo-electron microscopy. Two distinct eIF4G-interacting domains on the IRES are identified, and complex formation changes the angle therebetween. Further, we explore the dynamics of these domains by using solution NMR spectroscopy, revealing conformational equilibria in the microsecond to millisecond timescale. In the lowly-populated conformations, the base-pairing register of one domain is shifted with the structural transition of the three-way junction, as in the complex structure. Our study provides insights into the viral RNA's sophisticated strategy for optimal docking to hijack the host protein.

A functional SNP regulates E-cadherin expression by dynamically remodeling the 3D structure of a promoter-associated non-coding RNA transcript

Transcription of E-cadherin, a tumor suppressor that plays critical roles in cell adhesion and the epithelial-mesenchymal transition, is regulated by a promoter-associated non-coding RNA (paRNA). The sense-oriented paRNA (S-paRNA) includes a functional C/A single nucleotide polymorphism (SNP rs16260). The A-allele leads to decreased transcriptional activity and increased prostate cancer risk. The polymorphic site is known to affect binding of a microRNA-guided Argonaute 1 (AGO1) complex and recruitment of chromatin-modifying enzymes to silence the promoter. Yet the SNP is distant from the microRNA-AGO1 binding domain in both primary sequence and secondary structure, raising the question of how regulation occurs. Here we report the 3D NMR structure of the 104-nucleotide domain of the S-paRNA that encompasses the SNP and the microRNA-binding site. We show that the A to C change alters the locally dynamic and metastable structure of the S-paRNA, revealing how the single nucleotide mutation regulates the E-cadherin promoter through its effect on the non-coding RNA structure.

1H, 13C and 15N chemical shift assignment of the stem-loops 5b + c from the 5'-UTR of SARS-CoV-2

The ongoing pandemic of the respiratory disease COVID-19 is caused by the SARS-CoV-2 (SCoV2) virus. SCoV2 is a member of the Betacoronavirus genus. The 30 kb positive sense, single stranded RNA genome of SCoV2 features 5'- and 3'-genomic ends that are highly conserved among Betacoronaviruses. These genomic ends contain structured cis-acting RNA elements, which are involved in the regulation of viral replication and translation. Structural information about these potential antiviral drug targets supports the development of novel classes of therapeutics against COVID-19. The highly conserved branched stem-loop 5 (SL5) found within the 5'-untranslated region (5'-UTR) consists of a basal stem and three stem-loops, namely SL5a, SL5b and SL5c. Both, SL5a and SL5b feature a 5'-UUUCGU-3' hexaloop that is also found among Alphacoronaviruses. Here, we report the extensive ¹H, ¹³C and ¹⁵N resonance assignment of the 37 nucleotides (nts) long sequence spanning SL5b and SL5c (SL5b + c), as basis for further in-depth structural studies by solution NMR spectroscopy.

Bayesian probabilistic assignment of chemical shifts in organic solids

A prerequisite for NMR studies of organic materials is assigning each experimental chemical shift to a set of geometrically equivalent nuclei. Obtaining the assignment experimentally can be challenging and typically requires time-consuming multidimensional correlation experiments. An alternative solution for determining the assignment involves statistical analysis of experimental chemical shift databases, but no such database exists for molecular solids. Here, by combining the Cambridge Structural Database with a machine learning model of chemical shifts, we construct a statistical basis for probabilistic chemical shift assignment of organic crystals by calculating shifts for more than 200,000 compounds, enabling the probabilistic assignment of organic crystals directly from their two-dimensional chemical structure. The approach is demonstrated with the ¹³C and ¹H assignment of 11 molecular solids with experimental shifts and benchmarked on 100 crystals using predicted shifts. The correct assignment was found among the two most probable assignments in more than 80% of cases.

NMR chemical shift assignments of RNA oligonucleotides to expand the RNA chemical shift database

RNAs play myriad functional and regulatory roles in the cell. Despite their significance, three-dimensional structure elucidation of RNA molecules lags significantly behind that of proteins. NMR-based studies are often rate-limited by the assignment of chemical shifts. Automation of the chemical shift assignment process can greatly facilitate structural studies, however, accurate chemical shift predictions rely on a robust and complete chemical shift database for training. We searched the Biological Magnetic Resonance Data Bank (BMRB) to identify sequences that had no (or limited) chemical shift information. Here, we report the chemical shift assignments for 12 RNA hairpins designed specifically to help populate the BMRB.

Evaluation of Multi-Objective Optimization Algorithms for NMR Chemical Shift Assignment

An automated NMR chemical shift assignment algorithm was developed using multi-objective optimization techniques. The problem is modeled as a combinatorial optimization problem and its objective parameters are defined separately in different score functions. Some of the heuristic approaches of evolutionary optimization are employed in this problem model. Both, a conventional genetic algorithm and multi-objective methods, i.e., the non-dominated sorting genetic algorithms II and III (NSGA2 and NSGA3), are applied to the problem. The multi-objective approaches consider each objective parameter separately, whereas the genetic algorithm followed a conventional way, where all objectives are combined in one score function. Several improvement steps and repetitions on these algorithms are performed and their combinations are also created as a hyper-heuristic approach to the problem. Additionally, a hill-climbing algorithm is also applied after the evolutionary algorithm steps. The algorithms are tested on several different datasets with a set of 11 commonly used spectra. The test results showed that our algorithm could assign both sidechain and backbone atoms fully automatically without any manual interactions. Our approaches could provide around a 65% success rate and could assign some of the atoms that could not be assigned by other methods.

Chemical shift prediction of RNA imino groups: application toward characterizing RNA excited states

NH groups in proteins or nucleic acids are the most challenging target for chemical shift prediction. Here we show that the RNA base pair triplet motif dictates imino chemical shifts in its central base pair. A lookup table is established that links each type of base pair triplet to experimental chemical shifts of the central base pair, and can be used to predict imino chemical shifts of RNAs to remarkable accuracy. Strikingly, the semiempirical method can well interpret the variations of chemical shifts for different base pair triplets, and is even applicable to non-canonical motifs. This finding opens an avenue for predicting chemical shifts of more complicated RNA motifs. Furthermore, we combine the imino chemical shift prediction with NMR relaxation dispersion experiments targeting both ¹⁵N and ¹H^N of the imino group, and verify a previously characterized excited state of P5abc subdomain including an earlier speculated non-native G•G mismatch.

Prediction of chemical shifts is critical for extracting structural and dynamic information from biomolecular NMR data. Here the authors report an RNA imino group chemical shift predictor, showing that the imino chemical shifts of a residue are dictated by the surrounding base pair triplet.

Chemical shifts-based similarity restraints improve accuracy of RNA structures determined via NMR

Determination of structure of RNA via NMR is complicated in large part by the lack of a precise parameterization linking the observed chemical shifts to the underlying geometric parameters. In contrast to proteins, where numerous high-resolution crystal structures serve as coordinate templates for this mapping, such models are rarely available for smaller oligonucleotides accessible via NMR, or they exhibit crystal packing and counter-ion binding artifacts that prevent their use for the chemical shifts analysis. On the other hand, NMR-determined structures of RNA often are not solved at the density of restraints required to precisely define the variable degrees of freedom. In this study we sidestep the problems of direct parameterization of the RNA chemical shifts/structure relationship and examine the effects of imposing local fragmental coordinate similarity restraints based on similarities of the experimental secondary ribose ¹³C/¹H chemical shifts instead. The effect of such chemical shift similarity (CSS) restraints on the structural accuracy is assessed via residual dipolar coupling (RDC)-based cross-validation. Improvements in the coordinate accuracy are observed for all of the six RNA constructs considered here as test cases, which argues for routine inclusion of these terms during NMR-based oligonucleotide structure determination. Such accuracy improvements are expected to facilitate derivation of the chemical shift/structure relationships for RNA.

Automated assignment of methyl NMR spectra from large proteins

As structural biology trends towards larger and more complex biomolecular targets, a detailed understanding of their interactions and underlying structures and dynamics is required. The development of methyl-TROSY has enabled NMR spectroscopy to provide atomic-resolution insight into the mechanisms of large molecular assemblies in solution. However, the applicability of methyl-TROSY has been hindered by the laborious and time-consuming resonance assignment process, typically performed with domain fragmentation, site-directed mutagenesis, and analysis of NOE data in the context of a crystal structure. In response, several structure-based automatic methyl assignment strategies have been developed over the past decade. Here, we present a comprehensive analysis of all available methods and compare their input data requirements, algorithmic strategies, and reported performance. In general, the methods fall into two categories: those that primarily rely on inter-methyl NOEs, and those that utilize methyl PRE- and PCS-based restraints. We discuss their advantages and limitations, and highlight the potential benefits from standardizing and combining different methods.

Automatic structure-based NMR methyl resonance assignment in large proteins

Isotopically labeled methyl groups provide NMR probes in large, otherwise deuterated proteins. However, the resonance assignment constitutes a bottleneck for broader applicability of methyl-based NMR. Here, we present the automated MethylFLYA method for the assignment of methyl groups that is based on methyl-methyl nuclear Overhauser effect spectroscopy (NOESY) peak lists. MethylFLYA is applied to five proteins (28–358 kDa) comprising a total of 708 isotope-labeled methyl groups, of which 612 contribute NOESY cross peaks. MethylFLYA confidently assigns 488 methyl groups, i.e. 80% of those with NOESY data. Of these, 459 agree with the reference, 6 were different, and 23 were without reference assignment. MethylFLYA assigns significantly more methyl groups than alternative algorithms, has an average error rate of 1%, modest runtimes of 0.4–1.2 h, and can handle arbitrary isotope labeling patterns and data from other types of NMR spectra.

The structures and dynamics of large proteins can be studied with methyl-based NMR but peak assignment is still challenging. Here the authors present MethylFLYA that allows automated assignment of methyl groups and apply it to five proteins with molecular weights in the range from 28 to 358 kDa.

An unexpected RNA distal interaction mode found in an essential region of the hepatitis C virus genome

The 3’X tail is a functionally essential 98-nt sequence located at the 3′-end of the hepatitis C virus (HCV) RNA genome. The domain contains two absolutely conserved dimer linkage sequence (DLS) and k nucleotide segments involved in viral RNA dimerization and in a distal base-pairing interaction with stem-loop 5BSL3.2, respectively. We have previously shown that domain 3’X forms an elongated structure comprising two coaxially stacked SL1’ and SL2’ stem-loops. This conformation favors RNA dimerization by exposing a palindromic DLS segment in an apical loop, but buries in the upper stem of hairpin SL2’ the k nucleotides involved in the distal contact with 5BSL3.2. Using nuclear magnetic resonance spectroscopy and gel electrophoresis experiments, here we show that the establishment of the complex between domain 3’X and stem-loop 5BSL3.2 only requires a rearrangement of the nucleotides forming the upper region of subdomain SL2’. The results indicate that the interaction does not occur through a canonical kissing loop mechanism involving the unpaired nucleotides of two terminal loops, but rather involves a base-paired stem and an apical loop and may result in a kissing three-way junction. On the basis of this information we suggest how the 3’X tail switches between monomer, homodimer and heterodimer states to regulate the HCV viral cycle.

The Sorghum QTL Atlas: a powerful tool for trait dissection, comparative genomics and crop improvement

We describe the development and application of the Sorghum QTL Atlas, a high-resolution, open-access research platform to facilitate candidate gene identification across three cereal species, sorghum, maize and rice. The mechanisms governing the genetic control of many quantitative traits are only poorly understood and have yet to be fully exploited. Over the last two decades, over a thousand QTL and GWAS studies have been published in the major cereal crops including sorghum, maize and rice. A large body of information has been generated on the genetic basis of quantitative traits, their genomic location, allelic effects and epistatic interactions. However, such QTL information has not been widely applied by cereal improvement programs and genetic researchers worldwide. In part this is due to the heterogeneous nature of QTL studies which leads QTL reliability variation from study to study. Using approaches to adjust the QTL confidence interval, this platform provides access to the most updated sorghum QTL information than any database available, spanning 23 years of research since 1995. The QTL database provides information on the predicted gene models underlying the QTL CI, across all sorghum genome assembly gene sets and maize and rice genome assemblies and also provides information on the diversity of the underlying genes and information on signatures of selection in sorghum. The resulting high-resolution, open-access research platform facilitates candidate gene identification across 3 cereal species, sorghum, maize and rice. Using a number of trait examples, we demonstrate the power and resolution of the resource to facilitate comparative genomics approaches to provide a bridge between genomics and applied breeding.

Chemical shift-based methods in NMR structure determination

Chemical shifts are highly sensitive probes harnessed by NMR spectroscopists and structural biologists as conformational parameters to characterize a range of biological molecules. Traditionally, assignment of chemical shifts has been a labor-intensive process requiring numerous samples and a suite of multidimensional experiments. Over the past two decades, the development of complementary computational approaches has bolstered the analysis, interpretation and utilization of chemical shifts for elucidation of high resolution protein and nucleic acid structures. Here, we review the development and application of chemical shift-based methods for structure determination with a focus on ab initio fragment assembly, comparative modeling, oligomeric systems, and automated assignment methods. Throughout our discussion, we point out practical uses, as well as advantages and caveats, of using chemical shifts in structure modeling. We additionally highlight (i) hybrid methods that employ chemical shifts with other types of NMR restraints (residual dipolar couplings, paramagnetic relaxation enhancements and pseudocontact shifts) that allow for improved accuracy and resolution of generated 3D structures, (ii) the utilization of chemical shifts to model the structures of sparsely populated excited states, and (iii) modeling of sidechain conformations. Finally, we briefly discuss the advantages of contemporary methods that employ sparse NMR data recorded using site-specific isotope labeling schemes for chemical shift-driven structure determination of larger molecules. With this review, we aim to emphasize the accessibility and versatility of chemical shifts for structure determination of challenging biological systems, and to point out emerging areas of development that lead us towards the next generation of tools.

Application of Dirichlet process mixture model to the identification of spin systems in protein NMR spectra

Analysis of structure, function and interactions of proteins by NMR spectroscopy usually requires the assignment of resonances to the corresponding nuclei in protein. This task, although automated by methods such as FLYA or PINE, is still frequently performed manually. To facilitate the manual sequence-specific chemical shift assignment of complex proteins, we propose a method based on Dirichlet process mixture model (DPMM) that performs automated matching of groups of signals observed in NMR spectra to corresponding nuclei in protein sequence. The model has been extensively tested on 80 proteins retrieved from the BMRB database and has shown superior performance to the reference method.

Efficient Detection of Structure and Dynamics in Unlabeled RNAs: The SELOPE Approach

The knowledge of structure and dynamics is crucial to explain the function of RNAs. While nuclear magnetic resonance (NMR) is well suited to probe these for complex biomolecules, it requires expensive, isotopically labeled samples, and long measurement times. Here we present SELOPE, a new robust, proton-only NMR method that allows us to obtain site-specific overview of structure and dynamics in an entire RNA molecule using an unlabeled sample. SELOPE simplifies assignment and allows for cost-effective screening of the response of nucleic acids to physiological changes (e.g. ion concentration) or screening of drugs in a high throughput fashion. This single technique allows us to probe an unprecedented range of exchange time scales (the whole μs to ms motion range) with increased sensitivity, surpassing all current experiments to detect chemical exchange. For the first time we could describe an RNA excited state using an unlabeled RNA.

NMR in structure-based drug design

NMR spectroscopy is a powerful technique that can provide valuable structural information for drug discovery endeavors. Here, we discuss the strengths (and limitations) of NMR applications to structure-based drug discovery, highlighting the different levels of resolution and throughput obtainable. Additionally, the emerging field of paramagnetic NMR in drug discovery and recent developments in approaches to speed up and automate protein-observed NMR data collection and analysis are discussed.

Combining asymmetric 13C-labeling and isotopic filter/edit NOESY: a novel strategy for rapid and logical RNA resonance assignment

Although ∼98% of the human genomic output is transcribed as non-protein coding RNA, <2% of the protein data bank structures comprise RNA. This huge structural disparity stems from combined difficulties of crystallizing RNA for X-ray crystallography along with extensive chemical shift overlap and broadened linewidths associated with NMR of RNA. While half of the deposited RNA structures in the PDB were solved by NMR methods, the usefulness of NMR is still limited by the high cost of sample preparation and challenges of resonance assignment. Here we propose a novel strategy for resonance assignment that combines new strategic 13C labeling technologies with filter/edit type NOESY experiments to greatly reduce spectral complexity and crowding. This new strategy allowed us to assign important non-exchangeable resonances of proton and carbon (1', 2', 2, 5, 6 and 8) nuclei using only one sample and <24 h of NMR instrument time for a 27 nt model RNA. The method was further extended to assigning a 6 nt bulge from a 61 nt viral RNA element justifying its use for a wide range RNA chemical shift resonance assignment problems.

NMR-based automated protein structure determination

NMR spectra analysis for protein structure determination can now in many cases be performed by automated computational methods. This overview of the computational methods for NMR protein structure analysis presents recent automated methods for signal identification in multidimensional NMR spectra, sequence-specific resonance assignment, collection of conformational restraints, and structure calculation, as implemented in the CYANA software package. These algorithms are sufficiently reliable and integrated into one software package to enable the fully automated structure determination of proteins starting from NMR spectra without manual interventions or corrections at intermediate steps, with an accuracy of 1-2 Å backbone RMSD in comparison with manually solved reference structures.

Capturing Excited States in the Fast-Intermediate Exchange Limit in Biological Systems Using 1 H NMR Spectroscopy

Changes in molecular structure are essential for the function of biomolecules. Characterization of these structural fluctuations can illuminate alternative states and help in correlating structure to function. NMR relaxation dispersion (RD) is currently the only method for detecting these alternative, high-energy states. In this study, we present a versatile ¹ H R_1ρ RD experiment that not only extends the exchange timescales at least three times beyond the rate limits of ¹³ C/¹⁵ N R_1ρ and ten times for CPMG experiments, but also makes use of easily accessible probes, thus allowing a general description of biologically important excited states. This technique can be used to extract chemical shifts for the structural characterization of excited states and to elucidate complex excited states.

NMR solution structure determination of large RNA-protein complexes

Structure determination of RNA-protein complexes is essential for our understanding of the multiple layers of RNA-mediated posttranscriptional regulation of gene expression. Over the past 20years, NMR spectroscopy became a key tool for structural studies of RNA-protein interactions. Here, we review the progress being made in NMR structure determination of large ribonucleoprotein assemblies. We discuss approaches for the design of RNA-protein complexes for NMR structural studies, established and emerging isotope and segmental labeling schemes suitable for large RNPs and how to gain distance restraints from NOEs, PREs and EPR and orientational information from RDCs and SAXS/SANS in such systems. The new combination of NMR measurements with MD simulations and its potential will also be discussed. Application and combination of these various methods for structure determination of large RNPs will be illustrated with three large RNA-protein complexes (>40kDa) and other interesting complexes determined in the past six and a half years.

Integrative NMR for biomolecular research

NMR spectroscopy is a powerful technique for determining structural and functional features of biomolecules in physiological solution as well as for observing their intermolecular interactions in real-time. However, complex steps associated with its practice have made the approach daunting for non-specialists. We introduce an NMR platform that makes biomolecular NMR spectroscopy much more accessible by integrating tools, databases, web services, and video tutorials that can be launched by simple installation of NMRFAM software packages or using a cross-platform virtual machine that can be run on any standard laptop or desktop computer. The software package can be downloaded freely from the NMRFAM software download page ( http://pine.nmrfam.wisc.edu/download_packages.html ), and detailed instructions are available from the Integrative NMR Video Tutorial page ( http://pine.nmrfam.wisc.edu/integrative.html ).

High resolution 4D HPCH experiment for sequential assignment of (13)C-labeled RNAs via phosphodiester backbone

The three-dimensional structure determination of RNAs by NMR spectroscopy requires sequential resonance assignment, often hampered by assignment ambiguities and limited dispersion of (1)H and (13)C chemical shifts, especially of C4'/H4'. Here we present a novel through-bond 4D HPCH NMR experiment involving phosphate backbone where C4'-H4' correlations are resolved along the (1)H3'-(31)P spectral planes. The experiment provides high peak resolution and effectively removes ambiguities encountered during assignments. Enhanced peak dispersion is provided by the inclusion of additional (31)P and (1)H3' dimensions and constant-time evolution of chemical shifts. High spectral resolution is obtained by using non-uniform sampling in three indirect dimensions. The experiment fully utilizes the isotopic (13)C-labeling with evolution of C4' carbons. Band selective (13)C inversion pulses are used to achieve selectivity and prevent signal dephasing due to the C4'-C3' and C4'-C5' homonuclear couplings. Multiple quantum line narrowing is employed to minimize sensitivity loses. The 4D HPCH experiment is verified and successfully applied to a non-coding 34-nt RNA consisting typical structure elements and a 14-nt RNA hairpin capped by cUUCGg tetraloop.

Prediction of hydrogen and carbon chemical shifts from RNA using database mining and support vector regression

The Biological Magnetic Resonance Data Bank (BMRB) contains NMR chemical shift depositions for over 200 RNAs and RNA-containing complexes. We have analyzed the (1)H NMR and (13)C chemical shifts reported for non-exchangeable protons of 187 of these RNAs. Software was developed that downloads BMRB datasets and corresponding PDB structure files, and then generates residue-specific attributes based on the calculated secondary structure. Attributes represent properties present in each sequential stretch of five adjacent residues and include variables such as nucleotide type, base-pair presence and type, and tetraloop types. Attributes and (1)H and (13)C NMR chemical shifts of the central nucleotide are then used as input to train a predictive model using support vector regression. These models can then be used to predict shifts for new sequences. The new software tools, available as stand-alone scripts or integrated into the NMR visualization and analysis program NMRViewJ, should facilitate NMR assignment and/or validation of RNA (1)H and (13)C chemical shifts. In addition, our findings enabled the re-calibration a ring-current shift model using published NMR chemical shifts and high-resolution X-ray structural data as guides.

NMR proton chemical shift prediction of C·C mismatches in B-DNA

Accurate prediction of DNA chemical shifts facilitates resonance assignment and allows recognition of different conformational features. Based on the nearest neighbor model and base pair replacement approach, we have determined a set of triplet chemical shift values and correction factors for predicting the proton chemical shifts of B-DNA containing an internal C·C mismatch. Our results provide a reliable chemical shift prediction with an accuracy of 0.07 ppm for non-labile protons and 0.09 ppm for labile protons. In addition, we have also shown that the correction factors for C·C mismatches can be used interchangeably with those for T·T mismatches. As a result, we have generalized a set of correction factors for predicting the flanking residue chemical shifts of pyrimidine·pyrimidine mismatches.

Automated resonance assignment of the 21kDa stereo-array isotope labeled thioldisulfide oxidoreductase DsbA

The automated chemical shift assignment algorithm FLYA has been extended for use with stereo-array isotope labeled (SAIL) proteins to determine the sequence-specific resonance assignments of large proteins. Here we present the assignment of the backbone and sidechain chemical shifts of the 21kDa thioldisulfide oxidoreductase DsbA from Escherichia coli that were determined with the SAIL-FLYA algorithm in conjunction with automated peak picking. No manual corrections of peak lists or assignments were applied. The assignments agreed with manually determined reference assignments in 95.4% of the cases if 16 input spectra were used, 94.1% if only 3D ¹³C/¹⁵N-resolved NOESY, CBCA(CO)NH, and 2D [¹³C/¹⁵N,¹H]-HSQC were used, and 86.8% if exclusively 3D ¹³C/¹⁵N-resolved NOESY spectra were used. Considering only the assignments that are classified as reliable by the SAIL-FLYA algorithm, the degrees of agreement increased to 97.5%, 96.5%, and 94.2%, respectively. With our approach it is thus possible to automatically obtain almost complete and correct assignments of proteins larger than 20kDa.

C4'/H4' selective, non-uniformly sampled 4D HC(P)CH experiment for sequential assignments of (13)C-labeled RNAs

A through bond, C4'/H4' selective, "out and stay" type 4D HC(P)CH experiment is introduced which provides sequential connectivity via H4'(i)-C4'(i)-C4'(i-1)-H4'(i-1) correlations. The (31)P dimension (used in the conventional 3D HCP experiment) is replaced with evolution of better dispersed C4' dimension. The experiment fully utilizes (13)C-labeling of RNA by inclusion of two C4' evolution periods. An additional evolution of H4' is included to further enhance peak resolution. Band selective (13)C inversion pulses are used to achieve selectivity and prevent signal dephasing due to the of C4'-C3' and C4'-C5' homonuclear couplings. For reasonable resolution, non-uniform sampling is employed in all indirect dimensions. To reduce sensitivity losses, multiple quantum coherences are preserved during shared-time evolution and coherence transfer delays. In the experiment the intra-nucleotide peaks are suppressed whereas inter-nucleotide peaks are enhanced to reduce the ambiguities. The performance of the experiment is verified on a fully (13)C, (15)N-labeled 34-nt hairpin RNA comprising typical structure elements.

A simple and fast approach for predicting (1)H and (13)C chemical shifts: toward chemical shift-guided simulations of RNA

We introduce a simple and fast approach for predicting RNA chemical shifts from interatomic distances that performs with an accuracy similar to existing predictors and enables the first chemical shift-restrained simulations of RNA to be carried out. Our analysis demonstrates that the applied restraints can effectively guide conformational sampling toward regions of space that are more consistent with chemical shifts than the initial coordinates used for the simulations. As such, our approach should be widely applicable in mapping the conformational landscape of RNAs via chemical shift-guided molecular dynamics simulations. The simplicity and demonstrated sensitivity to three-dimensional structure should also allow our method to be used in chemical shift-based RNA structure prediction, validation, and refinement.

Nucleotide-type chemical shift assignment of the encapsulated 40 kbp dsDNA in intact bacteriophage T7 by MAS solid-state NMR

The icosahedral bacteriophage T7 is a 50 MDa double-stranded DNA (dsDNA) virus that infects Escherichia coli. Although there is substantial information on the physical and morphological properties of T7, structural information, based mostly on Raman spectroscopy and cryo-electron microscopy, is limited. Here, we apply the magic-angle spinning (MAS) solid-state NMR (SSNMR) technique to study a uniformly (13)C and (15)N labeled wild-type T7 phage. We describe the details of the large-scale preparation and purification of an isotopically enriched phage sample under fully hydrated conditions, and show a complete (13)C and a near-complete (15)N nucleotide-type specific assignment of the sugar and base moieties in the 40 kbp dsDNA of T7 using two-dimensional (13)C-(13)C and (15)N-(13)C correlation experiments. The chemical shifts are interpreted as reporters of a B-form conformation of the encapsulated dsDNA. While MAS SSNMR was found to be extremely useful in determining the structures of proteins in native-like environments, its application to nucleic acids has lagged behind, leaving a missing (13)C and (15)N chemical shift database. This work therefore expands the (13)C and (15)N database of real B-form DNA systems, and opens routes to characterize more complex nucleic acid systems by SSNMR.

Strategy for automated NMR resonance assignment of RNA: application to 48-nucleotide K10

A procedure is presented for automated sequence-specific assignment of NMR resonances of uniformly [(13)C, (15)N]-labeled RNA. The method is based on a suite of four through-bond and two through-space high-dimensional automated projection spectroscopy (APSY) experiments. The approach is exemplified with a 0.3 mM sample of an RNA stem-loop with 48 nucleotides, K10, which is responsible for dynein-mediated localization of Drosophila fs(1)K10 mRNA transcripts. The automated analysis of the APSY data led to highly accurate and precise 3- to 4-dimensional peak lists. They provided a reliable basis for the subsequent sequence-specific resonance assignment with the algorithm FLYA and resulted in the fully automated resonance assignment of more than 80 % of the resonances of the (13)C-(1)H moieties at the 1', 2', 5, 6, and 8 positions in the nucleotides. The procedure was robust with respect to numerous impurity peaks, low concentration of this for NMR comparably large RNA, and structural features such as a loop, single-nucleotide bulges and a non-Watson-Crick wobble base pairs. Currently, there is no precise chemical shift statistics (as used by FLYA) for RNA regions which deviate from the regular A-form helical structure. Reliable and precise peak lists are thus required for automated sequence-specific assignment, as provided by APSY.

Automated NMR resonance assignment strategy for RNA via the phosphodiester backbone based on high-dimensional through-bond APSY experiments

A fast, robust and reliable strategy for automated sequential resonance assignment for uniformly [(13)C, (15)N]-labeled RNA via its phosphodiester backbone is presented. It is based on a series of high-dimensional through-bond APSY experiments: a 5D HCP-CCH COSY, a 4D H1'C1'CH TOCSY for ribose resonances, a 5D HCNCH for ribose-to-base connection, a 4D H6C6C5H5 TOCSY for pyrimidine resonances, and a 4D H8C8(C)C2H2 TOCSY for adenine resonances. The utilized pulse sequences are partially novel, and optimized to enable long evolution times in all dimensions. The highly precise APSY peak lists derived with these experiments could be used directly for reliable automated resonance assignment with the FLYA algorithm. This approach resulted in 98 % assignment completeness for all (13)C-(1)H, (15)N1/9 and (31)P resonances of a stem-loop with 14 nucleotides.

Molecular basis for the wide range of affinity found in Csr/Rsm protein-RNA recognition

The carbon storage regulator/regulator of secondary metabolism (Csr/Rsm) type of small non-coding RNAs (sRNAs) is widespread throughout bacteria and acts by sequestering the global translation repressor protein CsrA/RsmE from the ribosome binding site of a subset of mRNAs. Although we have previously described the molecular basis of a high affinity RNA target bound to RsmE, it remains unknown how other lower affinity targets are recognized by the same protein. Here, we have determined the nuclear magnetic resonance solution structures of five separate GGA binding motifs of the sRNA RsmZ of Pseudomonas fluorescens in complex with RsmE. The structures explain how the variation of sequence and structural context of the GGA binding motifs modulate the binding affinity for RsmE by five orders of magnitude (∼10 nM to ∼3 mM, Kd). Furthermore, we see that conformational adaptation of protein side-chains and RNA enable recognition of different RNA sequences by the same protein contributing to binding affinity without conferring specificity. Overall, our findings illustrate how the variability in the Csr/Rsm protein-RNA recognition allows a fine-tuning of the competition between mRNAs and sRNAs for the CsrA/RsmE protein.

Reliability of exclusively NOESY-based automated resonance assignment and structure determination of proteins

Protein structure determination by NMR can in principle be speeded up both by reducing the measurement time on the NMR spectrometer and by a more efficient analysis of the spectra. Here we study the reliability of protein structure determination based on a single type of spectra, namely nuclear Overhauser effect spectroscopy (NOESY), using a fully automated procedure for the sequence-specific resonance assignment with the recently introduced FLYA algorithm, followed by combined automated NOE distance restraint assignment and structure calculation with CYANA. This NOESY-FLYA method was applied to eight proteins with 63-160 residues for which resonance assignments and solution structures had previously been determined by the Northeast Structural Genomics Consortium (NESG), and unrefined and refined NOESY data sets have been made available for the Critical Assessment of Automated Structure Determination of Proteins by NMR project. Using only peak lists from three-dimensional (13)C- or (15)N-resolved NOESY spectra as input, the FLYA algorithm yielded for the eight proteins 91-98 % correct backbone and side-chain assignments if manually refined peak lists are used, and 64-96 % correct assignments based on raw peak lists. Subsequent structure calculations with CYANA then produced structures with root-mean-square deviation (RMSD) values to the manually determined reference structures of 0.8-2.0 Å if refined peak lists are used. With raw peak lists, calculations for 4 proteins converged resulting in RMSDs to the reference structure of 0.8-2.8 Å, whereas no convergence was obtained for the four other proteins (two of which did already not converge with the correct manual resonance assignments given as input). These results show that, given high-quality experimental NOESY peak lists, the chemical shift assignments can be uncovered, without any recourse to traditional through-bond type assignment experiments, to an extent that is sufficient for calculating accurate three-dimensional structures.