Computational Methods for RNA Structure Validation and Improvement

The pseudotorsional space of RNA

The characterization of the conformational landscape of the RNA backbone is rather complex due to the ability of RNA to assume a large variety of conformations. These backbone conformations can be depicted by pseudotorsional angles linking RNA backbone atoms, from which Ramachandran-like plots can be built. We explore here different definitions of these pseudotorsional angles, finding that the most accurate ones are the traditional η (eta) and θ (theta) angles, which represent the relative position of RNA backbone atoms P and C4'. We explore the distribution of η - θ in known experimental structures, comparing the pseudotorsional space generated with structures determined exclusively by one experimental technique. We found that the complete picture only appears when combining data from different sources. The maps provide a quite comprehensive representation of the RNA accessible space, which can be used in RNA-structural predictions. Finally, our results highlight that protein interactions lead to significant changes in the population of the η - θ space, pointing toward the role of induced-fit mechanisms in protein-RNA recognition.

Machine learning modeling of RNA structures: methods, challenges and future perspectives

The three-dimensional structure of RNA molecules plays a critical role in a wide range of cellular processes encompassing functions from riboswitches to epigenetic regulation. These RNA structures are incredibly dynamic and can indeed be described aptly as an ensemble of structures that shifts in distribution depending on different cellular conditions. Thus, the computational prediction of RNA structure poses a unique challenge, even as computational protein folding has seen great advances. In this review, we focus on a variety of machine learning-based methods that have been developed to predict RNA molecules' secondary structure, as well as more complex tertiary structures. We survey commonly used modeling strategies, and how many are inspired by or incorporate thermodynamic principles. We discuss the shortcomings that various design decisions entail and propose future directions that could build off these methods to yield more robust, accurate RNA structure predictions.

Refinement of RNA Structures Using Amber Force Fields

Atomic models for nucleic acids derived from X-ray diffraction data at low resolution provide much useful information, but the observed scattering intensities can be fit with models that can differ in structural detail. Tradtional geometric restraints favor models that have bond length and angle terms derived from small molecule crystal structures. Here we explore replacing these restraints with energy gradients derived from force fields, including recently developed integral equation models to account for the effects of water molecules and ions that are not part of the explicit model. We compare conventional and force-field based refinements for 22 RNA crystals, ranging in resolution from 1.1 to 3.6 Å. As expected, it can be important to account for solvent screening of charge–charge interactions, especially in the crowded environment of a nucleic acid crystal. The newly refined models can show improvements in torsion angles and hydrogen-bonding interactions, and can significantly reduce unfavorable atomic clashes, while maintaining or improving agreement with observed scattering intensities.

Geometric deep learning of RNA structure

RNA molecules adopt three-dimensional structures that are critical to their function and of interest in drug discovery. Few RNA structures are known, however, and predicting them computationally has proven challenging. We introduce a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures. The resulting scoring function, the Atomic Rotationally Equivariant Scorer (ARES), substantially outperforms previous methods and consistently produces the best results in community-wide blind RNA structure prediction challenges. By learning effectively even from a small amount of data, our approach overcomes a major limitation of standard deep neural networks. Because it uses only atomic coordinates as inputs and incorporates no RNA-specific information, this approach is applicable to diverse problems in structural biology, chemistry, materials science, and beyond.

The Halastavi árva Virus Intergenic Region IRES Promotes Translation by the Simplest Possible Initiation Mechanism

Dicistrovirus intergenic region internal ribosomal entry sites (IGR IRESs) do not require initiator tRNA, an AUG codon, or initiation factors and jumpstart translation from the middle of the elongation cycle via formation of IRES/80S complexes resembling the pre-translocation state. eEF2 then translocates the [codon-anticodon]-mimicking pseudoknot I (PKI) from ribosomal A sites to P sites, bringing the first sense codon into the decoding center. Halastavi árva virus (HalV) contains an IGR that is related to previously described IGR IRESs but lacks domain 2, which enables these IRESs to bind to individual 40S ribosomal subunits. By using in vitro reconstitution and cryoelectron microscopy (cryo-EM), we now report that the HalV IGR IRES functions by the simplest initiation mechanism that involves binding to 80S ribosomes such that PKI is placed in the P site, so that the A site contains the first codon that is directly accessible for decoding without prior eEF2-mediated translocation of PKI.

Assessment of the nucleotide modifications in the high-resolution cryo-electron microscopy structure of the Escherichia coli 50S subunit

Post-transcriptional ribosomal RNA (rRNA) modifications are present in all organisms, but their exact functional roles and positions are yet to be fully characterized. Modified nucleotides have been implicated in the stabilization of RNA structure and regulation of ribosome biogenesis and protein synthesis. In some instances, rRNA modifications can confer antibiotic resistance. High-resolution ribosome structures are thus necessary for precise determination of modified nucleotides' positions, a task that has previously been accomplished by X-ray crystallography. Here, we present a cryo-electron microscopy (cryo-EM) structure of the Escherichia coli 50S subunit at an average resolution of 2.2 Å as an additional approach for mapping modification sites. Our structure confirms known modifications present in 23S rRNA and additionally allows for localization of Mg2+ ions and their coordinated water molecules. Using our cryo-EM structure as a testbed, we developed a program for assessment of cryo-EM map quality. This program can be easily used on any RNA-containing cryo-EM structure, and an associated Coot plugin allows for visualization of validated modifications, making it highly accessible.

Improved chemistry restraints for crystallographic refinement by integrating the Amber force field into Phenix

The refinement of biomolecular crystallographic models relies on geometric restraints to help to address the paucity of experimental data typical in these experiments. Limitations in these restraints can degrade the quality of the resulting atomic models. Here, an integration of the full all-atom Amber molecular-dynamics force field into Phenix crystallographic refinement is presented, which enables more complete modeling of biomolecular chemistry. The advantages of the force field include a carefully derived set of torsion-angle potentials, an extensive and flexible set of atom types, Lennard-Jones treatment of nonbonded interactions and a full treatment of crystalline electrostatics. The new combined method was tested against conventional geometry restraints for over 22 000 protein structures. Structures refined with the new method show substantially improved model quality. On average, Ramachandran and rotamer scores are somewhat better, clashscores and MolProbity scores are significantly improved, and the modeling of electrostatics leads to structures that exhibit more, and more correct, hydrogen bonds than those refined using traditional geometry restraints. In general it is found that model improvements are greatest at lower resolutions, prompting plans to add the Amber target function to real-space refinement for use in electron cryo-microscopy. This work opens the door to the future development of more advanced applications such as Amber-based ensemble refinement, quantum-mechanical representation of active sites and improved geometric restraints for simulated annealing.

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

Nucleobase carbonyl groups are poor Mg2+ inner-sphere binders but excellent monovalent ion binders-a critical PDB survey

Precise knowledge of Mg²⁺ inner-sphere binding site properties is vital for understanding the structure and function of nucleic acid systems. Unfortunately, the PDB, which represents the main source of Mg²⁺ binding sites, contains a substantial number of assignment issues that blur our understanding of the functions of these ions. Here, following a previous study devoted to Mg²⁺ binding to nucleobase nitrogens, we surveyed nucleic acid X-ray structures from the PDB with resolutions ≤2.9 Å to classify the Mg²⁺ inner-sphere binding patterns to nucleotide carbonyl, ribose hydroxyl, cyclic ether, and phosphodiester oxygen atoms. From this classification, we derived a set of "prior-knowledge" nucleobase Mg²⁺ binding sites. We report that crystallographic examples of trustworthy nucleobase Mg²⁺ binding sites are fewer than expected since many of those are associated with misidentified Na⁺ or K⁺ We also emphasize that binding of Na⁺ and K⁺ to nucleic acids is much more frequent than anticipated. Overall, we provide evidence derived from X-ray structures that nucleobases are poor inner-sphere binders for Mg²⁺ but good binders for monovalent ions. Based on strict stereochemical criteria, we propose an extended set of guidelines designed to help in the assignment and validation of ions directly contacting nucleobase and ribose atoms. These guidelines should help in the interpretation of X-ray and cryo-EM solvent density maps. When borderline Mg²⁺ stereochemistry is observed, alternative placement of Na⁺, K⁺, or Ca²⁺ must be considered. We also critically examine the use of lanthanides (Yb³⁺, Tb³⁺) as Mg²⁺ substitutes in crystallography experiments.

Assessment of detailed conformations suggests strategies for improving cryoEM models: Helix at lower resolution, ensembles, pre-refinement fixups, and validation at multi-residue length scale

We find that the overall quite good methods used in the CryoEM Model Challenge could still benefit greatly from several strategies for improving local conformations. Our assessments primarily use validation criteria from the MolProbity web service. Those criteria include MolProbity's all-atom contact analysis, updated versions of standard conformational validations for protein and RNA, plus two recent additions: first, flags for cis-nonPro and twisted peptides, and second, the CaBLAM system for diagnosing secondary structure, validating Cα backbone, and validating adjacent peptide CO orientations in the context of the Cα trace. In general, automated ab initio building of starting models is quite good at backbone connectivity but often fails at local conformation or sequence register, especially at poorer than 3.5 Å resolution. However, we show that even if criteria (such as Ramachandran or rotamer) are explicitly restrained to improve refinement behavior and overall validation scores, automated optimization of a deposited structure seldom corrects specific misfittings that start in the wrong local minimum, but just hides them. Therefore, local problems should be identified, and as many as possible corrected, before starting refinement. Secondary structures are confusing at 3-4 Å but can be better recognized at 6-8 Å. In future model challenges, specific steps being tested (such as segmentation) and the required documentation (such as PDB code of starting model) should each be explicitly defined, so competing methods on a given task can be meaningfully compared. Individual local examples are presented here, to understand what local mistakes and corrections look like in 3D, how they probably arise, and what possible improvements to methodology might help avoid them. At these resolutions, both structural biologists and end-users need meaningful estimates of local uncertainty, perhaps through explicit ensembles. Fitting problems can best be diagnosed by validation that spans multiple residues; CaBLAM is such a multi-residue tool, and its effectiveness is demonstrated.

Model validation: local diagnosis, correction and when to quit

Traditionally, validation was considered to be a final gatekeeping function, but refinement is smoother and results are better if model validation actively guides corrections throughout structure solution. This shifts emphasis from global to local measures: primarily geometry, conformations and sterics. A fit into the wrong local minimum conformation usually produces outliers in multiple measures. Moving to the right local minimum should be prioritized, rather than small shifts across arbitrary borderlines. Steric criteria work best with all explicit H atoms. `Backrub' motions should be used for side chains and `P-perp' diagnostics to correct ribose puckers. A `water' may actually be an ion, a relic of misfitting or an unmodeled alternate. Beware of wishful thinking in modeling ligands. At high resolution, internally consistent alternate conformations should be modeled and geometry in poor density should not be downweighted. At low resolution, CaBLAM should be used to diagnose protein secondary structure and ERRASER to correct RNA backbone. All atoms should not be forced inside density, beware of sequence misalignment, and very rare conformations such as cis-non-Pro peptides should be avoided. Automation continues to improve, but the crystallographer still must look at each outlier, in the context of density, and correct most of them. For the valid few with unambiguous density and something that is holding them in place, a functional reason should be sought. The expectation is a few outliers, not zero.

MolProbity: More and better reference data for improved all-atom structure validation

This paper describes the current update on macromolecular model validation services that are provided at the MolProbity website, emphasizing changes and additions since the previous review in 2010. There have been many infrastructure improvements, including rewrite of previous Java utilities to now use existing or newly written Python utilities in the open-source CCTBX portion of the Phenix software system. This improves long-term maintainability and enhances the thorough integration of MolProbity-style validation within Phenix. There is now a complete MolProbity mirror site at http://molprobity.manchester.ac.uk. GitHub serves our open-source code, reference datasets, and the resulting multi-dimensional distributions that define most validation criteria. Coordinate output after Asn/Gln/His "flip" correction is now more idealized, since the post-refinement step has apparently often been skipped in the past. Two distinct sets of heavy-atom-to-hydrogen distances and accompanying van der Waals radii have been researched and improved in accuracy, one for the electron-cloud-center positions suitable for X-ray crystallography and one for nuclear positions. New validations include messages at input about problem-causing format irregularities, updates of Ramachandran and rotamer criteria from the million quality-filtered residues in a new reference dataset, the CaBLAM Cα-CO virtual-angle analysis of backbone and secondary structure for cryoEM or low-resolution X-ray, and flagging of the very rare cis-nonProline and twisted peptides which have recently been greatly overused. Due to wide application of MolProbity validation and corrections by the research community, in Phenix, and at the worldwide Protein Data Bank, newly deposited structures have continued to improve greatly as measured by MolProbity's unique all-atom clashscore.

Structures and dynamics of hibernating ribosomes from Staphylococcus aureus mediated by intermolecular interactions of HPF

In bacteria, ribosomal hibernation shuts down translation as a response to stress, through reversible binding of stress-induced proteins to ribosomes. This process typically involves the formation of 100S ribosome dimers. Here, we present the structures of hibernating ribosomes from human pathogen Staphylococcus aureus containing a long variant of the hibernation-promoting factor (SaHPF) that we solved using cryo-electron microscopy. Our reconstructions reveal that the N-terminal domain (NTD) of SaHPF binds to the 30S subunit as observed for shorter variants of HPF in other species. The C-terminal domain (CTD) of SaHPF protrudes out of each ribosome in order to mediate dimerization. Using NMR, we characterized the interactions at the CTD-dimer interface. Secondary interactions are provided by helix 26 of the 16S ribosomal RNA We also show that ribosomes in the 100S particle adopt both rotated and unrotated conformations. Overall, our work illustrates a specific mode of ribosome dimerization by long HPF, a finding that may help improve the selectivity of antimicrobials.

The Role of Unconventional Hydrogen Bonds in Determining BII Propensities in B-DNA

An accurate understanding of DNA backbone transitions is likely to be the key for elucidating the puzzle of the intricate sequence-dependent mechanical properties that govern most of the biologically relevant functions of the double helix. One factor believed to be important in indirect recognition within protein-DNA complexes is the combined effect of two DNA backbone torsions (ε and ζ) which give rise to the well-known BI/BII conformational equilibrium. In this work we explain the sequence-dependent BII propensity observed in RpY steps (R = purine; Y = pyrimidine) at the tetranucleotide level with the help of a previously undetected C-H···O contact between atoms belonging to adjacent bases. Our results are supported by extensive multimicrosecond molecular dynamics simulations from the Ascona B-DNA Consortium, high-level quantum mechanical calculations, and data mining of the experimental structures deposited in the Protein Data Bank.

Structure of the 70S ribosome from human pathogen Staphylococcus aureus

Comparative structural studies of ribosomes from various organisms keep offering exciting insights on how species-specific or environment-related structural features of ribosomes may impact translation specificity and its regulation. Although the importance of such features may be less obvious within more closely related organisms, their existence could account for vital yet species-specific mechanisms of translation regulation that would involve stalling, cell survival and antibiotic resistance. Here, we present the first full 70S ribosome structure from Staphylococcus aureus, a Gram-positive pathogenic bacterium, solved by cryo-electron microscopy. Comparative analysis with other known bacterial ribosomes pinpoints several unique features specific to S. aureus around a conserved core, at both the protein and the RNA levels. Our work provides the structural basis for the many studies aiming at understanding translation regulation in S. aureus and for designing drugs against this often multi-resistant pathogen.

Structural Analysis of Multi-Helical RNAs by NMR-SAXS/WAXS: Application to the U4/U6 di-snRNA

NMR and SAXS (small-angle X-ray scattering)/WAXS (wide-angle X-ray scattering) are highly complementary approaches for the analysis of RNA structure in solution. Here we describe an efficient NMR-SAXS/WAXS approach for structural investigation of multi-helical RNAs. We illustrate this approach by determining the overall fold of a 92-nt 3-helix junction from the U4/U6 di-snRNA. The U4/U6 di-snRNA is conserved in eukaryotes and is part of the U4/U6.U5 tri-snRNP, a large ribonucleoprotein complex that comprises a major subunit of the assembled spliceosome. Helical orientations can be determined by X-ray scattering data alone, but the addition of NMR RDC (residual dipolar coupling) restraints improves the structure models. RDCs were measured in two different external alignment media and also by magnetic susceptibility anisotropy. The resulting alignment tensors are collinear, which is a previously noted problem for nucleic acids. Including WAXS data in the calculations produces models with significantly better fits to the scattering data. In solution, the U4/U6 di-snRNA forms a 3-helix junction with a planar Y-shaped structure and has no detectable tertiary interactions. Single-molecule Förster resonance energy transfer data support the observed topology. A comparison with the recently determined cryo-electron microscopy structure of the U4/U6.U5 tri-snRNP illustrates how proteins scaffold the RNA and dramatically alter the geometry of the U4/U6 3-helix junction.