RNA backbone: consensus all-angle conformers and modular string nomenclature (an RNA Ontology Consortium contribution)

Ramachandran-like Conformational Space for DNA

DNA's ability to exist in a wide variety of structural forms, subforms, and secondary motifs is fundamental to numerous biological processes and has driven the development of biotechnological applications. Major determinants of DNA flexibility are the multiple torsional degrees of freedom around the phosphodiester backbone. This high complexity can be rationalized by using two pseudotorsional angles linking atoms P and C4', from which Ramachandran-like plots can be built. In this contribution, we explore the distribution of η (eta: C4'i-1-Pi-C4'i-Pi+1) and θ (theta: Pi-C4'i-Pi+1-C4'i+1) angles in known experimental structures retrieved from the Protein Data Bank (PDB), subdividing the conformational space into different datasets. After the removal of the canonical/helical conformations typical of the B-form, we find the existence of a conformational map with clearly permitted and forbidden regions. Some of these regions are populated with specific DNA forms, like Z- or A-DNA, or by specific secondary motifs, like G-quadruplexes and junctions. We evaluated the sequence dependency and energy relationship among the high-density regions identified in the η-θ space. Furthermore, we analyzed the effect produced by proteins and cations when bound to DNA, finding that specific proteins produce some nonhelical conformations, while other regions appear to be stabilized by divalent cations.

Elucidating microRNA-34a organisation within human Argonaute-2 by dynamic nuclear polarisation-enhanced magic angle spinning NMR

Understanding mRNA regulation by microRNA (miR) relies on the structural understanding of the RNA-induced silencing complex (RISC). Here, we elucidate the structural organisation of miR-34a, which is de-regulated in various cancers, in human Argonaute-2 (hAgo2), the effector protein in RISC. This analysis employs guanosine-specific isotopic labelling and dynamic nuclear polarisation (DNP)-enhanced Magic Angle Spinning (MAS) NMR. Homonuclear correlation experiments revealed that the non-A-form helical conformation of miR-34a increases when incorporated into hAgo2 and subsequently bound to SIRT1 mRNA compared to the free miR-34a or the free mRNA:miR duplex. The C8-C1' correlation provided a nucleotide-specific distribution of C2'- and C3'-endo sugar puckering, revealing the capture of diverse dynamic conformations upon freezing. Predominantly C3'-endo puckering was observed for the seed region, while C2'-endo conformation was found in the central region, with a mixture of both conformations elsewhere. These observations provide insights into the molecular dynamics underlying miR-mediated mRNA regulation and demonstrate that experiments conducted under cryogenic conditions, such as at 90 K, can capture and reveal frozen dynamic states, using methods like DNP-enhanced MAS NMR or Cryo-Electron Microscopy.

RNAtango: Analysing and comparing RNA 3D structures via torsional angles

RNA molecules, essential for viruses and living organisms, derive their pivotal functions from intricate 3D structures. To understand these structures, one can analyze torsion and pseudo-torsion angles, which describe rotations around bonds, whether real or virtual, thus capturing the RNA conformational flexibility. Such an analysis has been made possible by RNAtango, a web server introduced in this paper, that provides a trigonometric perspective on RNA 3D structures, giving insights into the variability of examined models and their alignment with reference targets. RNAtango offers comprehensive tools for calculating torsion and pseudo-torsion angles, generating angle statistics, comparing RNA structures based on backbone torsions, and assessing local and global structural similarities using trigonometric functions and angle measures. The system operates in three scenarios: single model analysis, model-versus-target comparison, and model-versus-model comparison, with results output in text and graphical formats. Compatible with all modern web browsers, RNAtango is accessible freely along with the source code. It supports researchers in accurately assessing structural similarities, which contributes to the precision and efficiency of RNA modeling.

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores.

The structural basis for RNA slicing by human Argonaute2

Argonaute (AGO) proteins associate with guide RNAs to form complexes that slice transcripts that pair to the guide. This slicing drives post-transcriptional gene-silencing pathways that are essential for many eukaryotes and the basis for new clinical therapies. Despite this importance, structural information on eukaryotic AGOs in a fully paired, slicing-competent conformation-hypothesized to be intrinsically unstable-has been lacking. Here we present the cryogenic-electron microscopy structure of a human AGO-guide complex bound to a fully paired target, revealing structural rearrangements that enable this conformation. Critically, the N domain of AGO rotates to allow the RNA full access to the central channel and forms contacts that license rapid slicing. Moreover, a conserved loop in the PIWI domain secures the RNA near the active site to enhance slicing rate and specificity. These results explain how AGO accommodates targets possessing the pairing specificity typically observed in biological and clinical slicing substrates.

On the Power and Challenges of Atomistic Molecular Dynamics to Investigate RNA Molecules

RNA molecules play a vital role in biological processes within the cell, with significant implications for science and medicine. Notably, the biological functions exerted by specific RNA molecules are often linked to the RNA conformational ensemble. However, the experimental characterization of such three-dimensional RNA structures is challenged by the structural heterogeneity of RNA and by its multiple dynamic interactions with binding partners such as small molecules, proteins, and metal ions. Consequently, our current understanding of the structure-function relationship of RNA molecules is still limited. In this context, we highlight molecular dynamics (MD) simulations as a powerful tool to complement experimental efforts on RNAs. Despite the recognized limitations of current force fields for RNA MD simulations, examining the dynamics of selected RNAs has provided valuable functional insights into their structures.

The guide-RNA sequence dictates the slicing kinetics and conformational dynamics of the Argonaute silencing complex

The RNA-induced silencing complex (RISC), which powers RNA interference (RNAi), consists of a guide RNA and an Argonaute protein that slices target RNAs complementary to the guide. We find that, for different guide-RNA sequences, slicing rates of perfectly complementary bound targets can be surprisingly different (>250-fold range), and that faster slicing confers better knockdown in cells. Nucleotide sequence identities at guide-RNA positions 7, 10, and 17 underlie much of this variation in slicing rates. Analysis of one of these determinants implicates a structural distortion at guide nucleotides 6-7 in promoting slicing. Moreover, slicing directed by different guide sequences has an unanticipated, 600-fold range in 3'-mismatch tolerance, attributable to guides with weak (AU-rich) central pairing requiring extensive 3' complementarity (pairing beyond position 16) to more fully populate the slicing-competent conformation. Together, our analyses identify sequence determinants of RISC activity and provide biochemical and conformational rationale for their action.

Synthesis and properties of RNA constrained by a 2'-O-disulfide bridge

We recently reported the properties of RNA hairpins constrained by a dimethylene (DME) disulfide (S-S) linker incorporated between two adjacent nucleosides in the loop and showed that this linker locked the hairpin conformation thus disturbing the duplex/hairpin equilibrium. We have now investigated the influence of the length of the linker and synthesized oligoribonucleotides containing diethylene (DEE) and dipropylene (DPE) S-S bridges. This was achieved via the preparation of building blocks, namely 2'-O-acetylthioethyl (2'-O-AcSE) and 2'-O-acetylthiopropyl (2'-O-AcSP) uridine phosphoramidites, which were successfully incorporated into RNA sequences. Thermal denaturation analysis revealed that the DEE and DPE disulfide bridges destabilize RNA duplexes but do not disrupt the hairpin conformation. Furthermore, our investigation of the duplex/hairpin equilibrium indicated that sequences modified with DME and DEE S-S linkers predominantly lock the hairpin form, whereas the DPE S-S linker provides flexibility. These findings highlight the potential of S-S linkers to study RNA interactions.

The guide RNA sequence dictates the slicing kinetics and conformational dynamics of the Argonaute silencing complex

The RNA-induced silencing complex (RISC), which powers RNA interference (RNAi), consists of a guide RNA and an Argonaute protein that slices target RNAs complementary to the guide. We find that for different guide-RNA sequences, slicing rates of perfectly complementary, bound targets can be surprisingly different (>250-fold range), and that faster slicing confers better knockdown in cells. Nucleotide sequence identities at guide-RNA positions 7, 10, and 17 underlie much of this variation in slicing rates. Analysis of one of these determinants implicates a structural distortion at guide nucleotides 6-7 in promoting slicing. Moreover, slicing directed by different guide sequences has an unanticipated, 600-fold range in 3'-mismatch tolerance, attributable to guides with weak (AU-rich) central pairing requiring extensive 3' complementarity (pairing beyond position 16) to more fully populate the slicing-competent conformation. Together, our analyses identify sequence determinants of RISC activity and provide biochemical and conformational rationale for their action.

Energy landscapes of homopolymeric RNAs revealed by deep unsupervised learning

Conformational dynamics of RNA plays important roles in a variety of cellular functions such as transcriptional regulation, catalysis, scaffolding, and sensing. Recently, RNAs with low-complexity sequences have been shown to phase separate and form condensate phases similar to lowcomplexity protein domains. The affinity for phase separation and the material characteristics of RNA condensates are strongly dependent on sequence composition and patterning. We hypothesize that differences in the affinities for RNA phase separation can be uncovered by studying sequence-dependent conformational dynamics of single RNA chains. To this end, we have employed atomistic simulations and deep dimensionality reduction techniques to map temperature-dependent conformational free energy landscapes for 20 base-long homopolymeric RNA sequences: poly(U), poly(G), poly(C), and poly(A). The energy landscapes of homopolymeric RNAs reveal a plethora of metastable states with qualitatively different populations stemming from differences in base chemistry. Through detailed analysis of base, phosphate, and sugar interactions, we show that experimentally observed temperature-driven shifts in metastable state populations align with experiments on RNA phase transitions. Specifically, we find that the thermodynamics of unfolding of homopolymeric RNA follows the poly(G) > poly(A) > poly(C) > poly(U) order of stability, mirroring the propensity of RNA to form condensates. To conclude, this work shows that at least for homopolymeric RNA sequences the single-chain conformational dynamics contains sufficient information for predicting and quantifying condensate forming affinities of RNAs. Thus, we anticipate that atomically detailed studies of temeprature -dependent energy landscapes of RNAs will be a useful guide for understanding the propensity of various RNA molecules to form condensates.

CASP15 cryo-EM protein and RNA targets: Refinement and analysis using experimental maps

CASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, experimental structures by their nature are only models themselves-their construction involves a certain degree of subjectivity in interpreting density maps and translating them to atomic coordinates. Here, we directly utilized density maps to evaluate the predictions by employing a method for ranking the quality of protein chain predictions based on their fit into the experimental density. The fit-based ranking was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy, and occasionally even better than the reference structure in some regions of the model. Local assessment of predicted side chains in a 1.52 Å resolution map showed that side-chains are sometimes poorly positioned. Additionally, the top 118 predictions associated with 9 protein target reference structures were selected for automated refinement, in addition to the top 40 predictions for 11 RNA targets. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure. This refinement was successful despite large conformational changes often being required, showing that predictions from CASP-assessed methods could serve as a good starting point for building atomic models in cryo-EM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors, and together with the lack of consensus amongst models in these regions suggests that modeling, in combination with model-fit to the density, holds the potential for identifying more flexible regions within the structure.

Arena: Rapid and Accurate Reconstruction of Full Atomic RNA Structures From Coarse-grained Models

RNA tertiary structures from experiments or computational predictions often contain missing atoms, which prevent analyses requiring full atomic structures. Current programs for RNA reconstruction can be slow, inaccurate, and/or require specific atoms to be present in the input. We present Arena (Atomic Reconstruction of RNA), which reconstructs a full atomic RNA structure from residues that can have as few as one atom. Arena first fills in missing atoms and then iteratively refines their placement to reduce nonideal geometries. We benchmarked Arena on a dataset of 361 RNA structures, where Arena achieves high accuracy and speed compared to other structure reconstruction programs. For example, Arena was used to reconstruct full atomic structures from a single phosphorus atom per nucleotide to, on average, within 3.63 Å RMSD of the experimental structure, while virtually removing all clashes and running in <3 s, which is 353× and 46× faster than state-of-the-art programs PDBFixer and C2A, respectively. The Arena source code is available at https://github.com/pylelab/Arena and the webserver at https://zhanggroup.org/Arena/.

Structural basis for RNA-duplex unwinding by the DEAD-box helicase DbpA

DEAD-box RNA helicases are implicated in most aspects of RNA biology, where these enzymes unwind short RNA duplexes in an ATP-dependent manner. During the central step of the unwinding cycle, the two domains of the helicase core form a distinct closed conformation that destabilizes the RNA duplex, which ultimately leads to duplex melting. Despite the importance of this step for the unwinding process no high-resolution structures of this state are available. Here, I used nuclear magnetic resonance spectroscopy and X-ray crystallography to determine structures of the DEAD-box helicase DbpA in the closed conformation, complexed with substrate duplexes and single-stranded unwinding product. These structures reveal that DbpA initiates duplex unwinding by interacting with up to three base-paired nucleotides and a 5' single-stranded RNA duplex overhang. These high-resolution snapshots, together with biochemical assays, rationalize the destabilization of the RNA duplex and are integrated into a conclusive model of the unwinding process.

CASP15 cryoEM protein and RNA targets: refinement and analysis using experimental maps

CASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, errors in the reference structures can potentially reduce the accuracy of the assessment. This issue is particularly prominent in cryoEM-determined structures, and therefore, in the assessment of CASP15 cryoEM targets, we directly utilized density maps to evaluate the predictions. A method for ranking the quality of protein chain predictions based on rigid fitting to experimental density was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy although local assessment of predicted side chains in a 1.52 Å resolution map showed that side-chains are sometimes poorly positioned. The top 136 predictions associated with 9 protein target reference structures were selected for refinement, in addition to the top 40 predictions for 11 RNA targets. To this end, we have developed an automated hierarchical refinement pipeline in cryoEM maps. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure, including some regions with better fit to the density. This refinement was successful despite large conformational changes and secondary structure element movements often being required, suggesting that predictions from CASP-assessed methods could serve as a good starting point for building atomic models in cryoEM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors with even short loops failing to be accurately modeled or refined at times. The lack of consensus amongst models suggests that modeling holds the potential for identifying more flexible regions within the structure.

Structure, folding and flexibility of co-transcriptional RNA origami

RNA origami is a method for designing RNA nanostructures that can self-assemble through co-transcriptional folding with applications in nanomedicine and synthetic biology. However, to advance the method further, an improved understanding of RNA structural properties and folding principles is required. Here we use cryogenic electron microscopy to study RNA origami sheets and bundles at sub-nanometre resolution revealing structural parameters of kissing-loop and crossover motifs, which are used to improve designs. In RNA bundle designs, we discover a kinetic folding trap that forms during folding and is only released after 10 h. Exploration of the conformational landscape of several RNA designs reveal the flexibility of helices and structural motifs. Finally, sheets and bundles are combined to construct a multidomain satellite shape, which is characterized by individual-particle cryo-electron tomography to reveal the domain flexibility. Together, the study provides a structural basis for future improvements to the design cycle of genetically encoded RNA nanodevices.

Computer Aided Development of Nucleic Acid Applications in Nanotechnologies

Utilization of nucleic acids (NAs) in nanotechnologies and nanotechnology-related applications is a growing field with broad application potential, ranging from biosensing up to targeted cell delivery. Computer simulations are useful techniques that can aid design and speed up development in this field. This review focuses on computer simulations of hybrid nanomaterials composed of NAs and other components. Current state-of-the-art molecular dynamics simulations, empirical force fields (FFs), and coarse-grained approaches for the description of deoxyribonucleic acid and ribonucleic acid are critically discussed. Challenges in combining biomacromolecular and nanomaterial FFs are emphasized. Recent applications of simulations for modeling NAs and their interactions with nano- and biomaterials are overviewed in the fields of sensing applications, targeted delivery, and NA templated materials. Future perspectives of development are also highlighted.

Conformational Heterogeneity of RNA Stem-Loop Hairpins Bound to FUS-RNA Recognition Motif with Disordered RGG Tail Revealed by Unbiased Molecular Dynamics Simulations

RNA-protein complexes use diverse binding strategies, ranging from structurally well-defined interfaces to completely disordered regions. Experimental characterization of flexible segments is challenging and can be aided by atomistic molecular dynamics (MD) simulations. Here, we used an extended set of microsecond-scale MD trajectories (400 μs in total) to study two FUS-RNA constructs previously characterized by nuclear magnetic resonance (NMR) spectroscopy. The FUS protein contains a well-structured RNA recognition motif domain followed by a presumably disordered RGG tail that binds RNA stem-loop hairpins. Our simulations not only provide several suggestions complementing the experiments but also reveal major methodological difficulties in studies of such complex RNA-protein interfaces. Despite efforts to stabilize the binding via system-specific force-field adjustments, we have observed progressive distortions of the RNA-protein interface inconsistent with experimental data. We propose that the dynamics is so rich that its converged description is not achievable even upon stabilizing the system. Still, after careful analysis of the trajectories, we have made several suggestions regarding the binding. We identify substates in the RNA loops, which can explain the NMR data. The RGG tail localized in the minor groove remains disordered, sampling countless transient interactions with the RNA. There are long-range couplings among the different elements contributing to the recognition, which can lead to allosteric communication throughout the system. Overall, the RNA-FUS systems form dynamical ensembles that cannot be fully represented by single static structures. Thus, albeit imperfect, MD simulations represent a viable tool to investigate dynamic RNA-protein complexes.

Modification at the C2'-O-Position with 2-Methylbenzothiophene Induces Unique Structural Changes and Thermal Transitions on Duplexes of RNA and DNA

Oligonucleotides can be chemically modified for a variety of applications that include their use as biomaterials, in therapeutics, or as tools to understand biochemical processes, among others. This work focuses on the functionalization of oligonucleotides of RNA and DNA (12- or 14-nucleotides long) with methylbenzothiophene (BT), at the C2'-O-position, which led to unique structural features. Circular dichroism (CD) analyses showed that positioning the BT units on one strand led to significant thermal destabilization, while duplexes where each strand contained 4-BT rings formed a distinct arrangement with cooperativity/interactions among the modifications (evidenced from the appearance of a band with positive ellipticity at 235 nm). Interestingly, the structural arrays displayed increased duplex stabilization (>10 °C higher than the canonical analogue) as a function of [Na⁺] with an unexpected structural rearrangement at temperatures above 50 °C. Density functional theory-polarizable continuum model (DFT-PCM) calculations were carried out, and the analyses were in agreement with induced structural changes as a function of salt content. A model was proposed where the hydrophobic surface allows for an internal nucleobase rearrangement into a more thermodynamically stable structure, before undergoing full denaturation, with increased heat. While this behavior is not common, B- to Z-form duplex transitions can occur and are dependent on parameters that were probed in this work, i.e., temperature, nature of modification, or ionic content. To take advantage of this phenomenon, we probed the ability of the modified duplexes to be recognized by Zα (an RNA binding protein that targets Z-form RNA) via electrophoretic analysis and CD. Interestingly, the protein did not bind to canonical duplexes of DNA or RNA; however, it recognized the modified duplexes, in a [monovalent/divalent salt] dependent manner. Overall, the findings describe methodology to attain unique structural motifs of modified duplexes of DNA or RNA, and control their behavior as a function of salt concentration. While their affinity to RNA binding proteins, and the corresponding mechanism of action, requires further exploration, the tunable properties can be of potential use to study this, and other, types of modifications. The novel arrays that formed, under the conditions described herein, provide a useful way to explore the structure and behavior of modified oligonucleotides, in general.

Knowledge-based prediction of DNA hydration using hydrated dinucleotides as building blocks

Water plays an important role in stabilizing the structure of DNA and mediating its interactions. Here, the hydration of DNA was analyzed in terms of dinucleotide fragments from an ensemble of 2727 nonredundant DNA chains containing 41 853 dinucleotides and 316 265 associated first-shell water molecules. The dinucleotides were classified into categories based on their 16 sequences and the previously determined structural classes known as nucleotide conformers (NtCs). The construction of hydrated dinucleotide building blocks allowed dinucleotide hydration to be calculated as the probability of water density distributions. Peaks in the water densities, known as hydration sites (HSs), uncovered the interplay between base and sugar-phosphate hydration in the context of sequence and structure. To demonstrate the predictive power of hydrated DNA building blocks, they were then used to predict hydration in an independent set of crystal and NMR structures. In ten tested crystal structures, the positions of predicted HSs and experimental waters were in good agreement (more than 40% were within 0.5 Å) and correctly reproduced the known features of DNA hydration, for example the `spine of hydration' in B-DNA. Therefore, it is proposed that hydrated building blocks can be used to predict DNA hydration in structures solved by NMR and cryo-EM, thus providing a guide to the interpretation of experimental data and computer models. The data for the hydrated building blocks and the predictions are available for browsing and visualization at the website https://watlas.datmos.org/watna/.

Lone Pair…π Contacts and Structure Signatures of r(UNCG) Tetraloops, Z-Turns, and Z-Steps: A WebFR3D Survey

Z-DNA and Z-RNA have long appeared as oddities to nucleic acid scientists. However, their Z-step constituents are recurrently observed in all types of nucleic acid systems including ribosomes. Z-steps are NpN steps that are isostructural to Z-DNA CpG steps. Among their structural features, Z-steps are characterized by the presence of a lone pair…π contact that involves the stacking of the ribose O4′ atom of the first nucleotide with the 3′-face of the second nucleotide. Recently, it has been documented that the CpG step of the ubiquitous r(UNCG) tetraloops is a Z-step. Accordingly, such r(UNCG) conformations were called Z-turns. It has also been recognized that an r(GAAA) tetraloop in appropriate conditions can shapeshift to an unusual Z-turn conformation embedding an ApA Z-step. In this report, we explore the multiplicity of RNA motifs based on Z-steps by using the WebFR3D tool to which we added functionalities to be able to retrieve motifs containing lone pair…π contacts. Many examples that underscore the diversity and universality of these motifs are provided as well as tutorial guidance on using WebFR3D. In addition, this study provides an extensive survey of crystallographic, cryo-EM, NMR, and molecular dynamics studies on r(UNCG) tetraloops with a critical view on how to conduct database searches and exploit their results.

Automatic Learning of Hydrogen-Bond Fixes in the AMBER RNA Force Field

The capability of current force fields to reproduce RNA structural dynamics is limited. Several methods have been developed to take advantage of experimental data in order to enforce agreement with experiments. Here, we extend an existing framework which allows arbitrarily chosen force-field correction terms to be fitted by quantification of the discrepancy between observables back-calculated from simulation and corresponding experiments. We apply a robust regularization protocol to avoid overfitting and additionally introduce and compare a number of different regularization strategies, namely, L1, L2, Kish size, relative Kish size, and relative entropy penalties. The training set includes a GACC tetramer as well as more challenging systems, namely, gcGAGAgc and gcUUCGgc RNA tetraloops. Specific intramolecular hydrogen bonds in the AMBER RNA force field are corrected with automatically determined parameters that we call gHBfix_opt. A validation involving a separate simulation of a system present in the training set (gcUUCGgc) and new systems not seen during training (CAAU and UUUU tetramers) displays improvements regarding the native population of the tetraloop as well as good agreement with NMR experiments for tetramers when using the new parameters. Then, we simulate folded RNAs (a kink–turn and L1 stalk rRNA) including hydrogen bond types not sufficiently present in the training set. This allows a final modification of the parameter set which is named gHBfix21 and is suggested to be applicable to a wider range of RNA systems.

Developing Community Resources for Nucleic Acid Structures

In this review, we describe the creation of the Nucleic Acid Database (NDB) at Rutgers University and how it became a testbed for the current infrastructure of the RCSB Protein Data Bank. We describe some of the special features of the NDB and how it has been used to enable research. Plans for the next phase as the Nucleic Acid Knowledgebase (NAKB) are summarized.

Data-informed reparameterization of modified RNA and the effect of explicit water models: application to pseudouridine and derivatives

Pseudouridine is one of the most abundant post-transcriptional modifications in RNA. We have previously shown that the FF99-derived parameters for pseudouridine and some of its naturally occurring derivatives in the AMBER distribution either alone or in combination with the revised γ torsion parameters (parmbsc0) failed to reproduce their conformational characteristics observed experimentally (Deb et al. in J Chem Inf Model 54:1129–1142, 2014; Deb et al. in J Comput Chem 37:1576–1588, 2016; Dutta et al. in J Chem Inf Model 60:4995–5002, 2020). However, the application of the recommended bsc0 correction did lead to an improvement in the description not only of the distribution in the γ torsional space but also of the sugar pucker distributions. In an earlier study, we examined the transferability of the revised glycosidic torsion parameters (χ_IDRP) for Ψ to its derivatives. We noticed that although these parameters in combination with the AMBER FF99-derived parameters and the revised γ torsional parameters resulted in conformational properties of these residues that were in better agreement with experimental observations, the sugar pucker distributions were still not reproduced accurately. Here we report a new set of partial atomic charges for pseudouridine, 1-methylpseudouridine, 3-methylpseudouridine and 2′-O-methylpseudouridine and a new set of glycosidic torsional parameters (χ_ND) based on chosen glycosidic torsional profiles that most closely corresponded to the NMR data for conformational propensities and studied their effect on the conformational distributions using REMD simulations at the individual nucleoside level. We have also studied the effect of the choice of water model on the conformational characteristics of these modified nucleosides. Our observations suggest that the current revised set of parameters and partial atomic charges describe the sugar pucker distributions for these residues more accurately and that the choice of a suitable water model is important for the accurate description of their conformational properties. We have further validated the revised sets of parameters by studying the effect of substitution of uridine with pseudouridine within single stranded RNA oligonucleotides on their conformational and hydration characteristics.

Cyclic Tetra-Adenylate (cA4) Recognition by Csa3; Implications for an Integrated Class 1 CRISPR-Cas Immune Response in Saccharolobus solfataricus

Csa3 family transcription factors are ancillary CRISPR-associated proteins composed of N-terminal CARF domains and C-terminal winged helix-turn-helix domains. The activity of Csa3 transcription factors is thought to be controlled by cyclic oligoadenyate (cOA) second messengers produced by type III CRISPR-Cas surveillance complexes. Here we show that Saccharolobus solfataricus Csa3a recognizes cyclic tetra-adenylate (cA₄) and that Csa3a lacks self-regulating "ring nuclease" activity present in some other CARF domain proteins. The crystal structure of the Csa3a/cA4 complex was also determined and the structural and thermodynamic basis for cA₄ recognition are described, as are conformational changes in Csa3a associated with cA₄ binding. We also characterized the effect of cA₄ on recognition of putative DNA binding sites. Csa3a binds to putative promoter sequences in a nonspecific, cooperative and cA₄-independent manner, suggesting a more complex mode of transcriptional regulation. We conclude the Csa3a/cA₄ interaction represents a nexus between the type I and type III CRISPR-Cas systems present in S. solfataricus, and discuss the role of the Csa3/cA₄ interaction in coordinating different arms of this integrated class 1 immune system to mount a synergistic, highly orchestrated immune response.

Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement

Refining modelled structures to approach experimental accuracy is one of the most challenging problems in molecular biology. Despite many years’ efforts, the progress in protein or RNA structure refinement has been slow because the global minimum given by the energy scores is not at the experimentally determined “native” structure. Here, we propose a fully knowledge-based energy function that captures the full orientation dependence of base–base, base–oxygen and oxygen–oxygen interactions with the RNA backbone modelled by rotameric states and internal energies. A total of 4000 quantum-mechanical calculations were performed to reweight base–base statistical potentials for minimizing possible effects of indirect interactions. The resulting BRiQ knowledge-based potential, equipped with a nucleobase-centric sampling algorithm, provides a robust improvement in refining near-native RNA models generated by a wide variety of modelling techniques.

Predicting RNA structure from sequence is challenging due to the relative sparsity of experimentally-determined RNA 3D structures for model training. Here, the authors propose a way to incorporate knowledge on interactions at the atomic and base–base level to refine the prediction of RNA structures.

A general RNA force field: comprehensive analysis of energy minima of molecular fragments of RNA

Force fields are actively used to study RNA. Development of accurate force fields relies on a knowledge of how the variation of properties of molecules depends on their structure. Detailed scrutiny of RNA's conformational preferences is needed to guide such development. Towards this end, minimum energy structures for each of a set of 16 small RNA-derived molecules were obtained by geometry optimization at the HF/6-31G(d,p), B3LYP/apc-1, and MP2/cc-pVDZ levels of theory. The number of minima computed for a given fragment was found to be related to both its size and flexibility. Atomic electrostatic multipole moments of atoms occurring in the [HO-P(O₃)-CH₂-] fragment of 30 sugar-phosphate-sugar geometries were calculated at the HF/6-31G(d,p) and B3LYP/apc-1 levels of theory, and the transferability of these properties between different conformations was investigated. The atomic multipole moments were found to be highly transferable between different conformations with small standard deviations. These results indicate necessary elements of the development of accurate RNA force fields.

MD simulations reveal the basis for dynamic assembly of Hfq-RNA complexes

The conserved protein Hfq is a key factor in the RNA-mediated control of gene expression in most known bacteria. The transient intermediates Hfq forms with RNA support intricate and robust regulatory networks. In Pseudomonas, Hfq recognizes repeats of adenine–purine–any nucleotide (ARN) in target mRNAs via its distal binding side, and together with the catabolite repression control (Crc) protein, assembles into a translation–repression complex. Earlier experiments yielded static, ensemble-averaged structures of the complex, but details of its interface dynamics and assembly pathway remained elusive. Using explicit solvent atomistic molecular dynamics simulations, we modeled the extensive dynamics of the Hfq–RNA interface and found implications for the assembly of the complex. We predict that syn/anti flips of the adenine nucleotides in each ARN repeat contribute to a dynamic recognition mechanism between the Hfq distal side and mRNA targets. We identify a previously unknown binding pocket that can accept any nucleotide and propose that it may serve as a ‘status quo’ staging point, providing nonspecific binding affinity, until Crc engages the Hfq–RNA binary complex. The dynamical components of the Hfq–RNA recognition can speed up screening of the pool of the surrounding RNAs, participate in rapid accommodation of the RNA on the protein surface, and facilitate competition among different RNAs. The register of Crc in the ternary assembly could be defined by the recognition of a guanine-specific base–phosphate interaction between the first and last ARN repeats of the bound RNA. This dynamic substrate recognition provides structural rationale for the stepwise assembly of multicomponent ribonucleoprotein complexes nucleated by Hfq–RNA binding.

Conformational energies and equilibria of cyclic dinucleotides in vacuo and in solution: computational chemistry vs. NMR experiments

Performance of computational methods in modelling cyclic dinucleotides - an important and challenging class of compounds - has been evaluated by two different benchmarks: (1) gas-phase conformational energies and (2) qualitative agreement with NMR observations of the orientation of the χ-dihedral angle in solvent. In gas-phase benchmarks, where CCSD(T) and DLPNO-CCSD(T) methods have been used as the reference, most of the (dispersion corrected) density functional approximations are accurate enough to justify prioritizing computational cost and compatibility with other modelling options as the criterion of choice. NMR experiments of 3'3'-c-di-AMP, 3'3'-c-GAMP, and 3'3'-c-di-GMP show the overall prevalence of the anti-conformation of purine bases, but some population of syn-conformations is observed for guanines. Implicit solvation models combined with quantum-chemical methods struggle to reproduce this behaviour, probably due to a lack of dynamics and explicitly modelled solvent, leading to structures that are too compact. Molecular dynamics simulations overrepresent the syn-conformation of guanine due to the overestimation of an intramolecular hydrogen bond. Our combination of experimental and computational benchmarks provides "error bars" for modelling cyclic dinucleotides in solvent, where such information is generally difficult to obtain, and should help gauge the interpretability of studies dealing with binding of cyclic dinucleotides to important pharmaceutical targets. At the same time, the presented analysis calls for improvement in both implicit solvation models and force-field parameters.

Improving SARS-CoV-2 structures: Peer review by early coordinate release

This work builds upon the record-breaking speed and generous immediate release of new experimental three-dimensional structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins and complexes, which are crucial to downstream vaccine and drug development. We have surveyed those structures to catch the occasional errors that could be significant for those important uses and for which we were able to provide demonstrably higher-accuracy corrections. This process relied on new validation and correction methods such as CaBLAM and ISOLDE, which are not yet in routine use. We found such important and correctable problems in seven early SARS-CoV-2 structures. Two of the structures were soon superseded by new higher-resolution data, confirming our proposed changes. For the other five, we emailed the depositors a documented and illustrated report and encouraged them to make the model corrections themselves and use the new option at the worldwide Protein Data Bank for depositors to re-version their coordinates without changing the Protein Data Bank code. This quickly and easily makes the better-accuracy coordinates available to anyone who examines or downloads their structure, even before formal publication. The changes have involved sequence misalignments, incorrect RNA conformations near a bound inhibitor, incorrect metal ligands, and cis-trans or peptide flips that prevent good contact at interaction sites. These improvements have propagated into nearly all related structures done afterward. This process constitutes a new form of highly rigorous peer review, which is actually faster and more strict than standard publication review because it has access to coordinates and maps; journal peer review would also be strengthened by such access.

Seeing the PDB

Ever since the first structures of proteins were determined in the 1960s, structural biologists have required methods to visualize biomolecular structures, both as an essential tool for their research and also to promote 3D comprehension of structural results by a wide audience of researchers, students, and the general public. In this review to celebrate the 50th anniversary of the Protein Data Bank, we present our own experiences in developing and applying methods of visualization and analysis to the ever-expanding archive of protein and nucleic acid structures in the worldwide Protein Data Bank. Across that timespan, Jane and David Richardson have concentrated on the organization inside and between the macromolecules, with ribbons to show the overall backbone "fold" and contact dots to show how the all-atom details fit together locally. David Goodsell has explored surface-based representations to present and explore biological subjects that range from molecules to cells. This review concludes with some ideas about the current challenges being addressed by the field of biomolecular visualization.

UUCG RNA Tetraloop as a Formidable Force-Field Challenge for MD Simulations

Explicit solvent atomistic molecular dynamics (MD) simulations represent an established technique to study structural dynamics of RNA molecules and an important complement for diverse experimental methods. However, performance of molecular mechanical (MM) force fields (ff's) remains far from satisfactory even after decades of development, as apparent from a problematic structural description of some important RNA motifs. Actually, some of the smallest RNA molecules belong to the most challenging systems for MD simulations and, among them, the UUCG tetraloop is saliently difficult. We report a detailed analysis of UUCG MD simulations, depicting the sequence of events leading to the loss of the UUCG native state during MD simulations. The total amount of MD simulation data analyzed in this work is close to 1.3 ms. We identify molecular interactions, backbone conformations, and substates that are involved in the process. Then, we unravel specific ff deficiencies using diverse quantum mechanical/molecular mechanical (QM/MM) and QM calculations. Comparison between the MM and QM methods shows discrepancies in the description of the 5'-flanking phosphate moiety and both signature sugar-base interactions. Our work indicates that poor behavior of the UUCG tetraloop in simulations is a complex issue that cannot be attributed to one dominant and straightforwardly correctable factor. Instead, there is a concerted effect of multiple ff inaccuracies that are coupled and amplifying each other. We attempted to improve the simulation behavior by some carefully tailored interventions, but the results were still far from satisfactory, underlying the difficulties in development of accurate nucleic acid ff's.

Arginine Forks Are a Widespread Motif to Recognize Phosphate Backbones and Guanine Nucleobases in the RNA Major Groove

RNA recognition by proteins is central to biology. Here we demonstrate the existence of a recurrent structural motif, the "arginine fork", that codifies arginine readout of cognate backbone and guanine nucleobase interactions in a variety of protein-RNA complexes derived from viruses, metabolic enzymes, and ribosomes. Nearly 30 years ago, a theoretical arginine fork model was posited to account for the specificity between the HIV-1 Tat protein and TAR RNA. This model predicted that a single arginine should form four complementary contacts with nearby phosphates, yielding a two-pronged backbone readout. Recent high-resolution structures of TAR-protein complexes have unveiled new details, including (i) arginine interactions with the phosphate backbone and the major-groove edge of guanine and (ii) simultaneous cation-π contacts between the guanidinium group and flanking nucleobases. These findings prompted us to search for arginine forks within experimental protein-RNA structures retrieved from the Protein Data Bank. The results revealed four distinct classes of arginine forks that we have defined using a rigorous but flexible nomenclature. Examples are presented in the context of ribosomal and nonribosomal interfaces with analysis of arginine dihedral angles and structural (suite) classification of RNA targets. When arginine fork chemical recognition principles were applied to existing structures with unusual arginine-guanine recognition, we found that the arginine fork geometry was more consistent with the experimental data, suggesting the utility of fork classifications to improve structural models. Software to analyze arginine-RNA interactions has been made available to the community.

Molecular Dynamics Simulation of the Conformational Preferences of Pseudouridine Derivatives: Improving the Distribution in the Glycosidic Torsion Space

There are only four derivatives of pseudouridine (Ψ) that are known to occur naturally in RNA as post-transcriptional modifications. We have studied the conformational consequences of pseudouridylation and further modifications using replica exchange molecular dynamics simulations at the nucleoside level, and the simulated conformational preferences were compared with the available experimental (NMR) data. We found that the existing AMBER FF99-derived parameters for these nucleosides did not reproduce the observed experimental features and while the recommended bsc0 correction could be combined with these parameters leading to an improvement in the description of sugar pucker distributions, the χ_OL3 correction could not be applied to these nucleosides as such because of base isomerization. On the other hand, the revised χ torsion parameters (χ_IDRP) for Ψ developed earlier by us (Deb, I., J. Comput. Chem., 2016, 37, 1576-1588) in combination with the AMBER provided parameters and the revised γ torsion parameters generated conformational distributions, which generally were in better agreement with the experimental data. A significant shift of the distribution of base orientation toward the syn conformation was observed with our revised parameter sets compared to the large excess of anti conformation predicted by the FF99 parameters. Overall, our observations indicated that our revised set of parameters (χ_IDRP) for Ψ were also able to generate conformational distributions for all of the derivatives of Ψ in better agreement with the experimental data.

Structural basis for the recognition of transiently structured AU-rich elements by Roquin

Adenylate/uridylate-rich elements (AREs) are the most common cis-regulatory elements in the 3′-untranslated region (UTR) of mRNAs, where they fine-tune turnover by mediating mRNA decay. They increase plasticity and efficacy of mRNA regulation and are recognized by several ARE-specific RNA-binding proteins (RBPs). Typically, AREs are short linear motifs with a high content of complementary A and U nucleotides and often occur in multiple copies. Although thermodynamically rather unstable, the high AU-content might enable transient secondary structure formation and modify mRNA regulation by RBPs. We have recently suggested that the immunoregulatory RBP Roquin recognizes folded AREs as constitutive decay elements (CDEs), resulting in shape-specific ARE-mediated mRNA degradation. However, the structural evidence for a CDE-like recognition of AREs by Roquin is still lacking. We here present structures of CDE-like folded AREs, both in their free and protein-bound form. Moreover, the AREs in the UCP3 3′-UTR are additionally bound by the canonical ARE-binding protein AUF1 in their linear form, adopting an alternative binding-interface compared to the recognition of their CDE structure by Roquin. Strikingly, our findings thus suggest that AREs can be recognized in multiple ways, allowing control over mRNA regulation by adapting distinct conformational states, thus providing differential accessibility to regulatory RBPs.

Structure of the bacterial ribosome at 2 Å resolution

Using cryo-electron microscopy (cryo-EM), we determined the structure of the Escherichia coli 70S ribosome with a global resolution of 2.0 Å. The maps reveal unambiguous positioning of protein and RNA residues, their detailed chemical interactions, and chemical modifications. Notable features include the first examples of isopeptide and thioamide backbone substitutions in ribosomal proteins, the former likely conserved in all domains of life. The maps also reveal extensive solvation of the small (30S) ribosomal subunit, and interactions with A-site and P-site tRNAs, mRNA, and the antibiotic paromomycin. The maps and models of the bacterial ribosome presented here now allow a deeper phylogenetic analysis of ribosomal components including structural conservation to the level of solvation. The high quality of the maps should enable future structural analyses of the chemical basis for translation and aid the development of robust tools for cryo-EM structure modeling and refinement.

Structure of the bacterial ribosome at 2 Å resolution

Using cryo-electron microscopy (cryo-EM), we determined the structure of the Escherichia coli 70S ribosome with a global resolution of 2.0 Å. The maps reveal unambiguous positioning of protein and RNA residues, their detailed chemical interactions, and chemical modifications. Notable features include the first examples of isopeptide and thioamide backbone substitutions in ribosomal proteins, the former likely conserved in all domains of life. The maps also reveal extensive solvation of the small (30S) ribosomal subunit, and interactions with A-site and P-site tRNAs, mRNA, and the antibiotic paromomycin. The maps and models of the bacterial ribosome presented here now allow a deeper phylogenetic analysis of ribosomal components including structural conservation to the level of solvation. The high quality of the maps should enable future structural analyses of the chemical basis for translation and aid the development of robust tools for cryo-EM structure modeling and refinement.

Structural alphabets for conformational analysis of nucleic acids available at dnatco.datmos.org

A detailed description of the dnatco.datmos.org web server implementing the universal structural alphabet of nucleic acids is presented. It is capable of processing any mmCIF- or PDB-formatted files containing DNA or RNA molecules; these can either be uploaded by the user or supplied as the wwPDB or PDB-REDO structural database access code. The web server performs an assignment of the nucleic acid conformations and presents the results for the intuitive annotation, validation, modeling and refinement of nucleic acids.

FARFAR2: Improved De Novo Rosetta Prediction of Complex Global RNA Folds

Predicting RNA three-dimensional structures from sequence could accelerate understanding of the growing number of RNA molecules being discovered across biology. Rosetta's Fragment Assembly of RNA with Full-Atom Refinement (FARFAR) has shown promise in community-wide blind RNA-Puzzle trials, but lack of a systematic and automated benchmark has left unclear what limits FARFAR performance. Here, we benchmark FARFAR2, an algorithm integrating RNA-Puzzle-inspired innovations with updated fragment libraries and helix modeling. In 16 of 21 RNA-Puzzles revisited without experimental data or expert intervention, FARFAR2 recovers native-like structures more accurate than models submitted during the RNA-Puzzles trials. Remaining bottlenecks include conformational sampling for >80-nucleotide problems and scoring function limitations more generally. Supporting these conclusions, preregistered blind models for adenovirus VA-I RNA and five riboswitch complexes predicted native-like folds with 3- to 14 Å root-mean-square deviation accuracies. We present a FARFAR2 webserver and three large model archives (FARFAR2-Classics, FARFAR2-Motifs, and FARFAR2-Puzzles) to guide future applications and advances.

A unified dinucleotide alphabet describing both RNA and DNA structures

By analyzing almost 120 000 dinucleotides in over 2000 nonredundant nucleic acid crystal structures, we define 96+1 diNucleotide Conformers, NtCs, which describe the geometry of RNA and DNA dinucleotides. NtC classes are grouped into 15 codes of the structural alphabet CANA (Conformational Alphabet of Nucleic Acids) to simplify symbolic annotation of the prominent structural features of NAs and their intuitive graphical display. The search for nontrivial patterns of NtCs resulted in the identification of several types of RNA loops, some of them observed for the first time. Over 30% of the nearly six million dinucleotides in the PDB cannot be assigned to any NtC class but we demonstrate that up to a half of them can be re-refined with the help of proper refinement targets. A statistical analysis of the preferences of NtCs and CANA codes for the 16 dinucleotide sequences showed that neither the NtC class AA00, which forms the scaffold of RNA structures, nor BB00, the DNA most populated class, are sequence neutral but their distributions are significantly biased. The reported automated assignment of the NtC classes and CANA codes available at dnatco.org provides a powerful tool for unbiased analysis of nucleic acid structures by structural and molecular biologists.

Deconvolution of conformational exchange from Raman spectra of aqueous RNA nucleosides

Ribonucleic acids (RNAs) are key to the central dogma of molecular biology. While Raman spectroscopy holds great potential for studying RNA conformational dynamics, current computational Raman prediction and assignment methods are limited in terms of system size and inclusion of conformational exchange. Here, a framework is presented that predicts Raman spectra using mixtures of sub-spectra corresponding to major conformers calculated using classical and ab initio molecular dynamics. Experimental optimization allowed purines and pyrimidines to be characterized as predominantly syn and anti, respectively, and ribose into exchange between equivalent south and north populations. These measurements are in excellent agreement with Raman spectroscopy of ribonucleosides, and previous experimental and computational results. This framework provides a measure of ribonucleoside solution populations and conformational exchange in RNA subunits. It complements other experimental techniques and could be extended to other molecules, such as proteins and carbohydrates, enabling biological insights and providing a new analytical tool.

FSATOOL: A useful tool to do the conformational sampling and trajectory analysis work for biomolecules

Reliable conformational sampling and trajectory analysis are always important to the study of the folding or binding mechanisms of biomolecules. Generally, one has to prepare many complicated parameters and follow a lot of steps to obtain the final data. The whole process is too complicated to new users. In this article, we provide a convenient and user-friendly tool that is compatible to AMBER, called fast sampling and analysis tool (FSATOOL). FSATOOL has some useful features. First and the most important, the whole work is extremely simplified into two steps, one is the fast sampling procedure and the other is the trajectory analysis procedure. Second, it contains several powerful sampling methods for the simulation on graphics process unit, including our previous mixing replica exchange molecular dynamics method. The method combines the advantages of the biased and unbiased simulations. Finally, it extracts the dominant transition pathways automatically from the folding network by Markov state model. Users do not need to do the tedious intermediate steps by hand. To illustrate the usage of FSATOOL in practice, we perform one simulation for a RNA hairpin in explicit solvent. All the results are presented. © 2019 Wiley Periodicals, Inc.

Classification of RNA backbone conformations into rotamers using 13C' chemical shifts: exploring how far we can go

The conformational space of the ribose-phosphate backbone is very complex as it is defined in terms of six torsional angles. To help delimit the RNA backbone conformational preferences, 46 rotamers have been defined in terms of these torsional angles. In the present work, we use the ribose experimental and theoretical ¹³C′ chemical shifts data and machine learning methods to classify RNA backbone conformations into rotamers and families of rotamers. We show to what extent the experimental ¹³C′ chemical shifts can be used to identify rotamers and discuss some problem with the theoretical computations of ¹³C′ chemical shifts.

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.

Maximizing accuracy of RNA structure in refinement against residual dipolar couplings

Structural information about ribonucleic acid (RNA) is lagging behind that of proteins, in part due to its high charge and conformational variability. Molecular dynamics (MD) has played an important role in describing RNA structure, complementing information from both nuclear magnetic resonance (NMR), or X-ray crystallography. We examine the impact of the choice of the empirical force field for RNA structure refinement using cross-validation against residual dipolar couplings (RDCs) as structural accuracy reporter. Four force fields, representing both the state-of-the art in RNA simulation and the most popular selections in NMR structure determination, are compared for a prototypical A-RNA helix. RNA structural accuracy is also evaluated as a function of both density and nature of input NMR data including RDCs, anisotropic chemical shifts, and distance restraints. Our results show a complex interplay between the experimental restraints and the force fields indicating two best-performing choices: high-fidelity refinement in explicit solvent, and the conformational database-derived potentials. Accuracy of RNA models closely tracks the density of 1-bond C-H RDCs, with other data types having beneficial, but smaller effects. At lower RDC density, or when refining against NOEs only, the two selected force fields are capable of accurately describing RNA helices with little or no experimental RDC data, making them available for the higher order structure assembly or better quantification of the intramolecular dynamics. Unrestrained simulations of simple RNA motifs with state-of-the art MD force fields appear to capture the flexibility inherent in nucleic acids while also maintaining a good agreement with the experimental observables.

Barnaba: software for analysis of nucleic acid structures and trajectories

RNA molecules are highly dynamic systems characterized by a complex interplay between sequence, structure, dynamics, and function. Molecular simulations can potentially provide powerful insights into the nature of these relationships. The analysis of structures and molecular trajectories of nucleic acids can be nontrivial because it requires processing very high-dimensional data that are not easy to visualize and interpret. Here we introduce Barnaba, a Python library aimed at facilitating the analysis of nucleic acid structures and molecular simulations. The software consists of a variety of analysis tools that allow the user to (i) calculate distances between three-dimensional structures using different metrics, (ii) back-calculate experimental data from three-dimensional structures, (iii) perform cluster analysis and dimensionality reductions, (iv) search three-dimensional motifs in PDB structures and trajectories, and (v) construct elastic network models for nucleic acids and nucleic acids-protein complexes. In addition, Barnaba makes it possible to calculate torsion angles, pucker conformations, and to detect base-pairing/base-stacking interactions. Barnaba produces graphics that conveniently visualize both extended secondary structure and dynamics for a set of molecular conformations. The software is available as a command-line tool as well as a library, and supports a variety of file formats such as PDB, dcd, and xtc files. Source code, documentation, and examples are freely available at https://github.com/srnas/barnaba under GNU GPLv3 license.

RNA Polymerase Accommodates a Pause RNA Hairpin by Global Conformational Rearrangements that Prolong Pausing

Sequence-specific pausing by RNA polymerase (RNAP) during transcription plays crucial and diverse roles in gene expression. In bacteria, RNA structures are thought to fold within the RNA exit channel of the RNAP and can increase pause lifetimes significantly. The biophysical mechanism of pausing is uncertain. We used single-particle cryo-EM to determine structures of paused complexes, including a 3.8-Å structure of an RNA hairpin-stabilized, paused RNAP that coordinates RNA folding in the his operon attenuation control region of E. coli. The structures revealed a half-translocated pause state (RNA post-translocated, DNA pre-translocated) that can explain transcriptional pausing and a global conformational change of RNAP that allosterically inhibits trigger loop folding and can explain pause hairpin action. Pause hairpin interactions with the RNAP RNA exit channel suggest how RNAP guides the formation of nascent RNA structures.

Unraveling the structural basis for the exceptional stability of RNA G-quadruplexes capped by a uridine tetrad at the 3' terminus

Uridine tetrads (U-tetrads) are a structural element encountered in RNA G-quadruplexes, for example, in the structures formed by the biologically relevant human telomeric repeat RNA. For these molecules, an unexpectedly strong stabilizing influence of a U-tetrad forming at the 3' terminus of a quadruplex was reported. Here we present the high-resolution solution NMR structure of the r(UGGUGGU)4 quadruplex which, in our opinion, provides an explanation for this stabilization. Our structure features a distinctive, abrupt chain reversal just prior to the 3' uridine tetrad. Similar "reversed U-tetrads" were already observed in the crystalline phase. However, our NMR structure coupled with extensive explicit solvent molecular dynamics (MD) simulations identifies some key features of this motif that up to now remained overlooked. These include the presence of an exceptionally stable 2'OH to phosphate hydrogen bond, as well as the formation of an additional K+ binding pocket in the quadruplex groove.

Polarizable force field for RNA based on the classical drude oscillator

RNA molecules are highly dynamic and capable of adopting a wide range of complex, folded structures. The factors driving the folding and dynamics of these structures are dependent on a balance of base pairing, hydration, base stacking, ion interactions, and the conformational sampling of the 2'-hydroxyl group in the ribose sugar. The representation of these features is a challenge for empirical force fields used in molecular dynamics simulations. Toward meeting this challenge, the inclusion of explicit electronic polarization is important in accurately modeling RNA structure. In this work, we present a polarizable force field for RNA based on the classical Drude oscillator model, which represents electronic degrees of freedom via negatively charged particles attached to their parent atoms by harmonic springs. Beginning with parametrization against quantum mechanical base stacking interaction energy and conformational energy data, we have extended the Drude-2017 nucleic acid force field to include RNA. The conformational sampling of a range of RNA sequences were used to validate the force field, including canonical A-form RNA duplexes, stem-loops, and complex tertiary folds that bind multiple Mg2+ ions. Overall, the Drude-2017 RNA force field reproduces important properties of these structures, including the conformational sampling of the 2'-hydroxyl and key interactions with Mg2+ ions. © 2018 Wiley Periodicals, Inc.

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.