SAXS studies of RNA: structures, dynamics, and interactions with partners

Sampling globally and locally correct RNA 3D structures using Ernwin, SPQR and experimental SAXS data

The determination of the three-dimensional structure of large RNA macromolecules in solution is a challenging task that often requires the use of several experimental and computational techniques. Small-angle X-ray scattering can provide insight into some geometrical properties of the probed molecule, but this data must be properly interpreted in order to generate a three-dimensional model. Here, we propose a multiscale pipeline which introduces SAXS data into modelling the global shape of RNA in solution, which can be hierarchically refined until reaching atomistic precision in explicit solvent. The low-resolution helix model (Ernwin) deals with the exploration of the huge conformational space making use of the SAXS data, while a nucleotide-level model (SPQR) removes clashes and disentangles the proposed structures, leading the structure to an all-atom representation in explicit water. We apply the procedure on four different known pdb structures up to 159 nucleotides with promising results. Additionally, we predict an all-atom structure for the Plasmodium falceparum signal recognition particle ALU RNA based on SAXS data deposited in the SASBDB, which has an alternate conformation and better fit to the SAXS data than the previously published structure based on the same data but other modelling methods.

Identification of RNA structures and their roles in RNA functions

The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

Chemical screening by time-resolved X-ray scattering to discover allosteric probes

Drug discovery relies on efficient identification of small-molecule leads and their interactions with macromolecular targets. However, understanding how chemotypes impact mechanistically important conformational states often remains secondary among high-throughput discovery methods. Here, we present a conformational discovery pipeline integrating time-resolved, high-throughput small-angle X-ray scattering (TR-HT-SAXS) and classic fragment screening applied to allosteric states of the mitochondrial import oxidoreductase apoptosis-inducing factor (AIF). By monitoring oxidized and X-ray-reduced AIF states, TR-HT-SAXS leverages structure and kinetics to generate a multidimensional screening dataset that identifies fragment chemotypes allosterically stimulating AIF dimerization. Fragment-induced dimerization rates, quantified with time-resolved SAXS similarity analysis (kVR), capture structure-activity relationships (SAR) across the top-ranked 4-aminoquinoline chemotype. Crystallized AIF-aminoquinoline complexes validate TR-SAXS-guided SAR, supporting this conformational chemotype for optimization. AIF-aminoquinoline structures and mutational analysis reveal active site F482 as an underappreciated allosteric stabilizer of AIF dimerization. This conformational discovery pipeline illustrates TR-HT-SAXS as an effective technology for targeting chemical leads to important macromolecular states.

Hierarchical Assembly of Single-Stranded RNA

Single-stranded RNA (ssRNA) plays a major role in the flow of genetic information-most notably, in the form of messenger RNA (mRNA)-and in the regulation of biological processes. The highly dynamic nature of chains of unpaired nucleobases challenges structural characterizations of ssRNA by experiments or molecular dynamics (MD) simulations alike. Here, we use hierarchical chain growth (HCG) to construct ensembles of ssRNA chains. HCG assembles the structures of protein and nucleic acid chains from fragment libraries created by MD simulations. Applied to homo- and heteropolymeric ssRNAs of different lengths, we find that HCG produces structural ensembles that overall are in good agreement with diverse experiments, including nuclear magnetic resonance (NMR), small-angle X-ray scattering (SAXS), and single-molecule Förster resonance energy transfer (FRET). The agreement can be further improved by ensemble refinement using Bayesian inference of ensembles (BioEn). HCG can also be used to assemble RNA structures that combine base-paired and base-unpaired regions, as illustrated for the 5' untranslated region (UTR) of SARS-CoV-2 RNA.

Effect of lipid composition on RNA-Lipid nanoparticle properties and their sensitivity to thin-film freezing and drying

A library of 16 lipid nanoparticle (LNP) formulations with orthogonally varying lipid molar ratios was designed and synthesized, using polyadenylic acid [poly(A)] as a model for mRNA, to explore the effect of lipid composition in LNPs on (i) the initial size of the resultant LNPs and encapsulation efficiency of RNA and (ii) the sensitivity of the LNPs to various conditions including cold storage, freezing (slow vs. rapid) and thawing, and drying. Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to identify the optimal lipid molar ratios and interactions that favorably affect the physical properties of the LNPs and enhance their stability in various stress conditions. LNPs exhibited distinct responses under each stress condition, highlighting the effect of lipid molar ratios and lipid interactions on the LNP physical properties and stability. It was then demonstrated that it is feasible to use thin-film freeze-drying to convert poly(A)-LNPs from liquid dispersions to dry powders while maintaining the integrity of the LNPs. Importantly, the residual moisture content in LNP dry powders significantly affected the LNP integrity.Residual moisture content of ≤ 0.5% or > 3-3.5% w/w negatively affected the LNP size and/or RNA encapsulation efficiency, depending on the LNP composition. Finally, it was shown that the thin-film freeze-dried LNP powders have desirable aerosol properties for potential pulmonary delivery. It was concluded that Design of Experiments can be applied to identify mRNA-LNP formulations with the desired physical properties and stability profiles. Additionally, optimizing the residual moisture content in mRNA-LNP dry powders during (thin-film) freeze-drying is crucial to maintain the physical properties of the LNPs.

Biophysical screening and characterisation in medicinal chemistry

In the last two decades the use of biophysical assays and methods in medicinal chemistry has increased significantly, to meet the demands of the novel targets and modalities that drug discoverers are looking to tackle. The desire to obtain accurate affinities, kinetics, thermodynamics and structural data as early as possible in the drug discovery process has fuelled this innovation. This review introduces the principles underlying the techniques in common use and provides a perspective on the weaknesses and strengths of different methods. Case studies are used to further illustrate some of the applications in medicinal chemistry and a discussion of the emerging biophysical methods on the horizon is presented.

A generalizable scaffold-based approach for structure determination of RNAs by cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) can reveal the structures of large and often dynamic molecules, but smaller biomolecules (≤50 kDa) remain challenging targets due to their intrinsic low signal to noise ratio. Methods to help resolve small proteins have been applied but development of similar approaches to aid in structural determination of small, structured RNA elements have lagged. Here, we present a scaffold-based approach that we used to recover maps of sub-25 kDa RNA domains to 4.5-5.0 Å. While lacking the detail of true high-resolution maps, these maps are suitable for model building and preliminary structure determination. We demonstrate this method helped faithfully recover the structure of several RNA elements of known structure, and that it promises to be generalized to other RNAs without disturbing their native fold. This approach may streamline the sample preparation process and reduce the optimization required for data collection. This first-generation scaffold approach provides a robust system to aid in RNA structure determination by cryo-EM and lays the groundwork for further scaffold optimization to achieve higher resolution.

Atomistic structure of the SARS-CoV-2 pseudoknot in solution from SAXS-driven molecular dynamics

SARS-CoV-2 depends on -1 programmed ribosomal frameshifting (-1 PRF) to express proteins essential for its replication. The RNA pseudoknot stimulating -1 PRF is thus an attractive drug target. However, the structural models of this pseudoknot obtained from cryo-EM and crystallography differ in some important features, leaving the pseudoknot structure unclear. We measured the solution structure of the pseudoknot using small-angle X-ray scattering (SAXS). The measured profile did not agree with profiles computed from the previously solved structures. Beginning with each of these solved structures, we used the SAXS data to direct all atom molecular dynamics (MD) simulations to improve the agreement in profiles. In all cases, this refinement resulted in a bent conformation that more closely resembled the cryo-EM structures than the crystal structure. Applying the same approach to a point mutant abolishing -1 PRF revealed a notably more bent structure with reoriented helices. This work clarifies the dynamic structures of the SARS-CoV-2 pseudoknot in solution.

RNA structures and dynamics with Å resolution revealed by x-ray free-electron lasers

RNA macromolecules, like proteins, fold to assume shapes that are intimately connected to their broadly recognized biological functions; however, because of their high charge and dynamic nature, RNA structures are far more challenging to determine. We introduce an approach that exploits the high brilliance of x-ray free-electron laser sources to reveal the formation and ready identification of angstrom-scale features in structured and unstructured RNAs. Previously unrecognized structural signatures of RNA secondary and tertiary structures are identified through wide-angle solution scattering experiments. With millisecond time resolution, we observe an RNA fold from a dynamically varying single strand through a base-paired intermediate to assume a triple-helix conformation. While the backbone orchestrates the folding, the final structure is locked in by base stacking. This method may help to rapidly characterize and identify structural elements in nucleic acids in both equilibrium and time-resolved experiments.

Direct observation of tRNA-chaperoned folding of a dynamic mRNA ensemble

T-box riboswitches are multi-domain noncoding RNAs that surveil individual amino acid availabilities in most Gram-positive bacteria. T-boxes directly bind specific tRNAs, query their aminoacylation status to detect starvation, and feedback control the transcription or translation of downstream amino-acid metabolic genes. Most T-boxes rapidly recruit their cognate tRNA ligands through an intricate three-way stem I-stem II-tRNA interaction, whose establishment is not understood. Using single-molecule FRET, SAXS, and time-resolved fluorescence, we find that the free T-box RNA assumes a broad distribution of open, semi-open, and closed conformations that only slowly interconvert. tRNA directly binds all three conformers with distinct kinetics, triggers nearly instantaneous collapses of the open conformations, and returns the T-box RNA to their pre-binding conformations upon dissociation. This scissors-like dynamic behavior is enabled by a hinge-like pseudoknot domain which poises the T-box for rapid tRNA-induced domain closure. This study reveals tRNA-chaperoned folding of flexible, multi-domain mRNAs through a Venus flytrap-like mechanism.

RNA structure determination: From 2D to 3D

RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.

A Generalizable Scaffold-Based Approach for Structure Determination of RNAs by Cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) can reveal the structures of large and often dynamic molecules, but smaller biomolecules remain challenging targets due to their intrinsic low signal to noise ratio. Methods to resolve small proteins have been applied but development of similar approaches for small structured RNA elements have lagged. Here, we present a scaffold-based approach that we used to recover maps of sub-25 kDa RNA domains to 4.5 - 5.0 Å. While lacking the detail of true high-resolution maps, these are suitable for model building and preliminary structure determination. We demonstrate this method faithfully recovers the structure of several RNA elements of known structure, and it promises to be generalized to other RNAs without disturbing their native fold. This approach may streamline the sample preparation process and reduce the optimization required for data collection. This first-generation scaffold approach provides a system for RNA structure determination by cryo-EM and lays the groundwork for further scaffold optimization to achieve higher resolution.

Modelling the structures of frameshift-stimulatory pseudoknots from representative bat coronaviruses

Coronaviruses (CoVs) use -1 programmed ribosomal frameshifting stimulated by RNA pseudoknots in the viral genome to control expression of enzymes essential for replication, making CoV pseudoknots a promising target for anti-coronaviral drugs. Bats represent one of the largest reservoirs of CoVs and are the ultimate source of most CoVs infecting humans, including those causing SARS, MERS, and COVID-19. However, the structures of bat-CoV frameshift-stimulatory pseudoknots remain largely unexplored. Here we use a combination of blind structure prediction followed by all-atom molecular dynamics simulations to model the structures of eight pseudoknots that, together with the SARS-CoV-2 pseudoknot, are representative of the range of pseudoknot sequences in bat CoVs. We find that they all share some key qualitative features with the pseudoknot from SARS-CoV-2, notably the presence of conformers with two distinct fold topologies differing in whether or not the 5' end of the RNA is threaded through a junction, and similar conformations for stem 1. However, they differed in the number of helices present, with half sharing the 3-helix architecture of the SARS-CoV-2 pseudoknot but two containing 4 helices and two others only 2. These structure models should be helpful for future work studying bat-CoV pseudoknots as potential therapeutic targets.

Self-assembly of a fluorescent virus-like particle for imaging in tissues with high autofluorescence

Virus-like particles (VLPs) are engineered nanoparticles that mimic the properties of viruses-like high tolerance to heat and proteases-but lack a viral genome, making them non-infectious. They are easily modified chemically and genetically, making them useful in drug delivery, enhancing vaccine efficacy, gene delivery, and cancer immunotherapy. One such VLP is Qβ, which has an affinity towards an RNA hairpin structure found in its viral RNA that drives the self-assembly of the capsid. It is possible to usurp the native way infectious Qβ self-assembles to encapsidate its RNA to place enzymes inside the VLP's lumen as a protease-resistant cage. Further, using RNA templates that mimic the natural self-assembly of the native capsid, fluorescent proteins (FPs) have been placed inside VLPs in a "one pot" expression system. Autofluorescence in tissues can lead to misinterpretation of results and unreliable science, so we created a single-pot expression system that uses the fluorescent protein smURFP, which avoids autofluorescence and has spectral properties compatible with standard commercial filter sets on confocal microscopes. In this work, we were able to simplify the existing "one-pot" expression system while creating high-yielding fluorescent VLP nanoparticles that could easily be imaged inside lung epithelial tissue.

Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA

RNA structures regulate a wide range of processes in biology and disease, yet small molecule chemical probes or drugs that can modulate these functions are rare. Machine learning and other computational methods are well poised to fill gaps in knowledge and overcome the inherent challenges in RNA targeting, such as the dynamic nature of RNA and the difficulty of obtaining RNA high-resolution structures. Successful tools to date include principal component analysis, linear discriminate analysis, k-nearest neighbor, artificial neural networks, multiple linear regression, and many others. Employment of these tools has revealed critical factors for selective recognition in RNA:small molecule complexes, predictable differences in RNA- and protein-binding ligands, and quantitative structure activity relationships that allow the rational design of small molecules for a given RNA target. Herein we present our perspective on the value of using machine learning and other computation methods to advance RNA:small molecule targeting, including select examples and their validation as well as necessary and promising future directions that will be key to accelerate discoveries in this important field.

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.

Integrating experimental data with molecular simulations to investigate RNA structural dynamics

Conformational dynamics is crucial for ribonucleic acid (RNA) function. Techniques such as nuclear magnetic resonance, cryo-electron microscopy, small- and wide-angle X-ray scattering, chemical probing, single-molecule Förster resonance energy transfer, or even thermal or mechanical denaturation experiments probe RNA dynamics at different time and space resolutions. Their combination with accurate atomistic molecular dynamics (MD) simulations paves the way for quantitative and detailed studies of RNA dynamics. First, experiments provide a quantitative validation tool for MD simulations. Second, available data can be used to refine simulated structural ensembles to match experiments. Finally, comparison with experiments allows for improving MD force fields that are transferable to new systems for which data is not available. Here we review the recent literature and provide our perspective on this field.

Structural characterization of protein-DNA complexes using small angle X-ray scattering (SAXS) with contrast variation

Molecular and atomic level characterization of transcription factor (TF)-DNA complexes is critical for understanding DNA-binding specificity and potentially structural changes that may occur in protein and/or DNA upon complex formation. Often TFs are large, multidomain proteins or contain disordered regions that contribute to DNA recognition and/or binding affinity but are difficult to structurally characterize due to their high molecular weight and intrinsic flexibility. This results in challenges to obtaining high resolution structural information using Nuclear Magnetic Resonance (NMR) spectroscopy due to the relatively large size of the protein-DNA complexes of interest or macromolecular crystallography due to the difficulty in obtaining crystals of flexible proteins. Small angle X-ray scattering (SAXS) offers a complementary method to NMR and X-ray crystallography that allows for low-resolution structural characterization of protein, DNA, and protein-DNA complexes in solution over a greater size range and irrespective of interdomain flexibility and/or disordered regions. One important caveat to SAXS data interpretation, however, has been the inability to distinguish between scattering coming from the protein versus DNA component of the complex of interest. Here, we present a protocol using contrast variation via increasing sucrose concentrations to distinguish between protein and DNA using the model protein bovine serum albumin (BSA) and DNA and the LUX ARRYTHMO TF-DNA complex. Examination of the scattering curves of the components individually and in combination with contrast variation allows the differentiation of protein and DNA density in the derived models. This protocol is designed for use on high flux SAXS beamlines with temperature-controlled sample storage and sample exposure units.

3D Structural Analysis of Long Noncoding RNA by Small Angle X-ray Scattering and Computational Modeling

Small angle X-ray scattering (SAXS) has been widely applied as an enabling integrative technique for comprehensive analysis of the structure of biomacromolecules by multiple, complementary techniques in solution. SAXS in combination with computational modeling can be a powerful strategy bridging the secondary and 3D structural analysis of large RNAs, including the long noncoding RNAs (lncRNA). Here, we outline the major procedures and techniques in the combined use of SAXS and computational modeling for 3D structural characterization of a lncRNA, the subgenomic flaviviral RNA from Zika virus. lncRNA production and purification, RNA buffer and sample preparation for SAXS experiments, SAXS data collection and analysis, SAXS-aided RNA 3D structure prediction, and computational modeling are described.

Combining Biophysical Methods for Structure-Function Analyses of RNA in Solution

RNA-level regulation by riboswitches relies on the specific binding of small metabolites to the aptamer domain to trigger substantial conformational changes that affect transcription or translation. Although several biophysical methods have been employed to study such RNAs, the utility of any one single method is limited. Hybrid approaches, therefore, are essential to better characterize these intrinsically dynamic molecules and elucidate their regulatory mechanisms driven by ligand-induced conformational changes. This chapter outlines procedures for biochemical and biophysical characterization of RNA that employs a combination of solution-based methods: isothermal titration calorimetry (ITC), small-angle X-ray scattering (SAXS), and atomic force microscopy (AFM). Collectively, these tools provide a semi-quantitative assessment of the thermodynamics associated with ligand binding and subsequent conformational changes.

Biomotors, viral assembly, and RNA nanobiotechnology: Current achievements and future directions

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) serves to further the development of a wide variety of functional nucleic acids and other related nanotechnology platforms. To aid in the dissemination of the most recent advancements, a biennial discussion focused on biomotors, viral assembly, and RNA nanobiotechnology has been established where international experts in interdisciplinary fields such as structural biology, biophysical chemistry, nanotechnology, cell and cancer biology, and pharmacology share their latest accomplishments and future perspectives. The results summarized here highlight advancements in our understanding of viral biology and the structure-function relationship of frame-shifting elements in genomic viral RNA, improvements in the predictions of SHAPE analysis of 3D RNA structures, and the understanding of dynamic RNA structures through a variety of experimental and computational means. Additionally, recent advances in the drug delivery, vaccine design, nanopore technologies, biomotor and biomachine development, DNA packaging, RNA nanotechnology, and drug delivery are included in this critical review. We emphasize some of the novel accomplishments, major discussion topics, and present current challenges and perspectives of these emerging fields.

An overview of structural approaches to study therapeutic RNAs

RNAs provide considerable opportunities as therapeutic agent to expand the plethora of classical therapeutic targets, from extracellular and surface proteins to intracellular nucleic acids and its regulators, in a wide range of diseases. RNA versatility can be exploited to recognize cell types, perform cell therapy, and develop new vaccine classes. Therapeutic RNAs (aptamers, antisense nucleotides, siRNA, miRNA, mRNA and CRISPR-Cas9) can modulate or induce protein expression, inhibit molecular interactions, achieve genome editing as well as exon-skipping. A common RNA thread, which makes it very promising for therapeutic applications, is its structure, flexibility, and binding specificity. Moreover, RNA displays peculiar structural plasticity compared to proteins as well as to DNA. Here we summarize the recent advances and applications of therapeutic RNAs, and the experimental and computational methods to analyze their structure, by biophysical techniques (liquid-state NMR, scattering, reactivity, and computational simulations), with a focus on dynamic and flexibility aspects and to binding analysis. This will provide insights on the currently available RNA therapeutic applications and on the best techniques to evaluate its dynamics and reactivity.

Structural Characteristics of the 5′-Terminal Region of Mouse p53 mRNA and Identification of Proteins That Bind to This mRNA Region

A mouse model has often been used in studies of p53 gene expression. Detailed interpretation of functional studies is, however, hampered by insufficient knowledge of the impact of mouse p53 mRNA’s structure and its interactions with proteins in the translation process. In particular, the 5′-terminal region of mouse p53 mRNA is an important region which takes part in the regulation of the synthesis of p53 protein and its N-truncated isoform Δ41p53. In this work, the spatial folding of the 5′-terminal region of mouse p53 mRNA and its selected sub-fragments was proposed based on the results of the SAXS method and the RNAComposer program. Subsequently, RNA-assisted affinity chromatography was used to identify proteins present in mouse fibroblast cell lysates that are able to bind the RNA oligomer, which corresponds to the 5′-terminal region of mouse p53 mRNA. Possible sites to which the selected, identified proteins can bind were proposed. Interestingly, most of these binding sites coincide with the sites determined as accessible to hybridization of complementary oligonucleotides. Finally, the high binding affinity of hnRNP K and PCBP2 to the 5′-terminal region of mouse p53 mRNA was confirmed and their possible binding sites were proposed.

Sub-3-Å cryo-EM structure of RNA enabled by engineered homomeric self-assembly

High-resolution structural studies are essential for understanding the folding and function of diverse RNAs. Herein, we present a nanoarchitectural engineering strategy for efficient structural determination of RNA-only structures using single-particle cryogenic electron microscopy (cryo-EM). This strategy-ROCK (RNA oligomerization-enabled cryo-EM via installing kissing loops)-involves installing kissing-loop sequences onto the functionally nonessential stems of RNAs for homomeric self-assembly into closed rings with multiplied molecular weights and mitigated structural flexibility. ROCK enables cryo-EM reconstruction of the Tetrahymena group I intron at 2.98-Å resolution overall (2.85 Å for the core), allowing de novo model building of the complete RNA, including the previously unknown peripheral domains. ROCK is further applied to two smaller RNAs-the Azoarcus group I intron and the FMN riboswitch, revealing the conformational change of the former and the bound ligand in the latter. ROCK holds promise to greatly facilitate the use of cryo-EM in RNA structural studies.

SSRTool: a web tool for evaluating RNA secondary structure predictions based on species-specific functional interpretability

RNA secondary structures can carry out essential cellular functions alone or interact with one another to form the hierarchical tertiary structures. Experimental structure identification approa ches can show the in vitro structures of RNA molecules. However, they usually have limits in the resolution and are costly. In silico structure prediction tools are thus primarily relied on for pre-experiment analysis. Various structure prediction models have been developed over the decades. Since these tools are usually used before knowing the actual RNA structures, evaluating and ranking the pile of secondary structure predictions of a given sequence is essential in computational analysis. In this research, we implemented a web service called SSRTool (RNA Secondary Structure prediction Ranking Tool) to assist in the ranking and evaluation of the generated predicted structures of a given sequence. Based on the computed species-specific interpretability significance in four common RNA structure–function aspects, SSRTool provides three functions along with visualization interfaces: (1) Rank user-generated predictions. (2) Provide an automated streamline of structure prediction and ranking for a given sequence. (3) Infer the functional aspects of a given structure. We demonstrated the applicability of SSRTool via real case studies and reported the similar trends between computed species-specific rankings and the corresponding prediction F1 values. The SSRTool web service is available online at https://cobisHSS0.im.nuk.edu.tw/SSRTool/, http://cosbi3.ee.ncku.edu.tw/SSRTool/, or the redirecting site https://github.com/cobisLab/SSRTool/.

A novel algorithm for ranking RNA structure candidates

RNA research is advancing at an ever increasing pace. The newest and most state-of-the-art instruments and techniques have made possible the discoveries of new RNAs, and they have carried the field to new frontiers of disease research, vaccine development, therapeutics, and architectonics. Like proteins, RNAs show a marked relationship between structure and function. A deeper grasp of RNAs requires a finer understanding of their elaborate structures. In pursuit of this, cutting-edge experimental and computational structure-probing techniques output several candidate geometries for a given RNA, each of which is perfectly aligned with experimentally determined parameters. Identifying which structure is the most accurate, however, remains a major obstacle. In recent years, several algorithms have been developed for ranking candidate RNA structures in order from most to least probable, though their levels of accuracy and transparency leave room for improvement. Most recently, advances in both areas are demonstrated by rsRNASP, a novel algorithm proposed by Tan et al. rsRNASP is a residue-separation-based statistical potential for three-dimensional structure evaluation, and it outperforms the leading algorithms in the field.

Reweighting of molecular simulations with explicit-solvent SAXS restraints elucidates ion-dependent RNA ensembles

Small-angle X-ray scattering (SAXS) experiments are increasingly used to probe RNA structure. A number of forward models that relate measured SAXS intensities and structural features, and that are suitable to model either explicit-solvent effects or solute dynamics, have been proposed in the past years. Here, we introduce an approach that integrates atomistic molecular dynamics simulations and SAXS experiments to reconstruct RNA structural ensembles while simultaneously accounting for both RNA conformational dynamics and explicit-solvent effects. Our protocol exploits SAXS pure-solute forward models and enhanced sampling methods to sample an heterogenous ensemble of structures, with no information towards the experiments provided on-the-fly. The generated structural ensemble is then reweighted through the maximum entropy principle so as to match reference SAXS experimental data at multiple ionic conditions. Importantly, accurate explicit-solvent forward models are used at this reweighting stage. We apply this framework to the GTPase-associated center, a relevant RNA molecule involved in protein translation, in order to elucidate its ion-dependent conformational ensembles. We show that (a) both solvent and dynamics are crucial to reproduce experimental SAXS data and (b) the resulting dynamical ensembles contain an ion-dependent fraction of extended structures.

Diagrammatic approaches to RNA structures with trinucleotide repeats

Trinucleotide repeat expansion disorders are associated with the overexpansion of (CNG) repeats on the genome. Messenger RNA transcripts of sequences with greater than 60–100 (CNG) tandem units have been implicated in trinucleotide repeat expansion disorder pathogenesis. In this work, we develop a diagrammatic theory to study the structural diversity of these (CNG)_n RNA sequences. Representing structural elements on the chain’s conformation by a set of graphs and employing elementary diagrammatic methods, we have formulated a renormalization procedure to re-sum these graphs and arrive at a closed-form expression for the ensemble partition function. With a simple approximation for the renormalization and applied to extended (CNG)_n sequences, this theory can comprehensively capture an infinite set of conformations with any number and any combination of duplexes, hairpins, multiway junctions, and quadruplexes. To quantify the diversity of different (CNG)_n ensembles, the analytical equations derived from the diagrammatic theory were solved numerically to derive equilibrium estimates for the secondary structural contents of the chains. The results suggest that the structural ensembles of (CNG)_n repeat sequence with n ∼60 are surprisingly diverse, and the distribution is sensitive to the ability of the N nucleotide to make noncanonical pairs and whether the (CNG)_n sequence can sustain stable quadruplexes. The results show how perturbations in the form of biases on the stabilities of the various structural motifs, duplexes, junctions, helices, and quadruplexes could affect the secondary structures of the chains and how these structures may switch when they are perturbed.

Structural analyses of an RNA stability element interacting with poly(A)

Cis-acting RNA elements are crucial for the regulation of polyadenylated RNA stability. The element for nuclear expression (ENE) contains a U-rich internal loop flanked by short helices. An ENE stabilizes RNA by sequestering the poly(A) tail via formation of a triplex structure that inhibits a rapid deadenylation-dependent decay pathway. Structure-based bioinformatic studies identified numerous ENE-like elements in evolutionarily diverse genomes, including a subclass containing two ENE motifs separated by a short double-helical region (double ENEs [dENEs]). Here, the structure of a dENE derived from a rice transposable element (TWIFB1) before and after poly(A) binding (∼24 kDa and ∼33 kDa, respectively) is investigated. We combine biochemical structure probing, small angle X-ray scattering (SAXS), and cryo-electron microscopy (cryo-EM) to investigate the dENE structure and its local and global structural changes upon poly(A) binding. Our data reveal 1) the directionality of poly(A) binding to the dENE, and 2) that the dENE-poly(A) interaction involves a motif that protects the 3'-most seven adenylates of the poly(A). Furthermore, we demonstrate that the dENE does not undergo a dramatic global conformational change upon poly(A) binding. These findings are consistent with the recently solved crystal structure of a dENE+poly(A) complex [S.-F. Torabi et al., Science 371, eabe6523 (2021)]. Identification of additional modes of poly(A)-RNA interaction opens new venues for better understanding of poly(A) tail biology.

Modeling the structure of the frameshift-stimulatory pseudoknot in SARS-CoV-2 reveals multiple possible conformers

The coronavirus causing the COVID-19 pandemic, SARS-CoV-2, uses -1 programmed ribosomal frameshifting (-1 PRF) to control the relative expression of viral proteins. As modulating -1 PRF can inhibit viral replication, the RNA pseudoknot stimulating -1 PRF may be a fruitful target for therapeutics treating COVID-19. We modeled the unusual 3-stem structure of the stimulatory pseudoknot of SARS-CoV-2 computationally, using multiple blind structural prediction tools followed by μs-long molecular dynamics simulations. The results were compared for consistency with nuclease-protection assays and single-molecule force spectroscopy measurements of the SARS-CoV-1 pseudoknot, to determine the most likely conformations. We found several possible conformations for the SARS-CoV-2 pseudoknot, all having an extended stem 3 but with different packing of stems 1 and 2. Several conformations featured rarely-seen threading of a single strand through junctions formed between two helices. These structural models may help interpret future experiments and support efforts to discover ligands inhibiting -1 PRF in SARS-CoV-2.

Human DDX17 Unwinds Rift Valley Fever Virus Non-Coding RNAs

Rift Valley fever virus (RVFV) is a mosquito-transmitted virus from the Bunyaviridae family that causes high rates of mortality and morbidity in humans and ruminant animals. Previous studies indicated that DEAD-box helicase 17 (DDX17) restricts RVFV replication by recognizing two primary non-coding RNAs in the S-segment of the genome: the intergenic region (IGR) and 5' non-coding region (NCR). However, we lack molecular insights into the direct binding of DDX17 with RVFV non-coding RNAs and information on the unwinding of both non-coding RNAs by DDX17. Therefore, we performed an extensive biophysical analysis of the DDX17 helicase domain (DDX17135-555) and RVFV non-coding RNAs, IGR and 5' NCR. The homogeneity studies using analytical ultracentrifugation indicated that DDX17135-555, IGR, and 5' NCR are pure. Next, we performed small-angle X-ray scattering (SAXS) experiments, which suggested that DDX17 and both RNAs are homogenous as well. SAXS analysis also demonstrated that DDX17 is globular to an extent, whereas the RNAs adopt an extended conformation in solution. Subsequently, microscale thermophoresis (MST) experiments were performed to investigate the direct binding of DDX17 to the non-coding RNAs. The MST experiments demonstrated that DDX17 binds with the IGR and 5' NCR with a dissociation constant of 5.77 ± 0.15 µM and 9.85 ± 0.11 µM, respectively. As DDX17135-555 is an RNA helicase, we next determined if it could unwind IGR and NCR. We developed a helicase assay using MST and fluorescently-labeled oligos, which suggested DDX17135-555 can unwind both RNAs. Overall, our study provides direct evidence of DDX17135-555 interacting with and unwinding RVFV non-coding regions.

A robust and versatile method for production and purification of large-scale RNA samples for structural biology

Recent findings in genome-wide transcriptomics revealed that RNAs are involved in almost every biological process, across all domains of life. The characterization of native RNAs of unknown function and structure is particularly challenging due to their typical low abundance in the cell and the inherent sensitivity toward ubiquitous RNA degrading enzymes. Therefore, robust in vitro synthesis and extensive work-up methods are often needed to obtain samples amenable for biochemical, biophysical, and structural studies. Here, we present a protocol that combines the most recent advances in T7 in vitro transcription methodology with reverse phase ion pairing and ion exchange HPLC purification of RNAs for the production of yield-optimized large-scale samples. The method is easy to follow, robust and suitable for users with little or no experience within the field of biochemistry or chromatography. The complete execution of this method, for example, for production of isotopically labeled NMR samples, can be performed in less than a week.

Structure-based screening of binding affinities via small-angle X-ray scattering

Protein-protein and protein-ligand interactions often involve conformational changes or structural rearrangements that can be quantified by solution small-angle X-ray scattering (SAXS). These scattering intensity measurements reveal structural details of the bound complex, the number of species involved and, additionally, the strength of interactions if carried out as a titration. Although a core part of structural biology workflows, SAXS-based titrations are not commonly used in drug discovery contexts. This is because prior knowledge of expected sample requirements, throughput and prediction accuracy is needed to develop reliable ligand screens. This study presents the use of the histidine-binding protein (26 kDa) and other periplasmic binding proteins to benchmark ligand screen performance. Sample concentrations and exposure times were varied across multiple screening trials at four beamlines to investigate the accuracy and precision of affinity prediction. The volatility ratio between titrated scattering curves and a common apo reference is found to most reliably capture the extent of structural and population changes. This obviates the need to explicitly model scattering intensities of bound complexes, which can be strongly ligand-dependent. Where the dissociation constant is within 102 of the protein concentration and the total exposure times exceed 20 s, the titration protocol presented at 0.5 mg ml-1 yields affinities comparable to isothermal titration calorimetry measurements. Estimated throughput ranges between 20 and 100 ligand titrations per day at current synchrotron beamlines, with the limiting step imposed by sample handling and cleaning procedures.

Visualizing the functional 3D shape and topography of long noncoding RNAs by single-particle atomic force microscopy and in-solution hydrodynamic techniques

Long noncoding RNAs (lncRNAs) are recently discovered transcripts that regulate vital cellular processes, such as cellular differentiation and DNA replication, and are crucially connected to diseases. Although the 3D structures of lncRNAs are key determinants of their function, the unprecedented molecular complexity of lncRNAs has so far precluded their 3D structural characterization at high resolution. It is thus paramount to develop novel approaches for biochemical and biophysical characterization of these challenging targets. Here, we present a protocol that integrates non-denaturing lncRNA purification with in-solution hydrodynamic analysis and single-particle atomic force microscopy (AFM) imaging to produce highly homogeneous lncRNA preparations and visualize their 3D topology at ~15-Å resolution. Our protocol is suitable for imaging lncRNAs in biologically active conformations and for measuring structural defects of functionally inactive mutants that have been identified by cell-based functional assays. Once optimized for the specific target lncRNA of choice, our protocol leads from cloning to AFM imaging within 3-4 weeks and can be implemented using state-of-the-art biochemical and biophysical instrumentation by trained researchers familiar with RNA handling and supported by AFM and small-angle X-ray scattering (SAXS) experts.

Using FRET to measure the time it takes for a cell to destroy a virus

The emergence of viral nanotechnology over the preceding two decades has created a number of intellectually captivating possible translational applications; however, the in vitro fate of the viral nanoparticles in cells remains an open question. Herein, we investigate the stability and lifetime of virus-like particle (VLP) Qβ-a representative and popular VLP for several applications-following cellular uptake. By exploiting the available functional handles on the viral surface, we have orthogonally installed the known FRET pair, FITC and Rhodamine B, to gain insight of the particle's behavior in vitro. Based on these data, we believe VLPs undergo aggregation in addition to the anticipated proteolysis within a few hours of cellular uptake.

Supramolecular and biomacromolecular enhancement of metal-free magnetic resonance imaging contrast agents

Many contrast agents for magnetic resonance imaging are based on gadolinium, however side effects limit their use in some patients. Organic radical contrast agents (ORCAs) are potential alternatives, but are reduced rapidly in physiological conditions and have low relaxivities as single molecule contrast agents. Herein, we use a supramolecular strategy where cucurbit[8]uril binds with nanomolar affinities to ORCAs and protects them against biological reductants to create a stable radical in vivo. We further overcame the weak contrast by conjugating this complex on the surface of a self-assembled biomacromolecule derived from the tobacco mosaic virus.

Nuclear Magnetic Resonance of Single-Stranded RNAs and DNAs of CAAU and UCAAUC as Benchmarks for Molecular Dynamics Simulations

RNA and DNA are rapidly emerging as targets for therapeutics and as potential frameworks for nanotechnology. Accurate methods for predicting and designing structures and dynamics of nucleic acids would accelerate progress in these and other applications. Suitable approximations for modeling nucleic acids are being developed but require validation against disparate experimental observations. Here, nuclear magnetic resonance spectra for RNA and DNA single strands, CAAU and UCAAUC, are used as benchmarks to test molecular dynamics simulations with AMBER force fields OL3 and ROC-RNA for RNA and BSC1 for DNA. A detailed scheme for making comparisons is also presented. The results reflect recent progress in approximations and reveal remaining challenges.

Nanoscale Structure Determination of Murray Valley Encephalitis and Powassan Virus Non-Coding RNAs

Viral infections are responsible for numerous deaths worldwide. Flaviviruses, which contain RNA as their genetic material, are one of the most pathogenic families of viruses. There is an increasing amount of evidence suggesting that their 5' and 3' non-coding terminal regions are critical for their survival. Information on their structural features is essential to gain detailed insights into their functions and interactions with host proteins. In this study, the 5' and 3' terminal regions of Murray Valley encephalitis virus and Powassan virus were examined using biophysical and computational modeling methods. First, we used size exclusion chromatography and analytical ultracentrifuge methods to investigate the purity of in-vitro transcribed RNAs. Next, we employed small-angle X-ray scattering techniques to study solution conformation and low-resolution structures of these RNAs, which suggest that the 3' terminal regions are highly extended as compared to the 5' terminal regions for both viruses. Using computational modeling tools, we reconstructed 3-dimensional structures of each RNA fragment and compared them with derived small-angle X-ray scattering low-resolution structures. This approach allowed us to reinforce that the 5' terminal regions adopt more dynamic structures compared to the mainly double-stranded structures of the 3' terminal regions.

Zinc-finger protein CNBP alters the 3-D structure of lncRNA Braveheart in solution

Long non-coding RNAs (lncRNAs) constitute a significant fraction of the transcriptome, playing important roles in development and disease. However, our understanding of structure-function relationships for this emerging class of RNAs has been limited to secondary structures. Here, we report the 3-D atomistic structural study of epigenetic lncRNA, Braveheart (Bvht), and its complex with CNBP (Cellular Nucleic acid Binding Protein). Using small angle X-ray scattering (SAXS), we elucidate the ensemble of Bvht RNA conformations in solution, revealing that Bvht lncRNA has a well-defined, albeit flexible 3-D structure that is remodeled upon CNBP binding. Our study suggests that CNBP binding requires multiple domains of Bvht and the RHT/AGIL RNA motif. We show that RHT/AGIL, previously shown to interact with CNBP, contains a highly flexible loop surrounded by more ordered helices. As one of the largest RNA-only 3-D studies, the work lays the foundation for future structural studies of lncRNA-protein complexes.

Structural Analysis of RNA by Small-Angle X-ray Scattering

Over the past two decades small-angle X-ray scattering (SAXS) has become a popular method to characterize solutions of biomolecules including ribonucleic acid (RNA). In an integrative structural approach, SAXS is complementary to crystallography, NMR, and electron microscopy and provides information about RNA architecture and dynamics. This chapter highlights the practical advantages of combining size-exclusion chromatography and SAXS at synchrotron facilities. It is illustrated by practical case studies of samples ranging from single hairpins and tRNA to a large IRES. The emphasis is also put on sample preparation which is a critical step of SAXS analysis and on optimized protocols for in vitro RNA synthesis ensuring the production of mg amount of pure and homogeneous molecules.

Site-Directed Spin Labeling of RNA with a Gem-Diethylisoindoline Spin Label: PELDOR, Relaxation, and Reduction Stability

Ribonucleic acid function is governed by its structure, dynamics, and interaction with other biomolecules and influenced by the local environment. Thus, methods are needed that enable one to study RNA under conditions as natural as possible, possibly within cells. Site-directed spin-labeling of RNA with nitroxides in combination with, for example, pulsed electron-electron double resonance (PELDOR or DEER) spectroscopy has been shown to provide such information. However, for in-cell measurements, the usually used gem-dimethyl nitroxides are less suited, because they are quickly reduced under in-cell conditions. In contrast, gem-diethyl nitroxides turned out to be more stable, but labeling protocols for binding these to RNA have been sparsely reported. Therefore, we describe here the bioconjugation of an azide functionalized gem-diethyl isoindoline nitroxide to RNA using a copper (I)-catalyzed azide-alkyne cycloaddition ("click"-chemistry). The labeling protocol provides high yields and site selectivity. The analysis of the orientation selective PELDOR data show that the gem-diethyl and gem-dimethyl labels adopt similar conformations. Interestingly, in deuterated buffer, both labels attached to RNA yield TM relaxation times that are considerably longer than observed for the same type of label attached to proteins, enabling PELDOR time windows of up to 20 microseconds. Together with the increased stability in reducing environments, this label is very promising for in-cell Electron Paramagnetic Resonance (EPR) studies.

Conserved Pseudoknots in lncRNA MEG3 Are Essential for Stimulation of the p53 Pathway

Long non-coding RNAs (lncRNAs) are key regulatory molecules, but unlike with other RNAs, the direct link between their tertiary structure motifs and their function has proven elusive. Here we report structural and functional studies of human maternally expressed gene 3 (MEG3), a tumor suppressor lncRNA that modulates the p53 response. We found that, in an evolutionary conserved region of MEG3, two distal motifs interact by base complementarity to form alternative, mutually exclusive pseudoknot structures ("kissing loops"). Mutations that disrupt these interactions impair MEG3-dependent p53 stimulation in vivo and disrupt MEG3 folding in vitro. These findings provide mechanistic insights into regulation of the p53 pathway by MEG3 and reveal how conserved motifs of tertiary structure can regulate lncRNA biological function.

Differentiation and classification of RNA motifs using small molecule-based pattern recognition

Understanding how to design small molecules that target coding and non-coding RNA has the potential to exponentially increase the number of therapeutically-relevant druggable targets, which are currently mostly proteins. However, there is limited information on the principles at the basis of RNA recognition. In this chapter, we describe a pattern-based technique that can be used for the simultaneous elucidation of RNA motifs and small molecule features for RNA selective recognition, termed Pattern Recognition of RNA by Small Molecules (PRRSM). We provide protocols for the computational design and synthetic preparation of an RNA training set as well as how to perform the assay in plate reader format. Furthermore, we provide details on how to perform and interpret the statistical analysis and indicate possible future extensions of the technique. By combining insights into characteristics of the small molecules and of the RNA that leads to differentiation, PRRSM promises to accelerate the elucidation of the determinants at the basis of RNA recognition.

NMR characterization of RNA small molecule interactions

Exciting discoveries of naturally occurring ligand-sensing and disease-linked noncoding RNAs have promoted significant interests in understanding RNA-small molecule interactions. NMR spectroscopy is a powerful tool for characterizing intermolecular interactions. In this review, we describe protocols and approaches for applying NMR spectroscopy to investigate interactions between RNA and small molecules. We review protocols for RNA sample preparation, methods for identifying RNA-binding small molecules, approaches for mapping RNA-small molecule interactions, determining complex structures, and characterizing binding kinetics. We hope this review will provide a guideline to streamline NMR applications in studying RNA-small molecule interactions, facilitating both basic mechanistic understandings of RNA functions and translational efforts in developing RNA-targeted therapeutics.

Plant virus-based materials for biomedical applications: Trends and prospects

Nanomaterials composed of plant viral components are finding their way into medical technology and health care, as they offer singular properties. Precisely shaped, tailored virus nanoparticles (VNPs) with multivalent protein surfaces are efficiently loaded with functional compounds such as contrast agents and drugs, and serve as carrier templates and targeting vehicles displaying e.g. peptides and synthetic molecules. Multiple modifications enable uses including vaccination, biosensing, tissue engineering, intravital delivery and theranostics. Novel concepts exploit self-organization capacities of viral building blocks into hierarchical 2D and 3D structures, and their conversion into biocompatible, biodegradable units. High yields of VNPs and proteins can be harvested from plants after a few days so that various products have reached or are close to commercialization. The article delineates potentials and limitations of biomedical plant VNP uses, integrating perspectives of chemistry, biomaterials sciences, molecular plant virology and process engineering.

RNA Structural Differentiation: Opportunities with Pattern Recognition

Our awareness and appreciation of the many regulatory roles of RNA have dramatically increased in the past decade. This understanding, in addition to the impact of RNA in many disease states, has renewed interest in developing selective RNA-targeted small molecule probes. However, the fundamental guiding principles in RNA molecular recognition that could accelerate these efforts remain elusive. While high-resolution structural characterization can provide invaluable insight, examples of well-characterized RNA structures, not to mention small molecule:RNA complexes, remain limited. This Perspective provides an overview of the current techniques used to understand RNA molecular recognition when high-resolution structural information is unavailable. We will place particular emphasis on a new method, pattern recognition of RNA with small molecules (PRRSM), that provides rapid insight into critical components of RNA recognition and differentiation by small molecules as well as into RNA structural features.

Concentration-dependent and configuration-dependent interactions of monovalent ions with an RNA tetraloop

Monovalent salt solutions have strongly coupled interactions with biopolymers, from large polyelectrolytes to small RNA oligomers. High salt concentrations have been known to induce transitions in the structure of RNA, producing non-canonical configurations and even driving RNA to precipitate out of solution. Using all-atom molecular dynamics simulations, we model a monovalent salt species (KCL) at high concentrations (0.1-3m) and calculate the equilibrium distributions of water and ions around a small tetraloop-forming RNA oligomer in a variety of structural arrangements: folded A-RNA (canonical) and Z-RNA (non-canonical) tetraloops and unfolded configurations. From these data, we calculate the ion preferential binding coefficients and Donnan coefficients for the RNA oligomer as a function of concentration and structure. We find that cation accumulation is highest around non-canonical Z-RNA configurations at concentrations below 0.5m, while unfolded configurations accumulate the most co-ions in all concentrations. By contrast, canonical A-RNA structures consistently show the lowest accumulations for all ion species. Water distributions vary markedly with RNA configuration but show little dependency on KCL concentration. Based on Donnan coefficient calculations, the net charge of the solution at the surface of the RNA decreases linearly as a function of salt concentration and becomes net-neutral near 2.5-3m KCL for folded configurations, while unfolded configurations still show a positive solution charge. Our findings show that all-atom molecular dynamics can describe the equilibrium distributions of monovalent salt in the presence of small RNA oligomers at KCL concentrations where ion correlation effects become important. Furthermore, these results provide valuable insights into the distributions of water and ions near the RNA oligomer surface as a function of structural configuration.

A guide to large-scale RNA sample preparation

RNA is becoming more important as an increasing number of functions, both regulatory and enzymatic, are being discovered on a daily basis. As the RNA boom has just begun, most techniques are still in development and changes occur frequently. To understand RNA functions, revealing the structure of RNA is of utmost importance, which requires sample preparation. We review the latest methods to produce and purify a variation of RNA molecules for different purposes with the main focus on structural biology and biophysics. We present a guide aimed at identifying the most suitable method for your RNA and your biological question and highlighting the advantages of different methods. Graphical abstract In this review we present different methods for large-scale production and purification of RNAs for structural and biophysical studies.

Progress in small-angle scattering from biological solutions at high-brilliance synchrotrons

Small-angle X-ray scattering (SAXS) is an established technique that provides low-resolution structural information on macromolecular solutions. Recent decades have witnessed significant progress in both experimental facilities and in novel data-analysis approaches, making SAXS a mainstream method for structural biology. The technique is routinely applied to directly reconstruct low-resolution shapes of proteins and to generate atomistic models of macromolecular assemblies using hybrid approaches. Very importantly, SAXS is capable of yielding structural information on systems with size and conformational polydispersity, including highly flexible objects. In addition, utilizing high-flux synchrotron facilities, time-resolved SAXS allows analysis of kinetic processes over time ranges from microseconds to hours. Dedicated bioSAXS beamlines now offer fully automated data-collection and analysis pipelines, where analysis and modelling is conducted on the fly. This enables SAXS to be employed as a high-throughput method to rapidly screen various sample conditions and additives. The growing SAXS user community is supported by developments in data and model archiving and quality criteria. This review illustrates the latest developments in SAXS, in particular highlighting time-resolved applications aimed at flexible and evolving systems.