Small-angle scattering and 3D structure interpretation

Benchmarking predictive methods for small-angle X-ray scattering from atomic coordinates of proteins using maximum likelihood consensus data

Stimulated by informal conversations at the XVII International Small Angle Scattering (SAS) conference (Traverse City, 2017), an international team of experts undertook a round-robin exercise to produce a large dataset from proteins under standard solution conditions. These data were used to generate consensus SAS profiles for xylose isomerase, urate oxidase, xylanase, lysozyme and ribonuclease A. Here, we apply a new protocol using maximum likelihood with a larger number of the contributed datasets to generate improved consensus profiles. We investigate the fits of these profiles to predicted profiles from atomic coordinates that incorporate different models to account for the contribution to the scattering of water molecules of hydration surrounding proteins in solution. Programs using an implicit, shell-type hydration layer generally optimize fits to experimental data with the aid of two parameters that adjust the volume of the bulk solvent excluded by the protein and the contrast of the hydration layer. For these models, we found the error-weighted residual differences between the model and the experiment generally reflected the subsidiary maxima and minima in the consensus profiles that are determined by the size of the protein plus the hydration layer. By comparison, all-atom solute and solvent molecular dynamics (MD) simulations are without the benefit of adjustable parameters and, nonetheless, they yielded at least equally good fits with residual differences that are less reflective of the structure in the consensus profile. Further, where MD simulations accounted for the precise solvent composition of the experiment, specifically the inclusion of ions, the modelled radius of gyration values were significantly closer to the experiment. The power of adjustable parameters to mask real differences between a model and the structure present in solution is demonstrated by the results for the conformationally dynamic ribonuclease A and calculations with pseudo-experimental data. This study shows that, while methods invoking an implicit hydration layer have the unequivocal advantage of speed, care is needed to understand the influence of the adjustable parameters. All-atom solute and solvent MD simulations are slower but are less susceptible to false positives, and can account for thermal fluctuations in atomic positions, and more accurately represent the water molecules of hydration that contribute to the scattering profile.

Contrast variation method applied to structural evaluation of catalysts by X-ray small-angle scattering

In the process of developing carbon-supported metal catalysts, determining the catalyst particle-size distribution is an essential step, because this parameter is directly related to the catalytic activities. The particle-size distribution is most effectively determined by small-angle X-ray scattering (SAXS). When metal catalysts are supported by high-performance mesoporous carbon materials, however, their mesopores may lead to erroneous particle-size estimation if the sizes of the catalysts and mesopores are comparable. Here we propose a novel approach to particle-size determination by introducing contrast variation-SAXS (CV-SAXS). In CV-SAXS, a multi-component sample is immersed in an inert solvent with a density equal to that of one of the components, thereby rendering that particular component invisible to X-rays. We used a mixture of tetrabromoethane and dimethyl sulfoxide as a contrast-matching solvent for carbon. As a test sample, we prepared a mixture of a small amount of platinum (Pt) catalyst and a bulk of mesoporous carbon, and subjected it to SAXS measurement in the absence and presence of the solvent. In the absence of the solvent, the estimated Pt particle size was affected by the mesopores, but in the presence of the solvent, the Pt particle size was correctly estimated in spite of the low Pt content. The results demonstrate that the CV-SAXS technique is useful for correctly determining the particle-size distribution for low-Pt-content catalysts, for which demands are increasing to reduce the use of expensive Pt.

An ensemble of cadherin-catenin-vinculin complex employs vinculin as the major F-actin binding mode

The cell-cell adhesion cadherin-catenin complexes recruit vinculin to the adherens junction (AJ) to modulate the mechanical couplings between neighboring cells. However, it is unclear how vinculin influences the AJ structure and function. Here, we identified two patches of salt bridges that lock vinculin in the head-tail autoinhibited conformation and reconstituted the full-length vinculin activation mimetics bound to the cadherin-catenin complex. The cadherin-catenin-vinculin complex contains multiple disordered linkers and is highly dynamic, which poses a challenge for structural studies. We determined the ensemble conformation of this complex using small-angle x-ray and selective deuteration/contrast variation small-angle neutron scattering. In the complex, both α-catenin and vinculin adopt an ensemble of flexible conformations, but vinculin has fully open conformations with the vinculin head and actin-binding tail domains well separated from each other. F-actin binding experiments show that the cadherin-catenin-vinculin complex binds and bundles F-actin. However, when the vinculin actin-binding domain is removed from the complex, only a minor fraction of the complex binds to F-actin. The results show that the dynamic cadherin-catenin-vinculin complex employs vinculin as the primary F-actin binding mode to strengthen AJ-cytoskeleton interactions.

Enabling Efficient Design of Biological Formulations Through Advanced Characterization

The present review summarizes the use of differential scanning calorimetry (DSC) and scattering techniques in the context of protein formulation design and characterization. The scattering techniques include wide angle X-ray diffractometry (XRD), small-angle neutron scattering (SANS) and small-angle X-ray scattering (SAXS). While DSC is valuable for understanding thermal behavior of the excipients, XRD provides critical information about physical state of solutes during freezing, annealing and in the final lyophile. However, as these techniques lack the sensitivity to detect biomolecule-related transitions, complementary characterization techniques such as small-angle scattering can provide valuable insights.

2023 update of template tables for reporting biomolecular structural modelling of small-angle scattering data

In 2017, guidelines were published for reporting structural modelling of small-angle scattering (SAS) data from biomolecules in solution that exemplified best-practice documentation of experiments and analysis. Since then, there has been significant progress in SAS data and model archiving, and the IUCr journal editors announced that the IUCr biology journals will require the deposition of SAS data used in biomolecular structure solution into a public archive, as well as adherence to the 2017 reporting guidelines. In this context, the reporting template tables accompanying the 2017 publication guidelines have been reviewed with a focus on making them both easier to use and more general. With input from the SAS community via the IUCr Commission on SAS and attendees of the triennial 2022 SAS meeting (SAS2022, Campinas, Brazil), an updated reporting template table has been developed that includes standard descriptions for proteins, glycosylated proteins, DNA and RNA, with some reorganization of the data to improve readability and interpretation. In addition, a specialized template has been developed for reporting SAS contrast-variation (SAS-cv) data and models that incorporates the additional reporting requirements from the 2017 guidelines for these more complicated experiments. To demonstrate their utility, examples of reporting with these new templates are provided for a SAS study of a DNA-protein complex and a SAS-cv experiment on a protein complex. The examples demonstrate how the tabulated information promotes transparent reporting that, in combination with the recommended figures and additional information best presented in the main text, enables the reader of the work to readily draw their own conclusions regarding the quality of the data and the validity of the models presented.

Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scattering

Key to small-angle scattering (SAS) maturing and becoming a mainstream structural biology technique was the work done by the SAS community to establish standards for data quality, model validation and data sharing. Through a consultative process spanning more than a decade and a half, guidelines for publication have been established that include criteria for evaluating data quality and for model validation. In this process gaps were identified that stimulated innovation and development of new tools, for example new measures of model ambiguity and of the goodness-of-fit of a model to SAS data that complement the traditional global fit parameter χ². The need for a global repository for biomolecular SAS data and models was identified and the SASBDB was established as a searchable, curated, freely accessible, downloadable database of experimental data, experimental conditions, sample details, derived models, and their fit to the data. Importantly, the SASBDB uses a common dictionary format that supports archiving of structures solved using integrative methods to support seamless data exchange with a federated system of public databanks that includes the world-wide Protein Data Bank (wwPDB) as the major repository for structural biology. Thus, biomolecular SAS is now well-positioned to achieve its full potential as a mainstream structural biology technique contributing at the frontier of integrative structural biology and meeting "best practice" standards for data quality assurance and data sharing.

Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models

Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, structural characterization of antibody-antigen complexes remains challenging. On the one hand, X-ray crystallography or cryo-electron microscopy provide atomic resolution characterization of the epitope, but the data collection process is typically long and the success rate is low. On the other hand, computational methods for modeling antibody-antigen structures from the individual components frequently suffer from a high false positive rate, rarely resulting in a unique solution. Recent deep learning models for structure prediction are also successful in predicting protein-protein complexes. However, they do not perform well for antibody-antigen complexes. Small Angle X-ray Scattering (SAXS) is a reliable technique for rapid structural characterization of protein samples in solution albeit at low resolution. Here, we present an integrative approach for modeling antigen-antibody complexes using the antibody sequence, antigen structure, and experimentally determined SAXS profiles of the antibody, antigen, and the complex. The method models antibody structures using a novel deep-learning approach, NanoNet. The structures of the antibodies and antigens are represented using multiple 3D conformations to account for compositional and conformational heterogeneity of the protein samples that are used to collect the SAXS data. The complexes are predicted by integrating the SAXS profiles with scoring functions for protein-protein interfaces that are based on statistical potentials and antibody-specific deep-learning models. We validated the method via application to four Fab:EGFR and one Fab:PCSK9 antibody:antigen complexes with experimentally available SAXS datasets. The integrative approach returns accurate predictions (interface RMSD<4Å) in the top five predictions for four out of five complexes (respective interface RMSD values of 1.95, 2.18, 2.66 and 3.87Å), providing support for the utility of such a computational pipeline for epitope characterization during therapeutic antibody discovery.

Photoredox C-H functionalization leads the site-selective phenylalanine bioconjugation

Site-selectively chemical bioconjugation of peptides and proteins can improve the therapeutic exploration of modified protein drugs. Only 3.8% natural abundance of phenylalanine in protein and nearly 90% of proteins contain at least one phenylalanine residue in their sequenced, showing the potential in biopharmaceutical utility of the phenylalanine bioconjugation. However, the covalent bioconjugation of native phenylalanine is one of the most challenging problems in protein modification. Herein, an approach to protein modification is described that relies on a photoredox method for the site-selective bioconjugation of phenylalanine. This methodology has been validated on peptides as well as protein insulin using a straightforward and mild condition. In addition, based on characterization by near-UV CD spectroscopy and small angle X-ray scattering (SAXS), this pyrazole labeling approach permitted the insulin hexamer to completely dissociate into the monomeric form, thus making it a potential candidate for use as rapid-acting insulin for the treatment of diabetes.

A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking

Through an expansive international effort that involved data collection on 12 small-angle X-ray scattering (SAXS) and four small-angle neutron scattering (SANS) instruments, 171 SAXS and 76 SANS measurements for five proteins (ribonuclease A, lysozyme, xylanase, urate oxidase and xylose isomerase) were acquired. From these data, the solvent-subtracted protein scattering profiles were shown to be reproducible, with the caveat that an additive constant adjustment was required to account for small errors in solvent subtraction. Further, the major features of the obtained consensus SAXS data over the q measurement range 0-1 Å-1 are consistent with theoretical prediction. The inherently lower statistical precision for SANS limited the reliably measured q-range to <0.5 Å-1, but within the limits of experimental uncertainties the major features of the consensus SANS data were also consistent with prediction for all five proteins measured in H2O and in D2O. Thus, a foundation set of consensus SAS profiles has been obtained for benchmarking scattering-profile prediction from atomic coordinates. Additionally, two sets of SAXS data measured at different facilities to q > 2.2 Å-1 showed good mutual agreement, affirming that this region has interpretable features for structural modelling. SAS measurements with inline size-exclusion chromatography (SEC) proved to be generally superior for eliminating sample heterogeneity, but with unavoidable sample dilution during column elution, while batch SAS data collected at higher concentrations and for longer times provided superior statistical precision. Careful merging of data measured using inline SEC and batch modes, or low- and high-concentration data from batch measurements, was successful in eliminating small amounts of aggregate or interparticle interference from the scattering while providing improved statistical precision overall for the benchmarking data set.

Recent advances in small-angle scattering and its expanding impact in structural biology

Applications of small-angle scattering (SAS) in structural biology have benefited from continuing developments in instrumentation, tools for data analysis, modeling capabilities, standards for data and model presentation, and data archiving. The interplay of these capabilities has enabled SAS to contribute to advances in structural biology as the field pushes the boundaries in studies of biomolecular complexes and assemblies as large as whole cells, membrane proteins in lipid environments, and dynamic systems on time scales ranging from femtoseconds to hours. This review covers some of the important advances in biomolecular SAS capabilities for structural biology focused on over the last 5 years and presents highlights of recent applications that demonstrate how the technique is exploring new territories.

Nanopores: a versatile tool to study protein dynamics

Proteins are the active workhorses in our body. These biomolecules perform all vital cellular functions from DNA replication and general biosynthesis to metabolic signaling and environmental sensing. While static 3D structures are now readily available, observing the functional cycle of proteins - involving conformational changes and interactions - remains very challenging, e.g., due to ensemble averaging. However, time-resolved information is crucial to gain a mechanistic understanding of protein function. Single-molecule techniques such as FRET and force spectroscopies provide answers but can be limited by the required labelling, a narrow time bandwidth, and more. Here, we describe electrical nanopore detection as a tool for probing protein dynamics. With a time bandwidth ranging from microseconds to hours, nanopore experiments cover an exceptionally wide range of timescales that is very relevant for protein function. First, we discuss the working principle of label-free nanopore experiments, various pore designs, instrumentation, and the characteristics of nanopore signals. In the second part, we review a few nanopore experiments that solved research questions in protein science, and we compare nanopores to other single-molecule techniques. We hope to make electrical nanopore sensing more accessible to the biochemical community, and to inspire new creative solutions to resolve a variety of protein dynamics - one molecule at a time.

The molecular structure of long non-coding RNAs: emerging patterns and functional implications

Long non-coding RNAs (lncRNAs) are recently-discovered transcripts that regulate vital cellular processes and are crucially connected to diseases. Despite their unprecedented molecular complexity, it is emerging that lncRNAs possess distinct structural motifs. Remarkably, the 3D shape and topology of full-length, native lncRNAs have been visualized for the first time in the last year. These studies reveal that lncRNA structures dictate lncRNA functions. Here, we review experimentally determined lncRNA structures and emphasize that lncRNA structural characterization requires synergistic integration of computational, biochemical and biophysical approaches. Based on these emerging paradigms, we discuss how to overcome the challenges posed by the complex molecular architecture of lncRNAs, with the goal of obtaining a detailed understanding of lncRNA functions and molecular mechanisms in the future.

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.

Robosample: A rigid-body molecular simulation program based on robot mechanics

BACKGROUND

Compared with all-atom molecular dynamics (MD), constrained MD methods allow for larger time steps, potentially reducing computational cost. For this reason, there has been continued interest in improving constrained MD algorithms to increase configuration space sampling in molecular simulations.

METHODS

Here, we introduce Robosample, a software package that implements high-performance constrained dynamics algorithms, originally developed for robotics, and applies them to simulations of biomolecular systems. As in the gMolmodel package developed by Spiridon and Minh in 2017, Robosample uses Constrained Dynamics Hamiltonian Monte Carlo (CDHMC) as a Gibbs sampling move - a type of Monte Carlo move where a subset of coordinates is allowed to change. In addition to the previously described Cartesian and torsional dynamics moves, Robosample implements spherical and cylindrical joints that can be distributed along the molecule by the user.

RESULTS

In alanine dipeptide simulations, the free energy surface is recovered by mixing fully flexible with torsional, cylindrical, or spherical dynamics moves. Ramachandran dynamics, where only the two key torsions are mobile, accelerate the slowest transition by an order of magnitude. We also show that simulations of a complex glycan cover significantly larger regions of the configuration space when mixed with constrained dynamics.

MAJOR CONCLUSIONS

Robosample is a tool of choice for efficient conformational sampling of large biomolecules.

GENERAL SIGNIFICANCE

Robosample is intended as a reliable and user-friendly simulation package for fast biomolecular sampling that does not require extensive expertise in mechanical engineering or in the statistical mechanics of reduced coordinates.

Small-Angle X-ray Scattering Curves of Detergent Micelles: Effects of Asymmetry, Shape Fluctuations, Disorder, and Atomic Details

Small-angle X-ray scattering (SAXS) is a widely used experimental technique, providing structural and dynamic insight into soft-matter complexes and biomolecules under near-native conditions. However, interpreting the one-dimensional scattering profiles in terms of three-dimensional structures and ensembles remains challenging, partly because it is poorly understood how structural information is encoded along the measured scattering angle. We combined all-atom SAXS-restrained ensemble simulations, simplified continuum models, and SAXS experiments of a n-dodecyl-β-d-maltoside (DDM) micelle to decipher the effects of model asymmetry, shape fluctuations, atomic disorder, and atomic details on SAXS curves. Upon interpreting the small-angle regime, we find remarkable agreement between (i) a two-component triaxial ellipsoid model fitted against the data and (ii) a SAXS-refined all-atom ensemble. However, continuum models fail at wider angles, even if they account for shape fluctuations, disorder, and asymmetry of the micelle. We conclude that modeling atomic details is mandatory for explaining SAXS curves at wider angles.

Generation of the configurational ensemble of an intrinsically disordered protein from unbiased molecular dynamics simulation

Intrinsically disordered proteins (IDPs) are abundant in eukaryotic proteomes, play a major role in cell signaling, and are associated with human diseases. To understand IDP function it is critical to determine their configurational ensemble, i.e., the collection of 3-dimensional structures they adopt, and this remains an immense challenge in structural biology. Attempts to determine this ensemble computationally have been hitherto hampered by the necessity of reweighting molecular dynamics (MD) results or biasing simulation in order to match ensemble-averaged experimental observables, operations that reduce the precision of the generated model because different structural ensembles may yield the same experimental observable. Here, by employing enhanced sampling MD we reproduce the experimental small-angle neutron and X-ray scattering profiles and the NMR chemical shifts of the disordered N terminal (SH4UD) of c-Src kinase without reweighting or constraining the simulations. The unbiased simulation results reveal a weakly funneled and rugged free energy landscape of SH4UD, which gives rise to a heterogeneous ensemble of structures that cannot be described by simple polymer theory. SH4UD adopts transient helices, which are found away from known phosphorylation sites and could play a key role in the stabilization of structural regions necessary for phosphorylation. Our findings indicate that adequately sampled molecular simulations can be performed to provide accurate physical models of flexible biosystems, thus rationalizing their biological function.

BEES: Bayesian Ensemble Estimation from SAS

Many biomolecular complexes exist in a flexible ensemble of states in solution that is necessary to perform their biological function. Small-angle scattering (SAS) measurements are a popular method for characterizing these flexible molecules because of their relative ease of use and their ability to simultaneously probe the full ensemble of states. However, SAS data is typically low dimensional and difficult to interpret without the assistance of additional structural models. In theory, experimental SAS curves can be reconstituted from a linear combination of theoretical models, although this procedure carries a significant risk of overfitting the inherently low-dimensional SAS data. Previously, we developed a Bayesian-based method for fitting ensembles of model structures to experimental SAS data that rigorously avoids overfitting. However, we have found that these methods can be difficult to incorporate into typical SAS modeling workflows, especially for users that are not experts in computational modeling. To this end, we present the Bayesian Ensemble Estimation from SAS (BEES) program. Two forks of BEES are available, the primary one existing as a module for the SASSIE web server and a developmental version that is a stand-alone Python program. BEES allows users to exhaustively sample ensemble models constructed from a library of theoretical states and to interactively analyze and compare each model's performance. The fitting routine also allows for secondary data sets to be supplied, thereby simultaneously fitting models to both SAS data as well as orthogonal information. The flexible ensemble of K63-linked ubiquitin trimers is presented as an example of BEES' capabilities.

Small-Angle Scattering as a Structural Probe for Nucleic Acid Nanoparticles (NANPs) in a Dynamic Solution Environment

Nucleic acid-based technologies are an emerging research focus area for pharmacological and biological studies because they are biocompatible and can be designed to produce a variety of scaffolds at the nanometer scale. The use of nucleic acids (ribonucleic acid (RNA) and/or deoxyribonucleic acid (DNA)) as building materials in programming the assemblies and their further functionalization has recently established a new exciting field of RNA and DNA nanotechnology, which have both already produced a variety of different functional nanostructures and nanodevices. It is evident that the resultant architectures require detailed structural and functional characterization and that a variety of technical approaches must be employed to promote the development of the emerging fields. Small-angle X-ray and neutron scattering (SAS) are structural characterization techniques that are well placed to determine the conformation of nucleic acid nanoparticles (NANPs) under varying solution conditions, thus allowing for the optimization of their design. SAS experiments provide information on the overall shapes and particle dimensions of macromolecules and are ideal for following conformational changes of the molecular ensemble as it behaves in solution. In addition, the inherent differences in the neutron scattering of nucleic acids, lipids, and proteins, as well as the different neutron scattering properties of the isotopes of hydrogen, combined with the ability to uniformly label biological macromolecules with deuterium, allow one to characterize the conformations and relative dispositions of the individual components within an assembly of biomolecules. This article will review the application of SAS methods and provide a summary of their successful utilization in the emerging field of NANP technology to date, as well as share our vision on its use in complementing a broad suite of structural characterization tools with some simulated results that have never been shared before.

Integrative Structure Modeling: Overview and Assessment

Integrative structure modeling computationally combines data from multiple sources of information with the aim of obtaining structural insights that are not revealed by any single approach alone. In the first part of this review, we survey the commonly used sources of structural information and the computational aspects of model building. Throughout the past decade, integrative modeling was applied to various biological systems, with a focus on large protein complexes. Recent progress in the field of cryo-electron microscopy (cryo-EM) has resolved many of these complexes to near-atomic resolution. In the second part of this review, we compare a range of published integrative models with their higher-resolution counterparts with the aim of critically assessing their accuracy. This comparison gives a favorable view of integrative modeling and demonstrates its ability to yield accurate and informative results. We discuss possible roles of integrative modeling in the new era of cryo-EM and highlight future challenges and directions.

Bayesian inference of protein conformational ensembles from limited structural data

Many proteins consist of folded domains connected by regions with higher flexibility. The details of the resulting conformational ensemble play a central role in controlling interactions between domains and with binding partners. Small-Angle Scattering (SAS) is well-suited to study the conformational states adopted by proteins in solution. However, analysis is complicated by the limited information content in SAS data and care must be taken to avoid constructing overly complex ensemble models and fitting to noise in the experimental data. To address these challenges, we developed a method based on Bayesian statistics that infers conformational ensembles from a structural library generated by all-atom Monte Carlo simulations. The first stage of the method involves a fast model selection based on variational Bayesian inference that maximizes the model evidence of the selected ensemble. This is followed by a complete Bayesian inference of population weights in the selected ensemble. Experiments with simulated ensembles demonstrate that model evidence is capable of identifying the correct ensemble and that correct number of ensemble members can be recovered up to high level of noise. Using experimental data, we demonstrate how the method can be extended to include data from Nuclear Magnetic Resonance (NMR) and structural energies of conformers extracted from the all-atom energy functions. We show that the data from SAXS, NMR chemical shifts and energies calculated from conformers can work synergistically to improve the definition of the conformational ensemble.

The role of small-angle scattering in structure-based screening applications

In many biomolecular interactions, changes in the assembly states and structural conformations of participants can act as a complementary reporter of binding to functional and thermodynamic assays. This structural information is captured by a number of structural biology and biophysical techniques that are viable either as primary screens in small-scale applications or as secondary screens to complement higher throughput methods. In particular, small-angle X-ray scattering (SAXS) reports the average distance distribution between all atoms after orientational averaging. Such information is important when for example investigating conformational changes involved in inhibitory and regulatory mechanisms where binding events do not necessarily cause functional changes. Thus, we summarise here the current and prospective capabilities of SAXS-based screening in the context of other methods that yield structural information. Broad guidelines are also provided to assist readers in preparing screening protocols that are tailored to available X-ray sources.

α-Catenin Structure and Nanoscale Dynamics in Solution and in Complex with F-Actin

As a core component of the adherens junction, α-catenin stabilizes the cadherin/catenin complexes to the actin cytoskeleton for the mechanical coupling of cell-cell adhesion. α-catenin also modulates actin dynamics, cell polarity, and cell-migration functions that are independent of the adherens junction. We have determined the solution structures of the α-catenin monomer and dimer using in-line size-exclusion chromatography small-angle X-ray scattering, as well as the structure of α-catenin dimer in complex to F-actin filament using selective deuteration and contrast-matching small angle neutron scattering. We further present the first observation, to our knowledge, of the nanoscale dynamics of α-catenin by neutron spin-echo spectroscopy, which explicitly reveals the mobile regions of α-catenin that are crucial for binding to F-actin. In solution, the α-catenin monomer is more expanded than either protomer shown in the crystal structure dimer, with the vinculin-binding M fragment and the actin-binding domain being able to adopt different configurations. The α-catenin dimer in solution is also significantly more expanded than the dimer crystal structure, with fewer interdomain and intersubunit contacts than the crystal structure. When in complex to F-actin, the α-catenin dimer has an even more open and extended conformation than in solution, with the actin-binding domain further separated from the main body of the dimer. The α-catenin-assembled F-actin bundle develops into an ordered filament packing arrangement at increasing α-catenin/F-actin molar ratios. Together, the structural and dynamic studies reveal that α-catenin possesses dynamic molecular conformations that prime this protein to function as a mechanosensor protein.

Sample and Buffer Preparation for SAXS

In this book chapter, a practical approach for conducting small angle X-ray scattering (SAXS) experiments is given. Our aim is to guide SAXS users through a three-step process of planning, preparing and performing a basic SAXS measurement. The minimal requirements necessary to prepare samples are described specifically for protein and other macromolecular samples in solution. We address the very important aspects in terms of sample characterization using additional techniques as well as the essential role of accurately subtracting background scattering contributions. At the end of the chapter some advice is given for trouble-shooting problems that may occur during the course of the SAXS measurements. Automated pipelines for data processing are described which are useful in allowing users to evaluate the quality of the data 'on the spot' and consequently react to events such as radiation damage, the presence of unwanted sample aggregates or miss-matched buffers.

An optimized SEC-SAXS system enabling high X-ray dose for rapid SAXS assessment with correlated UV measurements for biomolecular structure analysis

A new optimized size exclusion chromatography small-angle X-ray scattering (SEC-SAXS) system for biomolecular SAXS at the Australian Synchrotron SAXS/WAXS beamline has been developed. The compact configuration reduces sample dilution to maximize sensitivity. Coflow sample presentation allows an 11-fold increase in flux on sample without capillary fouling, improving throughput and data quality, which are now primarily limited by the full flux available on the beamline. Multi-wavelength fibre optic UV analysis in close proximity to the X-ray beam allows for accurate concentration determination for samples with known UV extinction coefficients and thus estimation of the molecular weight of the scattering particle from the forward X-ray scattering intensity. Fast-flow low-volume SEC columns provide sample throughput competitive with batch concentration series measurements, albeit with a concomitant reduction of potential resolution relative to lower flow rates and larger SEC columns. The performance of the system is demonstrated using a set of model proteins, and its utility to solve various challenges is illustrated with a diverse suite of protein samples. These developments increase the quality and rigor of SEC-SAXS analysis and open new avenues for biomolecular solution SEC-SAXS studies that have been challenged by low sample yields, temporal instability, radiation sensitivity and complex mixtures.

Quantifying the influence of the ion cloud on SAXS profiles of charged proteins

MD simulations and Poisson–Boltzmann calculations predict ion cloud effects on SAXS experiments.

Small Angle Scattering and Structural Biology: Data Quality and Model Validation

This chapter provides a brief review of the current state-of-the-art in small-angle scattering (SAS) from biomolecules in solution in regard to: (1) sample preparation and instrumentation, (2) data reduction and analysis, and (3) three-dimensional structural modelling and validation. In this context, areas of ongoing research in regard to the interpretation of SAS data will be discussed with a particular focus on structural modelling using computational methods and data from different experimental techniques, including SAS (hybrid methods). Finally, progress made in establishing community accepted publication guidelines and a standard reporting framework that includes SAS data deposition in a public data bank will be described. Importantly, SAS data with associated meta-data can now be held in a format that supports exchange between data archives and seamless interoperability with the world-wide Protein Data Bank (wwPDB). Biomolecular SAS is thus well positioned to contribute to an envisioned federation of data archives in support of hybrid structural biology.

Solution scattering approaches to dynamical ordering in biomolecular systems

Clarification of solution structure and its modulation in proteins and protein complexes is crucially important to understand dynamical ordering in macromolecular systems. Small-angle x-ray scattering (SAXS) and small-angle neutron scattering (SANS) are among the most powerful techniques to derive structural information. Recent progress in sample preparation, instruments and software analysis is opening up a new era for small-angle scattering. In this review, recent progress and trends of SAXS and SANS are introduced from the point of view of instrumentation and analysis, touching on general features and standard methods of small-angle scattering. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato.

Integrative modelling of cellular assemblies

A wide variety of experimental techniques can be used for understanding the precise molecular mechanisms underlying the activities of cellular assemblies. The inherent limitations of a single experimental technique often requires integration of data from complementary approaches to gain sufficient insights into the assembly structure and function. Here, we review popular computational approaches for integrative modelling of cellular assemblies, including protein complexes and genomic assemblies. We provide recent examples of integrative models generated for such assemblies by different experimental techniques, especially including data from 3D electron microscopy (3D-EM) and chromosome conformation capture experiments, respectively. We highlight general concepts in integrative modelling and discuss the need for careful formulation and merging of different types of information.

Structural studies of Neurospora crassa LPMO9D and redox partner CDHIIA using neutron crystallography and small-angle scattering

Sensitivity to hydrogen/deuterium and lack of observable radiation damage makes cold neutrons an ideal probe the structural studies of proteins with highly photosensitive groups such as the copper center of lytic polysaccharide monooxygenases (LPMOs) and flavin adenine dinucleotide (FAD) and heme redox cofactors of cellobiose dehydrogenases (CDHs). Here, neutron crystallography and small-angle neutron scattering are used to investigate Neurospora crassa LPMO9D (NcLPMO9D) and CDHIIA (NcCDHIIA), respectively. The presence of LPMO greatly enhances the efficiency of commercial glycoside hydrolase cocktails in the depolymerization of cellulose. LPMOs can receive electrons from CDHs to activate molecular dioxygen for the oxidation of cellulose resulting in chain cleavage and disruption of local crystallinity. Using neutron protein crystallography, the hydrogen/deuterium atoms of NcLPMO9D could be located throughout the structure. At the copper active site, the protonation states of the side chains of His1, His84, His157 and Tyr168, and the orientation of water molecules could be determined. Small-angle neutron scattering measurements provided low resolution models of NcCDHIIA with both the dehydrogenase and cytochrome domains in oxidized states that exhibited elongated conformations. This work demonstrates the suitability of neutron diffraction and scattering for characterizing enzymes critical to oxidative cellulose deconstruction.

Probing the Acid-Induced Packing Structure Changes of the Molten Globule Domains of a Protein near Equilibrium Unfolding

Using simultaneously scanning small-angle X-ray scattering (SAXS) and UV-vis absorption with integrated online size exclusion chromatography, supplemental with molecular dynamics simulations, we unveil the long-postulated global structure evolution of a model multidomain protein bovine serum albumin (BSA) during acid-induced unfolding. Our results differentiate three global packing structures of the three molten globule domains of BSA, forming three intermediates I₁, I₂, and E along the unfolding pathway. The I₁-I₂ transition, overlooked in all previous studies, involves mainly coordinated reorientations across interconnected molten globule subdomains, and the transition activates a critical pivot domain opening of the protein for entering into the E form, with an unexpectedly large unfolding free energy change of -9.5 kcal mol^-1, extracted based on the observed packing structural changes. The revealed local packing flexibility and rigidity of the molten globule domains in the E form elucidate how collective motions of the molten globule domains profoundly influence the folding-unfolding pathway of a multidomain protein.

Structural studies of RNA-protein complexes: A hybrid approach involving hydrodynamics, scattering, and computational methods

The diverse functional cellular roles played by ribonucleic acids (RNA) have emphasized the need to develop rapid and accurate methodologies to elucidate the relationship between the structure and function of RNA. Structural biology tools such as X-ray crystallography and Nuclear Magnetic Resonance are highly useful methods to obtain atomic-level resolution models of macromolecules. However, both methods have sample, time, and technical limitations that prevent their application to a number of macromolecules of interest. An emerging alternative to high-resolution structural techniques is to employ a hybrid approach that combines low-resolution shape information about macromolecules and their complexes from experimental hydrodynamic (e.g. analytical ultracentrifugation) and solution scattering measurements (e.g., solution X-ray or neutron scattering), with computational modeling to obtain atomic-level models. While promising, scattering methods rely on aggregation-free, monodispersed preparations and therefore the careful development of a quality control pipeline is fundamental to an unbiased and reliable structural determination. This review article describes hydrodynamic techniques that are highly valuable for homogeneity studies, scattering techniques useful to study the low-resolution shape, and strategies for computational modeling to obtain high-resolution 3D structural models of RNAs, proteins, and RNA-protein complexes.