Reconstruction of SAXS Profiles from Protein Structures

Structural basis for IL-33 recognition and its antagonism by the helminth effector protein HpARI2

IL-33 plays a significant role in inflammation, allergy, and host defence against parasitic helminths. The model gastrointestinal nematode Heligmosomoides polygyrus bakeri secretes the Alarmin Release Inhibitor HpARI2, an effector protein that suppresses protective immune responses and asthma in its host by inhibiting IL-33 signalling. Here we reveal the structure of HpARI2 bound to mouse IL-33. HpARI2 contains three CCP-like domains, and we show that it contacts IL-33 primarily through the second and third of these. A large loop which emerges from CCP3 directly contacts IL-33 and structural comparison shows that this overlaps with the binding site on IL-33 for its receptor, ST2, preventing formation of a signalling complex. Truncations of HpARI2 which lack the large loop from CCP3 are not able to block IL-33-mediated signalling in a cell-based assay and in an in vivo female mouse model of asthma. This shows that direct competition between HpARI2 and ST2 is responsible for suppression of IL-33-dependent responses.

Lipids and proteins: Insights into the dynamics of assembly, recognition, condensate formation. What is still missing?

Lipid membranes and proteins, which are part of us throughout our lives, have been studied for decades. However, every year, new discoveries show how little we know about them. In a reader-friendly manner for people not involved in the field, this paper tries to serve as a bridge between physicists and biologists and new young researchers diving into the field to show its relevance, pointing out just some of the plethora of lines of research yet to be unraveled. It illustrates how new ways, from experimental to theoretical approaches, are needed in order to understand the structures and interactions that take place in a single lipid, protein, or multicomponent system, as we are still only scratching the surface.

A Review of Natural Polysaccharides: Sources, Characteristics, Properties, Food, and Pharmaceutical Applications

Natural polysaccharides, which are described in this study, are some of the most extensively used biopolymers in food, pharmaceutical, and medical applications, because they are renewable and have a high level of biocompatibility and biodegradability. The fundamental understanding required to properly exploit polysaccharides potential in the biocomposite, nanoconjugate, and pharmaceutical industries depends on detailed research of these molecules. Polysaccharides are preferred over other polymers because of their biocompatibility, bioactivity, homogeneity, and bioadhesive properties. Natural polysaccharides have also been discovered to have excellent rheological and biomucoadhesive properties, which may be used to design and create a variety of useful and cost-effective drug delivery systems. Polysaccharide-based composites derived from natural sources have been widely exploited due to their multifunctional properties, particularly in drug delivery systems and biomedical applications. These materials have achieved global attention and are in great demand because to their biochemical properties, which mimic both human and animal cells. Although synthetic polymers account for a substantial amount of organic chemistry, natural polymers play a vital role in a range of industries, including biomedical, pharmaceutical, and construction. As a consequence, the current study will provide information on natural polymers, their biological uses, and food and pharmaceutical applications.

The solution structure of the unbound IgG Fc receptor CD64 resembles its crystal structure: Implications for function

FcγRI (CD64) is the only high-affinity Fcγ receptor found on monocytes, macrophages, eosinophils, neutrophils and dendritic cells. It binds immunoglobulin G (IgG) antibody-antigen complexes at its Fc region to trigger key immune responses. CD64 contains three immunoglobulin-fold extracellular domains (D1, D2 and D3) and a membrane-spanning region. Despite the importance of CD64, no solution structure for this is known to date. To investigate this, we used analytical ultracentrifugation, small-angle X-ray scattering, and atomistic modelling. Analytical ultracentrifugation revealed that CD64 was monomeric with a sedimentation coefficient s020,w of 2.53 S, together with some dimer. Small-angle X-ray scattering showed that its radius of gyration RG was 3.3-3.4 nm and increased at higher concentrations to indicate low dimerization. Monte Carlo modelling implemented in the SASSIE-web package generated 279,162 physically-realistic trial CD64 structures. From these, the scattering best-fit models at the lowest measured concentrations that minimised dimers revealed that the D1, D2 and D3 domains were structurally similar to those seen in three CD64 crystal structures, but showed previously unreported flexibility between D1, D2 and D3. Despite the limitations of the scattering data, the superimposition of the CD64 solution structures onto crystal structures of the IgG Fc-CD64 complex showed that the CD64 domains do not sterically clash with the IgG Fc region, i.e. the solution structure of CD64 was sufficiently compact to allow IgG to bind to its high-affinity Fcγ receptor. This improved understanding may result in novel approaches to inhibit CD64 function, and opens the way for the solution study of the full-length CD64-IgG complex.

Small-angle scattering techniques for peptide and peptide hybrid nanostructures and peptide-based biomaterials

The use of small-angle scattering (SAS) in the study of the self-assembly of peptides and peptide conjugates (lipopeptides, polymer-peptide conjugates and others) is reviewed, highlighting selected research that illustrates different methods and analysis techniques. Both small-angle x-ray scattering (SAXS) and small-angle neutron scattering (SANS) are considered along with examples that exploit their unique capabilities. For SAXS, this includes the ability to perform rapid measurements enabling high throughput or fast kinetic studies and measurements under dilute conditions. For SANS, contrast variation using H2O/D2O mixtures enables the study of peptides interacting with lipids and TR-SANS (time-resolved SANS) studies of exchange kinetics and/or peptide-induced structural changes. Examples are provided of studies measuring form factors of different self-assembled structures (micelles, fibrils, nanotapes, nanotubes etc) as well as structure factors from ordered phases (lyotropic mesophases), peptide gels and hybrid materials such as membranes formed by mixing peptides with polysaccharides or peptide/liposome mixtures. SAXS/WAXS (WAXS: wide-angle x-ray scattering) on peptides and peptide hybrids is also discussed, and the review concludes with a perspective on potential future directions for research in the field.

Investigation of Dielectric and Mechanical Properties of Pretreated Natural Sunn Hemp Fiber-Reinforced Composite in Correlation with Macromolecular Structure of the Fiber

The present study attempts to establish a correlation between the macromolecular parameters obtained from small angle X-ray scattering (SAXS) analysis of pretreated sunn hemp (Crotalaria juncea) fibers with the dielectric and mechanical properties of their composites. Sunn hemp fiber is pretreated chemically by dewaxing and alkalization methods and physically by microwave irradiation. The treatment effect is structurally investigated using a correlation function from SAXS data and correlated with the mechanical as well as electrical properties of composites. The macromolecular parameters are observed to be influenced by pretreatment methods. Macromolecular structural modifications are seen in dewaxed fiber (DSHC), fiber treated with 10% of alkali soaked for 6 h (10K6C), and fiber microwave irradiated with 800 watts for 6 min (800W6M), improving the mechanical as well as electric properties of the reinforced composites.

Evaluation of optimal monoenergetic images acquired by dual-energy CT in the diagnosis of T staging of thoracic esophageal cancer

OBJECTIVES

The purpose of our study was to objectively and subjectively assess optimal monoenergetic image (MEI (+)) characteristics from dual-energy CT (DECT) and the diagnostic performance for the T staging in patients with thoracic esophageal cancer (EC).

METHODS

In this retrospective study, patients with histopathologically confirmed EC who underwent DECT from September 2019 to December 2020 were enrolled. One standard polyenergetic image (PEI) and five MEI (+) were reconstructed. Two readers independently assessed the lesion conspicuity subjectively and calculated the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) of EC. Two readers independently assessed the T stage on the optimal MEI (+) and PEI subjectively. Multiple quantitative parameters were measured to assess the diagnostic performance to identify T1-2 from T3-4 in EC patients.

RESULTS

The study included 68 patients. Subjectively, primary tumor delineation received the highest ratings in MEI (+) _40 keV of the venous phase. Objectively, MEI (+) images showed significantly higher SNR compared with PEI (p < 0.05), peaking at MEI (+) _40 keV in the venous phase. CNR of tumor (MEI (+) _{40 keV -80 keV}) was all significantly higher than PEI in arterial and venous phases (p < 0.05), peaking at MEI (+) _40 keV in venous phases. The agreement between MEI (+) _40 keV and pathologic T categories was 81.63% (40/49). Rho values in venous phases had excellent diagnostic efficiency for identifying T1-2 from T3-4 (AUC = 0.84).

CONCLUSIONS

MEI (+) reconstructions at low keV in the venous phase improved the assessment of lesion conspicuity and also have great potential for preoperative assessment of T staging in patients with EC.

Combining Experimental Data and Computational Methods for the Non-Computer Specialist

Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretation of the results is often a very challenging task. While experimental and computational methods are often considered as two different and separate approaches, the power and utility of combining both is undeniable. The integration of the experimental data with computational techniques can assist and enrich the interpretation, providing new detailed molecular understanding of the systems. Here, we briefly describe the basic principles of how experimental data can be combined with computational methods to obtain insights into the molecular mechanism and expand the interpretation through the generation of detailed models.

Structural characterization of supramolecular hollow nanotubes with atomistic simulations and SAXS

Self-assembled nanostructures arise when building blocks spontaneously organize into ordered aggregates that exhibit different properties compared to the disorganized monomers. Here, we study an amphiphilic cyanine dye (C8S3) that is known to self-assemble into double-walled, hollow, nanotubes with interesting optical properties. The molecular packing of the dyes inside the nanotubes, however, remains elusive. To reveal the structural features of the C8S3 nanotubes, we performed atomistic Molecular Dynamics simulations of preformed bilayers and nanotubes. We find that different packing arrangements lead to stable structures, in which the tails of the C8S3 molecules are interdigitated. Our results are verified by SAXS experiments. Together our data provide a detailed structural characterization of the C8S3 nanotubes. Furthermore, our approach was able to resolve the ambiguity inherent from cryo-TEM measurements in calculating the wall thickness of similar systems. The insights obtained are expected to be generally useful for understanding and designing other supramolecular assemblies.

Molecular packing structure of fibrin fibers resolved by X-ray scattering and molecular modeling

Fibrin is the major extracellular component of blood clots and a proteinaceous hydrogel used as a versatile biomaterial. Fibrin forms branched networks built of laterally associated double-stranded protofibrils. This multiscale hierarchical structure is crucial for the extraordinary mechanical resilience of blood clots, yet the structural basis of clot mechanical properties remains largely unclear due, in part, to the unresolved molecular packing of fibrin fibers. Here the packing structure of fibrin fibers is quantitatively assessed by combining Small Angle X-ray Scattering (SAXS) measurements of fibrin reconstituted under a wide range of conditions with computational molecular modeling of fibrin protofibrils. The number, positions, and intensities of the Bragg peaks observed in the SAXS experiments were reproduced computationally based on the all-atom molecular structure of reconstructed fibrin protofibrils. Specifically, the model correctly predicts the intensities of the reflections of the 22.5 nm axial repeat, corresponding to the half-staggered longitudinal arrangement of fibrin molecules. In addition, the SAXS measurements showed that protofibrils within fibrin fibers have a partially ordered lateral arrangement with a characteristic transverse repeat distance of 13 nm, irrespective of the fiber thickness. These findings provide fundamental insights into the molecular structure of fibrin clots that underlies their biological and physical properties.

Integrating solvation shell structure in experimentally driven molecular dynamics using x-ray solution scattering data

In the past few decades, prediction of macromolecular structures beyond the native conformation has been aided by the development of molecular dynamics (MD) protocols aimed at exploration of the energetic landscape of proteins. Yet, the computed structures do not always agree with experimental observables, calling for further development of the MD strategies to bring the computations and experiments closer together. Here, we report a scalable, efficient MD simulation approach that incorporates an x-ray solution scattering signal as a driving force for the conformational search of stable structural configurations outside of the native basin. We further demonstrate the importance of inclusion of the hydration layer effect for a precise description of the processes involving large changes in the solvent exposed area, such as unfolding. Utilization of the graphics processing unit allows for an efficient all-atom calculation of scattering patterns on-the-fly, even for large biomolecules, resulting in a speed-up of the calculation of the associated driving force. The utility of the methodology is demonstrated on two model protein systems, the structural transition of lysine-, arginine-, ornithine-binding protein and the folding of deca-alanine. We discuss how the present approach will aid in the interpretation of dynamical scattering experiments on protein folding and association.

Using Spectral Representation to Classify Proteins' Conformational States

Numerous proteins are molecular targets for drug action and hence are important in drug discovery. Structure-based computational drug discovery relies on detailed information regarding protein conformations for subsequent drug screening in silico. There are two key issues in analyzing protein conformations in virtual screening. The first considers the protein’s conformational change in response to physical and chemical conditions. The second is the protein’s atomic resolution reconstruction from X-ray crystallography or nuclear magnetic resonance (NMR) data. In this latter problem, information is needed regarding the sample’s position relative to the source of X-rays. Here, we introduce a new measure for classifying protein conformational states using spectral representation and Wigner’s D-functions. Predictions based on the new measure are in good agreement with conformational states of proteins. These results could also be applied to improve conformational alignment of the snapshots given by protein crystallography.

Evaluating Anti-CD32b F(ab) Conformation Using Molecular Dynamics and Small-Angle X-Ray Scattering

Complementary strategies of small-angle x-ray scattering (SAXS) and crystallographic analysis are often used to determine atomistic three-dimensional models of macromolecules and their variability in solution. This combination of techniques is particularly valuable when applied to macromolecular complexes to detect changes within the individual binding partners. Here, we determine the x-ray crystallographic structure of a F(ab) fragment in complex with CD32b, the only inhibitory Fc-γ receptor in humans, and compare the structure of the F(ab) from the crystal complex to SAXS data for the F(ab) alone in solution. We investigate changes in F(ab) structure by predicting theoretical scattering profiles for atomistic structures extracted from molecular dynamics (MD) simulations of the F(ab) and assessing the agreement of these structures to our experimental SAXS data. Through principal component analysis, we are able to extract principal motions observed during the MD trajectory and evaluate the influence of these motions on the agreement of structures to the F(ab) SAXS data. Changes in the F(ab) elbow angle were found to be important to reach agreement with the experimental data; however, further discrepancies were apparent between our F(ab) structure from the crystal complex and SAXS data. By analyzing multiple MD structures observed in similar regions of the principal component analysis, we were able to pinpoint these discrepancies to a specific loop region in the F(ab) heavy chain. This method, therefore, not only allows determination of global changes but also allows identification of localized motions important for determining the agreement between atomistic structures and SAXS data. In this particular case, the findings allowed us to discount the hypothesis that structural changes were induced upon complex formation, a significant find informing the drug development process. The methodology described here is generally applicable to deconvolute global and local changes of macromolecular structures and is well suited to other systems.

Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments

In bionanotechnology, the field of creating functional materials consisting of bio-inspired molecules, the function and shape of a nanostructure only appear through the assembly of many small molecules together. The large number of building blocks required to define a nanostructure combined with the many degrees of freedom in packing small molecules has long precluded molecular simulations, but recent advances in computational hardware as well as software have made classical simulations available to this strongly expanding field. Here, we review the state of the art in simulations of self-assembling bio-inspired supramolecular systems. We will first discuss progress in force fields, simulation protocols and enhanced sampling techniques using recent examples. Secondly, we will focus on efforts to enable the comparison of experimentally accessible observables and computational results. Experimental quantities that can be measured by microscopy, spectroscopy and scattering can be linked to simulation output either directly or indirectly, via quantum mechanical or semi-empirical techniques. Overall, we aim to provide an overview of the various computational approaches to understand not only the molecular architecture of nanostructures, but also the mechanism of their formation.

On the Calculation of SAXS Profiles of Folded and Intrinsically Disordered Proteins from Computer Simulations

Solution techniques such as small-angle X-ray scattering (SAXS) play a central role in structural studies of intrinsically disordered proteins (IDPs); yet, due to low resolution, it is generally necessary to combine SAXS with additional experimental sources of data and to use molecular simulations. Computational methods for the calculation of theoretical SAXS intensity profiles can be separated into two groups, depending on whether the solvent is modeled implicitly as continuous electron density or considered explicitly. The former offers reduced computational cost but requires the definition of a number of free parameters to account for, for example, the excess density of the solvation layer. Overfitting can thus be an issue, particularly when the structural ensemble is unknown. Here, we investigate and show how small variations of the contrast of the hydration shell, δρ, severely affect the outcome, analysis and interpretation of computed SAXS profiles for folded and disordered proteins. For both the folded and disordered proteins studied here, using a default δρ may, in some cases, result in the calculation of non-representative SAXS profiles, leading to an overestimation of their size and a misinterpretation of their structural nature. The solvation layer of the different IDP simulations also impacts their size estimates differently, depending on the protein force field used. The same is not true for the folded protein simulations, suggesting differences in the solvation of the two classes of proteins, and indicating that different force fields optimized for IDPs may cause expansion of the polypeptide chain through different physical mechanisms.

Eye patches: Protein assembly of index-gradient squid lenses

A parabolic relationship between lens radius and refractive index allows spherical lenses to avoid spherical aberration. We show that in squid, patchy colloidal physics resulted from an evolutionary radiation of globular S-crystallin proteins. Small-angle x-ray scattering experiments on lens tissue show colloidal gels of S-crystallins at all radial positions. Sparse lens materials form via low-valence linkages between disordered loops protruding from the protein surface. The loops are polydisperse and bind via a set of hydrogen bonds between disordered side chains. Peripheral lens regions with low particle valence form stable, volume-spanning gels at low density, whereas central regions with higher average valence gel at higher densities. The proteins demonstrate an evolved set of linkers for self-assembly of nanoparticles into volumetric materials.

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.

Calculation of two-dimensional scattering patterns for oriented systems

A versatile procedure to calculate two-dimensional scattering patterns of oriented systems is presented. The systems are represented by a set of dummy atoms with different scattering length densities, which allows the construction of very complex shapes either for single particles or for sets of particles. By the use of oriented pair distance distribution functions it is possible to perform a fast calculation of the scattering intensity from the oriented system in a given direction in the scattering vector (q) space and generate the two-dimensional scattering pattern on a givenqplane. Several examples of the calculations are presented, demonstrating the method and its applicability. The presented results open new possibilities for the analysis of scattering patters obtained from oriented systems.

100 years of Debye's scattering equation

Debye's scattering equation (DSE) has spanned a century of scientific development, from the dawn of quantum mechanics and the investigation of the structure of atoms and molecules to the era of nanotechnology, paving the way tototal scatteringmethods. The formulation offers the most accurate representation of the intensity scattered by randomly oriented atomic aggregates, constructed by superimposing the signal from each atomic distance in the molecule. The present paper reviews some of the milestone applications, from the interpretation of the intensity curves from gases and vapours, to aggregates of increasing size and more extended order. Important developments, aimed at mitigating the prohibitive computational complexity of the DSE, and state-of-the-art methods for the characterization of static and dynamic displacements are also discussed.

A new definition and properties of the similarity value between two protein structures

Knowledge regarding the 3D structure of a protein provides useful information about the protein's functional properties. Particularly, structural similarity between proteins can be used as a good predictor of functional similarity. One method that uses the 3D geometrical structure of proteins in order to compare them is the similarity value (SV). In this paper, we introduce a new definition of the SV measure for comparing two proteins. To this end, we consider the mass of the protein's atoms and concentrate on the number of protein's atoms to be compared. This defines a new measure, called the weighted similarity value (WSV), adding physical properties to geometrical properties. We also show that our results are in good agreement with the results obtained by TM-SCORE and DALILITE. WSV can be of use in protein classification and in drug discovery.

BCL::SAXS: GPU accelerated Debye method for computation of small angle X-ray scattering profiles

Small angle X-ray scattering (SAXS) is an experimental technique used for structural characterization of macromolecules in solution. Here, we introduce BCL::SAXS--an algorithm designed to replicate SAXS profiles from rigid protein models at different levels of detail. We first show our derivation of BCL::SAXS and compare our results with the experimental scattering profile of hen egg white lysozyme. Using this protein we show how to generate SAXS profiles representing: (1) complete models, (2) models with approximated side chain coordinates, and (3) models with approximated side chain and loop region coordinates. We evaluated the ability of SAXS profiles to identify a correct protein topology from a non-redundant benchmark set of proteins. We find that complete SAXS profiles can be used to identify the correct protein by receiver operating characteristic (ROC) analysis with an area under the curve (AUC) > 99%. We show how our approximation of loop coordinates between secondary structure elements improves protein recognition by SAχS for protein models without loop regions and side chains. Agreement with SAXS data is a necessary but not sufficient condition for structure determination. We conclude that experimental SAXS data can be used as a filter to exclude protein models with large structural differences from the native.

Ab initio RNA folding

RNA molecules are essential cellular machines performing a wide variety of functions for which a specific three-dimensional structure is required. Over the last several years, the experimental determination of RNA structures through x-ray crystallography and NMR seems to have reached a plateau in the number of structures resolved each year, but as more and more RNA sequences are being discovered, the need for structure prediction tools to complement experimental data is strong. Theoretical approaches to RNA folding have been developed since the late nineties, when the first algorithms for secondary structure prediction appeared. Over the last 10 years a number of prediction methods for 3D structures have been developed, first based on bioinformatics and data-mining, and more recently based on a coarse-grained physical representation of the systems. In this review we are going to present the challenges of RNA structure prediction and the main ideas behind bioinformatic approaches and physics-based approaches. We will focus on the description of the more recent physics-based phenomenological models and on how they are built to include the specificity of the interactions of RNA bases, whose role is critical in folding. Through examples from different models, we will point out the strengths of physics-based approaches, which are able not only to predict equilibrium structures, but also to investigate dynamical and thermodynamical behavior, and the open challenges to include more key interactions ruling RNA folding.

WAXSiS: a web server for the calculation of SAXS/WAXS curves based on explicit-solvent molecular dynamics

Small- and wide-angle X-ray scattering (SWAXS) has evolved into a powerful tool to study biological macromolecules in solution. The interpretation of SWAXS curves requires their accurate predictions from structural models. Such predictions are complicated by scattering contributions from the hydration layer and by effects from thermal fluctuations. Here, we describe the new web server WAXSiS (WAXS in solvent) that computes SWAXS curves based on explicit-solvent all-atom molecular dynamics (MD) simulations (http://waxsis.uni-goettingen.de/). The MD simulations provide a realistic model for both the hydration layer and the excluded solvent, thereby avoiding any solvent-related fitting parameters, while naturally accounting for thermal fluctuations.

Investigating increasingly complex macromolecular systems with small-angle X-ray scattering

The biological solution small-angle X-ray scattering (BioSAXS) field has undergone tremendous development over recent decades. This means that increasingly complex biological questions can be addressed by the method. An intricate synergy between advances in hardware and software development, data collection and evaluation strategies and implementations that readily allow integration with complementary techniques result in significant results and a rapidly growing user community with ever increasing ambitions. Here, a review of these developments, by including a selection of novel BioSAXS method-ologies and recent results, is given.