Interpreting solution X-ray scattering data using molecular simulations

Perspectives on solution-based small angle X-ray scattering for protein and biological macromolecule structural biology

Small-angle X-ray scattering (SAXS) is used to extract structural information from a wide variety of non-crystalline samples in different fields (e.g., materials science, physics, chemistry, and biology). This review provides an overview of SAXS as applied to structural biology, specifically for proteins and other biomacromolecules in solution with an emphasis on extracting key structural parameters and the interpretation of SAXS data using a diverse array of techniques. These techniques cover aspects of building and assessing models to describe data measured from monodispersed and ideal dilute samples through to more complicated structurally polydisperse systems. Ab initio modelling, rigid body modelling as well as normal-mode analysis, molecular dynamics, mixed component and structural ensemble modelling are discussed. Dealing with polydispersity both physically in terms of component separation as well as approaching the analysis and modelling of data of mixtures and evolving systems are described, including methods for data decomposition such as single value decomposition/principle component analysis and evolving factor analysis. This review aims to highlight that solution SAXS, with the cohort of developments in data analysis and modelling, is well positioned to build upon the traditional 'single particle view' foundation of structural biology to take the field into new areas for interpreting the structures of proteins and biomacromolecules as population-states and dynamic structural systems.

Binding structures of SERF1a with NT17-polyQ peptides of huntingtin exon 1 revealed by SEC-SWAXS, NMR and molecular simulation

The aberrant fibrillization of huntingtin exon 1 (Httex1) characterized by an expanded polyglutamine (polyQ) tract is a defining feature of Huntington's disease, a neurodegenerative disorder. Recent investigations underscore the involvement of a small EDRK-rich factor 1a (SERF1a) in promoting Httex1 fibrillization through interactions with its N terminus. By establishing an integrated approach with size-exclusion-column-based small- and wide-angle X-ray scattering (SEC-SWAXS), NMR, and molecular simulations using Rosetta, the analysis here reveals a tight binding of two NT17 fragments of Httex1 (comprising the initial 17 amino acids at the N terminus) to the N-terminal region of SERF1a. In contrast, examination of the complex structure of SERF1a with a coiled NT17-polyQ peptide (33 amino acids in total) indicates sparse contacts of the NT17 and polyQ segments with the N-terminal side of SERF1a. Furthermore, the integrated SEC-SWAXS and molecular-simulation analysis suggests that the coiled NT17 segment can transform into a helical conformation when associated with a polyQ segment exhibiting high helical content. Intriguingly, NT17-polyQ peptides with enhanced secondary structures display diminished interactions with SERF1a. This insight into the conformation-dependent binding of NT17 provides clues to a catalytic association mechanism underlying SERF1a's facilitation of Httext1 fibrillization.

Scattering approaches to unravel protein solution behaviors in ionic liquids and deep eutectic solvents: From basic principles to recent developments

Proteins in ionic liquids (ILs) and deep eutectic solvents (DESs) have gained significant attention due to their potential applications in various fields, including biocatalysis, bioseparation, biomolecular delivery, and structural biology. Scattering approaches including dynamic light scattering (DLS) and small-angle X-ray and neutron scattering (SAXS and SANS) have been used to understand the solution behavior of proteins at the nanoscale and microscale. This review provides a thorough exploration of the application of these scattering techniques to elucidate protein properties in ILs and DESs. Specifically, the review begins with the theoretical foundations of the relevant scattering approaches and describes the essential solvent properties of ILs and DESs linked to scattering such as refractive index, scattering length density, ion-pairs, liquid nanostructure, solvent aggregation, and specific ion effects. Next, a detailed introduction is provided on protein properties such as type, concentration, size, flexibility and structure as observed through scattering methodologies. This is followed by a review of the literature on the use of scattering for proteins in ILs and DESs. It is highlighted that enhanced data analysis and modeling tools are necessary for assessing protein flexibility and structure, and for understanding protein hydration, aggregation and specific ion effects. It is also noted that complementary approaches are recommended for comprehensively understanding the behavior of proteins in solution due to the complex interplay of factors, including ion-binding, dynamic hydration, intermolecular interactions, and specific ion effects. Finally, the challenges and potential research directions for this field are proposed, including experimental design, data analysis approaches, and supporting methods to obtain fundamental understandings of complex protein behavior and protein systems in solution. We envisage that this review will support further studies of protein interface science, and in particular studies on solvent and ion effects on proteins.

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

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

Small angle X-ray scattering analysis of thermophilic cytochrome P450 CYP119 and the effects of the N-terminal histidine tag

Combining size exclusion chromatography-small angle X-ray scattering (SEC-SAXS) and molecular dynamics (MD) analysis is a promising approach to investigate protein behavior in solution, particularly for understanding conformational changes due to substrate binding in cytochrome P450s (CYPs). This study investigates conformational changes in CYP119, a thermophilic CYP from Sulfolobus acidocaldarius that exhibits structural flexibility similar to mammalian CYPs. Although the crystal structure of ligand-free (open state) and ligand-bound (closed state) forms of CYP119 is known, the overall structure of the enzyme in solution has not been explored until now. It was found that theoretical scattering profiles from the crystal structures of CYP119 did not align with the SAXS data, but conformers from MD simulations, particularly starting from the open state (46 % of all frames), agreed well. Interestingly, a small percentage of closed-state conformers also fit the data (9 %), suggesting ligand-free CYP119 samples ligand-bound conformations. Ab initio SAXS models for N-His tagged CYP119 revealed a tail-like unfolded structure impacting protein flexibility, which was confirmed by in silico modeling. SEC-SAXS analysis of N-His CYP119 indicated pentameric structures in addition to monomers in solution, affecting the stability and activity of the enzyme. This study adds insights into the conformational dynamics of CYP119 in solution.

Atomistic ensemble of active SHP2 phosphatase

SHP2 phosphatase plays an important role in regulating several intracellular signaling pathways. Pathogenic mutations of SHP2 cause developmental disorders and are linked to hematological malignancies and cancer. SHP2 comprises two tandemly-arranged SH2 domains, a catalytic PTP domain, and a disordered C-terminal tail. Under physiological, non-stimulating conditions, the catalytic site of PTP is occluded by the N-SH2 domain, so that the basal activity of SHP2 is low. Whereas the autoinhibited structure of SHP2 has been known for two decades, its active, open structure still represents a conundrum. Since the oncogenic mutant SHP2E76K almost completely populates the active, open state, this mutant has been extensively studied as a model for activated SHP2. By molecular dynamics simulations and accurate explicit-solvent SAXS curve predictions, we present the heterogeneous atomistic ensemble of constitutively active SHP2E76K in solution, encompassing a set of conformational arrangements and radii of gyration in agreement with experimental SAXS data.

Scrutinizing the protein hydration shell from molecular dynamics simulations against consensus small-angle scattering data

Biological macromolecules in solution are surrounded by a hydration shell, whose structure differs from the structure of bulk solvent. While the importance of the hydration shell for numerous biological functions is widely acknowledged, it remains unknown how the hydration shell is regulated by macromolecular shape and surface composition, mainly because a quantitative probe of the hydration shell structure has been missing. We show that small-angle scattering in solution using X-rays (SAXS) or neutrons (SANS) provide a protein-specific probe of the protein hydration shell that enables quantitative comparison with molecular simulations. Using explicit-solvent SAXS/SANS predictions, we derived the effect of the hydration shell on the radii of gyration Rg of five proteins using 18 combinations of protein force field and water model. By comparing computed Rg values from SAXS relative to SANS in D2O with consensus SAXS/SANS data from a recent worldwide community effort, we found that several but not all force fields yield a hydration shell contrast in remarkable agreement with experiments. The hydration shell contrast captured by Rg values depends strongly on protein charge and geometric shape, thus providing a protein-specific footprint of protein-water interactions and a novel observable for scrutinizing atomistic hydration shell models against experimental data.

Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations

Small-angle X-ray and neutron scattering (SAXS/SANS) provide valuable insights into the structure and dynamics of biomolecules in solution, complementing a wide range of structural techniques, including molecular dynamics simulations. As contrast-based methods, they are sensitive not only to structural properties but also to solvent-solute interactions. Their use in molecular dynamics simulations requires a forward model that should be as fast and accurate as possible. In this work, we demonstrate the feasibility of calculating SAXS and SANS intensities using a coarse-grained representation consisting of one bead per amino acid and three beads per nucleic acid, with form factors that can be corrected on the fly to account for solvation effects at no additional computational cost. By coupling this forward model with molecular dynamics simulations restrained with SAS data, it is possible to determine conformational ensembles or refine the structure and dynamics of proteins and nucleic acids in agreement with the experimental results. To assess the robustness of this approach, we applied it to gelsolin, for which we acquired SAXS data on its closed state, and to a UP1-microRNA complex, for which we used previously collected measurements. Our hybrid-resolution small-angle scattering (hySAS) implementation, being distributed in PLUMED, can be used with atomistic and coarse-grained simulations using diverse restraining strategies.

Molecular dynamics of JUNO-IZUMO1 complexation suggests biologically relevant mechanisms in fertilization

JUNO-IZUMO1 binding is the first known physical link created between the sperm and egg membranes in fertilization, however, how this initiates sperm-egg fusion remains elusive. As advanced structural insights will help to combat the infertility crisis, or advance fertility control, we employed all-atom Molecular Dynamics (MD) to derive dynamic structural insights that are difficult to obtain experimentally. We found that the hydrated JUNO-IZUMO1 interface is composed of a large set of short-lived non-covalent interactions. The contact interface is destabilized by strategically located point mutations, as well as by Zn2+ ions, which shift IZUMO1 into the non-binding "boomerang" conformation. We hypothesize that the latter might explain how the transient zinc spark, as released after sperm entry into the oocyte, might contribute to block polyspermy. To address a second mystery, we performed another set of simulations, as it was previously suggested that JUNO in solution is unable to bind to folate despite it belonging to the folate receptor family. MD now suggests that JUNO complexation with IZUMO1 opens up the binding pocket thereby enabling folate insertion. Our MD simulations thus provide crucial new hypotheses how the dynamics of the JUNO-IZUMO1 complex upon solvation might regulate fertility.

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.

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.

Structure and ensemble refinement against SAXS data: Combining MD simulations with Bayesian inference or with the maximum entropy principle

Small-angle X-ray scattering (SAXS) is a powerful method for tracking conformational transitions of proteins or soft-matter complexes in solution. However, the interpretation of the experimental data is challenged by the low spatial resolution and the low information content of the data, which lead to a high risk of overinterpreting the data. Here, we illustrate how SAXS data can be integrated into all-atom molecular dynamics (MD) simulation to derive atomic structures or heterogeneous ensembles that are compatible with the data. Besides providing atomistic insight, the MD simulation adds physicochemical information, as encoded in the MD force fields, which greatly reduces the risk of overinterpretation. We present an introduction into the theory of SAXS-driven MD simulations as implemented in GROMACS-SWAXS, a modified version of the GROMACS simulation software. We discuss SAXS-driven parallel-replica ensemble refinement with commitment to the maximum entropy principle as well as a Bayesian formulation of SAXS-driven structure refinement. Practical considerations for running and interpreting the simulations are presented. The methods are freely available via GitLab at https://gitlab.com/cbjh/gromacs-swaxs.

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.

Extracting structural insights from soft X-ray scattering of biological assemblies

Resonant soft X-ray scattering (RSoXS), a technique that combines X-ray absorption spectroscopy and X-ray scattering, can probe the nano- and meso-scale structure of biological assemblies with chemical specificity. RSoXS experiments yield scattering data collected at several photon energies, for example across an elemental absorption edge of interest. Collecting a near-edge X-ray absorption fine structure (NEXAFS) spectrum complements RSoXS experiments and determines X-ray energies that are best suited for RSoXS measurements. The analysis of RSoXS data is similar in many ways to analysis of small angle X-ray scattering using hard X-rays, with an added dimension that includes an X-ray energy dependence. This chapter discusses procedures for predicting scattering contrast and thereby identifying energies suitable for RSoXS measurements using NEXAFS spectra, analyses of 2D RSoXS images through integration into 1D profiles, and strategies for elucidating the origin of RSoXS scattering features. It also discusses existing and potential methods for interpretation of RSoXS data to gain detailed structural insights into biological systems.

Solution Structural Studies of Pre-amyloid Oligomer States of the Biofilm Protein Aap

Staphylococcus epidermidis is a commensal bacterium on human skin that is also the leading cause of medical device-related infections. The accumulation-associated protein (Aap) from S. epidermidis is a critical factor for infection via its ability to mediate biofilm formation. The B-repeat superdomain of Aap is composed of 5 to 17 Zn2+-binding B-repeats, which undergo rapid, reversible assembly to form dimer and tetramer species. The tetramer can then undergo a conformational change and nucleate highly stable functional amyloid fibrils. In this study, multiple techniques including analytical ultracentrifugation (AUC) and small-angle X-ray scattering (SAXS) are used to probe a panel of B-repeat mutant constructs that assemble to distinct oligomeric states to define the structural characteristics of B-repeat dimer and tetramer species. The B-repeat region from Aap forms an extremely elongated conformation that presents several challenges for standard SAXS analyses. Specialized approaches, such as cross-sectional analyses, allowed for in-depth interpretation of data, while explicit-solvent calculations via WAXSiS allowed for accurate evaluation of atomistic models. The resulting models suggest mechanisms by which Aap functional amyloid fibrils form, illuminating an important contributing factor to recurrent staphylococcal infections.

Structural interpretations of a flexible cold-active AMS8 lipase by combining small-angle X-ray scattering and molecular dynamics simulation (SAXS-MD)

Determining structure of highly flexible protein with multiple conformations can be challenging. This paper aims to combine molecular dynamics (MD) and small angle X-ray diffraction (SAX) techniques as a solution to overcome issues related to protein conformation in hardly crystallized protein. Based on prior studies, a cold-active lipase AMS8 was simulated in solvents showing stability in its N-terminal and high flexibility in its C-terminal. However, MD in its own algorithm could not explain the basis of macromolecule conformational transitions or changes related to protein through folding. Hence, by combining SAXS with MD, it is possible to understand the structure of flexible AMS8 lipase in natural space. Based on the findings, SAXS ab-initio model of AMS8 lipase was identified as a monomeric protein in which the optimized model of cold-active lipase AMS8 derived from SAXS data was found to be aligned with AMS8 homology model under series of MD timeframe.

SAXS-guided unbiased coarse-grained Monte Carlo simulation for identification of self-assembly nanostructures and dimensions

Recent studies have shown that solvated amphiphiles can form nanostructured self-assemblies called dynamic binary complexes (DBCs) in the presence of ions. Since the nanostructures of DBCs are directly related to their viscoelastic properties, it is important to understand how the nanostructures change under different solution conditions. However, it is challenging to obtain a three-dimensional molecular description of these nanostructures by utilizing conventional experimental characterization techniques or thermodynamic models. To this end, we combined the structural data from small angle X-ray scattering (SAXS) experiments and thermodynamic knowledge from coarse-grained Monte Carlo (CGMC) simulations to identify the detailed three-dimensional nanostructure of DBCs. Specifically, unbiased CGMC simulations are performed with SAXS-guided initial conditions, which aids us to sample accurate nanostructures in a computationally efficient fashion. As a result, an elliptical bilayer nanostructure is obtained as the most probable nanostructure of DBCs whose dimensions are validated by scanning electron microscope (SEM) images. Then, utilizing the obtained molecular model of DBCs, we could also explain the pH tunability of the system. Overall, our results from SAXS-guided unbiased CGMC simulations highlight that using potential energy combined with SAXS data, we can distinguish otherwise degenerate nanostructures resulting from the inherent ambiguity of SAXS patterns.

Recent Advances in Understanding the Structures of Translesion Synthesis DNA Polymerases

DNA damage in the template strand causes replication forks to stall because replicative DNA polymerases are unable to efficiently incorporate nucleotides opposite template DNA lesions. To overcome these replication blocks, cells are equipped with multiple translesion synthesis polymerases that have evolved specifically to incorporate nucleotides opposite DNA lesions. Over the past two decades, X-ray crystallography has provided a wealth of information about the structures and mechanisms of translesion synthesis polymerases. This approach, however, has been limited to ground state structures of these polymerases bound to DNA and nucleotide substrates. Three recent methodological developments have extended our understanding of the structures and mechanisms of these polymerases. These include time-lapse X-ray crystallography, which allows one to identify novel reaction intermediates; full-ensemble hybrid methods, which allow one to examine the conformational flexibility of the intrinsically disordered regions of proteins; and cryo-electron microscopy, which allows one to determine the high-resolution structures of larger protein complexes. In this article, we will discuss how these three methodological developments have added to our understanding of the structures and mechanisms of translesion synthesis polymerases.

Exciton decay mechanism in DNA single strands: back-electron transfer and ultrafast base motions

The photochemistry of DNA systems is characterized by the ultraviolet (UV) absorption of π-stacked nucleobases, resulting in exciton states delocalized over several bases. As their relaxation sensitively depends on local stacking conformations, disentangling the ensuing electronic and structural dynamics has remained an experimental challenge, despite their fundamental role in protecting the genome from potentially harmful UV radiation. Here we use transient absorption and transient absorption anisotropy spectroscopy with broadband femtosecond deep-UV pulses (250–360 nm) to resolve the exciton dynamics of UV-excited adenosine single strands under physiological conditions. Due to the exceptional deep-UV bandwidth and polarization sensitivity of our experimental approach, we simultaneously resolve the population dynamics, charge-transfer (CT) character and conformational changes encoded in the UV transition dipoles of the π-stacked nucleotides. Whilst UV excitation forms fully charge-separated CT excitons in less than 0.3 ps, we find that most decay back to the ground state via a back-electron transfer. Based on the anisotropy measurements, we propose that this mechanism is accompanied by a structural relaxation of the photoexcited base-stack, involving an inter-base rotation of the nucleotides. Our results finally complete the exciton relaxation mechanism for adenosine single strands and offer a direct view into the coupling of electronic and structural dynamics in aggregated photochemical systems.

Despite its key role in DNA photochemistry, the decay mechanism of excitons in stacked bases has remained difficult to resolve. Ultrafast polarization spectroscopy now reveals a back-electron transfer and ultrafast base motions in adenosine strands.

A database of calculated solution parameters for the AlphaFold predicted protein structures

Recent spectacular advances by AI programs in 3D structure predictions from protein sequences have revolutionized the field in terms of accuracy and speed. The resulting “folding frenzy” has already produced predicted protein structure databases for the entire human and other organisms’ proteomes. However, rapidly ascertaining a predicted structure’s reliability based on measured properties in solution should be considered. Shape-sensitive hydrodynamic parameters such as the diffusion and sedimentation coefficients (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${D_{t(20,w)}^{0}}$$\end{document}Dt(20,w)0, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${s_{{\left( {{20},w} \right)}}^{{0}} }$$\end{document}s20,w0) and the intrinsic viscosity ([η]) can provide a rapid assessment of the overall structure likeliness, and SAXS would yield the structure-related pair-wise distance distribution function p(r) vs. r. Using the extensively validated UltraScan SOlution MOdeler (US-SOMO) suite, a database was implemented calculating from AlphaFold structures the corresponding \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${D_{t(20,w)}^{0}}$$\end{document}Dt(20,w)0, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${s_{{\left( {{20},w} \right)}}^{{0}} }$$\end{document}s20,w0, [η], p(r) vs. r, and other parameters. Circular dichroism spectra were computed using the SESCA program. Some of AlphaFold’s drawbacks were mitigated, such as generating whenever possible a protein’s mature form. Others, like the AlphaFold direct applicability to single-chain structures only, the absence of prosthetic groups, or flexibility issues, are discussed. Overall, this implementation of the US-SOMO-AF database should already aid in rapidly evaluating the consistency in solution of a relevant portion of AlphaFold predicted protein structures.

Performance of the new biological small- and wide-angle X-ray scattering beamline 13A at the Taiwan Photon Source

A new endstation for biological small- and wide-angle X-ray scattering is detailed, which provides development opportunities for studying correlated local and global structures of biomolecules in solution.

Recent developments in the instrumentation and data analysis of synchrotron small-angle X-ray scattering (SAXS) on biomolecules in solution have made biological SAXS (BioSAXS) a mature and popular tool in structural biology. This article reports on an advanced endstation developed at beamline 13A of the 3.0 GeV Taiwan Photon Source for biological small- and wide-angle X-ray scattering (SAXS–WAXS or SWAXS). The endstation features an in-vacuum SWAXS detection system comprising two mobile area detectors (Eiger X 9M/1M) and an online size-exclusion chromatography system incorporating several optical probes including a UV–Vis absorption spectrometer and refractometer. The instrumentation and automation allow simultaneous SAXS–WAXS data collection and data reduction for high-throughput biomolecular conformation and composition determinations. The performance of the endstation is illustrated with the SWAXS data collected for several model proteins in solution, covering a scattering vector magnitude q across three orders of magnitude. The crystal-model fittings to the data in the q range ∼0.005–2.0 Å⁻¹ indicate high similarity of the solution structures of the proteins to their crystalline forms, except for some subtle hydration-dependent local details. These results open up new horizons of SWAXS in studying correlated local and global structures of biomolecules in solution.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

Visualizing RNA Structures by SAXS-Driven MD Simulations

The biological role of biomolecules is intimately linked to their structural dynamics. Experimental or computational techniques alone are often insufficient to determine accurate structural ensembles in atomic detail. We use all-atom molecular dynamics (MD) simulations and couple it to small-angle X-ray scattering (SAXS) experiments to resolve the structural dynamics of RNA molecules. To accomplish this task, we utilize a set of re-weighting and biasing techniques tailored for RNA molecules. To showcase our approach, we study two RNA molecules: a riboswitch that shows structural variations upon ligand binding, and a two-way junction RNA that displays structural heterogeneity and sensitivity to salt conditions. Integration of MD simulations and experiments allows the accurate construction of conformational ensembles of RNA molecules. We observe a dynamic change of the SAM-I riboswitch conformations depending on its binding partners. The binding of SAM and Mg2+ cations stabilizes the compact state. The absence of Mg2+ or SAM leads to the loss of tertiary contacts, resulting in a dramatic expansion of the riboswitch conformations. The sensitivity of RNA structures to the ionic strength demonstrates itself in the helix junction helix (HJH). The HJH shows non-monotonic compaction as the ionic strength increases. The physics-based picture derived from the experimentally guided MD simulations allows biophysical characterization of RNA molecules. All in all, SAXS-guided MD simulations offer great prospects for studying RNA structural dynamics.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

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.

Refining conformational ensembles of flexible proteins against small-angle x-ray scattering data

Intrinsically disordered proteins and flexible regions in multidomain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modeling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model (i.e., an algorithm to calculate experimental observables from individual conformations or ensembles). In many cases, this involves one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle x-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data but across the entire ensemble. Here, we present a protocol to dissect the effect of the free parameters on the calculated SAXS intensities and to identify a reliable set of values. We have implemented this procedure in our Bayesian/maximum entropy framework for ensemble refinement and demonstrate the results on four intrinsically disordered proteins and a protein with three domains connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects and suggest that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins.

Time-resolved X-ray scattering studies of proteins

Time-resolved small- and wide-angle X-ray scattering studies of proteins in solution based on the pump-probe approach unveil structural information from intermediates over a broad range of length and time scales. In spite of the promise of this methodology, only a fraction of the wealth of information encoded in scattering data has been extracted in studies performed thus far. Here, we discuss the methodology, summarize results from recent time-resolved X-ray scattering studies, and examine the potential to extract additional information from these scattering curves.

Advanced Methods for the Characterization of Supramolecular Hydrogels

With the increased research on supramolecular hydrogels, many spectroscopic, diffraction, microscopic, and rheological techniques have been employed to better understand and characterize the material properties of these hydrogels. Specifically, spectroscopic methods are used to characterize the structure of supramolecular hydrogels on the atomic and molecular scales. Diffraction techniques rely on measurements of crystallinity and help in analyzing the structure of supramolecular hydrogels, whereas microscopy allows researchers to inspect these hydrogels at high resolution and acquire a deeper understanding of the morphology and structure of the materials. Furthermore, mechanical characterization is also important for the application of supramolecular hydrogels in different fields. This can be achieved through atomic force microscopy measurements where a probe interacts with the surface of the material. Additionally, rheological characterization can investigate the stiffness as well as the shear-thinning and self-healing properties of the hydrogels. Further, mechanical and surface characterization can be performed by micro-rheology, dynamic light scattering, and tribology methods, among others. In this review, we highlight state-of-the-art techniques for these different characterization methods, focusing on examples where they have been applied to supramolecular hydrogels, and we also provide future directions for research on the various strategies used to analyze this promising type of material.

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.

On the potential of machine learning to examine the relationship between sequence, structure, dynamics and function of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs-and intrinsically disordered regions (IDRs) interspersed between folded domains-are generally characterized as having no persistent tertiary structure; instead they interconvert between a large number of different and often expanded structures. IDPs and IDRs are involved in an enormously wide range of biological functions and reveal novel mechanisms of interactions, and while they defy the common structure-function paradigm of folded proteins, their structural preferences and dynamics are important for their function. We here discuss open questions in the field of IDPs and IDRs, focusing on areas where machine learning and other computational methods play a role. We discuss computational methods aimed to predict transiently formed local and long-range structure, including methods for integrative structural biology. We discuss the many different ways in which IDPs and IDRs can bind to other molecules, both via short linear motifs, as well as in the formation of larger dynamic complexes such as biomolecular condensates. We discuss how experiments are providing insight into such complexes and may enable more accurate predictions. Finally, we discuss the role of IDPs in disease and how new methods are needed to interpret the mechanistic effects of genomic variants in IDPs.

Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions

Molecular simulations are a powerful tool to complement and interpret ambiguous experimental data on biomolecules to obtain structural models. Such data-assisted simulations often rely on parameters, the choice of which is highly non-trivial and crucial to performance. The key challenge is weighting experimental information with respect to the underlying physical model. We introduce FLAPS, a self-adapting variant of dynamic particle swarm optimization, to overcome this parameter selection problem. FLAPS is suited for the optimization of composite objective functions that depend on both the optimization parameters and additional, a priori unknown weighting parameters, which substantially influence the search-space topology. These weighting parameters are learned at runtime, yielding a dynamically evolving and iteratively refined search-space topology. As a practical example, we show how FLAPS can be used to find functional parameters for small-angle X-ray scattering-guided protein simulations.

Small-angle X-ray scattering for the proteomics community: current overview and future potential

Introduction: Proteins are biological nanoparticles. For structural proteomics and hybrid structural biology, complementary methods are required that allow both high throughput and accurate automated data analysis. Small-angle X-ray scattering (SAXS) is a method for observing the size and shape of particles, such as proteins and complexes, in solution. SAXS data can be used to model both the structure, oligomeric state, conformational changes, and flexibility of biomolecular samples.Areas covered: The key principles of SAXS, its sample requirements, and its current and future applications for structural proteomics are briefly reviewed. Recent technical developments in SAXS experiments are discussed, and future potential of the method in structural proteomics is evaluated.Expert opinion: SAXS is a method suitable for several aspects of integrative structural proteomics, with current technical developments allowing for higher throughput and time-resolved studies, as well as the analysis of complex samples, such as membrane proteins. Increasing automation and streamlined data analysis are expected to equip SAXS for structure-based screening workflows. Originally, structural genomics had a heavy focus on folded, crystallizable proteins and complexes - SAXS is a method allowing an expansion of this focus to flexible and disordered systems.

Gold Nanomaterials as a Promising Integrated Tool for Diagnosis and Treatment of Pathogenic Infections-A Review

This review summarizes research on functionalized gold nanomaterials as pathogen detection sensors and pathogen elimination integrated tools. After presenting the challenge of current severe threat from pathogenic bacteria and the increasingly serious growth rate of drug resistance, the first section mainly introduces the conspectus of gold nanostructures from synthesis, characterization, physicochemical properties and applications of gold nanomaterials. The next section deals with gold nanomaterials-based pathogen detection sensors such as colorimetric sensors, fluorescence sensors and Surface-Enhanced Raman Scattering sensors. We then discuss strategies based on gold nanomaterials for eliminating pathogenic infections, such as the dual sterilization strategy for grafting gold nanomaterials with antibacterial substances, photothermal antibacterial and photodynamic antibacterial methods. The fourth part briefly introduces the comprehensive strategy for diagnosis and sterilization of pathogen infection based on gold nanomaterials, such as the diagnosis and treatment strategy for pathogen infection using Roman signals real-time monitoring and photothermal sterilization. A concluding section that summarizes the current status and challenges of the novel diagnosis and treatment integrated strategy for pathogenic infections, gives an outlook on potential future perspectives.

Refinement of α-Synuclein Ensembles Against SAXS Data: Comparison of Force Fields and Methods

The inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulation times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein α-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.

Comment on the Optimal Parameters to Derive Intrinsically Disordered Protein Conformational Ensembles from Small-Angle X-ray Scattering Data Using the Ensemble Optimization Method

The Ensemble Optimization Method (EOM) is a popular approach to describe small-angle X-ray scattering (SAXS) data from highly disordered proteins. The EOM algorithm selects subensembles of coexisting states from large pools of randomized conformations to fit the SAXS data. Based on the unphysical bimodal radius of gyration (R_g) distribution of conformations resulting from the EOM analysis, a recent article (Fagerberg et al. J. Chem. Theory Comput. 2019, 15 (12), 6968-6983) concluded that this approach inadequately described the SAXS data measured for human Histatin 5 (Hst5), a peptide with antifungal properties. Using extensive experimental and synthetic data, we explored the origin of this observation. We found that the one-bead-per-residue coarse-grained representation with averaged scattering form factors (provided in the EOM as an add-on to represent disordered missing loops or domains) may not be appropriate for EOM analyses of scattering data from short (below 50 residues) proteins/peptides. The method of choice for these proteins is to employ atomistic models (e.g., from molecular dynamics simulations) to sample the protein conformational landscape. As a convenient alternative, we have also improved the coarse-grained approach by introducing amino acid specific form factors in the calculations. We also found that, for small proteins, the search for relatively large subensembles of 20-50 conformers (as implemented in the original EOM version) more adequately describes the conformational space sampled in solution than the procedures optimizing the ensemble size. Our observations have been added as recommendations into the information for EOM users to promote the proper utilization of the program for ensemble-based modeling of SAXS data for all types of disordered systems.

Solvation of nonionic poly(ethylene oxide) surfactant Brij 35 in organic and aqueous-organic solvents

HYPOTHESIS

By combining the experimental small- and wide-angle x-ray scattering (SWAXS) method with molecular dynamics simulations and the theoretical 'complemented-system approach' it is possible to obtain detailed information about the intra- and inter-molecular structure and dynamics of the solvation and hydration of the surfactant in organic and mixed solvents, e.g., of the nonionic surfactant Brij 35 (C₁₂E₂₃) in alcohols and aqueous alcohol-rich ternary systems. This first application of the complemented-system approach to the surfactant system will promote the use of this powerful methodology that is based on experimental and calculated SWAXS data in studies of colloidal systems. By applying high-performance computing systems, such an approach is readily available for studies in the colloidal domain.

EXPERIMENTS

SWAXS experiments and MD simulations were performed for binary Brij 35/alcohol and ternary Brij 35/water/alcohol systems with ethanol, n-butanol and n-hexanol as the organic solvent component at 25 °C.

FINDINGS

We confirmed the presence of solvated Brij 35 monomers in the studied organic media, revealed their preferential hydration and discussed their structural and dynamic features at the intra- and inter-molecular levels. Anisotropic effective surfactant molecular conformations were found. The influence of the hydrophobicity of the organic solvent on the hydration phenomena of surfactant molecules was explained.

Structural insights into the membrane receptor ShuA in DDM micelles and in a model of gram-negative bacteria outer membrane as seen by SAXS and MD simulations

Successful crystallization of membrane proteins in detergent micelles depends on key factors such as conformational stability of the protein in micellar assemblies, the protein-detergent complex (PDC) monodispersity and favorable protein crystal contacts by suitable shielding of the protein hydrophobic surface by the detergent belt. With the aim of studying the influence of amphiphilic environment on membrane protein structure, stability and crystallizability, we combine molecular dynamics (MD) simulations with SEC-MALLS and SEC-SAXS (Size Exclusion Chromatography in line with Multi Angle Laser Light Scattering or Small Angle X-ray Scattering) experiments to describe the protein-detergent interactions that could help to rationalize PDC crystallization. In this context, we compare the protein-detergent interactions of ShuA from Shigella dysenteriae in n-Dodecyl-β-D-Maltopyranoside (DDM) with ShuA inserted in a realistic model of gram-negative bacteria outer membrane (OM) containing a mixture of bacterial lipopolysaccharide and phospholipids. To evaluate the quality of the PDC models, we compute the corresponding SAXS curves from the MD trajectories and compare with the experimental ones. We show that computed SAXS curves obtained from the MD trajectories reproduce better the SAXS obtained from the SEC-SAXS experiments for ShuA surrounded by 268 DDM molecules. The MD results show that the DDM molecules form around ShuA a closed belt whose the hydrophobic thickness appears slightly smaller (~22 Å) than the hydrophobic transmembrane domain of the protein (24.6 Å) suggested by Orientations of Proteins in Membranes (OPM) database. The simulations also show that ShuA transmembrane domain is remarkably stable in all the systems except for the extracellular and periplasmic loops that exhibit larger movements due to specific molecular interactions with lipopolysaccharides (LPS). We finally point out that this detergent behavior may lead to the occlusion of the periplasmic hydrophilic surface and poor crystal contacts leading to difficulties in crystallization of ShuA in DDM.

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.

Machine learning deciphers structural features of RNA duplexes measured with solution X-ray scattering

Macromolecular structures can be determined from solution X-ray scattering. Small-angle X-ray scattering (SAXS) provides global structural information on length scales of 10s to 100s of Ångstroms, and many algorithms are available to convert SAXS data into low-resolution structural envelopes. Extension of measurements to wider scattering angles (WAXS or wide-angle X-ray scattering) can sharpen the resolution to below 10 Å, filling in structural details that can be critical for biological function. These WAXS profiles are especially challenging to interpret because of the significant contribution of solvent in addition to solute on these smaller length scales. Based on training with molecular dynamics generated models, the application of extreme gradient boosting (XGBoost) is discussed, which is a supervised machine learning (ML) approach to interpret features in solution scattering profiles. These ML methods are applied to predict key structural parameters of double-stranded ribonucleic acid (dsRNA) duplexes. Duplex conformations vary with salt and sequence and directly impact the foldability of functional RNA molecules. The strong structural periodicities in these duplexes yield scattering profiles with rich sets of features at intermediate-to-wide scattering angles. In the ML models, these profiles are treated as 1D images or features. These ML models identify specific scattering angles, or regions of scattering angles, which correspond with and successfully predict distinct structural parameters. Thus, this work demonstrates that ML strategies can integrate theoretical molecular models with experimental solution scattering data, providing a new framework for extracting highly relevant structural information from solution experiments on biological macromolecules.

Real-time tracking of protein unfolding with time-resolved x-ray solution scattering

The correct folding of proteins is of paramount importance for their function, and protein misfolding is believed to be the primary cause of a wide range of diseases. Protein folding has been investigated with time-averaged methods and time-resolved spectroscopy, but observing the structural dynamics of the unfolding process in real-time is challenging. Here, we demonstrate an approach to directly reveal the structural changes in the unfolding reaction. We use nano- to millisecond time-resolved x-ray solution scattering to probe the unfolding of apomyoglobin. The unfolding reaction was triggered using a temperature jump, which was induced by a nanosecond laser pulse. We demonstrate a new strategy to interpret time-resolved x-ray solution scattering data, which evaluates ensembles of structures obtained from molecular dynamics simulations. We find that apomyoglobin passes three states when unfolding, which we characterize as native, molten globule, and unfolded. The molten globule dominates the population under the conditions investigated herein, whereas native and unfolded structures primarily contribute before the laser jump and 30 μs after it, respectively. The molten globule retains much of the native structure but shows a dynamic pattern of inter-residue contacts. Our study demonstrates a new strategy to directly observe structural changes over the cause of the unfolding reaction, providing time- and spatially resolved atomic details of the folding mechanism of globular proteins.

New Light on the Mechanism of Phototransduction in Phototropin

Phototropins are photoreceptor proteins that regulate blue light-dependent biological processes for efficient photosynthesis in plants and algae. The proteins consist of a photosensory domain that responds to the ambient light and an output module that triggers cellular responses. The photosensory domain of phototropin from Chlamydomonas reinhardtii contains two conserved LOV (light-oxygen-voltage) domains with flavin chromophores. Blue light triggers the formation of a covalent cysteine-flavin adduct and upregulates the phototropin kinase activity. Little is known about the structural mechanism that leads to kinase activation and how the two LOV domains contribute to this. Here, we investigate the role of the LOV1 domain from C. reinhardtii phototropin by characterizing the structural changes occurring after blue light illumination with nano- to millisecond time-resolved X-ray solution scattering. By structurally fitting the data with atomic models generated by molecular dynamics simulations, we find that adduct formation induces a rearrangement of the hydrogen bond network from the buried chromophore to the protein surface. In particular, the change in conformation and the associated hydrogen bonding of the conserved glutamine 120 induce a global movement of the β-sheet, ultimately driving a change in the electrostatic potential on the protein surface. On the basis of the change in the electrostatics, we propose a structural model of how LOV1 and LOV2 domains interact and regulate the full-length phototropin from C. reinhardtii. This provides a rationale for how LOV photosensor proteins function and contributes to the optimal design of optogenetic tools based on LOV domains.

Structural ensemble and biological activity of DciA intrinsically disordered region

DciA is a newly discovered bacterial protein involved in loading the replicative helicase DnaB onto DNA at the initiation step of chromosome replication. Its three-dimensional structure is composed of a folded N-terminal domain (residues 1-111) resembling K Homology domains and a long disordered C-terminal tail (residues 112-157) which structure-activity relationship remains to be elucidated. In the present study on Vibrio cholerae DciA, we emphasize the importance of its disordered region to load DnaB onto DNA using surface plasmon resonance (SPR) and isothermal titration microcalorimetry (ITC). Then we characterize the conformational ensemble of the full-length protein using a combination of circular dichroism (CD), small angle X-ray scattering (SAXS), and molecular dynamics (MD) simulations. The atomic-level structural ensemble generated by MD simulations is in very good agreement with SAXS data. From initial conformations of the C-terminal tail without any secondary structure, our simulations bring to light several transient helical structures in this segment, which might be molecular recognition features (MoRFs) for the binding to DnaB and its recruitment and loading onto DNA.

Combining molecular dynamics simulations with small-angle X-ray and neutron scattering data to study multi-domain proteins in solution

Many proteins contain multiple folded domains separated by flexible linkers, and the ability to describe the structure and conformational heterogeneity of such flexible systems pushes the limits of structural biology. Using the three-domain protein TIA-1 as an example, we here combine coarse-grained molecular dynamics simulations with previously measured small-angle scattering data to study the conformation of TIA-1 in solution. We show that while the coarse-grained potential (Martini) in itself leads to too compact conformations, increasing the strength of protein-water interactions results in ensembles that are in very good agreement with experiments. We show how these ensembles can be refined further using a Bayesian/Maximum Entropy approach, and examine the robustness to errors in the energy function. In particular we find that as long as the initial simulation is relatively good, reweighting against experiments is very robust. We also study the relative information in X-ray and neutron scattering experiments and find that refining against the SAXS experiments leads to improvement in the SANS data. Our results suggest a general strategy for studying the conformation of multi-domain proteins in solution that combines coarse-grained simulations with small-angle X-ray scattering data that are generally most easy to obtain. These results may in turn be used to design further small-angle neutron scattering experiments that exploit contrast variation through 1H/2H isotope substitutions.

Determination of Protein Structural Ensembles by Hybrid-Resolution SAXS Restrained Molecular Dynamics

Small-angle X-ray scattering (SAXS) experiments provide low-resolution but valuable information about the dynamics of biomolecular systems, which could be ideally integrated into molecular dynamics (MD) simulations to accurately determine conformational ensembles of flexible proteins. The applicability of this strategy is hampered by the high computational cost required to calculate scattering intensities from three-dimensional structures. We previously presented a hybrid resolution method that makes atomistic SAXS-restrained MD simulation feasible by adopting a coarse-grained approach to efficiently back-calculate scattering intensities; here, we extend this technique, applying it in the framework of metainference with the aim to investigate the dynamical behavior of flexible biomolecules. The efficacy of the method is assessed on the K63-diubiquitin, showing that the inclusion of SAXS restraints is effective in generating a reliable conformational ensemble, improving the agreement with independent experimental data.

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.

Structural Modeling Using Solution Small-Angle X-ray Scattering (SAXS)

Small-angle X-ray scattering (SAXS) offers a way to examine the overall shape and oligomerization state of biological macromolecules under quasi native conditions in solution. In the past decades, SAXS has become a standard tool for structure biologists due to the availability of high brilliance X-ray sources and the development of data analysis/interpretation methods. Sample handling robots and software pipelines have significantly reduced the time necessary to conduct SAXS experiments. Presently, most synchrotrons feature beamlines dedicated to biological SAXS, and the SAXS-derived models are deposited into dedicated and accessible databases. The size of macromolecules that may be analyzed ranges from small peptides or snippets of nucleic acids to gigadalton large complexes or even entire viruses. Compared to other structural methods, sample preparation is straightforward, and the risk of inducing preparation artefacts is minimal. Very importantly, SAXS is a method of choice to study flexible systems like unfolded or disordered proteins, providing the structural ensembles compatible with the data. Although it may be utilized stand-alone, SAXS profits a lot from available experimental or predicted high-resolution data and information from complementary biophysical methods. Here, we show the basic principles of SAXS and review latest developments in the fields of hybrid modeling and flexible systems.