Upgraded SSRF BL19U2 beamline for small-angle X-ray scattering of biological macromolecules in solution

Synchrotron Radiation: A Key Tool for Drug Discovery

Synchrotron radiation is extensively utilized in the domains of materials science, physical chemistry, and life science, resulting from its high intensity, exceptional monochromaticity, superior collimation, and broad wave spectrum. This top-notch light source has also made significant contributions to the progress of biomedicine. The advancement of synchrotron radiation-based X-ray and protein crystallography technologies has created new prospects for drug discovery. These innovative techniques have opened up exciting avenues in the field. The investigation of protein crystal structures and the elucidation of the spatial configuration of biological macromolecules have revealed intricate details regarding the modes of protein binding. Furthermore, the screening of crystal polymorphs and ligands has laid the groundwork for rational drug modification and the improvement of drug physicochemical properties. As science and technology continue to advance, the techniques for analyzing structures using synchrotron radiation sources and the design of corresponding crystallographic beamline stations are undergoing continuous enhancement. These cutting-edge tools and facilities are expected to expedite the drug development process and rectify the current situation of a lack of targeted drugs.

Visualization of conformational transition of GRP94 in solution

GRP94, an ER paralog of the heat-shock protein 90 family, binds and hydrolyses ATP to chaperone the folding and maturation of its selected clients. Compared with other hsp90 proteins, the in-solution conformational dynamics of GRP94 along the ATP hydrolysis cycle are less understood, hindering our understanding of its chaperoning mechanism. Leveraging small-angle X-ray scattering, negative-staining EM, and hydrogen-deuterium exchange coupled mass-spec, here we show that in its apo form, ∼60% of mouse GRP94 (mGRP94) populates an "extended" conformation, whereas the rest exist in either "close V" or "twist V" like "compact" conformations. Different from other hsp90 proteins, the presence of AMPPNP only impacts the relative abundance of the two compact conformations, rather than shifting the equilibrium between the "extended" and "compact" conformations of mGRP94. HDX-MS study of apo, AMPPNP-bound, and ADP-bound mGRP94 suggests a conformational transition from "twist V" to "close V" upon ATP binding and a back transition from "close V" to "twist V" upon ATP hydrolysis. These results illustrate the dissimilarities of GRP94 in conformation transition during ATP hydrolysis from other hsp90 paralogs.

Form factor determination of biological molecules with X-ray free electron laser small-angle scattering (XFEL-SAS)

Free-electron lasers (FEL) are revolutionizing X-ray-based structural biology methods. While protein crystallography is already routinely performed at FELs, Small Angle X-ray Scattering (SAXS) studies of biological macromolecules are not as prevalent. SAXS allows the study of the shape and overall structure of proteins and nucleic acids in solution, in a quasi-native environment. In solution, chemical and biophysical parameters that have an influence on the structure and dynamics of molecules can be varied and their effect on conformational changes can be monitored in time-resolved XFEL and SAXS experiments. We report here the collection of scattering form factors of proteins in solution using FEL X-rays. The form factors correspond to the scattering signal of the protein ensemble alone; the scattering contributions from the solvent and the instrument are separately measured and accurately subtracted. The experiment was done using a liquid jet for sample delivery. These results pave the way for time-resolved studies and measurements from dilute samples, capitalizing on the intense and short FEL X-ray pulses.

Small-Angle X-ray Scattering for PEGylated Liposomal Doxorubicin Drugs: An Analytical Model Comparison Study

Liposomal delivery systems are recognized as efficient and safe platforms for chemotherapeutic agents, with doxorubicin-loaded liposomes being the most representative nanopharmaceuticals. Characterizing the structure of liposomal nanomedicines in high spatial and temporal resolution is critical to analyze and evaluate their stability and efficacy. Small-angle X-ray scattering (SAXS) is a powerful tool increasingly used to investigate liposomal delivery systems. In this study, we chose a Doxil-like PEGylated liposomal doxorubicin (PLD) as an example and characterized the liposomal drug structure using synchrotron SAXS. Classical analytical models, including the spherical-shell or flat-slab geometries with Gaussian or uniform electron density profiles, were used to model the internal structure of the liposomal membrane. A cylinder model was applied to fit the scattering from the drug crystal loaded in the liposomes. The high-resolution structures of the original drug, Caelyx, and a similar research drug prepared in our laboratory were characterized using these analytical models. The structural parameters of PLDs, including the thickness of the liposomal membrane and morphology of the drug crystal, were further compared. The results demonstrated that both spherical-shell and flat-slab geometries with Gaussian electron density distribution were suitable to elucidate the structural features of the liposomal membrane under a certain range of scattering vectors, while models with uniform electron density distribution exhibited poor fitting performance. This study highlights the technical features of SAXS, which provides structural information at the nanoscale for liposomal drugs. The demonstrated methods are reliable and easy-to-use for the structural analysis of liposomal drugs, which are helpful for a broader application of SAXS in the production and regulation of nanopharmaceuticals.

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

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

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

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

Luminescence Ratiometric Nanothermometry Regulated by Tailoring Annihilators of Triplet-Triplet Annihilation Upconversion Nanomicelles

Triplet-triplet annihilation (TTA) upconversion is a special non-linear photophysical process that converts low-energy photons into high-energy photons based on sensitizer/annihilator pairs. Here, we constructed a novel luminescence ratiometric nanothermometer based on TTA upconversion nanomicelles by encapsulating sensitizer/annihilator molecules into a temperature-sensitive amphiphilic triblock polymer and obtained good linear relationships between the luminescence ratio (integrated intensity ratio of upconverted luminescence peak to the downshifted phosphorescence peak) and the temperature. We also found chemical modification of annihilators would rule out the interference of the polymer concentration and stereochemical engineering of annihilators would readily regulate the thermal sensitivity.

Unveiling the structure of the primary caseinate particle using small-angle X-ray scattering and simulation methodologies

The low-resolution structure of casein (CN) clusters in sodium caseinate (NaCas) solution and its conformational dynamics were obtained by size-exclusion chromatography (SEC), analytical ultracentrifugation (AUC), small-angle X-ray scattering (SAXS), and molecular dynamics (MD) simulations. The results of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and native PAGE revealed that the casein clusters consisted predominantly of α- and β-CN complexes, and a trace amount of κ-CN. The AUC analysis indicated that the casein clusters were composed of 34.6% of casein monomers, 19.2%, 20.4%, and 25.8% of complexes with molar weight (M_w) of ~50.3, ~70.6, and ~133 kDa, respectively. The volume fractions of components in casein clusters were quantified as 64.3% of α_s1-β-α_s2-CN, 22.3% of α_s1-CN, 8.5% of α_s2-CN, and 4.4% of α_s1-α_s2-CN, respectively. The ensemble optimization method (EOM) gave a fitting result where α_s1-β-α_s2-CN species coexisted in ~35.3% under compact conformation and ~64.7% in elongated conformation in solution. The three-dimensional structures of α_s1-β-α_s2-CN from EOM showed a good overlay on the casein clusters ab initio model obtained from DAMMIN and DAMMIX program. MD simulations revealed that α_s1-β-α_s2-CN underwent a conformational change from the elongated state into the compact state within the initial 200 ns of simulations. The addition of nonionic surfactants affected little the backbone-to-backbone interactions in the formation of the casein clusters. We propose that α_s1-CN, β-CN, α_s2-CN, and κ-CN associated in consecutive steps into casein clusters, and a trace of κ-CN may be located at the surface of the assemblies limiting the growth of casein aggregates.

Deploying the Big Data Science Center at the Shanghai Synchrotron Radiation Facility: the first superfacility platform in China

With recent technological advances, large-scale experimental facilities generate huge datasets, into the petabyte range, every year, thereby creating the Big Data deluge effect. Data management, including the collection, management, and curation of these large datasets, is a significantly intensive precursor step in relation to the data analysis that underpins scientific investigations. The rise of artificial intelligence (AI), machine learning (ML), and robotic automation has changed the landscape for experimental facilities, producing a paradigm shift in how different datasets are leveraged for improved intelligence, operation, and data analysis. Therefore, such facilities, known as superfacilities, which fully enable user science while addressing the challenges of the Big Data deluge, are critical for the scientific community. In this work, we discuss the process of setting up the Big Data Science Center within the Shanghai Synchrotron Radiation Facility (SSRF), China’s first superfacility. We provide details of our initiatives for enabling user science at SSRF, with particular consideration given to recent developments in AI, ML, and robotic automation.

Investigations of structural and dynamical mechanisms of ice formation regulated by graphene oxide nanosheets

Recent research indicates that graphene oxide (GO) nanosheets can be used to regulate ice formation by controlling critical ice nucleus growth in water at supercooling temperatures. In addition, the study of ice formation mechanisms regulated by GO nanosheets, a good model system for antifreeze proteins (AFPs), will shed light on how AFPs regulate ice formation in nature. In this work, time-resolved small-angle x-ray scattering (TR-SAXS) and quasi-elastic neutron scattering (QENS) experiments were carried out to investigate the structural and dynamical mechanisms of ice formation regulated by GO nanosheets. Strikingly, a transient intermediate state was observed in TR-SAXS experiments that only exists in the aqueous dispersions with a larger GO size (11 nm). This serves as evidence that the size of GO is critical for regulating ice formation. Elastic neutron scattering results indicate that ice is formed in all samples and thermal hysteresis occurs in GO aqueous dispersions in both H₂O and D₂O. The structural and dynamics information about water molecules in GO, extracted from QENS, reveals different dynamical behaviors of water molecules in GO aqueous dispersions when approaching the ice formation temperature.

ATSAS 3.0: expanded functionality and new tools for small-angle scattering data analysis

The ATSAS software suite encompasses a number of programs for the processing, visualization, analysis and modelling of small-angle scattering data, with a focus on the data measured from biological macromolecules. Here, new developments in the ATSAS 3.0 package are described. They include IMSIM, for simulating isotropic 2D scattering patterns; IMOP, to perform operations on 2D images and masks; DATRESAMPLE, a method for variance estimation of structural invariants through parametric resampling; DATFT, which computes the pair distance distribution function by a direct Fourier transform of the scattering data; PDDFFIT, to compute the scattering data from a pair distance distribution function, allowing comparison with the experimental data; a new module in DATMW for Bayesian consensus-based concentration-independent molecular weight estimation; DATMIF, an ab initio shape analysis method that optimizes the search model directly against the scattering data; DAMEMB, an application to set up the initial search volume for multiphase modelling of membrane proteins; ELLLIP, to perform quasi-atomistic modelling of liposomes with elliptical shapes; NMATOR, which models conformational changes in nucleic acid structures through normal mode analysis in torsion angle space; DAMMIX, which reconstructs the shape of an unknown intermediate in an evolving system; and LIPMIX and BILMIX, for modelling multilamellar and asymmetric lipid vesicles, respectively. In addition, technical updates were deployed to facilitate maintainability of the package, which include porting the PRIMUS graphical interface to Qt5, updating SASpy - a PyMOL plugin to run a subset of ATSAS tools - to be both Python 2 and 3 compatible, and adding utilities to facilitate mmCIF compatibility in future ATSAS releases. All these features are implemented in ATSAS 3.0, freely available for academic users at https://www.embl-hamburg.de/biosaxs/software.html.

SAS-cam: a program for automatic processing and analysis of small-angle scattering data

Small-angle X-ray scattering (SAXS) is a widely used method for investigating biological macromolecules in structural biology, providing information on macromolecular structures and dynamics in solution. Modern synchrotron SAXS beamlines are characterized as high-throughput, capable of collecting large volumes of data and thus demanding fast data processing for efficient beamline operations. This article presents a fully automated and high-throughput SAXS data analysis pipeline, SAS-cam, primarily based on the SASTBX package. Five modules are included in SAS-cam, encompassing the data analysis process from data reduction to model interpretation. The model parameters are extracted from SAXS profiles and stored in an HTML summary file, ready for online visualization using a web browser. SAS-cam can provide the user with the possibility of optimizing experimental parameters based on real-time feedback and it therefore significantly improves the efficiency of beam time. SAS-cam is installed on the BioSAXS beamline at the Shanghai Synchrotron Radiation Facility. The source code is available upon request.