Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application

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.

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.

Decoupling copolymer, lipid and carbon nanotube interactions in hybrid, biomimetic vesicles

Bilayer vesicles that mimic a real biological cell can be tailored to carry out a specific function by manipulating the molecular composition of the amphiphiles. These bio-inspired and bio-mimetic structures are increasingly being employed for a number of applications from drug delivery to water purification and beyond. Complex hybrid bilayers are the key building blocks for fully synthetic vesicles that can mimic biological cell membranes, which often contain a wide variety of molecular species. While the assembly and morpholgy of pure phospholid bilayer vesicles is well understood, the functionality and structure dramaticlly changes when copolymer and/or carbon nanotube porins (CNTP) are added. The aim of this study is to understand how the collective molecular interactions within hybrid vesicles affect their nanoscale structure and properties. In situ small and wide angle X-ray scattering (SAXS/WAXS) and molecular dynamics simulations (MD) are used to investigate the morphological effect of molecular interactions between polybutadiene polyethylene oxide, lipids and carbon nanotubes (CNT) within the hybrid vesicle bilayer. Within the lipid/copolymer system, the hybrid bilayer morphology transitions from phase separated lipid and compressed copolymer at low copolymer loadings to a mixed bilayer where opposing lipids are mostly separated from the inner region. This transition begins between 60 wt% and 70 wt%, with full homogenization observed by 80 wt% copolymer. The incorporation of CNT into the hybrid vesicles increases the bilayer thickness and enhances the bilayer symmetry. Analysis of the WAXS and MD indicate that the CNT-dioleoyl interactions are much stronger than the CNT-polybutadiene.

Enhanced sampling and free energy calculations for protein simulations

Molecular dynamics simulation is a powerful computational technique to study biomolecular systems, which complements experiments by providing insights into the structural dynamics relevant to biological functions at atomic scale. It can also be used to calculate the free energy landscapes of the conformational transitions to better understand the functions of the biomolecules. However, the sampling of biomolecular configurations is limited by the free energy barriers that need to be overcome, leading to considerable gaps between the timescales reached by MD simulation and those governing biological processes. To address this issue, many enhanced sampling methodologies have been developed to increase the sampling efficiency of molecular dynamics simulations and free energy calculations. Usually, enhanced sampling algorithms can be classified into methods based on collective variables (CV-based) and approaches which do not require predefined CVs (CV-free). In this chapter, the theoretical basis of free energy estimation is briefly reviewed first, followed by the reviews of the most common CV-based and CV-free methods including the presentation of some examples and recent developments. Finally, the combination of different enhanced sampling methods is discussed.

Studying viruses using solution X-ray scattering

Viruses have been of interest to mankind since their discovery as small infectious agents in the nineteenth century. Because many viruses cause diseases to humans and agriculture, they were rigorously studied for biological and medical purposes. Viruses have remarkable properties such as the symmetry and self-assembly of their protein envelope, maturation into infectious virions, structural stability, and disassembly. Solution X-ray scattering can probe structures and reactions in solutions, down to subnanometer spatial resolution and millisecond temporal resolution. It probes the bulk solution and reveals the average shape and average mass of particles in solution and can be used to study kinetics and thermodynamics of viruses at different stages of their life cycle. Here we review recent work that demonstrates the capabilities of solution X-ray scattering to study in vitro the viral life cycle.

Protein encapsulation: a new approach for improving the capability of small-molecule fluorogenic probes

Herein, we report a protein-based hybridization strategy that exploits the host-guest chemistry of HSA (human serum albumin) to solubilize the otherwise cell impermeable ONOO^- fluorescent probe Pinkment-OAc. Formation of a HSA/Pinkment-OAc supramolecular hybrid was confirmed by SAXS and solution-state analyses. This HSA/Pinkment-OAc hybrid provided an enhanced fluorescence response towards ONOO^- versus Pinkment-OAc alone, as determined by in vitro experiments. The HSA/Pinkment-OAc hybrid was also evaluated in RAW 264.7 macrophages and HeLa cancer cell lines, which displayed an enhanced cell permeability enabling the detection of SIN-1 and LPS generated ONOO^- and the in vivo imaging of acute inflammation in LPS-treated mice. A remarkable 5.6 fold (RAW 264.7), 8.7-fold (HeLa) and 2.7-fold increased response was seen relative to Pinkment-OAc alone at the cellular level and in vivo, respectively. We anticipate that HSA/fluorescent probe hybrids will soon become ubiquitous and routinely applied to overcome solubility issues associated with hydrophobic fluorescent imaging agents designed to detect disease related biomarkers.

BEES: Bayesian Ensemble Estimation from SAS

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

Elucidating the role of an immunomodulatory protein in cancer: From protein expression to functional characterization

Several fundamental discoveries made over the last two decades, in the field of cancer biology, have increased our understanding of the complex tumor micro- and macroenvironments. This has shifted the current empirical cancer therapies to more rationalized treatments targeting immunomodulatory proteins. From the point of identification, a protein target undergoes several interrogations, which are necessary to truly define its druggability. Here, we outline some basic steps that can be followed for in vitro characterization of a potential immunomodulatory protein target. We describe procedures for recombinant protein expression and purification including key annotations on protein cloning, expression systems, purification strategies and protein characterization using structural and biochemical approaches. For functional characterization, we provide detailed protocols for using flow-cytometric techniques in cell lines or primary cells to study protein expression profiles, proliferation, apoptosis and cell-cycle changes. This multilevel approach can provide valuable, in-depth understanding of any protein target with potential immunomodulatory effects.

An introduction to classical molecular dynamics simulation for experimental scattering users

Classical molecular dynamics simulations are a common component of multi-modal analyses of scattering measurements, such as small-angle scattering and diffraction. Users of these experimental techniques often have no formal training in the theory and practice of molecular dynamics simulation, leading to the possibility of these simulations being treated as a 'black box' analysis technique. This article describes an open educational resource (OER) designed to introduce classical molecular dynamics to users of scattering methods. This resource is available as a series of interactive web pages, which can be easily accessed by students, and as an open-source software repository, which can be freely copied, modified and redistributed by educators. The topics covered in this OER include classical atomistic modelling, parameterizing interatomic potentials, molecular dynamics simulations, typical sources of error and some of the approaches to using simulations in the analysis of scattering data.

Modeling Conformationally Flexible Proteins With X-ray Scattering and Molecular Simulations

Proteins and protein complexes with high conformational flexibility participate in a wide range of biological processes. These processes include genome maintenance, gene expression, signal transduction, cell cycle regulation, and many others. Gaining a structural understanding of conformationally flexible proteins and protein complexes is arguably the greatest problem facing structural biologists today. Over the last decade, some progress has been made toward understanding the conformational flexibility of such systems using hybrid approaches. One particularly fruitful strategy has been the combination of small-angle X-ray scattering (SAXS) and molecular simulations. In this article, we provide a brief overview of SAXS and molecular simulations and then discuss two general approaches for combining SAXS data and molecular simulations: minimal ensemble approaches and full ensemble approaches. In minimal ensemble approaches, one selects a minimal ensemble of structures from the simulations that best fit the SAXS data. In full ensemble approaches, one validates a full ensemble of structures from the simulations using SAXS data. We argue that full ensemble models are more realistic than minimal ensemble searches models and that full ensemble approaches should be used wherever possible.

Self-assembled amphiphilic chitosan: A time-dependent nanostructural evolution and associated drug encapsulation/elution mechanism

This investigation reports the nanostructural evolution and associated encapsulation and elution of a hydrophobic drug, demethoxycurcumin (DMC), as a molecular probe, with the carboxymethyl-hexanoyl chitosan (CHC), which has been a technically interesting amphiphilic chitosan-based polymer successfully developed in this lab for years. The self-assembly nature of the CHC in neutral aqueous solutions allowed efficient encapsulation of various drugs without deteriorating or changing drugs' activity. However, its self-assembly behavior associated with nanostructural stability or variation, in terms of residence time in aqueous solution has not been well characterized and how the CHC nanostructure may be altered upon entrapping a drug, followed releasing out of the nanostructure. In this study, the CHC/DMC assembled model was used to evaluate entrapping efficiency, CHC-DMC interaction, and nanostructural variation while the drug being encapsulated and released from the CHC nanoparticles. Experimental outcomes showed a fractal transition between nanoparticulate and short fiber-like network evolution of the CHC as time elapsed, with the presence or absence of the DMC probe. This entrapment of DMC is relatively efficient upon CHC assembly and the associated DMC arrangement inside the helical CHC macromolecule gave largely increasing space over the resulting CHC/DMC assembly. Its excellent colloidal and nanostructural stability over a reasonably long period of time in testing environment suggests that this CHC/DMC assembly not only provides a crucial advantage for drug delivery application but also considers as a nanostructural model for better understanding of the mechanism upon drug encapsulation and elution which may be applicable to alternative amphiphilic polysaccharide-based macromolecules.

Understanding the role of co-surfactants in microemulsions on the growth of copper oxalate using SAXS

SAXS study for evaluating the effect of variation of co-surfactants on the shape of reverse micelles and growth of copper oxalate nanostructures.

SAXS-guided Enhanced Unbiased Sampling for Structure Determination of Proteins and Complexes

Molecular simulations can be utilized to predict protein structure ensembles and dynamics, though sufficient sampling of molecular ensembles and identification of key biologically relevant conformations remains challenging. Low-resolution experimental techniques provide valuable structural information on biomolecule at near-native conditions, which are often combined with molecular simulations to determine and refine protein structural ensembles. In this study, we demonstrate how small angle x-ray scattering (SAXS) information can be incorporated in Markov state model-based adaptive sampling strategy to enhance time efficiency of unbiased MD simulations and identify functionally relevant conformations of proteins and complexes. Our results show that using SAXS data combined with additional information, such as thermodynamics and distance restraints, we are able to distinguish otherwise degenerate structures due to the inherent ambiguity of SAXS pattern. We further demonstrate that adaptive sampling guided by SAXS and hybrid information can significantly reduce the computation time required to discover target structures. Overall, our findings demonstrate the potential of this hybrid approach in predicting near-native structures of proteins and complexes. Other low-resolution experimental information can be incorporated in a similar manner to collectively enhance unbiased sampling and improve the accuracy of structure prediction from simulation.

The pearl necklace model in protein A chromatography: Molecular mechanisms at the resin interface

Staphylococcal protein A chromatography is an established core technology for monoclonal antibody purification and capture in the downstream processing. MabSelect SuRe involves a tetrameric chain of a recombinant form of the B domain of staphylococcal protein A, called the Z-domain. Little is known about the stoichiometry, binding orientation, or preferred binding. We analyzed small-angle X-ray scattering data of the antibody-protein A complex immobilized in an industrial highly relevant chromatographic resin at different antibody concentrations. From scattering data, we computed the normalized radial density distributions. We designed three-dimensional (3D) models with protein data bank crystallographic structures of an IgG1 (the isoform of trastuzumab, used here; Protein Data Bank: 1HZH) and the staphylococcal protein A B domain (the native form of the recombinant structure contained in MabSelect SuRe resin; Protein Data Bank: 1BDD). We computed different binding conformations for different antibody to protein A stoichiometries (1:1, 2:1, and 3:1) and compared the normalized radial density distributions computed from 3D models with those obtained from the experimental data. In the linear range of the isotherm we favor a 1:1 ratio, with the antibody binding to the outer domains in the protein A chain at very low and high concentrations. In the saturation region, a 2:1 ratio is more likely to occur. A 3:1 stoichiometry is excluded because of steric effects.

A methodology to calculate small-angle scattering profiles of macromolecular solutions from molecular simulations in the grand-canonical ensemble

The theoretical framework to evaluate small-angle scattering (SAS) profiles for multi-component macromolecular solutions is re-examined from the standpoint of molecular simulations in the grand-canonical ensemble, where the chemical potentials of all species in solution are fixed. This statistical mechanical ensemble resembles more closely scattering experiments, capturing concentration fluctuations that arise from the exchange of molecules between the scattering volume and the bulk solution. The resulting grand-canonical expression relates scattering intensities to the different intra- and intermolecular pair distribution functions, as well as to the distribution of molecular concentrations on the scattering volume. This formulation represents a generalized expression that encompasses most of the existing methods to evaluate SAS profiles from molecular simulations. The grand-canonical SAS methodology is probed for a series of different implicit-solvent, homogeneous systems at conditions ranging from dilute to concentrated. These systems consist of spherical colloids, dumbbell particles, and highly flexible polymer chains. Comparison of the resulting SAS curves against classical methodologies based on either theoretical approaches or canonical simulations (i.e., at a fixed number of molecules) shows equivalence between the different scattering intensities so long as interactions between molecules are net repulsive or weakly attractive. On the other hand, for strongly attractive interactions, grand-canonical SAS profiles deviate in the low- and intermediate-q range from those calculated in a canonical ensemble. Such differences are due to the distribution of molecules becoming asymmetric, which yields a higher contribution from configurations with molecular concentrations larger than the nominal value. Additionally, for flexible systems, explicit discrimination between intra- and inter-molecular SAS contributions permits the implementation of model-free, structural analysis such as Guinier's plots at high molecular concentrations, beyond what the traditional limits are for such analysis.

The Role of Molecular Flexibility in Antigen Presentation and T Cell Receptor-Mediated Signaling

Antigen presentation is a cellular process that involves a number of steps, beginning with the production of peptides by proteolysis or aberrant synthesis and the delivery of peptides to cellular compartments where they are loaded on MHC class I (MHC-I) or MHC class II (MHC-II) molecules. The selective loading and editing of high-affinity immunodominant antigens is orchestrated by molecular chaperones: tapasin/TAP-binding protein, related for MHC-I and HLA-DM for MHC-II. Once peptide/MHC (pMHC) complexes are assembled, following various steps of quality control, they are delivered to the cell surface, where they are available for identification by αβ receptors on CD8⁺ or CD4⁺ T lymphocytes. In addition, recognition of cell surface peptide/MHC-I complexes by natural killer cell receptors plays a regulatory role in some aspects of the innate immune response. Many of the components of the pathways of antigen processing and presentation and of T cell receptor (TCR)-mediated signaling have been studied extensively by biochemical, genetic, immunological, and structural approaches over the past several decades. Until recently, however, dynamic aspects of the interactions of peptide with MHC, MHC with molecular chaperones, or of pMHC with TCR have been difficult to address experimentally, although computational approaches such as molecular dynamics (MD) simulations have been illuminating. Studies exploiting X-ray crystallography, cryo-electron microscopy, and multidimensional nuclear magnetic resonance (NMR) spectroscopy are beginning to reveal the importance of molecular flexibility as it pertains to peptide loading onto MHC molecules, the interactions between pMHC and TCR, and subsequent TCR-mediated signals. In addition, recent structural and dynamic insights into how molecular chaperones define peptide selection and fine-tune the MHC displayed antigen repertoire are discussed. Here, we offer a review of current knowledge that highlights experimental data obtained by X-ray crystallography and multidimensional NMR methodologies. Collectively, these findings strongly support a multifaceted role for protein plasticity and conformational dynamics throughout the antigen processing and presentation pathway in dictating antigen selection and recognition.

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

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

Hybrid Methods for Modeling Protein Structures Using Molecular Dynamics Simulations and Small-Angle X-Ray Scattering Data

Small-angle X-ray scattering (SAXS) is an efficient experimental tool to measure the overall shape of macromolecular structures in solution. However, due to the low resolution of SAXS data, high-resolution data obtained from X-ray crystallography or NMR and computational methods such as molecular dynamics (MD) simulations are complementary to SAXS data for understanding protein functions based on their structures at atomic resolution. Because MD simulations provide a physicochemically proper structural ensemble for flexible proteins in solution and a precise description of solvent effects, the hybrid analysis of SAXS and MD simulations is a promising method to estimate reasonable solution structures and structural ensembles in solution. Here, we review typical and useful in silico methods for modeling three dimensional protein structures, calculating theoretical SAXS profiles, and analyzing ensemble structures consistent with experimental SAXS profiles. We also review two examples of the hybrid analysis, termed MD-SAXS method in which MD simulations are carried out without any knowledge of experimental SAXS data, and the experimental SAXS data are used only to assess the consistency of the solution model from MD simulations with those observed in experiments. One example is an investigation of the intrinsic dynamics of EcoO109I using the computational method to obtain a theoretical profile from the trajectory of an MD simulation. The other example is a structural investigation of the vitamin D receptor ligand-binding domain using snapshots generated by MD simulations and assessment of the snapshots by experimental SAXS data.

A Gallium-Based Magnetocaloric Liquid Metal Ferrofluid

We demonstrate a magnetocaloric ferrofluid based on a gadolinium saturated liquid metal matrix, using a gallium-based liquid metal alloy as the solvent and suspension medium. The material is liquid at room temperature, while exhibiting spontaneous magnetization and a large magnetocaloric effect. The magnetic properties were attributed to the formation of gadolinium nanoparticles suspended within the liquid gallium alloy, which acts as a reaction solvent during the nanoparticle synthesis. High nanoparticle weight fractions exceeding 2% could be suspended within the liquid metal matrix. The liquid metal ferrofluid shows promise for magnetocaloric cooling due to its high thermal conductivity and its liquid nature. Magnetic and thermoanalytic characterizations reveal that the developed material remains liquid within the temperature window required for domestic refrigeration purposes, which enables future fluidic magnetocaloric devices. Additionally, the observed formation of nanometer-sized metallic particles within the supersaturated liquid metal solution has general implications for chemical synthesis and provides a new synthetic pathway toward metallic nanoparticles based on highly reactive rare earth metals.

Homology Modeling and Molecular Dynamics Simulation Combined with X-ray Solution Scattering Defining Protein Structures of Thromboxane and Prostacyclin Synthases

A combination of molecular dynamics (MD) simulations and X-ray scattering (SAXS) has emerged as the approach of choice for studying protein structures and dynamics in solution. This approach has potential applications for membrane proteins that neither are soluble nor form crystals easily. We explore the water-coupled dynamic structures of thromboxane synthase (TXAS) and prostacyclin synthase (PGIS) from scanning HPLC-SAXS measurements combined with MD ensemble analyses. Both proteins are heme-containing enzymes in the cytochrome P450 family, known as prostaglandin H₂ (PGH₂) isomerase, with counter-functions in regulation of platelet aggregation. Currently, the X-ray crystallographic structures of PGIS are available, but those for TXAS are not. The use of homology modeling of the TXAS structure with ns-μs explicit water solvation MD simulations allows much more accurate estimation of the configuration space with loop motion and origin of the protein behaviors in solution. In contrast to the stability of the conserved PGIS structure in solution, the pronounced TXAS flexibility has been revealed to have unstructured loop regions in connection with the characteristic P450 structural elements. The MD-derived and experimental-solution SAXS results are in excellent agreement. The significant protein internal motions, whole-molecule structures, and potential problems with protein folding, crystallization, and functionality are examined.

Circular Dichroism Spectroscopy of Collagen Fibrillogenesis: A New Use for an Old Technique

Type-I collagen assembles in a stepwise, hierarchic fashion from the folding of the triple helix to the assembly of fibrils into fibers. The mature assembled fibers are crucial for tissue structure and mechanics, cell interactions, and other functions in vivo. Although triple helix folding can be followed with the use of optical methods such as circular dichroism (CD) spectroscopy, fibrillogenesis is typically measured by alternative methods such as turbidity, rheology, and microscopy. Together, these approaches allow for investigation of the mechanical properties and architectures of collagen-based scaffolds and excised tissues. Herein, we demonstrate that CD spectroscopy, a technique that is used primarily to evaluate the secondary structure of proteins, can also be employed to monitor collagen fibrillogenesis. Type-I collagen suspensions demonstrated a strong, negative ellipticity band between 204 and 210 nm under conditions consistent with fibrillogenesis. Deconvolution of CD spectra before, during, and after fibrillogenesis identified a unique fibril spectrum distinct from triple helix and random coil conformations. The ability to monitor multiple states of collagen simultaneously in one experiment using one modality provides a powerful platform for studying this complex assembly process and the effects of other factors, such as collagenases, on fibrillogenesis and degradation.

Determining Atomistic SAXS Models of Tri-Ubiquitin Chains from Bayesian Analysis of Accelerated Molecular Dynamics Simulations

Small-angle X-ray scattering (SAXS) has become an increasingly popular technique for characterizing the solution ensemble of flexible biomolecules. However, data resulting from SAXS is typically low-dimensional and is therefore difficult to interpret without additional structural knowledge. In theory, molecular dynamics (MD) trajectories can provide this information, but conventional simulations rarely sample the complete ensemble. Here, we demonstrate that accelerated MD simulations can be used to produce higher quality models in shorter time scales than standard simulations, and we present an iterative Bayesian Monte Carlo method that is able to identify multistate ensembles without overfitting. This methodology is applied to several ubiquitin trimers to demonstrate the effect of linkage type on the solution states of the signaling protein. We observe that the linkage site directly affects the solution flexibility of the trimer and theorize that this difference in plasticity contributes to their disparate roles in vivo.

SLADS: a parallel code for direct simulations of scattering of large anisotropic dense nanoparticle systems

SLADS(http://www.pims.ac.cn/Resources.html), a parallel code for direct simulations of X-ray scattering of large anisotropic dense nanoparticle systems of arbitrary species and atomic configurations, is presented. Particles can be of arbitrary shapes and dispersities, and interactions between particles are considered. Parallelization is achieved in real space for the sake of memory limitation. The system sizes attempted are up to one billion atoms, and particle concentrations in dense systems up to 0.36. Anisotropy is explored in terms of superlattices. One- and two-dimensional small-angle scattering or diffraction patterns are obtained.SLADSis validated self-consistently or against cases with analytical solutions.

Deciphering conformational transitions of proteins by small angle X-ray scattering and normal mode analysis

Structural flexibility and conformational rearrangements are often related to important functions of biological macromolecules, but the experimental characterization of such transitions with high-resolution techniques is challenging. At a lower resolution, small angle X-ray scattering (SAXS) can be used to obtain information on biomolecular shapes and transitions in solution. Here, we present SREFLEX, a hybrid modeling approach that uses normal mode analysis (NMA) to explore the conformational space of high-resolution models and refine the structure guided by the agreement with the experimental SAXS data. The method starts from a given conformation of the protein (which does not agree with the SAXS data). The structure is partitioned into pseudo-domains either using structural classification databases or automatically from the protein dynamics as predicted by the NMA. The algorithm proceeds hierarchically employing NMA to first probe large rearrangements and progresses into smaller and more localized movements. At the large rearrangements stage the pseudo-domains stay as rigid bodies allowing one to avoid structural disruptions inherent to the earlier NMA-based algorithms. To validate the approach, we compiled a representative benchmark set of 88 conformational states known experimentally at high resolution. The performance of the algorithm is demonstrated in the simulated data on the benchmark set and also in a number of experimental examples. SREFLEX is included into the ATSAS program package freely available to the academic users, both for download and in the on-line mode.

Molecular emulsions: from charge order to domain order

Aqueous mixtures of small molecules, such as lower n-alkanols for example, are known to be micro-segregated, with domains in the nano-meter range.

Small Angle X-ray Scattering for Nanoparticle Research

X-ray scattering is a structural characterization tool that has impacted diverse fields of study. It is unique in its ability to examine materials in real time and under realistic sample environments, enabling researchers to understand morphology at nanometer and angstrom length scales using complementary small and wide angle X-ray scattering (SAXS, WAXS), respectively. Herein, we focus on the use of SAXS to examine nanoscale particulate systems. We provide a theoretical foundation for X-ray scattering, considering both form factor and structure factor, as well as the use of correlation functions, which may be used to determine a particle's size, size distribution, shape, and organization into hierarchical structures. The theory is expanded upon with contemporary use cases. Both transmission and reflection (grazing incidence) geometries are addressed, as well as the combination of SAXS with other X-ray and non-X-ray characterization tools. We conclude with an examination of several key areas of research where X-ray scattering has played a pivotal role, including in situ nanoparticle synthesis, nanoparticle assembly, and operando studies of catalysts and energy storage materials. Throughout this review we highlight the unique capabilities of X-ray scattering for structural characterization of materials in their native environment.

How Do Spherical Diblock Copolymer Nanoparticles Grow during RAFT Alcoholic Dispersion Polymerization?

A poly(2-(dimethylamino)ethyl methacrylate) (PDMA) chain transfer agent (CTA) is used for the reversible addition-fragmentation chain transfer (RAFT) alcoholic dispersion polymerization of benzyl methacrylate (BzMA) in ethanol at 70 °C. THF GPC analysis indicated a well-controlled polymerization with molecular weight increasing linearly with conversion. GPC traces also showed high blocking efficiency with no homopolymer contamination apparent and Mw/Mn values below 1.35 in all cases. 1H NMR studies confirmed greater than 98% BzMA conversion for a target PBzMA degree of polymerization (DP) of up to 600. The PBzMA block becomes insoluble as it grows, leading to the in situ formation of sterically stabilized diblock copolymer nanoparticles via polymerization-induced self-assembly (PISA). Fixing the mean DP of the PDMA stabilizer block at 94 units and systematically varying the DP of the PBzMA block enabled a series of spherical nanoparticles of tunable diameter to be obtained. These nanoparticles were characterized by TEM, DLS, MALLS, and SAXS, with mean diameters ranging from 35 to 100 nm. The latter technique was particularly informative: data fits to a spherical micelle model enabled calculation of the core diameter, surface area occupied per copolymer chain, and the mean aggregation number (Nagg). The scaling exponent derived from a double-logarithmic plot of core diameter vs PBzMA DP suggests that the conformation of the PBzMA chains is intermediate between the collapsed and fully extended state. This is in good agreement with 1H NMR studies, which suggest that only 5-13% of the BzMA residues of the core-forming chains are solvated. The Nagg values calculated from SAXS and MALLS are in good agreement and scale approximately linearly with PBzMA DP. This suggests that spherical micelles grow in size not only as a result of the increase in copolymer molecular weight during the PISA synthesis but also by exchange of individual copolymer chains between micelles and/or by sphere-sphere fusion events.

Toward a modular multi-material nanoparticle synthesis and assembly strategy via bionanocombinatorics: bifunctional peptides for linking Au and Ag nanomaterials

Materials-binding peptides provide the basis for new nanoparticle assembly strategies.