Effects of ionic strength on SAXS data for proteins revealed by molecular dynamics simulations

Combination of coarse-grained molecular dynamics simulations and small-angle X-ray scattering experiments

The combination of molecular dynamics (MD) simulations and small-angle X-ray scattering (SAXS), called the MD-SAXS method, is efficient for investigating protein dynamics. To overcome the time-scale limitation of all-atom MD simulations, coarse-grained (CG) representations are often utilized for biomolecular simulations. In this study, we propose a method to combine CG MD simulations with SAXS, termed the CG-MD-SAXS method. In the CG-MD-SAXS method, the scattering factors of CG particles for proteins and nucleic acids are evaluated using high-resolution structural data in the Protein Data Bank, and the excluded volume and the hydration shell are modeled using two adjustable parameters to incorporate solvent effects. To avoid overfitting, only the two parameters are adjusted for an entire structure ensemble. To verify the developed method, theoretical SAXS profiles for various proteins, DNA/RNA, and a protein-RNA complex are compared with both experimental profiles and theoretical profiles obtained by the all-atom representation. In the present study, we applied the CG-MD-SAXS method to the Swi5-Sfr1 complex and three types of nucleosomes to obtain reliable ensemble models consistent with the experimental SAXS data.

Dipole-dipole interactions between tryptophan side chains and hydration water molecules dominate the observed dynamic stokes shift of lysozyme

The fluorescence intensity of tryptophan residues in hen egg-white lysozyme was measured up to 500 ps after the excitation by irradiation pulses at 290 nm. From the time-dependent variation of fluorescence intensity in a wavelength range of 320-370 nm, the energy relaxation in the dynamic Stokes shift was reconstructed as the temporal variation in wavenumber of the estimated fluorescence maximum. The relaxation was approximated by two exponential curves with decay constants of 1.2 and 26.7 ps. To interpret the relaxation, a molecular dynamics simulation of 75 ns was conducted for lysozyme immersed in a water box. From the simulation, the energy relaxation in the electrostatic interactions of each tryptophan residue was evaluated by using a scheme derived from the linear response theory. Dipole-dipole interactions between each of the Trp62 and Trp123 residues and hydration water molecules displayed an energy relaxation similar to that experimentally observed regarding time constants and magnitudes. The side chains of these residues were partly or fully exposed to the solvent. In addition, by inspecting the variation in dipole moments of the hydration water molecules around lysozyme, it was suggested that the observed relaxation could be attributed to the orientational relaxation of hydration water molecules participating in the hydrogen-bond network formed around each of the two tryptophan residues.

Inferring Structural Ensembles of Flexible and Dynamic Macromolecules Using Bayesian, Maximum Entropy, and Minimal-Ensemble Refinement Methods

The flexible and dynamic nature of biomolecules and biomolecular complexes is essential for many cellular functions in living organisms but poses a challenge for experimental methods to determine high-resolution structural models. To meet this challenge, experiments are combined with molecular simulations. The latter propose models for structural ensembles, and the experimental data can be used to steer these simulations and to select ensembles that most likely underlie the experimental data. Here, we explain in detail how the "Bayesian Inference Of ENsembles" (BioEn) method can be used to refine such ensembles using a wide range of experimental data. The "Ensemble Refinement of SAXS" (EROS) method is a special case of BioEn, inspired by the Gull-Daniell formulation of maximum entropy image processing and focused originally on X-ray solution scattering experiments (SAXS) and then extended to integrative structural modeling. We also briefly sketch the "minimum ensemble method," a maximum-parsimony refinement method that seeks to represent an ensemble with a minimal number of representative structures.

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.

Computational approaches for deciphering the equilibrium and kinetic properties of iron transport proteins

With the advances in three-dimensional structure determination techniques, high quality structures of the iron transport proteins transferrin and the bacterial ferric binding protein (FbpA) have been deposited in the past decade. These are proteins of relatively large size, and developments in hardware and software have only recently made it possible to study their dynamics using standard computational resources. We review computational techniques towards understanding the equilibrium and kinetic properties of iron transport proteins under different environmental conditions. At the level of detail that requires quantum chemical treatments, the octahedral geometry around iron has been scrutinized and it has been established that the iron coordinating tyrosines are in an unusual deprotonated state. At the atomistic level, both the N-lobe and the full bilobal structure of transferrin have been studied under varying conditions of pH, ionic strength and binding of other metal ions by molecular dynamics (MD) simulations. These studies have allowed questions to be answered, among others, on the function of second shell residues in iron release, the role of synergistic anions in preparing the active site for iron binding, and the differences between the kinetics of the N- and the C-lobe. MD simulations on FbpA have led to the detailed observation of the binding kinetics of phosphate to the apo form, and to the conformational preferences of the holo form under conditions mimicking the environmental niches provided by the periplasmic space. To study the dynamics of these proteins with their receptors, one must resort to coarse-grained methodologies, since these systems are prohibitively large for atomistic simulations. A study of the complex of human transferrin (hTf) with its pathogenic receptor by such methods has revealed a potential mechanistic explanation for the defense mechanism that arises in evolutionary warfare. Meanwhile, the motions in the transferrin receptor bound hTf have been shown to disfavor apo hTf dissociation, explaining why the two proteins remain in complex during the recycling process from the endosome to the cell surface. Open problems and possible technological applications related to metal ion binding-release in iron transport proteins that may be handled by hybrid use of quantum mechanical, MD and coarse-grained approaches are discussed.

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.

Hybrid Methods for Macromolecular Modeling by Molecular Mechanics Simulations with Experimental Data

Hybrid approaches for the modeling of macromolecular complexes that combine computational molecular mechanics simulations with experimental data are discussed. Experimental data for biological molecular structures are often low-resolution, and thus, do not contain enough information to determine the atomic positions of molecules. This is especially true when the dynamics of large macromolecules are the focus of the study. However, computational modeling can complement missing information. Significant increase in computational power, as well as the development of new modeling algorithms allow us to model structures of biological macromolecules reliably, using experimental data as references. We review the basics of molecular mechanics approaches, such as atomic model force field, and coarse-grained models, molecular dynamics simulation and normal mode analysis and describe how they could be used for flexible fitting hybrid modeling with experimental data, especially from cryo-EM and SAXS.

Validating solution ensembles from molecular dynamics simulation by wide-angle X-ray scattering data

Wide-angle x-ray scattering (WAXS) experiments of biomolecules in solution have become increasingly popular because of technical advances in light sources and detectors. However, the structural interpretation of WAXS profiles is problematic, partly because accurate calculations of WAXS profiles from structural models have remained challenging. In this work, we present the calculation of WAXS profiles from explicit-solvent molecular dynamics (MD) simulations of five different proteins. Using only a single fitting parameter that accounts for experimental uncertainties because of the buffer subtraction and dark currents, we find excellent agreement to experimental profiles both at small and wide angles. Because explicit solvation eliminates free parameters associated with the solvation layer or the excluded solvent, which would require fitting to experimental data, we minimize the risk of overfitting. We further find that the influence from water models and protein force fields on calculated profiles are insignificant up to q≈15nm(-1). Using a series of simulations that allow increasing flexibility of the proteins, we show that incorporating thermal fluctuations into the calculations significantly improves agreement with experimental data, demonstrating the importance of protein dynamics in the interpretation of WAXS profiles. In addition, free MD simulations up to one microsecond suggest that the calculated profiles are highly sensitive with respect to minor conformational rearrangements of proteins, such as an increased flexibility of a loop or an increase of the radius of gyration by < 1%. The present study suggests that quantitative comparison between MD simulations and experimental WAXS profiles emerges as an accurate tool to validate solution ensembles of biomolecules.

Interpretation of solution x-ray scattering by explicit-solvent molecular dynamics

Small- and wide-angle x-ray scattering (SWAXS) and molecular dynamics (MD) simulations are complementary approaches that probe conformational transitions of biomolecules in solution, even in a time-resolved manner. However, the structural interpretation of the scattering signals is challenging, while MD simulations frequently suffer from incomplete sampling or from a force-field bias. To combine the advantages of both techniques, we present a method that incorporates solution scattering data as a differentiable energetic restraint into explicit-solvent MD simulations, termed SWAXS-driven MD, with the aim to direct the simulation into conformations satisfying the experimental data. Because the calculations fully rely on explicit solvent, no fitting parameters associated with the solvation layer or excluded solvent are required, and the calculations remain valid at wide angles. The complementarity of SWAXS and MD is illustrated using three biological examples, namely a periplasmic binding protein, aspartate carbamoyltransferase, and a nuclear exportin. The examples suggest that SWAXS-driven MD is capable of refining structures against SWAXS data without foreknowledge of possible reaction paths. In turn, the SWAXS data accelerates conformational transitions in MD simulations and reduces the force-field bias.

Fast-SAXS-pro: a unified approach to computing SAXS profiles of DNA, RNA, protein, and their complexes

A generalized method, termed Fast-SAXS-pro, for computing small angle x-ray scattering (SAXS) profiles of proteins, nucleic acids, and their complexes is presented. First, effective coarse-grained structure factors of DNA nucleotides are derived using a simplified two-particle-per-nucleotide representation. Second, SAXS data of a 18-bp double-stranded DNA are measured and used for the calibration of the scattering contribution from excess electron density in the DNA solvation layer. Additional test on a 25-bp DNA duplex validates this SAXS computational method and suggests that DNA has a different contribution from its hydration surface to the total scattering compared to RNA and protein. To account for such a difference, a sigmoidal function is implemented for the treatment of non-uniform electron density across the surface of a protein/nucleic-acid complex. This treatment allows differential scattering from the solvation layer surrounding protein/nucleic-acid complexes. Finally, the applications of this Fast-SAXS-pro method are demonstrated for protein/DNA and protein/RNA complexes.

Atomic-resolution structural information from scattering experiments on macromolecules in solution

The pair-distance distribution function (PDDF) contains all structural information probed in an elastic scattering experiment of macromolecular solutions. However, in small-angle x-ray scattering (SAXS) or small-angle neutron scattering (SANS) experiments only their Fourier transform is measured over a restricted range of scattering angles. We therefore developed a mathematically simple and computationally efficient method to calculate the PDDFs as well as accurate scattering intensities from molecular dynamics simulations. The calculated solution scattering intensities are in excellent agreement with SAXS and wide-angle x-ray scattering (WAXS) experiments for a series of proteins. The corresponding PDDFs are remarkably rich in features reporting on the detailed protein structure. Using an inverse Fourier transform method, most of these features can be recovered if scattering intensities are measured up to a momentum transfer of q≈2-3Å(-1). Our results establish that high-precision solution scattering experiments utilizing x-ray free-electron lasers and third generation synchrotron sources can resolve subnanometer structural detail, well beyond size, shape, and fold.

Effect of the solute–solvent interface on small-angle neutron scattering from organic solutions of short alkyl chain molecules as revealed by molecular dynamics simulation

The problem of describing the experimental small-angle neutron scattering (SANS) from diluted solutions of saturated monocarboxylic acids with short chain lengths (myristic and stearic acids) in deuterated decalin is considered. The method of classical molecular dynamics simulation (MDS) is used to obtain the atomic number density distributions, and, as a consequence, the scattering length density (SLD) distribution in the solute–solvent interface area (about 1 nm around the acid molecules), assuming the acid molecules to be rigid and non-associated in the solutions. MDS is performed for solutions in a parallelepiped cell of 5.5 × 5.3 × 5.3 nm (one acid molecule per cell) under normal conditions. The time averaging of the obtained distributions is done over 2 ns (after the system thermalization). It is shown that a specific short-range ordering organization of the solvent molecules in the vicinity of the acid molecules has a significant effect on the scattering, which is mainly determined by a relatively large ratio between the effective size of the solvent molecule and the cross-section diameter of the acid molecule. Various approximations to the simulated SLD distributions, based on the cylinder-type symmetry of the acid molecules, are probed to achieve the best consistency with the experimental SANS curves by varying the residual incoherent background.

Aggregation of amyloids in a cellular context: modelling and experiment

Amyloid-related diseases are a group of illnesses in which an abnormal accumulation of proteins into fibrillar structures is evident. Results from a wide range of studies, ranging from identification of amyloid-β dimers in the brain to biophysical characterization of the interactions between amyloidogenic peptides and lipid membranes during fibril growth shed light on the initial events which take place during amyloid aggregation. Accounts of fibril disaggregation and formation of globular aggregates due to interactions with lipids or fatty acids further demonstrate the complexity of the aggregation process and the difficulty to treat amyloid-related diseases. There is an inherent difficulty in generalizing from studies of aggregation in vitro, but the involvement of too many cellular components limits the ability to follow amyloid aggregation in a cellular (or extracellular) context. Fortunately, the development of experimental methods to generate stable globular aggregates suggests new means of studying the molecular events associated with amyloid aggregation. Furthermore, simulation studies enable deeper understanding of the experimental results and provide useful predictions that can be tested in the laboratory. Computer simulations can nowadays provide molecular or even atomistic details that are experimentally not available or very difficult to obtain. In the present review, recent developments on modelling and experiments of amyloid aggregation are reviewed, and an integrative account on how isolated interactions (as observed in vitro and in silico) combine during the course of amyloid-related diseases is presented. Finally, it is argued that an integrative approach is necessary to get a better understanding of the protein aggregation process.