Molecular Simulations of Liquid Jet Explosions and Shock Waves Induced by X-Ray Free-Electron Lasers.

X-ray free-electron lasers (XFELs) produce x-ray pulses with high brilliance and short pulse duration. These properties enable structural investigations of biomolecular nanocrystals, and they allow one to resolve the dynamics of biomolecules down to the femtosecond timescale. Liquid jets are widely used to deliver samples into the XFEL beam. The impact of the x-ray pulse leads to vaporization and explosion of the liquid jet, while the expanding gas triggers the formation of shock wave trains traveling along the jet, which may affect biomolecular samples before they have been probed. Here, we used molecular dynamics simulations to reveal the structural dynamics of shock waves after an x-ray impact. Analysis of the density and temperature in the jet revealed shock waves that form close to the explosion center, travel along the jet with supersonic velocities, and decay exponentially with an attenuation length proportional to the jet diameter. A trailing shock wave formed after the first shock wave, similar to the shock wave trains in experiments. High shock wave velocities in our simulations are compatible with the phenomenon of "fast sound," as emerging at large sound frequencies. Although using purely classical models in the simulations, the resulting explosion geometry and shock wave dynamics closely resemble experimental findings, and they highlight the importance of atomistic details for modeling shock wave attenuation.

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.

Predicting solution scattering patterns with explicit-solvent molecular simulations.

Small-angle X-ray or neutron scattering (SAXS/SANS/SAS) is widely used to obtain structural information on biomolecules or soft-matter complexes in solution. Deriving a molecular interpretation of the scattering signals requires methods for predicting SAS patterns from a given atomistic structural model. Such SAS predictions are nontrivial because the patterns are influenced by the hydration layer of the solute, the excluded solvent, and by thermal fluctuations. Many computationally efficient methods use simplified, implicit models for the hydration layer and excluded solvent, leading to some uncertainties and to free parameters that require fitting against experimental data. SAS predictions based on explicit-solvent molecular dynamics (MD) simulations overcome such limitations at the price of an increased computational cost. To rationalize the need for explicit-solvent methods, we first review the approximations underlying implicit-solvent methods. Next, we describe the theory behind explicit-solvent SAS predictions that are easily accessible via the WAXSiS web server. We present the workflow for computing SAS pattern from a given molecular dynamics trajectory. The calculations are available via a modified version of the GROMACS simulations software, coined GROMACS-SWAXS, which implements the WAXSiS method. Practical considerations for running routine explicit-solvent SAS predictions are discussed.

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.