Comparing state-of-the-art approaches to back-calculate SAXS spectra from atomistic molecular dynamics simulations

Abstract

Small-angle X-ray scattering (SAXS) experiments are arising as an effective instrument in the structural characterization of biomolecules in solution. However, they suffer from limited resolution, and complementing them with molecular dynamics (MD) simulations can be a successful strategy to obtain information at a finer scale. To this end, tools that allow computing SAXS spectra from MD-sampled structures have been designed over the years, mainly differing in how the solvent contribution is accounted for. In this context, RNA molecules represent a particularly challenging case, as they can have a remarkable effect on the surrounding solvent. Herein, we provide a comparison of SAXS spectra computed through different available software packages for a prototypical RNA system. RNA conformational dynamics is intentionally neglected so as to focus on solvent effects. The results highlight that solvent effects are important also at relatively low scattering vector, suggesting that approaches explicitly modeling solvent contribution are advisable when comparing with experimental data, while more efficient implicit-solvent methods can be a better choice as reaction coordinates to improve MD sampling on-the-fly. Graphic abstract

Enhanced sampling for lipid-protein interactions during membrane dynamics

“…Improved simulation packages (Brooks et al, 2021;Suh et al, 2022), better force-fields (Klein et al, 2021;Souza et al, 2021;Cruz-León et al, 2021;Yungerman et al, 2022), unprecedented supercomputer power (Yamazaki et al, 2021;Kutzner et al, 2022) and creative sampling techniques (Gilabert et al, 2019;Bonati et al, 2021) have boosted the study of exceptionally complex biological problems (Mosalaganti et al, 2022;Lotz and Dickson, 2018). More studies combining theoretical approaches, computer simulations, and experiments are currently envisioning new possibilities (Sica and Smulski, 2021;Bernetti and Bussi, 2021;Miguel et al, 2021;Quevedo et al, 2019;Saen-oon et al, 2015). Although computational models containing conceptual simplifications may, of course, exhibit inherent limitations (Alessandri et al, 2019;Jarin et al, 2021;Masone et al, 2012), the recent overall progress in the biomolecular simulations field at varied lengths and timescales has been outstanding (Schlick and Portillo-Ledesma, 2021;Pezeshkian et al, 2020).…”

Combining simulations and experiments to investigate RNA dynamics

“…Some of these models were developed considering reference static structures and might benefit from a revisiting with dynamics in mind [67]. For SAXS experiments, different models include solvent effects to a different degree [68]. Chemical probing experiments are extremely cheap and scalable.…”

RNA triplex structures revealed by WAXS-driven MD simulations

“…Many factors impact the accuracy of the interpretation of the results, [63][64][65][66] such as the resolution of the experimental data, the accurate reflection in the measurement of welldefined structural correlations in the molecules, the type and magnitude of the errors, and finally the accuracy of the back-calculation. 67 Computational challenges are also important, especially selection of a good starting model, assessment of overlap between the experimental and computational ensemble(s), and the role of forcefield and coupling methods on the ensemble generated need to be investigated more in depth to develop a robust computational strategy. Here, we proposed and demonstrated a strategy for solving the solution structure of RNA molecules possessing tertiary motifs.…”