2017 publication guidelines for structural modelling of small-angle scattering data from biomolecules in solution: an update

Abstract

In 2012, preliminary guidelines were published addressing sample quality, data acquisition and reduction, presentation of scattering data and validation, and modelling for biomolecular small-angle scattering (SAS) experiments. Biomolecular SAS has since continued to grow and authors have increasingly adopted the preliminary guidelines. In parallel, integrative/hybrid determination of biomolecular structures is a rapidly growing field that is expanding the scope of structural biology. For SAS to contribute maximally to this field, it is essential to ensure open access to the information required for evaluation of the quality of SAS samples and data, as well as the validity of SAS-based structural models. To this end, the preliminary guidelines for data presentation in a publication are reviewed and updated, and the deposition of data and associated models in a public archive is recommended. These guidelines and recommendations have been prepared in consultation with the members of the International Union of Crystallography (IUCr) Small-Angle Scattering and Journals Commissions, the Worldwide Protein Data Bank (wwPDB) Small-Angle Scattering Validation Task Force and additional experts in the field.

Keywords: DNA; RNA; SANS; SAXS; biomolecular structure; hybrid structural modelling; integrative structural biology; proteins; publication guidelines; small-angle scattering; structural modelling.

Figure 1

SEC–SAXS results for GI (blue), BSA (red) and CaM (black). (a) Plots showing I(0) (hollow squares) and R _g (filled squares) as a function of time for the SEC–SAXS run. Data frames between the vertical bars were selected for averaging to obtain I(q) versus q. (b) I(q) versus q as log-linear plots with the inset showing the Guinier fits (yellow lines) for qR _g < 1.3 with open symbols indicating data beyond the Guinier region. (c) Dimensionless Kratky plots for the data in (b). (d) P(r) versus r profiles from the data in (b) normalized to equal areas [i.e. proportional to P(r)/I(0)] for ease of comparison.

Figure 2

Crystal structure modelling results. FoXS-derived models (red and black solid lines) for GI (PDB entry 1oad, tetramer), BSA (PDB entry 4f5s, chain A) and CaM (PDB entry 1cll with the additional N- and C-terminal residues modelled) fitted to I(q) versus q. The upper plot shows log I(q) versus q, while the lower inset plot is the error-weighted residual difference plot Δ/σ = [I _exp(q) − cI _mod(q)]/σ(q) versus q. The colour key for the data plots is the same as in Fig. 1 ▸.

Figure 3

MultiFoXS modelling results for BSA and CaM. (a) Model fits for BSA: I(q) versus q (red squares) for one-state (black line) and three-state (cyan line) models assuming flexible residues 183–187 and 381–384. The lower inset shows the error-weighted residual difference plots for one-state (black squares) and three-state (cyan squares) models. (b) BSA DAMMIN model (wheat spheres) overlaid with the crystal structure (PDB entry 4f5s, chain A, blue ribbon) and one-state optimized model (magenta ribbon) and representative structures from the three-state optimized model (cyan ribbon models). (c) Model fits to I(q) versus q for CaM: I(q) versus q (black squares) for one-state (red line) and two-state (cyan line) models assuming flexible residues 1–3 and 77–81; the lower inset shows the error-weighted residual difference plots for the one-state (red squares) and two-state (cyan squares) models. (d) CaM DAMMIN model (wheat spheres) overlaid with the crystal structure (PDB entry 1cll, blue ribbon) and the one-state model (magenta ribbon) with the representative two-state models to the right (pink; calcium ions are depicted as yellow spheres). Model overlays were optimized using SUPCOMB (Kozin & Svergun, 2001 ▸).

Figure 4

Ensemble modelling results for CaM. (a) I(q) versus q (black squares) with the EOM model (red line) and error-weighted difference plot for the model and experimental profiles (red squares). (b) Averaged and filtered DAMMIN model (grey spheres) overlaid with representative structures from the optimized ensemble. Structures are aligned by their N-terminal domains (magenta), showing variability in the relative disposition of the C-terminal domains (cyan). The calcium ions are depicted as yellow spheres. Given the variations in the selected structures, the overlay with the DAMMIN model was performed simply by eye in PyMOL. (c, d) R _g and d _max distributions, respectively, from EOM for the starting pool (black line) and the optimized ensemble (red line).