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

Jill Trewhella,Masaaki Sugiyama,Andrew E Whitten,Anthony P Duff,Timothy M Ryan,Dmitri I Svergun,Ann H Kwan,Greg L Hura,Torsten Schwede,Frank Gabel,John A Tainer,Lois Pollack,J Mitchell Guss,Dominique Durand,Patrice Vachette,Wayne A Hendrickson,Javier Pérez,Andrej Šali ,Dina Stroopinsky ,John D Westbrook ,D.a Jacques ,Nigel Kirby

doi:10.1107/s2059798317011597

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.

Highlights

The objective of publishing the preliminary guidelines for biomolecular small-angle scattering (SAS) experiments (Jacques, Guss, Svergun et al, 2012; Jacques, Guss & Trewhella, 2012) was to provide a reporting framework so that ‘readers can independently assess the quality of the data and the basis for any interpretations presented’
For bovine serum albumin (BSA), the differences appear to be quite subtle, and further they occur in the lowest q and high-q regimes, unlike the statistically superior CaM example where for the one-state model at least, the locus is in the mid-q regime that we expect to be most sensitive to domain dispositions
The example sizeexclusion chromatography (SEC)–small-angle X-ray scattering (SAXS) experiments on glucose isomerase (GI), BSA and CaM illustrate the value of comprehensive reporting so that data quality and model accuracy are clearly communicated

Summary

Introduction

The objective of publishing the preliminary guidelines for biomolecular small-angle scattering (SAS) experiments (Jacques, Guss, Svergun et al, 2012; Jacques, Guss & Trewhella, 2012) was to provide a reporting framework so that ‘readers can independently assess the quality of the data and the basis for any interpretations presented’. In regard to modelling SAS data, there has been significant increased interest and methods development in multistate/ensemblebased methods for flexible biomolecules (Tria et al, 2015; Berlin et al, 2013; Schneidman-Duhovny et al, 2016; Perkins et al, 2016; Kikhney & Svergun, 2015; Terakawa et al, 2014) and structural modelling based on combined SAS and NMR data (Schwieters & Clore, 2014). The objective is to ensure that the reader understands the accuracy and precision of the derived parameters and models and any limitations to the data This understanding is essential for quantifying uncertainty in IHM structural modelling using SAS data (Schneidman-Duhovny et al, 2014; Yang et al, 2012). It is important in evaluating data that might be limited in some way and yet still provide reliable structural insights

Sample quality

Data acquisition and reduction

Structure modelling

An example

Findings

Conclusions