A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking

Structural highlights of macromolecular complexes and assemblies

The structures of macromolecular assemblies have given us deep insights into cellular processes and have profoundly impacted biological research and drug discovery. We highlight the structures of macromolecular assemblies that have been modeled using integrative and computational methods and describe how open access to these structures from structural archives has empowered the research community. The arsenal of experimental and computational methods for structure determination ensures a future where whole organelles and cells can be modeled.

IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods

IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB.

Computation of X-ray and Neutron Scattering Patterns to Benchmark Atomistic Simulations against Experiments

Molecular Dynamics simulations study material structure and dynamics at the atomic level. X-ray and neutron scattering experiments probe exactly the same time- and length scales as the simulations. In order to benchmark simulations against measured scattering data, a program is required that computes scattering patterns from simulations with good single-core performance and support for parallelization. In this work, the existing program Sassena is used as a potent solution to this requirement for a range of scattering methods, covering pico- to nanosecond dynamics, as well as the structure from some Ångströms to hundreds of nanometers. In the case of nanometer-level structures, the finite size of the simulation box, which is referred to as the finite size effect, has to be factored into the computations for which a method is described and implemented into Sassena. Additionally, the single-core and parallelization performance of Sassena is investigated, and several improvements are introduced.

AlphaFold, small-angle X-ray scattering and ensemble modelling: a winning combination for intrinsically disordered proteins

A recent article by Brookes, Rocco, Vachette & Trewhella [J. Appl. Cryst. (2023), 56, 910-926] on improving the accuracy of AlphaFold structural predictions for disordered proteins is discussed.

AlphaFold-predicted protein structures and small-angle X-ray scattering: insights from an extended examination of selected data in the Small-Angle Scattering Biological Data Bank

By providing predicted protein structures from nearly all known protein sequences, the artificial intelligence program AlphaFold (AF) is having a major impact on structural biology. While a stunning accuracy has been achieved for many folding units, predicted unstructured regions and the arrangement of potentially flexible linkers connecting structured domains present challenges. Focusing on single-chain structures without prosthetic groups, an earlier comparison of features derived from small-angle X-ray scattering (SAXS) data taken from the Small-Angle Scattering Biological Data Bank (SASBDB) is extended to those calculated using the corresponding AF-predicted structures. Selected SASBDB entries were carefully examined to ensure that they represented data from monodisperse protein solutions and had sufficient statistical precision and q resolution for reliable structural evaluation. Three examples were identified where there is clear evidence that the single AF-predicted structure cannot account for the experimental SAXS data. Instead, excellent agreement is found with ensemble models generated by allowing for flexible linkers between high-confidence predicted structured domains. A pool of representative structures was generated using a Monte Carlo method that adjusts backbone dihedral allowed angles along potentially flexible regions. A fast ensemble modelling method was employed that optimizes the fit of pair distance distribution functions [P(r) versus r] and intensity profiles [I(q) versus q] computed from the pool to their experimental counterparts. These results highlight the complementarity between AF prediction, solution SAXS and molecular dynamics/conformational sampling for structural modelling of proteins having both structured and flexible regions.

Upgraded D22 SEC-SANS setup dedicated to the biology community

Described here is the current status of the upgraded in situ size-exclusion chromatography (SEC) system implemented with the D22 small-angle neutron scattering (SANS) instrument at the Institut Laue-Langevin. Since its initial proof of principle in 2016, this SEC-SANS arrangement has been continuously requested by the user community, leading to the design of an upgraded version. A detailed description of the setup and its control is provided, and a few examples of protein structural investigations are presented, which will highlight the various possibilities and limitations of the setup to optimize experimental success.

Hybrid computational methods combining experimental information with molecular dynamics

A goal of structural biology is to understand how macromolecules carry out their biological roles by identifying their metastable states, mechanisms of action, pathways leading to conformational changes, and the thermodynamic and kinetic relationships between those states. Integrative modeling brings structural insights into systems where traditional structure determination approaches cannot help. We focus on the synergies and challenges of integrative modeling combining experimental data with molecular dynamics simulations.

2023 update of template tables for reporting biomolecular structural modelling of small-angle scattering data

In 2017, guidelines were published for reporting structural modelling of small-angle scattering (SAS) data from biomolecules in solution that exemplified best-practice documentation of experiments and analysis. Since then, there has been significant progress in SAS data and model archiving, and the IUCr journal editors announced that the IUCr biology journals will require the deposition of SAS data used in biomolecular structure solution into a public archive, as well as adherence to the 2017 reporting guidelines. In this context, the reporting template tables accompanying the 2017 publication guidelines have been reviewed with a focus on making them both easier to use and more general. With input from the SAS community via the IUCr Commission on SAS and attendees of the triennial 2022 SAS meeting (SAS2022, Campinas, Brazil), an updated reporting template table has been developed that includes standard descriptions for proteins, glycosylated proteins, DNA and RNA, with some reorganization of the data to improve readability and interpretation. In addition, a specialized template has been developed for reporting SAS contrast-variation (SAS-cv) data and models that incorporates the additional reporting requirements from the 2017 guidelines for these more complicated experiments. To demonstrate their utility, examples of reporting with these new templates are provided for a SAS study of a DNA-protein complex and a SAS-cv experiment on a protein complex. The examples demonstrate how the tabulated information promotes transparent reporting that, in combination with the recommended figures and additional information best presented in the main text, enables the reader of the work to readily draw their own conclusions regarding the quality of the data and the validity of the models presented.

Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scattering

Key to small-angle scattering (SAS) maturing and becoming a mainstream structural biology technique was the work done by the SAS community to establish standards for data quality, model validation and data sharing. Through a consultative process spanning more than a decade and a half, guidelines for publication have been established that include criteria for evaluating data quality and for model validation. In this process gaps were identified that stimulated innovation and development of new tools, for example new measures of model ambiguity and of the goodness-of-fit of a model to SAS data that complement the traditional global fit parameter χ². The need for a global repository for biomolecular SAS data and models was identified and the SASBDB was established as a searchable, curated, freely accessible, downloadable database of experimental data, experimental conditions, sample details, derived models, and their fit to the data. Importantly, the SASBDB uses a common dictionary format that supports archiving of structures solved using integrative methods to support seamless data exchange with a federated system of public databanks that includes the world-wide Protein Data Bank (wwPDB) as the major repository for structural biology. Thus, biomolecular SAS is now well-positioned to achieve its full potential as a mainstream structural biology technique contributing at the frontier of integrative structural biology and meeting "best practice" standards for data quality assurance and data sharing.