Acta Crystallographica. Section D, Structural Biology最新文献

In macromolecular structure refinement, the low observation-to-parameter ratio and the lack of high-resolution data are countered by using a priori information in the form of restraints. Having accurate geometries of the chemical entities in the sample is paramount for generating accurate chemical restraints and, therefore, accurate macromolecular structures. In particular, it is desirable to have accurate restraints for known and novel ligand entities. Quantum mechanics (QM) can minimize the energy of a ligand by adjusting its geometry, and these geometries can be used to generate restraints for macromolecular refinement. This article describes a library of approximately 37 000 small molecules extracted from the Chemical Component Dictionary in the Protein Data Bank and minimized by density-functional QM. The library includes restraint files for use in crystallography or cryo-EM refinement, along with files suitable for molecular-dynamics simulation. Because the geometries are validated using the Cambridge Structural Database, the restraints library provides users with both functional restraints and minimized geometries. This work also provides procedures for generating new and accurate restraints.

Cryo-electron microscopy (cryo-EM) has transformed structural biology by enabling near-atomic resolution of large macromolecular complexes without the need for crystallization. Here, we describe our laboratory's transition from X-ray crystallography to single-particle cryo-EM to investigate the ATPase family AAA+ domain-containing protein 2B (ATAD2B), a chromatin regulator implicated in epigenetic signaling. We outline the challenges encountered during protein expression, purification and sample preparation, including co-purification of the chaperonin GroEL, and the strategies employed to overcome these obstacles. Our workflow highlights critical steps in sample optimization, grid vitrification and data processing using CryoSPARC, cisTEM and Topaz, as well as computational requirements for high-resolution reconstructions. We also discuss model-building, refinement and validation approaches, emphasizing best practices for new cryo-EM users. This work provides practical insights for structural biologists adopting cryo-EM, particularly for large, flexible protein complexes, and underscores the importance of integrated approaches combining biochemical, computational and imaging strategies.

Phosphatidylinositol transfer proteins (PITPs) are essential lipid-binding proteins that regulate phosphoinositide signaling, membrane trafficking and autophagy through the transport of phosphatidylinositol and other phospholipids between intracellular membranes. Microcolin compounds have been identified as selective inhibitors of class I PITPs, revealing important roles of PITPs in Hippo signaling and autophagy. Here, we report the crystal structure of human PITPα in complex with microcolin H at 2.0 Å resolution. The structure enables a detailed description of the interaction between microcolin H and the lipid-binding cavity. Besides the expected covalent bond to the Cys94 residue, the structure also reveals an extensive network of hydrogen bonds, water bridges and hydrophobic interactions. Importantly, PITPα remains in the open conformation upon binding to microcolin H. Quantitative cavity analysis confirms that the microcolin-bound structure adopts a volume comparable to that of the unliganded PITPα and is markedly larger than that of the lipid-bound state. These findings demonstrate that microcolins selectively trap PITPα in an open conformation and provide a structural basis for their inhibitory mechanism. Furthermore, our results show that ligand binding can profoundly change protein conformation, which underscores the limitation of docking experiments.

Specific radiation damage (SRD) to proteins is a pertinent issue discovered during the development of cryo-crystallography at synchrotrons, often affecting the macromolecular active site and thus complicating the understanding of mechanistic insights from structural analysis. For proteins with a spectroscopic signature in the visible light spectrum, in crystallo UV-Vis absorption spectroscopy has regularly been used to estimate the dose scale of specific damage build-up and to develop diffraction data-collection strategies to mitigate its effects. Using a coupled spectroscopic and crystallographic approach, here we show that for two metal-containing proteins the structural response to X-ray-induced reduction of metals in their active site is markedly different at room temperature than at cryogenic temperature. This suggests that the use of controlled specific radiation damage to mimic and study a physiological redox transition in a metal-containing protein by X-ray crystallography should preferably be performed at room temperature rather than at cryogenic temperature.

The Small-Angle Scattering Biological Data Bank (SASBDB) has recently reached a milestone of 5000 entries, reflecting over a decade of community-driven efforts to support open and reusable biological small-angle scattering data. SASBDB provides curated experimental scattering profiles together with metadata describing samples, experimental conditions and associated structural models, thereby enabling transparent data sharing, reproducibility and comparative analysis. The archive has become an important resource for benchmarking, reanalysis and method development, including the evaluation of structure-based modelling approaches and the integration of solution scattering data with high-resolution predictive models. Its growing content also supports benchmarking, method development, and emerging data-driven and machine-learning approaches that rely on curated collections of real experimental data. This milestone highlights the role of SASBDB as a foundational infrastructure for contemporary and future developments in biological small-angle scattering.

The interaction between transition-metal ions and amyloid-β (Aβ) peptides is linked to the pathogenesis of Alzheimer's disease. X-ray absorption spectroscopy is widely used to investigate the coordination of these metal-peptide complexes, but exposure to synchrotron radiation can induce artefacts due to interaction with the X-ray beam. In this work, we examine the effects of X-ray irradiation on Cu(I), Cu(II) and Zn(II) complexes with two truncated Aβ fragments, Aβ_1-6 and Aβ_1-16. Experiments performed at 10 K reveal a marked photoreduction-associated effect: while the spectra of Cu(I)- and Zn(II)-bound peptides remain unchanged, Cu(II) complexes undergo significant spectral modifications. To probe structural relaxation following reduction, we exposed samples at 10 K, raised the temperature to 200 K and then collected additional spectra upon re-cooling. These experiments reveal that higher temperatures promote relaxation processes that are otherwise kinetically limited, and that the extent of relaxation, depending on the metal-binding mode, differs for Aβ_1-6 and Aβ_1-16. Overall, our experiments show that major structural modifications only take place in the presence of X-ray-induced metal reduction and that they are modulated by temperature. Thus, X-ray irradiation can be exploited not only as a probe but also as a trigger to study the redox-associated structural dynamics of copper-Aβ complexes and beyond.

In cryo-electron microscopy (cryo-EM), imaging of biological specimens is restricted by the limited field of view and by sample thickness. Hard X-ray imaging, with its ability to penetrate samples several tens of micrometres thick, offers a complementary approach for high-resolution visualization. A major concern is whether cryo-preserved samples can withstand the handling conditions at synchrotron facilities without excessive icing, and whether the radiation exposure during X-ray imaging compromises specimen integrity, thereby hindering subsequent attempts to achieve high-resolution 3D reconstructions via cryo-EM. To evaluate this, we deposited apoferritin samples on a cryo-EM grid, exposed them to varied X-ray doses typical for X-ray tomography experiments at a synchrotron facility, and subsequently analysed the exposed particles by cryo-EM. Despite the apparent damage sustained throughout the experiment, the samples remained amenable to cryo-EM analysis, with structural details at a resolution of ∼4 Å at the highest absorbed X-ray dose of 100 MGy. By comparison, a similar cryo-EM dataset of apoferritin particles that were not exposed to X-rays but were mounted on the same cryo-EM grid resulted in a 3D reconstruction at 3.17 Å resolution. Thus, while radiation damage may limit the high-resolution information in specimens processed by cryo-X-ray tomography, the cryo-preserved biological material exposed to these high X-ray doses can still be used for subsequent cryo-EM workflows aiming to obtain structural biology insights at intermediate to high resolution. These findings lay the groundwork for an integrated imaging workflow that combines X-ray and cryo-EM techniques to enable multiscale analysis of thick vitrified biological specimens.

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021), Nat. Methods, 18, 186-193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, subtomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L₁/L₂ losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

While cryo-electron microscopy (cryo-EM) has come to prominence in the last decade due to its ability to resolve biomolecular complexes at atomic resolution, advancements in experimental and computational methods have made cryo-EM promising for investigating intracellular organization and heterogeneous molecular states. A primary challenge for these alternative applications is the development of techniques for cryo-EM data analysis, which are very computationally demanding. To this end, it is advantageous to leverage advanced scientific computing frameworks for statistical analysis. One such framework is JAX, an emerging array-oriented Python numerical computing package for automatic differentiation and vectorization with a growing ecosystem for statistical inference and machine learning. We have developed cryoJAX, a cryo-EM image-simulation library for building computational data-analysis applications in JAX. CryoJAX is a flexible modeling language for cryo-EM image formation and therefore can support a wide range of data analysis downstream. By integrating with the JAX ecosystem, cryoJAX enables the development and deployment of algorithms for the growing breadth of scientific applications for cryo-EM.

In previous articles in this series, a novel probabilistic method was described which is capable of estimating triplet invariants using the Patterson map as prior information. The first experimental tests demonstrated the superiority of the new method compared with the traditional Cochran estimate. The advantages were so significant that the ab initio solution of macromolecular structures was considered to be feasible even when the data resolution is worse than 2 Å. However, several questions remained unanswered. For example: (i) which and how many Patterson peaks should be used to optimize a direct-methods phasing procedure applied to experimental data up to 2.2 Å resolution?, (ii) is the presence of heavy atoms a necessary ingredient for the validity of the method?, (iii) which and how many reflections must be used in the triplet search?, (iv) is the information contained in the Patterson map able to identify negative cosine triplets? and (v) may a computer program be made that routinary solves macromolecular structures with data resolution up to 2.2 Å? This article recalls these five unresolved questions and answers them. In particular, criteria have been defined to determine both the number of Patterson peaks to be actively used for triplet estimation and the number of reflections to be used in the triplet search. It has also been shown that the presence of heavy atoms is a necessary ingredient for success of the theory. In particular, the theory is unable to accurately identify triplet invariants with a negative cosine, but rather can identify enantiomorph-sensitive triplets. A paradox of the theory is discussed and resolved. Finally, a computer program is presented that is capable of automatically, with a few directives, solving some of the test structures at non-atomic resolution (proteins and nucleic acids) with data resolution up to 2.2 Å, but not in a straightforward way. The limitations of the computer program and its prospects are discussed.