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Cryo-electron microscopy (cryo-EM) enables macromolecular structure determination in vitro and inside cells. In addition to aligning individual particles, accurate registration of sample motion and three-dimensional deformation during exposures are crucial for achieving high-resolution reconstructions. Here we describe M, a software tool that establishes a reference-based, multi-particle refinement framework for cryo-EM data and couples a comprehensive spatial deformation model to in silico correction of electron-optical aberrations. M provides a unified optimization framework for both frame-series and tomographic tilt-series data. We show that tilt-series data can provide the same resolution as frame-series data on a purified protein specimen, indicating that the alignment step no longer limits the resolution obtainable from tomographic data. In combination with Warp and RELION, M resolves to residue level a 70S ribosome bound to an antibiotic inside intact bacterial cells. Our work provides a computational tool that facilitates structural biology in cells.The software M establishes a reference-based multi-particle refinement framework for cryo-EM data. Combined with CTF correction and map denoising, M enables residue-level structure determination inside cells.

In electron cryomicroscopy (cryo-EM), molecular images of vitrified biological samples are obtained by conventional transmission microscopy (CTEM) using large underfocuses and subsequently computationally combined into a high-resolution three-dimensional structure. Here, we apply scanning transmission electron microscopy (STEM) using the integrated differential phase contrast mode also known as iDPC–STEM to two cryo-EM test specimens, keyhole limpet hemocyanin (KLH) and tobacco mosaic virus (TMV). The micrographs show complete contrast transfer to high resolution and enable the cryo-EM structure determination for KLH at 6.5 Å resolution, as well as for TMV at 3.5 Å resolution using single-particle reconstruction methods, which share identical features with maps obtained by CTEM of a previously acquired same-sized TMV data set. These data show that STEM imaging in general, and in particular the iDPC–STEM approach, can be applied to vitrified single-particle specimens to determine near-atomic resolution cryo-EM structures of biological macromolecules. This paper explores the use of scanning transmission electron microscopy (STEM) to vitrified biological samples for biomolecular structure elucidation. Integrated differential phase contrast (iDPC)–STEM imaging of keyhole limpet hemocyanin and tobacco mosaic virus enabled cryo-EM structure determination at 6.5 and 3.5 Å resolution, respectively.

Plant-based melanin seems to be abundant, but it did not receive scientific attention despite its importance in plant biology and medicinal applications, e.g. photoprotection, radical scavenging, antimicrobial properties, etc. Date fruit melanin (DM) has complex, graphene-like, polymeric structure that needs characterization to understand its molecular properties and potential applications. This study provides the first investigation of the possible molecular composition of DM. High performance size-exclusion chromatography (HPSEC) suggested that DM contains oligomeric structures (569–3236 Da) and transmission electron microscopy (TEM) showed agglomeration of these structures in granules of low total porosity (10–1000 Å). Nuclear magnetic resonance (NMR) spectroscopy provided evidence for the presence of oligomeric proanthocyanidins and electron paramagnetic resonance (EPR) spectroscopy revealed a g-factor in the range 2.0034–2.005. Density functional theory (DFT) calculations suggested that the EPR signals can be associated with oligomeric proanthocyanidin structures having 4 and above molecular units of (−)-epicatechin. The discovery of edible melanin in date fruits and its characterization are expected to open a new area of research on its significance to nutritional and sensory characteristics of plant-based foods.

While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the ‘preferred’ orientation problem) remains a complication for most specimens. Existing solutions have relied on biochemical and physical strategies applied to the specimen and are often complex and challenging. Here, we develop spIsoNet, an end-to-end self-supervised deep learning-based software to address map anisotropy and particle misalignment caused by the preferred-orientation problem. Using preferred-orientation views to recover molecular information in under-sampled views, spIsoNet improves both angular isotropy and particle alignment accuracy during 3D reconstruction. We demonstrate spIsoNet’s ability to generate near-isotropic reconstructions from representative biological systems with limited views, including ribosomes, β-galactosidases and a previously intractable hemagglutinin trimer dataset. spIsoNet can also be generalized to improve map isotropy and particle alignment of preferentially oriented molecules in subtomogram averaging. Therefore, without additional specimen-preparation procedures, spIsoNet provides a general computational solution to the preferred-orientation problem. spIsoNet is an end-to-end self-supervised deep learning-based software to address the reconstruction and misalignment challenge in single-particle cryo-EM caused by the preferred-orientation problem. spIsoNet can also improve map isotropy and particle alignment of preferentially oriented molecules during subtomogram averaging in cryogenic electron tomography.

Key Points Since 2007, the number of high-resolution studies of seven transmembrane domain (7TM) receptors (including G protein-coupled receptors) has greatly increased, providing new insights into signalling by a formerly intractable family of integral membrane proteins. Although new structures have revealed many important pharmacological details about specific ligand-binding sites in different receptor classes, how signals are transduced by 7TM receptors from their ligand-binding pockets to their cytoplasmic partners remains poorly understood. Structures of the β 2 -adrenergic receptor in complex with the heterotrimeric G protein G s , and of rhodopsin in complex with arrestin, along with complementary biophysical studies, provide the most detailed views of how such signalling might occur. Both heterotrimeric G proteins and arrestins, and probably G protein-coupled receptor kinases (GRKs), recognize activated 7TM receptors via a common mechanism involving a structural projection that packs into the cytoplasmic pockets formed on activated receptors. The projection is allosterically coupled to other domains, such that receptor docking translates into functional consequences inside the cell. Interactions with activated receptors seem to involve relatively few specific contacts, which probably explains how a relatively small number of G proteins, arrestins and GRKs can recognize the activated state of hundreds of different 7TM receptors. Seven transmembrane domain (7TM) receptors are a vast group of proteins that respond to various cues and transmit signals intracellularly by interacting with heterotrimeric G proteins, arrestins and G protein-coupled receptor kinases. Recent structural analyses reveal common means of interaction between 7TM receptors and these intracellular signalling components. A revolution in the analysis of seven transmembrane domain (7TM) receptors has provided detailed information about how these physiologically important signalling proteins interact with extracellular cues. However, it has proved much more challenging to understand how 7TM receptors convey information to their principal intracellular targets: heterotrimeric G proteins, G protein-coupled receptor kinases and arrestins. Recent structures now suggest a common mechanism that enables these structurally diverse cytoplasmic proteins to 'hitch a ride' on hundreds of different activated 7TM receptors in order to instigate physiological change.

CAMSAP/Patronins regulate microtubule minus-end dynamics. Their end specificity is mediated by their CKK domains, which we proposed recognise specific tubulin conformations found at minus ends. To critically test this idea, we compared the human CAMSAP1 CKK domain (HsCKK) with a CKK domain from Naegleria gruberi (NgCKK), which lacks minus-end specificity. Here we report near-atomic cryo-electron microscopy structures of HsCKK- and NgCKK-microtubule complexes, which show that these CKK domains share the same protein fold, bind at the intradimer interprotofilament tubulin junction, but exhibit different footprints on microtubules. NMR experiments show that both HsCKK and NgCKK are remarkably rigid. However, whereas NgCKK binding does not alter the microtubule architecture, HsCKK remodels its microtubule interaction site and changes the underlying polymer structure because the tubulin lattice conformation is not optimal for its binding. Thus, in contrast to many MAPs, the HsCKK domain can differentiate subtly specific tubulin conformations to enable microtubule minus-end recognition. CKK domain containing CAMSAP/Patronins recognise and regulate microtubule (MT) minus end dynamics. Here the authors compare cryo-EM structures of MT-bound human CKK and Naegleria gruberi CKK which lacks minus-end binding preference, finding NgCKK has a different interaction with, and inability to remodel, its MT binding site, shedding light on the CAMSAP/Patronin end binding mechanism.

Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction. An analysis of AlphaFold protein structure predictions shows that while in many cases the predictions are highly accurate, there are also many instances where the predicted structures or parts of predicted structures do not agree with experimentally resolved data. Therefore, care must be taken when using these predictions for informing structural hypotheses.

Imaging large fields of view at a high magnification requires tiling. Transmission electron microscopes typically have round beam profiles; therefore, tiling across a large area is either imperfect or results in uneven exposures, a problem for dose-sensitive samples. Here, we introduce a square electron beam that can easily be retrofitted in existing microscopes, and demonstrate its application, showing that it can tile nearly perfectly and deliver cryo-electron microscopy imaging with a resolution comparable to conventional set-ups. A square electron beam improves imaging of large fields of view in transmission electron microscopes by facilitating montage tomography of vitrified specimens with no loss in data quality relative to conventional round beams.

Fragmentation of large, imperfect crystals into nanocrystals by sonication, vortexing, or vigorous pipetting facilitates atomic-resolution analysis by the cryo-EM method MicroED. Traditionally, crystallographic analysis of macromolecules has depended on large, well-ordered crystals, which often require significant effort to obtain. Even sizable crystals sometimes suffer from pathologies that render them inappropriate for high-resolution structure determination. Here we show that fragmentation of large, imperfect crystals into microcrystals or nanocrystals can provide a simple path for high-resolution structure determination by the cryoEM method MicroED and potentially by serial femtosecond crystallography.

Bioconjugation is one of the most promising strategies to improve drug delivery, especially in cancer therapy. Biomolecules such as bile acids (BAs) have been intensively explored as carriers, due to their peculiar physicochemical properties and biocompatibility. BAs trafficking is regulated by intracellular lipid-binding proteins and their transport in the liver can be studied using chicken liver Bile Acid-Binding Proteins (cL-BABPs) as a reference model. Therefore, we conceived the idea of developing a BA-conjugate with Mirin, an exonuclease inhibitor of Mre11 endowed with different anticancer activities, to direct its transport to the liver. Following computational analysis of various BAs in complex with cL-BABP, we identified cholic acid (CA) as the most promising candidate as carrier, leading to the synthesis of a novel bioconjugate named CA-M11. As predicted by computational data and confirmed by X-ray crystallographic studies, CA-M11 was able to accommodate into the binding pocket of BABP. Hence, it can enter BAs trafficking in the hepatic compartment and here release Mirin. The effect of CA-M11, evaluated in combination with varying concentrations of Doxorubicin on HepG2 cell line, demonstrated a significant increase in cell mortality compared to the use of the cytotoxic drug or Mirin alone, thus highlighting chemo-sensitizing properties. The promising results regarding plasma stability for CA-M11 validate its potential as a valuable agent or adjuvant for hepatic cancer therapy.