Anti-sense oligonucleotide probing as a structural platform for studying ribonucleoprotein complex assembly.

Cryo-electron microscopy (cryo-EM) has transformed structural biology by enabling the determination of macromolecular structures at near-atomic resolution. The recent Nobel Prizes awarded to John Hopfield and Geoffrey Hinton in Physics, and to David Baker, Demis Hassabis, and John Jumper in Chemistry, highlight the growing convergence of artificial intelligence (AI) and computational innovation in advancing scientific discovery. Cryo-EM has emerged as a powerful tool for elucidating the architectures and dynamics of complex biological assemblies. Its ability to capture multiple conformational states provides mechanistic insights that are critical for understanding molecular function. However, traditional cryo-EM data processing pipelines face challenges in handling large, heterogeneous datasets. Manual particle selection, extensive computational demands, and uneven sampling of conformational states often limit resolution, especially for rare or transient conformations. Recent advances in AI-driven methods are reshaping this landscape. Deep neural networks now facilitate automated particle picking, denoising, classification, and three-dimensional reconstruction, substantially reducing human bias and computational bottlenecks. Machine learning models have also enhanced the accuracy of map interpretation and atomic modeling, accelerating the transition from raw micrographs to high-resolution structures. These developments represent a paradigm shift, positioning AI as an integral component of the “resolution revolution” in structural biology. This comprehensive article examines the state of the art in cryo-electron microscopy, highlighting how artificial intelligence is redefining every stage of the workflow-from automated particle picking and map reconstruction to structure modeling and high-resolution refinement. The integration of deep learning and neural network-based tools has transformed cryo-EM into a data-driven and highly precise discovery platform. By showcasing these innovations, we emphasize AI’s pivotal role in advancing next-generation cryo-EM research and accelerating molecular insights with profound implications for structural biology and drug discovery. Not applicable.

Co-transcriptional assembly is an integral feature of the formation of RNA-protein complexes that mediate translation. For ribosome synthesis, prior studies have indicated that the strict order of transcription of rRNA domains may not be obligatory during bacterial ribosome biogenesis, since a series of circularly permuted rRNAs are viable. In this work, we report the insights into assembly of the bacterial ribosome large subunit (LSU) based on cryo-EM density maps of intermediates that accumulate during in vitro ribosome synthesis using a set of circularly permuted (CiPer) rRNAs. The observed ensemble of twenty-three resolved ribosome large subunit intermediates reveals conserved assembly routes with an underlying hierarchy among cooperative assembly blocks. There are intricate interdependencies for the formation of key structural rRNA helices revealed from the circular permutation of rRNA. While the order of domain synthesis is not obligatory, the order of domain association does appear to proceed with a particular order, likely due to the strong evolutionary pressure on efficient ribosome synthesis. This work reinforces the robustness of the known assembly hierarchy of the bacterial large ribosomal subunit, and offers a coherent view of how efficient assembly of CiPer rRNAs can be understood in that context.

Editorial overview: New protein production tools for structural biology

Efforts in structural biology have targeted the systematic determination of all protein structures through experimental determination or modeling. In recent years, 3-D electron cryomicroscopy (cryoEM) has assumed an increasingly important role in determining the structures of these large macromolecular assemblies to intermediate resolutions (6–10 Å). While these structures provide a snapshot of the assembly and its components in well-defined functional states, the resolution limits the ability to build accurate structural models. In contrast, sequence-based modeling techniques are capable of producing relatively robust structural models for isolated proteins or domains. In this work, we developed and applied a hybrid modeling approach, utilizing cryoEM density and ab initio modeling to produce a structural model for the core domain of a herpesvirus structural protein, VP26. Specifically, this method, first tested on simulated data, utilizes the cryoEM density map as a geometrical constraint in identifying the most native-like models from a gallery of models generated by ab initio modeling. The resulting model for the core domain of VP26, based on the 8.5-Å resolution herpes simplex virus type 1 (HSV-1) capsid cryoEM structure and mutational data, exhibited a novel fold. Additionally, the core domain of VP26 appeared to have a complementary interface to the known upper-domain structure of VP5, its cognate binding partner. While this new model provides for a better understanding of the assembly and interactions of VP26 in HSV-1, the approach itself may have broader applications in modeling the components of large macromolecular assemblies.

Robotic assembly of architectural structures has been an area of research for a few decades. Yet, current methods impose a large number of constraints on the geometry of those structures. In this paper we introduce a method for robotic assembly that enables the construction of double curved self-supporting structures. Latest research challenges have focused on the assembly of sophisticated brick structures and on sensor feedback systems for handling accuracy. We propose an alternative strategy to tackle tolerance handling in complex structures that rely on geometry. The intelligence of the system lies in two main aspects: a subdivision technique that incorporates the robot’s constraints as well as the structural equilibrium of the structure during each step of assembly, in order to omit the use of scaffolding; and a match between geometric information and the robot’s movements in a robot programming environment. As a proof of concept, we fabricated a portion of a full-scale double-curved structure. The structure was assembled without scaffolding by a portable KUKA KR10 on a randomly picked site. This project aims to demonstrate an easy and simple method for robotic assembly that enables the realization of digitally generated complex geometries as concrete complex structures.

Kenneth Holmes catalysed the transformation of ‘protein crystallography’ into ‘structural biology’. His demonstration in 1970, with his student Gerd Rosenbaum, and with the collaboration of Jean Witz from Strasbourg, that synchrotron radiation could be a suitable X- ray source for biological diffraction experiments opened vast new possibilities for visualizing the molecules of life. Holmes’ move from Cambridge to Heidelberg in 1968, which enabled the landmark 1970 experiment at the Deutsches Elektronen-Synchrotron in Hamburg, was a critical event in bringing structural biology to continental Europe—a science born in England and for which Cambridge continued at that time to be the locus of its most important innovations. Holmes’ own analysis of the molecular mechanism of muscle contraction exemplified the power of this new technology and the importance of visualizing the atomic structures of dynamic molecular assemblies.

The assembly of glutamatergic postsynaptic densities (PSDs) seems to involve the gradual recruitment of molecular components from diffuse cellular pools. Whether the glutamate receptors themselves are needed to instruct the structural and molecular assembly of the PSD has hardly been addressed. Here, we engineered Drosophila neuromuscular junctions (NMJs) to express none or only drastically reduced amounts of their postsynaptic non-NMDA-type glutamate receptors. At such NMJs, principal synapse formation proceeded and presynaptic active zones showed normal composition and ultrastructure as well as proper glutamate release. At the postsynaptic site, initial steps of molecular and structural assembly took place as well. However, growth of the nascent PSDs to mature size was inhibited, and proteins normally excluded from PSD membranes remained at these apparently immature sites. Intriguingly, synaptic transmission as well as glutamate binding to glutamate receptors appeared dispensable for synapse maturation. Thus, our data suggest that incorporation of non-NMDA-type glutamate receptors and likely their protein-protein interactions with additional PSD components triggers a conversion from an initial to a mature stage of PSD assembly.

In the most recent years, cryo-electron microscopy has made substantial technical breakthrough in both hardware equipment and software algorithm for structural analysis. It is becoming one of the most important techniques in structural biology and draws attention from more and more biologists. The technical properties of cryo-electron microscopy defines its unique advantages and developing direction. As a fast developing new field, cryo-electron microscopy highly demands for interdisciplinary research efforts. This review introduces the current status of cryo-electron microscopy and discusses the technical challenges of the field. Cryo-electron microscopy may promote the merge of structural biology and cell biology at multiple scales in the future.

In 2021, the release of AlphaFold2 - the DeepMind’s machine-learning protein structure prediction program - revolutionized structural biology. Results of the CASP14 contest were an immense surprise as AlphaFold2 successfully predicted 3D structures of nearly all submitted protein sequences. The AlphaFold2 craze has rapidly spread the life science community since structural biologists as well as untrained biologists have now the possibility to obtain high-confidence protein structures. This revolution is opening new avenues to address challenging biological questions. Moreover, AlphaFold2 is imposing itself as an essential step of any structural biology project, and requires us to revisit our structural biology workflows. On one hand, AlphaFold2 synergizes with experimental methods including X-ray crystallography and cryo-electron microscopy. On the other hand, it is, to date, the only method enabling structural analyses of large and flexible assemblies resistant to experimental approaches. We illustrate this valuable application of AlphaFold2 with the structure prediction of the whole host adhesion device from the Lactobacillus casei bacteriophage J-1. With the ongoing improvement of AlphaFold2 algorithms and notebooks, there is no doubt that AlphaFold2-driven biological stories will increasingly be reported, which questions the future directions of experimental structural biology.

In the recent years, cryo-electron microscopy (cryo-EM) single-particle analysis (SPA) has greatly benefited from a multitude of technological advances cumulating in breaking the atomic-resolution barrier for biological macromolecules. Since then, structural insights by cryo-EM have led to driving rational design of new vaccines and therapeutics due to high throughput and high-resolution screening and data collection technologies. Additionally, cryo-electron tomography (cryo-ET) has become an indispensable tool for structural cell biology. In this presentation we elaborate on the latest Thermo Fisher Scientific innovations for 300kV cryo electron microscopy for SPA and cryo-ET to advance more workflow efficiency and performance. Our ongoing mission is to further improve the connectivity between the cryo-FIB and cryo-TEM for an even more streamlined tomography workflow that is safer, faster and cleaner. Data acquisition and processing can be a significant cryo-ET bottleneck. Our integrated solution, combining Thermo Scientific Tomography 5 and Tomo Live, automates pre-acquisition tasks, enhances productivity with predictive tracking and enables rapid quality assessment. Robust and optimized motion correction helps produce crisp tomograms and image quality needed for sub-tomogram averaging. Results are displayed with new quality metrics on a web platform, making the workflow user-friendly and facilitating structural biology advancements.

At the subcellular level, macromolecules self-assemble to form molecular machinery in which the assembly modes play critical roles: the structural integrity of cell walls that allows mechanical growth, the maintenance and repair of the genetic material, membrane flow control, protein chaperoning, and ATP production, to cite just a few examples. As molecular modeling expands its scope to such systems, structural biologists are faced with the difficulty of understanding the structure and dynamics of these supramolecular assemblies. We present Heligeom, a webserver that offers a simple and efficient means for analyzing and constructing oligomeric assemblies based on user-provided structures of two interacting units. The input 3D coordinates may result from structure determination, simulations, docking trials, or deep-learning tools such as AlphaFold. For a given interface, Heligeom outputs the mathematical helical parameters of the corresponding oligomeric form, including axis, pitch, handedness, number of monomers per turn, etc. The server also allows leveraging these parameters to construct oligomers of specified size, visualizing them interactively, and downloading them as PDB files. For subunits (protomers) having multiple interaction geometries, the different interfaces and their global assembly geometry can be visualized and compared. Heligeom thus allows explicitly linking protomer-protomer interfaces to the oligomeric architecture, illuminating possible sources of plasticity in protein filaments such as mutations or thermal, mechanical, or chemical perturbations. Heligeom thus constitutes an intuitive tool to accompany integrative modeling of oligomeric filamentous assemblies. Examples of its application at different structural levels are presented. Heligeom webserver can be accessed at https://heligeom.galaxy.ibpc.fr.

Ribosome biogenesis is a highly complex process in eukaryotes, involving temporally and spatially regulated ribosomal protein (r-protein) binding and ribosomal RNA remodelling events in the nucleolus, nucleoplasm and cytoplasm. Hundreds of assembly factors, organized into sequential functional groups, facilitate and guide the maturation process into productive assembly branches in and across different cellular compartments. However, the precise mechanisms by which these assembly factors function are largely unknown. Here we use cryo-electron microscopy to characterize the structures of yeast nucleoplasmic pre-60S particles affinity-purified using the epitope-tagged assembly factor Nog2. Our data pinpoint the locations and determine the structures of over 20 assembly factors, which are enriched in two areas: an arc region extending from the central protuberance to the polypeptide tunnel exit, and the domain including the internal transcribed spacer 2 (ITS2) that separates 5.8S and 25S ribosomal RNAs. In particular, two regulatory GTPases, Nog2 and Nog1, act as hub proteins to interact with multiple, distant assembly factors and functional ribosomal RNA elements, manifesting their critical roles in structural remodelling checkpoints and nuclear export. Moreover, our snapshots of compositionally and structurally different pre-60S intermediates provide essential mechanistic details for three major remodelling events before nuclear export: rotation of the 5S ribonucleoprotein, construction of the active centre and ITS2 removal. The rich structural information in our structures provides a framework to dissect molecular roles of diverse assembly factors in eukaryotic ribosome assembly.

The pyruvate dehydrogenase multienzyme complexes are among the largest multifunctional catalytic machines in cells, catalyzing the production of acetyl CoA from pyruvate. We have previously reported the molecular architecture of an 11-MDa subcomplex comprising the 60-mer icosahedral dihydrolipoyl acetyltransferase (E2) decorated with 60 copies of the heterotetrameric (alpha(2)beta(2)) 153-kDa pyruvate decarboxylase (E1) from Bacillus stearothermophilus (Milne, J. L. S., Shi, D., Rosenthal, P. B., Sunshine, J. S., Domingo, G. J., Wu, X., Brooks, B. R., Perham, R. N., Henderson, R., and Subramaniam, S. (2002) EMBO J. 21, 5587-5598). An annular gap of approximately 90 A separates the acetyltransferase catalytic domains of the E2 from an outer shell formed of E1 tetramers. Using cryoelectron microscopy, we present here a three-dimensional reconstruction of the E2 core decorated with 60 copies of the homodimeric 100-kDa dihydrolipoyl dehydrogenase (E3). The E2E3 complex has a similar annular gap of approximately 75 A between the inner icosahedral assembly of acetyltransferase domains and the outer shell of E3 homodimers. Automated fitting of the E3 coordinates into the map suggests excellent correspondence between the density of the outer shell map and the positions of the two best fitting orientations of E3. As in the case of E1 in the E1E2 complex, the central 2-fold axis of the E3 homodimer is roughly oriented along the periphery of the shell, making the active sites of the enzyme accessible from the annular gap between the E2 core and the outer shell. The similarities in architecture of the E1E2 and E2E3 complexes indicate fundamental similarities in the mechanism of active site coupling involved in the two key stages requiring motion of the swinging lipoyl domain across the annular gap, namely the synthesis of acetyl CoA and regeneration of the dithiolane ring of the lipoyl domain.

Native Mass Spectrometry for Structural Biophysics

Specific Interaction between EF-G and RRF and Its Implication for GTP-Dependent Ribosome Splitting into Subunits