Structure of cytoplasmic ring of nuclear pore complex by integrative cryo-EM and AlphaFold

Modulating nanopore size and ion transport using (Anti)-Polyelectrolyte effects inspired by the nuclear pore complex

This study explores the modulation of nanopore size and ion transport through (anti)-polyelectrolyte effects, which is inspired by the nuclear pore complex. We aimed to control ionic selectivity and rectification by applying these effects to synthetic nanopores. Single bicylindrical nanopores were fabricated on the PET membranes and functionalized with PEI/HA or PLL/PAA polyelectrolyte layers. Varying the structural and charge characteristics under different pH levels and ionic strengths revealed that at low salt concentrations, charge density and surface charge polarity significantly impacted ion selectivity and transport. At higher concentrations, conformational changes in the polyelectrolytes influenced the conductance via volume expansion or compaction. Our findings highlight the distinct roles of charge inversion and molecular expansion in nanopore transport, which can be modulated by pH and ionic environment. This work provides insights for developing highly selective ion channels with potential applications in filtration, biosensing, and nanofluidics, where precise ion transport and selective rectification are essential.

Nucleoporins shape germ granule architecture and balance small RNA silencing pathways

Animals use small RNA pathways, such as PIWI-interacting RNA (piRNA) and small interfering RNA (siRNA), to silence harmful genetic elements. In Caenorhabditis elegans, piRNA pathway components are organized into sub-compartments within germ granules near nuclear pore complexes, but the basis and function of this association have remained unclear. Here, our data suggest that germ granule formation and nuclear pore clustering are interdependent processes. We identify the conserved nucleoporins NPP-14/NUP214 and NPP-24/NUP88, along with the germ granule protein EPS-1, as key factors anchoring germ granules to nuclear pores. Loss of these factors leads to disorganized, fused granules and enhanced piRNA silencing. Artificial tethering of granule sub-compartments mimics this effect. However, this increase in piRNA silencing comes at the expense of RNA interference efficiency and heritability. Our findings reveal the molecular factors mediating germ granule-nuclear pore interaction and highlight how spatial organization of RNA silencing machinery fine-tunes gene regulation.

Recent progress and future challenges in structure-based protein-protein interaction prediction

Protein-protein interactions (PPIs) play a fundamental role in cellular processes, and understanding these interactions is crucial for advances in both basic biological science and biomedical applications. This review presents an overview of recent progress in computational methods for modeling protein complexes and predicting PPIs based on 3D structures, focusing on the transformative role of artificial intelligence-based approaches. We further discuss the expanding biomedical applications of PPI research, including the elucidation of disease mechanisms, drug discovery, and therapeutic design. Despite these advances, significant challenges remain in predicting host-pathogen interactions, interactions between intrinsically disordered regions, and interactions related to immune responses. These challenges are worthwhile for future explorations and represent the frontier of research in this field.

Design and development of drug delivery nanocarriers based on liquid-liquid phase separation, improved stability, cell-penetration and anti-cancer effect

Liquid-liquid phase separation (LLPS) of nuclear pore complex (NPC) with nuclear transport proteins (NTPs) via intrinsically disordered regions (IDRs) plays a crucial role in the nucleocytoplasmic transport. The development of efficient targeted delivery systems based on LLPS has attracted widespread attention. Here, we developed nanocarriers of casein peptides, a natural intrinsically disordered proteins (IDPs), modified with fatty acids of different alkyl chains (C10-C18) and decorated by shellac for highly effective drug delivery and cancer therapy. The curcumin (Cur)-loading nanocarriers (CSLNCs) showed excellent stability and dispersity in the natural environment over 30 days, with Cur encapsulation efficiency and loading capacity of ~90 % and ~57 %. Electron microscope (EM) indicated an aggregated homogeneous elliptical shape of CSLNCs(C10) and the morphology of CSLNCs(C18) transited to a distributed cubic shape. CSLNCs(C10, C12, C14 and C18) exhibited cytotoxicity against human lung adenocarcinoma NCI-H1975 cells with an IC50 value of 17.5 μM, 17.3 μM, 10.2 μM and 19.3 μM after 24 h of incubation, respectively. CSLNCs were also found to inhibit the cell wound healing with a migration rate of 12.72 %, 10.93 %, 4.28 % and 13.62 %, respectively. CSLNCs especially increased the percentage of late apoptotic cells. As indications of confocal microscopy, the fluorescence intensities of NCI-H1975 cells were enhanced with a cytosolic distribution and noticeably florescence in the nucleus after 0.5 h of incubation CSLNCs. CSLNCs treated cells adopted a rounded morphology with a dramatic reduction in fluorescence intensity after 1 h of incubation. Among CSLNCs, CSLNCs(C14) improved considerably the cytotoxicity activity and intercellular localization in the nucleus. The cell-penetration ability was also confirmed by the binding of CSLNCs in a model bicelles membrane system composed of DMPC and DHPC investigated by 1H NMR. It was proposed that CSLNCs with cell-penetrating and nuclear targeting performance may regulate the LLPS of nuclear pore complex and thus improved its nuclear penetration and cytotoxic activity.

Interaction mapping between nucleoporins in the fission yeast Schizosaccharomyces pombe using mass-spectrometry

Nuclear pore complexes (NPCs) act as gateways across the nuclear envelope for molecular transport between the nucleus and the cytoplasm in eukaryotes. NPCs consist of several subcomplexes formed by multiple copies of approximately 30 different proteins known as nucleoporins (Nups). In the fission yeast Schizosaccharomyces pombe, the NPC structure is unique, particularly in its outer ring subcomplexes, where the cytoplasmic and nucleoplasmic outer rings are composed of distinct sets of proteins. However, it remains unclear how this unique outer ring structure in S. pombe is supported by interactions between subcomplexes or individual Nups. In this study, we investigated protein-protein interactions between S. pombe Nups using mass spectrometry and identified Nups that interact with each subcomplex or a specific Nup. The cytoplasmic outer ring Nups bind to both the cytoplasmic filament Nups and the inner ring Nups, while the nucleoplasmic outer ring Nups bind to the nuclear basket Nups in addition to the inner ring Nups. Among the inner ring Nups, Nup155 interacts with most of the cytoplasmic and nucleoplasmic outer ring Nups, suggesting that Nup155 may serve as a hub supporting the uniquely asymmetric outer ring structure of the S. pombe NPC.

Role of pore dilation in molecular transport through the nuclear pore complex: Insights from polymer scaling theory

The nuclear pore complex (NPC), a channel within the nuclear envelope filled with intrinsically disordered proteins, regulates the transport of macromolecules between the nucleus and the cytoplasm. Recent studies have highlighted the NPC's ability to adjust its diameter in response to the membrane tension, underscoring the importance of exploring how variations in pore size influence molecular transport through the NPC. In this study, we investigated the relationship between pore size and transport rate and proposed a mathematical model describing this connection. We began by theoretically analyzing how the pore size scales with the characteristic dimensions of the mesh-like structure within the pore. By introducing key assumptions about how the meshwork structure influences molecular diffusion, we derived a mathematical expression for the transport rate based on the size of the pore and the transported molecules. To validate our model, we conducted Brownian dynamics simulations using a coarse-grained representation of the NPC. These simulations, performed across a range of pore sizes, demonstrated strong agreement with our model's predictions, confirming its accuracy and applicability. Our model is specifically tailored for small-to-medium-sized molecules, approximately 5 nanometers in size, making it relevant to a wide range of transcription factors and signaling molecules. It also extends to molecules with weak and transient interactions with FG-Nups, such as importin-β. By presenting this model formula, our study offers a quantitative framework for analyzing the effects of pore dilation on nucleocytoplasmic transport.

Emerging frontiers in protein structure prediction following the AlphaFold revolution

Models of protein structures enable molecular understanding of biological processes. Current protein structure prediction tools lie at the interface of biology, chemistry and computer science. Millions of protein structure models have been generated in a very short space of time through a revolution in protein structure prediction driven by deep learning, led by AlphaFold. This has provided a wealth of new structural information. Interpreting these predictions is critical to determining where and when this information is useful. But proteins are not static nor do they act alone, and structures of proteins interacting with other proteins and other biomolecules are critical to a complete understanding of their biological function at the molecular level. This review focuses on the application of state-of-the-art protein structure prediction to these advanced applications. We also suggest a set of guidelines for reporting AlphaFold predictions.

Protein-Variant-Phenotype Study of NBAS Using AlphaFold in the Aspect of SOPH Syndrome

NBAS gene variants cause phenotypically distinct and nonoverlapping conditions, SOPH syndrome and ILFS2. NBAS is a so-called "moonlighting" protein responsible for retrograde membrane trafficking and nonsense-mediated decay. However, its three-dimensional model and the nature of its possible interactions with other proteins have remained elusive. Here, we used AlphaFold to predict protein-protein interaction (PPI) sites and mapped them to NBAS pathogenic variants. We repeated in silico milestone studies of the NBAS protein to explain the multisystem phenotype of its variants, with particular emphasis on the SOPH variant (p.R1914H). We revealed the putative binding sites for the main interaction partners of NBAS and assessed the implications of these binding sites for the subdomain architecture of the NBAS protein. Using AlphaFold, we disclosed the far-reaching impact of NBAS variants on the development of each phenotypic trait in patients with NBAS-related pathologies.

Integrative spatiotemporal modeling of biomolecular processes: Application to the assembly of the nuclear pore complex

Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. First, for each time point, a set of coarse models of compositional and structural heterogeneity is computed (heterogeneity models). Second, for each heterogeneity model, a set of static integrative structure models is computed (a snapshot model). Finally, these snapshot models are selected and connected into a series of trajectories that optimize the likelihood of both the snapshot models and transitions between them (a trajectory model). The method is demonstrated by application to the assembly process of the human nuclear pore complex in the context of the reforming nuclear envelope during mitotic cell division, based on live-cell correlated electron tomography, bulk fluorescence correlation spectroscopy-calibrated quantitative live imaging, and a structural model of the fully assembled nuclear pore complex. Modeling of the assembly process improves the model precision over static integrative structure modeling alone. The method is applicable to a wide range of time-dependent systems in cell biology and is available to the broader scientific community through an implementation in the open source Integrative Modeling Platform (IMP) software.

Neutrophil elastase binds at the central domain of extracellular Toll-like receptor 4: AI prediction, docking, and validation in disease model

The interaction between Neutrophil Elastase (NE) and Toll-like receptor 4 (TLR4) has attracted substantial scientific attention, particularly regarding its potential role in cardiovascular diseases. Employing AlphaFold2, biomolecular docking, and MMGBSA calculation we aimed to predict their binding and validated the results through a co-immunoprecipitation study in a rat model with isoproterenol (ISO) -induced cardiac hypertrophy. Our findings strongly suggest a specific and plausible interaction between rat NE and rat TLR4, distinct from other neutrophil-derived serine proteases. Notably, AlphaFold2's precision was confirmed through cross-validation with known protein crystal structures, while Consurf analysis emphasized the evolutionary variable to conserve the rat NE - rat TLR4 binding site. HADDOCK, RosettaDock, ZDOCK, MD simulation, MMGBSA calculations, and superimposition with the stabilized structure complex all predicted strong binding between rat NE and rat TLR4. Our animal experiments revealed elevated NE and TLR4 expression in the hypertrophied myocardium following ISO infusion, with data confirming the physical interaction between NE and TLR4. Overall, this study sheds light on the intricate molecular association between NE and TLR4, underlining their potential significance in cardiovascular pathophysiology. Furthermore, it underscores AlphaFold2's reliability as a robust tool for predicting protein-protein interactions and complex structures.

DeepPath: Overcoming data scarcity for protein transition pathway prediction using physics-based deep learning

The structural dynamics of proteins play a crucial role in their function, yet most experimental and deep learning methods produce only static models. While molecular dynamics (MD) simulations provide atomistic insight into conformational transitions, they remain computationally prohibitive, particularly for large-scale motions. Here, we introduce DeepPath, a deep-learning-based framework that rapidly generates physically realistic transition pathways between known protein states. Unlike conventional supervised learning approaches, DeepPath employs active learning to iteratively refine its predictions, leveraging molecular mechanical force fields as an oracle to guide pathway generation. We validated DeepPath on three biologically relevant test cases: SHP2 activation, CdiB H1 secretion, and the BAM complex lateral gate opening. DeepPath accurately predicted the transition pathways for all test cases, reproducing key intermediate structures and transient interactions observed in previous studies. Notably, DeepPath also predicted an intermediate between the BAM inward- and outward-open states that closely aligns with an experimentally observed hybrid-barrel structure (TMscore = 0.91). Across all cases, DeepPath achieved accurate pathway predictions within hours, showcasing an efficient alternative to MD simulations for exploring protein conformational transitions.

Slice'N'Dice: maximizing the value of predicted models for structural biologists

With the advent of next-generation modelling methods, such as AlphaFold2, structural biologists are increasingly using predicted structures to obtain structure solutions via molecular replacement (MR) or model fitting in single-particle cryogenic sample electron microscopy (cryoEM). Differences between the domain-domain orientations represented in a predicted model and a crystal structure are often a key limitation when using predicted models. Slice'N'Dice is a software package designed to address this issue by first slicing models into distinct structural units and then automatically placing the slices using either Phaser, MOLREP or PowerFit. The slicing step can use the AlphaFold predicted aligned error (PAE) or can operate via a variety of Cα-atom-based clustering algorithms, extending the applicability to structures of any origin. The number of splits can either be selected by the user or determined automatically. Slice'N'Dice is available for both MR and automated map fitting in the CCP4 and CCP-EM software suites.

Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR

We introduce AlphaFold-NMR, a novel approach to NMR structure determination that reveals previously undetected protein conformational states. Unlike conventional NMR methods that rely on NOE-derived spatial restraints, AlphaFold-NMR combines AI-driven conformational sampling with Bayesian scoring of realistic protein models against NOESY and chemical shift data. This method uncovers alternative conformational states of the enzyme Gaussia luciferase, involving large-scale changes in the lid, binding pockets, and other surface cavities. It also identifies similar yet distinct conformational states of the human tumor suppressor Cyclin-Dependent Kinase 2-Associated Protein 1. These studies demonstrate the potential of AI-based modeling with enhanced sampling to generate diverse structural models followed by conformer selection and validation with experimental data as an alternative to traditional restraint-satisfaction protocols for protein NMR structure determination. The AlphaFold-NMR framework enables discovery of conformational heterogeneity and cryptic pockets that conventional NMR analysis methods do not distinguish, providing new insights into protein structure-function relationships.

Conformational dynamics of the nuclear pore complex central channel

The nuclear pore complex (NPC) is a vital regulator of molecular transport between the nucleus and cytoplasm in eukaryotic cells. At the heart of the NPC's function are intrinsically disordered phenylalanineglycine-rich nucleoporins (FG-Nups), which form a dynamic permeability barrier within the central channel. This disordered nature facilitates efficient nucleocytoplasmic transport but also poses significant challenges to its characterization, especially within the nano-confined environment of the NPC. Recent advances in experimental techniques, such as cryo-electron microscopy, atomic force microscopy, fluorescence microscopy, and nuclear magnetic resonance, along with computational modeling, have illuminated the conformational flexibility of FG-Nups, which underpins their functional versatility. This review synthesizes these advancements, emphasizing how disruptions in FG-Nup behavior-caused by mutations or pathological interactions-contribute to diseases such as neurodegenerative disorders, aging-related decline, and viral infections. Despite progress, challenges persist in deciphering FG-Nup dynamics within the crowded and complex cellular environment, especially under pathological conditions. Addressing these gaps is critical for advancing therapeutic strategies targeting NPC dysfunction in disease progression.

Nuclear pore permeability and fluid flow are modulated by its dilation state

Changing environmental conditions necessitate rapid adaptation of cytoplasmic and nuclear volumes. We use the slime mold Dictyostelium discoideum, known for its ability to tolerate extreme changes in osmolarity, to assess which role nuclear pore complexes (NPCs) play in achieving nuclear volume adaptation and relieving mechanical stress. We capitalize on the unique properties of D. discoideum to quantify fluid flow across NPCs. D. discoideum has an elaborate NPC structure in situ. Its dilation state affects NPC permeability for nucleocytosolic flow. Based on mathematical concepts adapted from hydrodynamics, we conceptualize this phenomenon as porous flow across NPCs, which is distinct from canonically characterized modes of nucleocytoplasmic transport because of its dependence on pressure. Viral NPC blockage decreased nucleocytosolic flow. Our results may be relevant for any biological conditions that entail rapid nuclear size adaptation, including metastasizing cancer cells, migrating cells, or differentiating tissues.

The functions of herpesvirus shuttling proteins in the virus lifecycle

During viral infection, the transport of various proteins between the nucleus and cytoplasm plays an important role in the viral lifecycle. Shuttling proteins are key factors in the transmission of nucleocytoplasmic information within cells and usually contain nuclear localization signals and nuclear export signals to mediate correct positioning for themselves and other proteins. The nucleocytoplasmic transport process is carried out through the nuclear pore complex on the nuclear envelope and is mediated by specific protein carriers. The viral proteins that function through nucleocytoplasmic shuttling in herpesviruses have gradually been identified as research advances. This article provides an overview of how shuttling proteins utilize nucleocytoplasmic shuttling signals and nuclear transport receptors for nucleocytoplasmic transport, as well as discusses how herpesvirus shuttling proteins enhance the effective infection of viruses by affecting their lifecycle and participating in innate immunity, this review provides a reference for understanding the pathogenesis of herpesvirus infection and determining new antiviral strategies.

Polymeric nanocarriers for therapeutic gene delivery

The recent commercialization of gene products has sparked significant interest in gene therapy, necessitating efficient and precise gene delivery via various vectors. Currently, viral vectors and lipid-based nanocarriers are the predominant choices and have been extensively investigated and reviewed. Beyond these vectors, polymeric nanocarriers also hold the promise in therapeutic gene delivery owing to their versatile functionalities, such as improving the stability, cellar uptake and endosomal escape of nucleic acid drugs, along with precise delivery to targeted tissues. This review presents a brief overview of the status quo of the emerging polymeric nanocarriers for therapeutic gene delivery, focusing on key cationic polymers, nanocarrier types, and preparation methods. It also highlights targeted diseases, strategies to improve delivery efficiency, and potential future directions in this research area. The review is hoped to inspire the development, optimization, and clinical translation of highly efficient polymeric nanocarriers for therapeutic gene delivery.

An outlook on structural biology after AlphaFold: tools, limits and perspectives

AlphaFold and similar groundbreaking, AI-based tools, have revolutionized the field of structural bioinformatics, with their remarkable accuracy in ab-initio protein structure prediction. This success has catalyzed the development of new software and pipelines aimed at incorporating AlphaFold's predictions, often focusing on addressing the algorithm's remaining challenges. Here, we present the current landscape of structural bioinformatics shaped by AlphaFold, and discuss how the field is dynamically responding to this revolution, with new software, methods, and pipelines. While the excitement around AI-based tools led to their widespread application, it is essential to acknowledge that their practical success hinges on their integration into established protocols within structural bioinformatics, often neglected in the context of AI-driven advancements. Indeed, user-driven intervention is still as pivotal in the structure prediction process as in complementing state-of-the-art algorithms with functional and biological knowledge.

The structure of apolipoprotein B100 from human low-density lipoprotein

Low-density lipoprotein (LDL) has a central role in lipid and cholesterol metabolism and is a key agent in the development and progression of atherosclerosis, the leading cause of mortality worldwide1,2. Apolipoprotein B100 (apoB100), one of the largest proteins in the genome, is the primary structural and functional component of LDL, yet its size and complex lipid associations have posed major challenges for structural studies3. Here we present the structure of apoB100 resolved to subnanometre resolution in most regions using an integrative approach of cryo-electron microscopy, AlphaFold24 and molecular-dynamics-based refinement5. The structure consists of a large globular N-terminal domain and an approximately 61-nm-long continuous amphipathic β-sheet that wraps around the LDL particle like a belt. Distributed quasi-symmetrically across the two sides of the β-belt are nine strategically located interstrand inserts that extend across the lipid surface to provide additional structural support through a network of long-range interactions. We further compare our structure to a comprehensive list of more than 200 intramolecular cross-links and find close agreement between the two. These results suggest a mechanism for how the various domains of apoB100 act in concert to maintain LDL shape and cohesion across a range of particle sizes. More generally, they advance our fundamental understanding of LDL synthesis, form and function, and will help to accelerate the design of potential therapeutics.

The role of ALDHs in lipid peroxidation-related diseases

Lipid peroxidation presents the oxidative degradation of polyunsaturated fatty acids lincited by reactive species. Excessive accumulation of lipid peroxidation byproducts, including 4-hydroxy-2-nonenal (4-HNE) and malondialdehyde (MDA), causes protein dysfunction and various illnesses. Aldehyde dehydrogenases (ALDHs) catalyze the metabolism of both endogenous and exogenous aldehydes. These enzymes participate in detoxification and intermediary metabolism. Contemporary research has affirmed the involvement of both enzymatic and non-enzymatic pathways of ALDHs in modulating the evolution of diseases associated with lipid peroxidation. This review provides an overview of the biological functions and clinical implications concerning the enzymatic and non-enzymatic pathways of ALDHs in diseases related to lipid peroxidation, such as, non-alcoholic fatty liver disease (NAFLD), atherosclerosis, and type 2 diabetes (T2DM). Furthermore, the activators or inhibitors of ALDHs represent a promising therapeutic strategy for lipid peroxidation-related diseases.

Opening the gate: Complexity and modularity of the nuclear pore scaffold and basket

Nuclear pore complexes (NPCs) are giant molecular assemblies that form the gateway between the nucleus and the cytoplasm and accommodate the bidirectional transport of a large variety of cargoes. Recent years have seen tremendous advances in our understanding of their building principles and have in particular called attention to the flexibility and variability of NPC composition and structure. Here, we review these recent advances and discuss how the newest technologies push the boundaries of nuclear pore research forward, with a specific highlight on the NPC scaffold and a prominent pore appendage, the nuclear basket, whose architecture has long been elusive.

Nup107 contributes to the maternal-to-zygotic transition by preventing the premature nuclear export of pri-miR427

Emerging evidence suggests that the nuclear pore complex can have unique compositions and distinct nucleoporin functions in different cells. Here, we show that Nup107, a key component of the NPC scaffold, varies in expression over development: it is expressed at higher levels in the blastula compared to the gastrula, suggesting a crucial role before gastrulation in Xenopus. We find that depletion of Nup107 affects the differentiation of the early germ layers leading to an expansion of the ectoderm at the expense of endoderm and mesoderm. By analyzing an RNA-sequencing time course, we observed that depletion of Nup107 affects the maternal-zygotic transition by delaying the degradation of maternal transcripts that occurs as zygotic transcription begins. The transcripts are enriched in recognition sites for miR427, a conserved microRNA that destabilizes maternal transcripts including REST, which encodes a Kruppel-type zinc-finger transcription factor that we demonstrate is crucial for ectodermal cell fates. Mechanistically, we show that Nup107 is required to prevent the premature export of pri-miR427 transcript before processing. Nup107 depletion leads to the reduced production of mature miR427 and maternal transcript stabilization. We conclude that high levels of Nup107 in the early embryo are crucial for the nuclear retention and subsequent processing of pri-miR427 transcripts that is required for timely maternal RNA clearance to enable gastrulation.

Graph-Theoretical Prediction and Analysis of Biologically Relevant Substructures in an Open and Closed Conformation of Respiratory Complex I

Protein complexes are functional modules within the hierarchy of the cellular organization. Large protein complexes often consist of smaller functional modules, which are biologically relevant substructures with specific functions. The first protein complex of the respiratory chain, complex I, consists of functional modules for the electron transfer from NADH to quinone and the translocation of protons across the inner mitochondrial membrane. Complex I is well-characterized and biological modules have been experimentally assigned. Nevertheless, there is an ongoing discussion about the coupling of the electron transfer and the proton translocation, and about the proton translocation pathways.We modelled a mammalian complex I in open and closed conformations as complex graphs, with vertices representing protein chains and edges representing chain-chain contacts. Using a graph-theoretical method, we computed the structural modules of complex I, which indicated functional, biological substructures. We described characteristic structural features of complex I and observed a rearrangement of the structural modules. The changes in the structural modules indicated the formation of a functional module in the membrane arm of complex I during the conformational change.

Nuclear-Targeting Peptides for Cancer Therapy

Nucleus is the central regulator of cells that controls cell proliferation, metabolism, and cell cycle, and is considered the most important organelle in cells. The precision medicine that can achieve nuclear targeting has achieved good therapeutic effects in anti-tumor therapy. However, the presence of biological barriers such as cell membranes and nuclear membranes in cells limit the delivery of therapeutic agents to the nucleus. Therefore, developing effective nuclear-targeting drug delivery strategies is particularly important. Nuclear-targeting peptides are a class of functional peptides that can penetrate cell membranes and target the nucleus. They mainly recognize and bind to the nuclear transport molecules (such as Importin-α/β) and transport the therapeutic agents to the nucleus through nuclear pore complexes (NPC). This review summarizes the most recent developments of strategies for anti-tumor therapy utilizing nuclear-targeting peptides, which will ultimately contribute to the development of more effective nuclear-targeting strategies to achieve better anti-tumor outcomes.

DiffModeler: large macromolecular structure modeling for cryo-EM maps using a diffusion model

Cryogenic electron microscopy (cryo-EM) has now been widely used for determining multichain protein complexes. However, modeling a large complex structure, such as those with more than ten chains, is challenging, particularly when the map resolution decreases. Here we present DiffModeler, a fully automated method for modeling large protein complex structures. DiffModeler employs a diffusion model for backbone tracing and integrates AlphaFold2-predicted single-chain structures for structure fitting. DiffModeler showed an average template modeling score of 0.88 and 0.91 for two datasets of cryo-EM maps of 0-5 Å resolution and 0.92 for intermediate resolution maps (5-10 Å), substantially outperforming existing methodologies. Further benchmarking at low resolutions (10-20 Å) confirms its versatility, demonstrating plausible performance.

Nuclear pore dysfunction and disease: a complex opportunity

The separation of genetic material from bulk cytoplasm has enabled the evolution of increasingly complex organisms, allowing for the development of sophisticated forms of life. However, this complexity has created new categories of dysfunction, including those related to the movement of material between cellular compartments. In eukaryotic cells, nucleocytoplasmic trafficking is a fundamental biological process, and cumulative disruptions to nuclear integrity and nucleocytoplasmic transport are detrimental to cell survival. This is particularly true in post-mitotic neurons, where nuclear pore injury and errors to nucleocytoplasmic trafficking are strongly associated with neurodegenerative disease. In this review, we summarize the current understanding of nuclear pore biology in physiological and pathological contexts and discuss potential therapeutic approaches for addressing nuclear pore injury and dysfunctional nucleocytoplasmic transport.

Deciphering the intrinsically disordered characteristics of the FG-Nups through the lens of polymer physics

The nuclear pore complex (NPC) is a critical gateway regulating molecular transport between the nucleus and cytoplasm. It allows small molecules to pass freely, while larger molecules require nuclear transport receptors to traverse the barrier. This selective permeability is maintained by phenylalanine-glycine-rich nucleoporins (FG-Nups), intrinsically disordered proteins that fill the NPC's central channel. The disordered and flexible nature of FG-Nups complicates their spatial characterization with conventional structural biology techniques. To address this challenge, polymer physics offers a valuable framework for describing FG-Nup behavior, reducing their complex structures to a few key parameters. In this review, we explore how polymer physics models FG-Nups using these parameters and discuss experimental efforts to quantify them in various contexts, providing insights into the conformational properties of FG-Nups.

Cytoplasmic nucleoporin assemblage: the cellular artwork in physiology and disease

Nucleoporins, essential proteins building the nuclear pore, are pivotal for ensuring nucleocytoplasmic transport. While traditionally confined to the nuclear envelope, emerging evidence indicates their presence in various cytoplasmic structures, suggesting potential non-transport-related roles. This review consolidates findings on cytoplasmic nucleoporin assemblies across different states, including normal physiological conditions, stress, and pathology, exploring their structural organization, formation dynamics, and functional implications. We summarize the current knowledge and the latest concepts on the regulation of nucleoporin homeostasis, aiming to enhance our understanding of their unexpected roles in physiological and pathological processes.

Nup210 Promotes Colorectal Cancer Progression by Regulating Nuclear Plasma Transport

The nuclear pore complex (NPC) regulates nucleoplasmic transport, transcription, and genomic integrity in eukaryotic cells. However, little is known about how NPC works in cancer. In this study, we investigated the role of the nuclear pore protein 210 (Nucleoporin 210, Nup210) in colorectal cancer (CRC). Bioinformatics analysis revealed that the expression of Nup210 was increased in CRC and was associated with poor patient prognosis, but it was not a statistically significant independent prognostic factor. Moreover, knockdown of Nup210 in CRC cells inhibited the proliferation, invasion, and metastasis of CRC cells in vivo and in vitro. Additionally, nuclear size and nuclear plasma material transport capacity decreased along with the number and density of NPCs on the surface of CRC cells when Nup210 expression was inhibited. Furthermore, Nup210 required nuclear localization sequences (NLS) to localize to the nuclear membrane surface and interact with importin-α/β, which in turn affected the transit of nuclear plasma material. Importazole, a small molecule inhibitor of importin, along with therapy that targets the Nup210 protein is anticipated to be a novel strategy for CRC treatment. Their combination may be able to more effectively lower CRC tumor load. In conclusion, Nup210 modulates cellular nucleoplasmic transport capability and cell surface NPC density via NLS, thus promoting CRC progression. This discovery validates the molecular function of NPC in the development of CRC and provides a theoretical foundation for NPC-regulated nuclear import targeting as a therapeutic strategy for CRC.

Cell-Free Nonequilibrium Assembly for Hierarchical Protein/Peptide Nanopillars

Cells contain intricate protein nanostructures, but replicating them outside of cells presents challenges. One such example is the vertical fibronectin pillars observed in embryos. Here, we demonstrate the creation of cell-free vertical fibronectin pillar mimics using nonequilibrium self-assembly. Our approach utilizes enzyme-responsive phosphopeptides that assemble into nanotubes. Enzyme action triggers shape changes in peptide assemblies, driving the vertical growth of protein nanopillars into bundles. These bundles, with peptide nanotubes serving as a template to remodel fibronectin, can then recruit collagen, which forms aggregates or bundles depending on their types. Nanopillar formation relies on enzyme-catalyzed nonequilibrium self-assembly and is governed by the concentrations of enzyme, protein, peptide, the structure of the peptide, and peptide assembly morphologies. Cryo-EM reveals unexpected nanotube thinning and packing after dephosphorylation, indicating a complex sculpting process during assembly. Our study demonstrates a cell-free method for constructing intricate, multiprotein nanostructures with directionality and composition.

Modular Structure and Polymerization Status of GABAA Receptors Illustrated with EM Analysis and AlphaFold2 Prediction

Type-A γ-aminobutyric acid (GABAA) receptors are channel proteins crucial to mediating neuronal balance in the central nervous system (CNS). The structure of GABAA receptors allows for multiple binding sites and is key to drug development. Yet the formation mechanism of the receptor's distinctive pentameric structure is still unknown. This study aims to investigate the role of three predominant subunits of the human GABAA receptor in the formation of protein pentamers. Through purifying and refolding the protein fragments of the GABAA receptor α1, β2, and γ2 subunits, the particle structures were visualised with negative staining electron microscopy (EM). To aid the analysis, AlphaFold2 was used to compare the structures. Results show that α1 and β2 subunit fragments successfully formed homo-oligomers, particularly homopentameric structures, while the predominant heteropentameric GABAA receptor was also replicated through the combination of the three subunits. However, homopentameric structures were not observed with the γ2 subunit proteins. A comparison of the AlphaFold2 predictions and the previously obtained cryo-EM structures presents new insights into the subunits' modular structure and polymerization status. By performing experimental and computational studies, a deeper understanding of the complex structure of GABAA receptors is provided. Hopefully, this study can pave the way to developing novel therapeutics for neuropsychiatric diseases.

O-GlcNAc transferase congenital disorder of glycosylation (OGT-CDG): Potential mechanistic targets revealed by evaluating the OGT interactome

O-GlcNAc transferase (OGT) is the sole enzyme responsible for the post-translational modification of O-GlcNAc on thousands of target nucleocytoplasmic proteins. To date, nine variants of OGT that segregate with OGT Congenital Disorder of Glycosylation (OGT-CDG) have been reported and characterized. Numerous additional variants have been associated with OGT-CDG, some of which are currently undergoing investigation. This disorder primarily presents with global developmental delay and intellectual disability (ID), alongside other variable neurological features and subtle facial dysmorphisms in patients. Several hypotheses aim to explain the etiology of OGT-CDG, with a prominent hypothesis attributing the pathophysiology of OGT-CDG to mutations segregating with this disorder disrupting the OGT interactome. The OGT interactome consists of thousands of proteins, including substrates as well as interactors that require noncatalytic functions of OGT. A key aim in the field is to identify which interactors and substrates contribute to the primarily neural-specific phenotype of OGT-CDG. In this review, we will discuss the heterogenous phenotypic features of OGT-CDG seen clinically, the variable biochemical effects of mutations associated with OGT-CDG, and the use of animal models to understand this disorder. Furthermore, we will discuss how previously identified OGT interactors causal for ID provide mechanistic targets for investigation that could explain the dysregulated gene expression seen in OGT-CDG models. Identifying shared or unique altered pathways impacted in OGT-CDG patients will provide a better understanding of the disorder as well as potential therapeutic targets.

Docking a flexible basket onto the core of the nuclear pore complex

The nuclear basket attaches to the nucleoplasmic side of the nuclear pore complex (NPC), coupling transcription to mRNA quality control and export. The basket expands the functional repertoire of a subset of NPCs in Saccharomyces cerevisiae by drawing a unique RNA/protein interactome. Yet, how the basket docks onto the NPC core remains unknown. By integrating AlphaFold-based interaction screens, electron microscopy and membrane-templated reconstitution, we uncovered a membrane-anchored tripartite junction between basket and NPC core. The basket subunit Nup60 harbours three adjacent short linear motifs, which connect Mlp1, a parallel homodimer consisting of coiled-coil segments interrupted by flexible hinges, and the Nup85 subunit of the Y-complex. We reconstituted the Y-complex•Nup60•Mlp1 assembly on a synthetic membrane and validated the protein interfaces in vivo. Here we explain how a short linear motif-based protein junction can substantially reshape NPC structure and function, advancing our understanding of compositional and conformational NPC heterogeneity.

The adhesin RadD enhances Fusobacterium nucleatum tumour colonization and colorectal carcinogenesis

Fusobacterium nucleatum can bind to host cells and potentiate intestinal tumorigenesis. Here we used a genome-wide screen to identify an adhesin, RadD, which facilitates the attachment of F. nucleatum to colorectal cancer (CRC) cells in vitro. RadD directly binds to CD147, a receptor overexpressed on CRC cell surfaces, which initiated a PI3K-AKT-NF-κB-MMP9 cascade, subsequently enhancing tumorigenesis in mice. Clinical specimen analysis showed that elevated radD gene levels in CRC tissues correlated positively with activated oncogenic signalling and poor patient outcomes. Finally, blockade of the interaction between RadD and CD147 in mice effectively impaired F. nucleatum attachment and attenuated F. nucleatum-induced oncogenic response. Together, our study provides insights into an oncogenic mechanism driven by F. nucleatum RadD and suggests that the RadD-CD147 interaction could be a potential therapeutic target for CRC.

Interdependence between Nuclear Pore Gatekeepers and Genome Caretakers: Cues from Genome Instability Syndromes

This review starts off with the first germline homozygous variants of the Nucleoporin 98 gene (NUP98) in siblings whose clinical presentation recalls Rothmund-Thomson (RTS) and Werner (WS) syndromes. The progeroid phenotype caused by a gene associated with haematological malignancies and neurodegenerative disorders primed the search for interplay between caretakers involved in genome instability syndromes and Nuclear Pore Complex (NPC) components. In the context of basic information on NPC architecture and functions, we discuss the studies on the interdependence of caretakers and gatekeepers in WS and Hereditary Fibrosing Poikiloderma (POIKTMP), both entering in differential diagnosis with RTS. In WS, the WRN/WRNIP complex interacts with nucleoporins of the Y-complex and NDC1 altering NPC architecture. In POIKTMP, the mutated FAM111B, recruited by the Y-complex's SEC13 and NUP96, interacts with several Nups safeguarding NPC structure. The linkage of both defective caretakers to the NPC highlights the attempt to activate a repair hub at the nuclear periphery to restore the DNA damage. The two separate WS and POIKTMP syndromes are drawn close by the interaction of their damage sensors with the NPC and by the shared hallmark of short fragile telomeres disclosing a major role of both caretakers in telomere maintenance.

Generative artificial intelligence performs rudimentary structural biology modeling

Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in scientific research. Intriguingly, capabilities of generative pre-trained transformer (GPT) language models beyond the scope of natural language tasks have recently been identified. Here we explored how GPT-4 might be able to perform rudimentary structural biology modeling. We prompted GPT-4 to model 3D structures for the 20 standard amino acids and an α-helical polypeptide chain, with the latter incorporating Wolfram mathematical computation. We also used GPT-4 to perform structural interaction analysis between the anti-viral nirmatrelvir and its target, the SARS-CoV-2 main protease. Geometric parameters of the generated structures typically approximated close to experimental references. However, modeling was sporadically error-prone and molecular complexity was not well tolerated. Interaction analysis further revealed the ability of GPT-4 to identify specific amino acid residues involved in ligand binding along with corresponding bond distances. Despite current limitations, we show the current capacity of natural language generative AI to perform basic structural biology modeling and interaction analysis with atomic-scale accuracy.

AlphaFold two years on: Validation and impact

Two years on from the initial release of AlphaFold, we have seen its widespread adoption as a structure prediction tool. Here, we discuss some of the latest work based on AlphaFold, with a particular focus on its use within the structural biology community. This encompasses use cases like speeding up structure determination itself, enabling new computational studies, and building new tools and workflows. We also look at the ongoing validation of AlphaFold, as its predictions continue to be compared against large numbers of experimental structures to further delineate the model's capabilities and limitations.

Insights into the interaction between UGGT, the gatekeeper of folding in the ER, and its partner, the selenoprotein SEP15

The enzyme UDP-glucose: glycoprotein glucosyltransferase (UGGT) is the gatekeeper of protein folding within the endoplasmic reticulum (ER). One-third of the human proteome traverses the ER where folding and maturation are facilitated by a complex protein homeostasis network. Both glycan modifications and disulfide bonds are of key importance in the maturation of these ER proteins. The actions of UGGT are intimately linked to the glycan code for folding and maturation of secretory proteins in the ER. UGGT selectively glucosylates the N-linked glycan of misfolded proteins so that they can reenter the lectin-folding chaperone cycle and be retained within the ER for further attempts at folding. An intriguing aspect of UGGT function is its interaction with its poorly understood cochaperone, the 15 kDa selenoprotein known as SELENOF or SEP15. This small protein contains a rare selenocysteine residue proposed to act as an oxidoreductase toward UGGT substrates. AlphaFold2 predictions of the UGGT1/SEP15 complex provide insight into this complex at a structural level. The predicted UGGT1/SEP15 interaction interface was validated by mutagenesis and coimmunoprecipitation experiments. These results serve as a springboard for models of the integrated action of UGGT1 and SEP15.

Integrative spatiotemporal modeling of biomolecular processes: application to the assembly of the Nuclear Pore Complex

Dynamic processes involving biomolecules are essential for the function of the cell. Here, we introduce an integrative method for computing models of these processes based on multiple heterogeneous sources of information, including time-resolved experimental data and physical models of dynamic processes. We first compute integrative structure models at fixed time points and then optimally select and connect these snapshots into a series of trajectories that optimize the likelihood of both the snapshots and transitions between them. The method is demonstrated by application to the assembly process of the human Nuclear Pore Complex in the context of the reforming nuclear envelope during mitotic cell division, based on live-cell correlated electron tomography, bulk fluorescence correlation spectroscopy-calibrated quantitative live imaging, and a structural model of the fully-assembled Nuclear Pore Complex. Modeling of the assembly process improves the model precision over static integrative structure modeling alone. The method is applicable to a wide range of time-dependent systems in cell biology, and is available to the broader scientific community through an implementation in the open source Integrative Modeling Platform software.

The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins

Artificial intelligence-driven advances in protein structure prediction in recent years have raised the question: has the protein structure-prediction problem been solved? Here, with a focus on nonglobular proteins, we highlight the many strengths and potential weaknesses of DeepMind's AlphaFold2 in the context of its biological and therapeutic applications. We summarize the subtleties associated with evaluation of AlphaFold2 model quality and reliability using the predicted local distance difference test (pLDDT) and predicted aligned error (PAE) values. We highlight various classes of proteins that AlphaFold2 can be applied to and the caveats involved. Concrete examples of how AlphaFold2 models can be integrated with experimental data in the form of small-angle X-ray scattering (SAXS), solution NMR, cryo-electron microscopy (cryo-EM) and X-ray diffraction are discussed. Finally, we highlight the need to move beyond structure prediction of rigid, static structural snapshots toward conformational ensembles and alternate biologically relevant states. The overarching theme is that careful consideration is due when using AlphaFold2-generated models to generate testable hypotheses and structural models, rather than treating predicted models as de facto ground truth structures.

Advances in the understanding of nuclear pore complexes in human diseases

BACKGROUND

Nuclear pore complexes (NPCs) are sophisticated and dynamic protein structures that straddle the nuclear envelope and act as gatekeepers for transporting molecules between the nucleus and the cytoplasm. NPCs comprise up to 30 different proteins known as nucleoporins (NUPs). However, a growing body of research has suggested that NPCs play important roles in gene regulation, viral infections, cancer, mitosis, genetic diseases, kidney diseases, immune system diseases, and degenerative neurological and muscular pathologies.

PURPOSE

In this review, we introduce the structure and function of NPCs. Then We described the physiological and pathological effects of each component of NPCs which provide a direction for future clinical applications.

METHODS

The literatures from PubMed have been reviewed for this article.

CONCLUSION

This review summarizes current studies on the implications of NPCs in human physiology and pathology, highlighting the mechanistic underpinnings of NPC-associated diseases.

Reducing Uncertainty Through Mutual Information in Structural and Systems Biology

Systems biology models are useful models of complex biological systems that may require a large amount of experimental data to fit each model's parameters or to approximate a likelihood function. These models range from a few to thousands of parameters depending on the complexity of the biological system modeled, potentially making the task of fitting parameters to the model difficult - especially when new experimental data cannot be gathered. We demonstrate a method that uses structural biology predictions to augment systems biology models to improve systems biology models' predictions without having to gather more experimental data. Additionally, we show how systems biology models' predictions can help evaluate novel structural biology hypotheses, which may also be expensive or infeasible to validate.

Unlocking the Gateway: The Spatio-Temporal Dynamics of the p53 Family Driven by the Nuclear Pores and Its Implication for the Therapeutic Approach in Cancer

The p53 family remains a captivating focus of an extensive number of current studies. Accumulating evidence indicates that p53 abnormalities rank among the most prevalent in cancer. Given the numerous existing studies, which mostly focus on the mutations, expression profiles, and functional perturbations exhibited by members of the p53 family across diverse malignancies, this review will concentrate more on less explored facets regarding p53 activation and stabilization by the nuclear pore complex (NPC) in cancer, drawing on several studies. p53 integrates a broad spectrum of signals and is subject to diverse regulatory mechanisms to enact the necessary cellular response. It is widely acknowledged that each stage of p53 regulation, from synthesis to degradation, significantly influences its functionality in executing specific tasks. Over recent decades, a large body of data has established that mechanisms of regulation, closely linked with protein activation and stabilization, involve intricate interactions with various cellular components. These often transcend canonical regulatory pathways. This new knowledge has expanded from the regulation of genes themselves to epigenomics and proteomics, whereby interaction partners increase in number and complexity compared with earlier paradigms. Specifically, studies have recently shown the involvement of the NPC protein in such complex interactions, underscoring the further complexity of p53 regulation. Furthermore, we also discuss therapeutic strategies based on recent developments in this field in combination with established targeted therapies.

AlphaFold2 as a replacement for solution NMR structure determination of small proteins: Not so fast!

The determination of a protein's structure is often a first step towards the development of a mechanistic understanding of its function. Considerable advances in computational protein structure prediction have been made in recent years, with AlphaFold2 (AF2) emerging as the primary tool used by researchers for this purpose. While AF2 generally predicts accurate structures of folded proteins, we present here a case where AF2 incorrectly predicts the structure of a small, folded and compact protein with high confidence. This protein, pro-interleukin-18 (pro-IL-18), is the precursor of the cytokine IL-18. Interestingly, the structure of pro-IL-18 predicted by AF2 matches that of the mature cytokine, and not the corresponding experimentally determined structure of the pro-form of the protein. Thus, while computational structure prediction holds immense promise for addressing problems in protein biophysics, there is still a need for experimental structure determination, even in the context of small well-folded, globular proteins.

Nucleoporin Nup98 is an essential factor for ipo4 dependent protein import

Nucleocytoplasmic transport of macromolecules is essential in eukaryotic cells. In this process, the karyopherins play a central role when they transport cargoes across the nuclear pore complex. Importin 4 belongs to the karyopherin β family. Many studies have focused on finding substrates for importin 4, but no direct mechanism studies of its precise transport function have been reported. Therefore, this paper mainly aimed to study the mechanism of nucleoporins in mediating nuclear import and export of importin 4. To address this question, we constructed shRNAs targeting Nup358, Nup153, Nup98, and Nup50. We found that depletion of Nup98 resulted in a shift in the subcellular localization of importin 4 from the cytoplasm to the nucleus. Mutational analysis demonstrated that Nup98 physically and functionally interacts with importin 4 through its N-terminal phenylalanine-glycine (FG) repeat region. Mutation of nine of these FG motifs to SG motifs significantly attenuated the binding of Nup98 to importin 4, and we further confirmed the essential role of the six FG motifs in amino acids 121-360 of Nup98 in binding with importin 4. In vitro transport assay also confirmed that VDR, the substrate of importin 4, could not be transported into the nucleus after Nup98 knockdown. Overall, our results showed that Nup98 is required for efficient importin 4-mediated transport. This is the first study to reveal the mechanism of importin 4 in transporting substrates into the nucleus.

Cracking AlphaFold2: Leveraging the power of artificial intelligence in undergraduate biochemistry curriculums

AlphaFold2 is an Artificial Intelligence-based program developed to predict the 3D structure of proteins given only their amino acid sequence at atomic resolution. Due to the accuracy and efficiency at which AlphaFold2 can generate 3D structure predictions and its widespread adoption into various aspects of biochemical research, the technique of protein structure prediction should be considered for incorporation into the undergraduate biochemistry curriculum. A module for introducing AlphaFold2 into a senior-level biochemistry laboratory classroom was developed. The module's focus was to have students predict the structures of proteins from the MPOX 22 global outbreak virus isolate genome, which had no structures elucidated at that time. The goal of this study was to both determine the impact the module had on students and to develop a framework for introducing AlphaFold2 into the undergraduate curriculum so that instructors for biochemistry courses, regardless of their background in bioinformatics, could adapt the module into their classrooms.

Overview of AlphaFold2 and breakthroughs in overcoming its limitations

Predicting three-dimensional (3D) protein structures has been challenging for decades. The emergence of AlphaFold2 (AF2), a deep learning-based machine learning method developed by DeepMind, became a game changer in the protein folding community. AF2 can predict a protein's three-dimensional structure with high confidence based on its amino acid sequence. Accurate prediction of protein structures can dramatically accelerate our understanding of biological mechanisms and provide a solid foundation for reliable drug design. Although AF2 breaks through the barriers in predicting protein structures, many rooms remain to be further studied. This review provides a brief historical overview of the development of protein structure prediction, covering template-based, template-free, and machine learning-based methods. In addition to reviewing the potential benefits (Pros) and considerations (Cons) of using AF2, this review summarizes the diverse applications, including protein structure predictions, dynamic changes, point mutation, integration of language model and experimental data, protein complex, and protein-peptide interaction. It underscores recent advancements in efficiency, reliability, and broad application of AF2. This comprehensive review offers valuable insights into the applications of AF2 and AF2-inspired AI methods in structural biology and its potential for clinically significant drug target discovery.

A checkpoint function for Nup98 in nuclear pore formation suggested by novel inhibitory nanobodies

Nuclear pore complex (NPC) biogenesis is a still enigmatic example of protein self-assembly. We now introduce several cross-reacting anti-Nup nanobodies for imaging intact nuclear pore complexes from frog to human. We also report a simplified assay that directly tracks postmitotic NPC assembly with added fluorophore-labeled anti-Nup nanobodies. During interphase, NPCs are inserted into a pre-existing nuclear envelope. Monitoring this process is challenging because newly assembled NPCs are indistinguishable from pre-existing ones. We overcame this problem by inserting Xenopus-derived NPCs into human nuclear envelopes and using frog-specific anti-Nup nanobodies for detection. We further asked whether anti-Nup nanobodies could serve as NPC assembly inhibitors. Using a selection strategy against conserved epitopes, we obtained anti-Nup93, Nup98, and Nup155 nanobodies that block Nup-Nup interfaces and arrest NPC assembly. We solved structures of nanobody-target complexes and identified roles for the Nup93 α-solenoid domain in recruiting Nup358 and the Nup214·88·62 complex, as well as for Nup155 and the Nup98 autoproteolytic domain in NPC scaffold assembly. The latter suggests a checkpoint linking pore formation to the assembly of the Nup98-dominated permeability barrier.

Structural anisotropy results in mechano-directional transport of proteins across nuclear pores

The nuclear pore complex regulates nucleocytoplasmic transport by means of a tightly synchronized suite of biochemical reactions. The physicochemical properties of the translocating cargos are emerging as master regulators of their shuttling dynamics. As well as being affected by molecular weight and surface-exposed amino acids, the kinetics of the nuclear translocation of protein cargos also depend on their nanomechanical properties, yet the mechanisms underpinning the mechanoselectivity of the nuclear pore complex are unclear. Here we show that proteins with locally soft regions in the vicinity of the nuclear-localization sequence exhibit higher nuclear-import rates, and that such mechanoselectivity is specifically impaired upon knocking down nucleoporin 153, a key protein in the nuclear pore complex. This allows us to design a short, easy-to-express and chemically inert unstructured peptide tag that accelerates the nuclear-import rate of stiff protein cargos. We also show that U2OS osteosarcoma cells expressing the peptide-tagged myocardin-related transcription factor import this mechanosensitive protein to the nucleus at higher rates and display faster motility. Locally unstructured regions lower the free-energy barrier of protein translocation and might offer a control mechanism for nuclear mechanotransduction.

Generative artificial intelligence performs rudimentary structural biology modeling

Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in scientific research. Intriguingly, capabilities of generative pre-trained transformer (GPT) language models beyond the scope of natural language tasks have recently been identified. Here we explored how GPT-4 might be able to perform rudimentary structural biology modeling. We prompted GPT-4 to model 3D structures for the 20 standard amino acids and an α-helical polypeptide chain, with the latter incorporating Wolfram mathematical computation. We also used GPT-4 to perform structural interaction analysis between nirmatrelvir and its target, the SARS-CoV-2 main protease. Geometric parameters of the generated structures typically approximated close to experimental references. However, modeling was sporadically error-prone and molecular complexity was not well tolerated. Interaction analysis further revealed the ability of GPT-4 to identify specific amino acid residues involved in ligand binding along with corresponding bond distances. Despite current limitations, we show the capacity of natural language generative AI to perform basic structural biology modeling and interaction analysis with atomic-scale accuracy.