Journal of Molecular Biology

Collagen I provides mechanical stability to organs and plays a critical role in several physiological processes such as wound healing and bone remodeling. Its ability to form fibrils depends on the proteolytic conversion of soluble procollagen I into mature protomers. However, the mechanistic aspects of this critical step have been difficult to analyze due to the lack of recombinant procollagen I suitable for structural and biochemical analyses. Here, we describe the successful production and purification of a heterotrimeric mini-procollagen I [1(I)22(I)] together with its homotrimeric counterpart [1(I)3] in HEK293-F cells. These tools were used to probe the specific role of the 2(I) chain both in procollagen I assembly and proteolytic maturation. While the presence of 2(I) in the heterotrimer does not strengthen trimer interfaces on its own, as revealed by cryo-electron microscopy, it provides a clear functional advantage to the procollagen substrate that is cleaved more efficiently by bone morphogenetic protein 1 (BMP-1) than the homotrimer. Furthermore, we demonstrate that the first cleavage event in the heterotrimer is at the level of the 2(I) chain, through a mechanism involving its C-telopeptide and a specific PRS motif close to the cleavage site. The preferential cleavage of 2(I) by BMP-1 can be partially corrected in the presence of PCPE-1 (procollagen C-proteinase enhancer 1) but the efficacy of the correction depends on its position on the procollagen trimer. Finally, we solved the high-resolution structure of the complex between the heterotrimer and PCPE-1 and proposed a new mechanism to explain the enhancing activity of PCPE-1.

AlphaFold 3 (AF3) has broadened the computational structural biology landscape by predicting all-atom complexes across proteins, nucleic acids, small-molecule ligands, and ions, including chemical modifications. For non-experts, Google provides a fully web-based service to utilize AlphaFold 3. Unfortunately, despite a flexible and rich interface for inputs, the server's outputs are incomplete and complicated for many users, as witnessed hands-on. Not all confidence metrics are displayed, and those that are shown do not present much interactivity; besides, only model number 1 is shown among the 5 produced by the software, and upon download the user finds the models are provided only in CIF format, which is not yet well-known especially among highly practical users. Here, we present the AlphaFold 3 Multi-Model Inspector (AF3 Inspector, https://pdbms.altervista.org/af3viewer/afviewer8.html), an open, client-side, zero-install web application designed to dissect, align, and interactively explore the complete ensemble of structural models produced by AlphaFold 3. Part of the PDB Manipulation Suite (https://pdbms.altervista.org/), the AF3 Inspector operates entirely within web browsers, meaning it is available out of the box in all devices and operating systems. AF3 Inspector delivers 3D visualization in various styles and colors for all models, overlay with backbone alignment if requested, interactive plots for pLDDT profiles, pAE matrices and contact maps, chain-pair interaction heatmaps, automated detection of ligands, ions and post-translational modifications, and rapid mmCIF-to-PDB conversion allowing users to download the more familiar files. The platform addresses critical practical considerations highlighted in recent community benchmarks, such as CASP16, and extends the lightweight, client-side biophysical toolkit paradigm established by the PDB Manipulation Suite (PDBMS).

In the post-AlphaFold era, advances in protein complex structure prediction have enabled the generation of thousands of candidate models per target, making the accurate and efficient selection of high-quality models from large candidate pools a critical challenge. Existing model-selection approaches commonly employ estimated model accuracy (EMA) methods, which include single-model and consensus-based methods. The former lack cross-model comparative information, whereas the latter often incur high computational costs from pairwise structural alignments and are influenced by candidate-pool quality. Here, we present DeepUMQA-Selection, a two-stage framework combining single-model accuracy estimators for preliminary selection with Ultrafast Shape Recognition (USR)-based structural alignment for consensus selection. Preliminary selection enriches the candidate pool with high-quality models and reduces subsequent structural comparisons, while USR-based structural alignment enables efficient consensus selection without explicit structural superposition. On the retrospective CASP16 QMODE3 benchmark dataset, DeepUMQA-Selection outperformed all participating methods and predictor-derived confidence metrics, as measured by mean Top-5 weighted penalty. The advantage was particularly pronounced for heteromeric targets, with a 13.9% improvement in model-selection performance relative to the best-performing CASP16 participating method. Furthermore, a confidence-assisted strategy enabled the framework to accommodate larger protein complexes while maintaining superior model-selection performance over competing methods, supporting its scalability. Runtime benchmarking showed that the proposed USR-based structural alignment achieved a substantial 317-fold speedup over US-align for candidate pools containing 1,000 models, demonstrating its computational efficiency for large-scale model selection. Our results demonstrate that DeepUMQA-Selection enables accurate and computationally efficient selection of high-quality protein complex models from large-scale candidate pools.

Human Ca2+/calmodulin (CaM)-dependent protein kinase II alpha (CaMKII) is a highly abundant and conserved protein in the brain. It is a multifunctional serine/threonine kinase that phosphorylates cellular substrates across subcellular compartments, activating signaling pathways essential for long-term memory storage. However, a detailed understanding of protein structure and enzyme-substrate interaction mechanisms require a method to produce active, stable, and pure proteins at scale. Since phosphorylation can alter catalytic activity and substrate affinity, examining the non-phosphorylated state enables an unbiased characterization of basal enzymatic function. Therefore, producing the non-phosphorylated form of the kinase is important for biochemical and structural studies aimed at understanding kinase activation mechanisms. We describe a detailed protocol for the expression and high-yield purification of full-length, non-phosphorylated human CaMKII in bacterial cells. CaMKII was co-expressed with {lambda}-phosphatase to maintain it in a non-phosphorylated state. Protein expression was induced by autoinduction at low temperature to enhance the stability and solubility of CaMKII. Recombinant CaMKII was purified by Ni-NTA affinity chromatography, followed by gel filtration chromatography. Although CaMKII has been considered difficult to purify in its non-phosphorylated form, we obtained it in high yield, and the protein was predominantly non-phosphorylated. Our results show that combining co-expression with autoinduction improves both the solubility and yield of the homogeneous non-phosphorylated form of CaMKII, which could be suitable for subsequent biochemical and structural studies.

In many neurodegenerative and systemic disorders, proteins can form insoluble protein aggregates called amyloids. Identification of amyloid forming regions in a protein remains central to understanding of its aggregation behaviour. Many predictors have been formed in the past and until recently which to estimate the aggregation-prone regions, which may not correspond to total residues found in actual disease associated fibril structures. To address this, we formed a sequence-based based predictor to ascertain structural amyloid-core propensity. The predictor was developed using experimentally determined fibril structures obtained from Amyloid Atlas. Ordered residues in the experimental structures were designated as core, and unresolved sampled from the same proteins as matched controls as non-core. Core and non-core regions were encoded using various physicochemical descriptors and protein language model (PLM) embeddings (ESM-2, ANKH, ProtT5) and evaluated using protein-grouped cross-validation. PLMs consistently outperformed physicochemical descriptors, with the best models reaching AUROC values of ~0.88 and AUPRC values of ~0.85. Locked full-length protein scans further localized experimental cores, with ESM-2/ExtraTrees W21 achieving AUROC 0.833, AUPRC 0.751, and a mean peak distance of 12.4 residues. In comparative benchmarking, our predictor showed better performance metrics than CrossBeta and AggrescanAI. The framework therefore provides residue-resolved prediction of structurally incorporated amyloid-core regions directly from sequence. AmyloCore-ML is easily accessible through an interactive Google Colab notebook, enabling sequence-based amyloid fibril-core prediction without local installation or dedicated computing infrastructure.

DNA polymerases generally interact with the processivity clamp (DnaN/{beta}-clamp) during replication via clamp-binding motifs (CBMs). Since a CBM was not detected in DNA Polymerase I (PolI) from E. coli, it is generally believed that PolI performs its functions in genome replication and repair, independently of the {beta}-clamp. We observe that, while PolI and {beta}-clamp proteins from E. coli do not interact, their homologs from Mycobacterium tuberculosis bind strongly, and the binding site localises to the Klenow fragment of PolI. The cryo-EM structure (4.9 [A]) of the Mtb-PolI-Klenow: Mtb-{beta}-clamp complex, coupled with continuous heterogeneity analysis of the cryo-EM data and binding experiments, showed that the primary CBM in PolI may be defined by the stretch 457QLSLLDD463. The crystal structure (2.9 [A]) of the {beta}-clamp with the CBM peptide revealed specific interactions that stabilise the peptide within the {beta}-clamp's canonical binding site. Phylogenetic analyses across different bacteria showed that the identified CBM is present only in PolI from members of the order Mycobacteriales. Overall, the interaction between PolI with the {beta}-clamp, mediated by a CBM unique to the Mycobacteriales order, highlights the mechanistic distinctiveness of genome replication in Mtb and phylogenetically related organisms, and has important implications for drug discovery.

There are many databases of post-translational modifications, but each has different protein and PTM coverage, making the current state of post-translational modifications difficult to obtain, assess, or harmonize. ProteomeScout has been a relational database that harmonized a myriad of resources to address this challenge. In this update, we wished to create a lightweight, sustainable open source resource for the community that retained the power of harmonization, protein visualization, and Python tools for interacting with the database. ProteomeScout-v4 presents an ecosystem of open-source tools for aggregating and updating proteins and post-translational modifications and presenting the web-based and code-based access tools for interacting with the data. ProteomeScout has moved from using a complex relational database to a flat-text file format. The database file update is version controlled on FigShare and all features have processes for continuous updating, including migrating PTMs to updated protein records, when external databases are updated. The open-source nature and flexibility allow for user-based control and community-based feature integration. Fast and easy analysis is possible with the API, with example analyses provided here.

Golgins are widely described as long coiled-coil proteins that contribute to the structural organisation and trafficking functions of the Golgi apparatus. Although experimental structures have been determined for a limited number of golgin regions, atomic-level information on their extended coiled-coil segments remains scarce, and the oligomeric state, topology, and register of most predicted regions remain unestablished. Here, we characterise a predicted coiled-coil region of the yeast golgin Bug1 (BUG1cc) using structural, biophysical, and computational approaches. X-ray crystallography revealed a parallel, in-register dimeric coiled-coil containing ten heptad repeats and a predominantly hydrophobic core, with specific polar interactions contributing to dimer stabilisation. In solution, BUG1cc was dimeric under SEC-MALS conditions and remained highly alpha-helical across the pH and ionic strength conditions examined. CD measurements revealed pronounced scan-rate-dependent hysteresis, while DSC independently confirmed an asymmetry between heating and cooling transitions. Increasing protein concentration shifted both apparent transition temperatures while preserving thermal hysteresis, supporting chain association and conformational rearrangements in structural recovery. Structure-based simulations indicated that interface contacts and intra-chain helicity are thermodynamically coupled and melt as a single cooperative unit, and that the monomer released on dissociation is compact and only partially helical, so that reassociation proceeds through a coupled folding-binding mechanism whose rate-limiting step is conformational rather than bimolecular. Together, these results establish the molecular architecture of a predicted coiled-coil region of Bug1 and reveal a complex folding landscape in which oligomerisation, secondary-structure recovery, and kinetic barriers are tightly coupled.

Small multifunctional viral membrane proteins called viroporins are attractive drug targets but are difficult to structurally characterize in a lipid-bilayer environment. We have successfully reconstituted the full-length Envelope (E) protein from SARS-CoV-2 in a lipid-bilayer, co-assembled with a native host factor that binds to E, the PDZ domain 2 of ZO1. We have leveraged the enhancement afforded by dynamic nuclear polarization NMR to determine that the ensemble-averaged oligomer state of E is a pentamer. Complexing the protein with a host PDZ domain did not impact the oligomer state, but resulted in structuring of the last four residues of E, and immobilization of the PDZ domain near the lipid surface. Combined with secondary structure information derived from the chemical shifts, these data were used to model an E protein pentamer together with the PDZ protein dimer. Inclusion of a relevant host factor, as well as a complex lipid bilayer that mimics conditions in the ER-Golgi intermediate compartment, approaches native conditions, and addresses the ongoing controversy regarding the functional oligomer state in an infected cell.

Maintenance of membrane homeostasis is essential for bacterial viability, yet the molecular functions of many membrane proteins involved in this process remain poorly understood. The widely distributed DedA superfamily of integral membrane proteins has been implicated in membrane homeostasis, with deletion of DedA genes resulting in sensitivities to temperature, pH and a range of antimicrobial compounds. Several bacterial DedA proteins have been linked to lipid transport, providing a potential connection between function and phenotype. However, a lack of direct functional and structural data means that the precise role of DedA proteins in bacterial membrane homeostasis remains unclear. Here, using analytical ultracentrifugation (AUC), we show that the Escherichia coli DedA protein YqjA exists predominantly as a dimer and, by combining structural modelling with site-specific cysteine crosslinking, we have identified the most likely dimer interface. Modelling of dimeric YqjA in the presence of lipids predicts an interfacial lipid-binding site located in close proximity to several conserved, functionally important residues. Consistent with lipid binding, addition of lipid substantially increased the thermal stability of YqjA. Furthermore, mutation of residues associated with the predicted binding site impaired YqjA function. Together, these findings provide new structural and functional insights into the DedA family and support a role for lipid binding in the activity of YqjA.

Diffusion-based models have substantially advanced biomolecular structure prediction. Within this framework, restraint-guided inference (RGI) corrects the denoiser output at each reverse-diffusion step using a differentiable restraint loss, allowing available experimental information, stereochemical requirements, or a specified target conformational state to be incorporated into predictions without retraining the model. Here, we present RGI-Toolkit, a general-purpose Python library that makes RGI available for a range of structure predictors. The toolkit consolidates restraint definition, atom selection, loss evaluation, and coordinate optimization into a shared, backend-agnostic engine, limiting predictor-specific code to a thin preprocessing adapter and a single hook in the denoising loop. Restraints on distances, angles, and dihedrals, on deviations from reference structures, and on user-defined reaction coordinates, together with ligand conformer restraints, are all specified in a common configuration format. The toolkit currently supports six predictors, including AlphaFold3. Across all six predictors, conformer restraints eliminated chirality and cis/trans errors in the predicted ligands and improved their local geometry, while geometric and custom restraints systematically shifted the sampled protein conformations toward the specified target states. RGI-Toolkit thus provides a unified framework for integrating experimental information and prior geometric knowledge into structure prediction and for generating biomolecular structures with specified conformational and stereochemical properties.

Protein-protein interactions (PPIs) govern fundamental biological processes and are central to therapeutic discovery, yet computational prediction methods remain severely limited by a lack of high-quality negative data (non-interacting PPIs). Existing models are trained almost exclusively on positive interactions or random pairs designated as negatives, while legacy negative datasets are limited in scale and contain correctness errors. To address this, we introduce Flock, a negative-enriched PPI dataset of unprecedented scale, containing 26,934 positive and 377,643 negative pairs. Flock integrates biological assemblies from the PDB with highly confident, curated negatives mined from scientific literature using a state-of-the-art agentic LLM workflow. To address the evaluation leakage seen in protein structure modelling, we also present Flock's Leakage-Free Set, a benchmark that strictly controls for sequence and interface similarity, and historical date-based cutoffs used in the training of co-folding models. Our evaluation reveals that the co-folding model ESMFold2 shows performance degradation on the Leakage-Free set, whereas the protein language model ESMC demonstrates stronger generalisation. Flock provides the most comprehensive and challenging PPI benchmark to date, establishing a rigorous new standard for evaluating the generalisability of protein structure and language models on this task.

Mitochondrial NADH-ubiquinone (UQ) oxidoreductase (respiratory complex I) reduces UQ within its long tunnel-like cavity, which is coupled to triggering proton translocation at the membrane domain. Although mammalian complex I adopts distinct "open" and "closed" conformations, the architecture of the UQ-accessing tunnel in the open conformation remains poorly defined owing to partial disorder of the UQ catalytic region near Fe-S cluster N2 in the tunnel. Here, we applied cryo-electron microscopy (EM) single particle analysis to determine the structures of complex I in bovine heart submitochondrial particles in the presence or absence of a mycothiazole-type inhibitor. Preceding photoaffinity labeling experiments using a synthetic photoreactive derivative ([125I]pMT) revealed that mycothiazole specifically labels the 49-kDa and ND1 subunits, both of which form a part of the UQ-accessing tunnel. Cryo-EM analysis demonstrated that bound mycothiazole reorganizes and stabilizes the UQ catalytic region in both open and closed conformations, enabling the first complete structural modeling of the entire UQ-accessing tunnel in the open conformation. Unexpectedly, in the presence of bound mycothiazole, loops of the PSST subunit forming the catalytic region in the tunnel adopted closed conformation-like features, whereas open conformation-like features were determined for the transmembrane helices of ND1 and ND6 subunits. The present study revealed that bound mycothiazole can reorganize the UQ catalytic region in the UQ-accessing tunnel and lead to a hybrid conformational state beyond the canonical open-versus-closed conformational model.

In a companion study, we introduced ProDive and used it to identify 318,289 high-confidence cross-family segment correspondences across all 25,545 Pfam families. Here we characterize the pervasiveness and biophysical context of the resulting mapped fragment resource. Graph-based community analysis shows that segment reuse is broadly distributed across the protein family universe, with thousands of mostly small modules rather than concentration in a small number of family pairs. Comparison between Pfam families and de novo designed proteins reveals an approximately 2.1-fold enrichment of cross-family segment correspondences relative to the Pfam-Pfam background. Mapped fragments are strongly enriched in helix-dominant secondary structures with intermediate solvent exposure, occupy a narrowed sequence-context entropy regime, and show a significant shift toward lower fragment-associated contact order relative to random control windows, directly supporting a folding-compatible local structural regime. Matched annotation analyses show depletion from known domain-based interaction interfaces and mild depletion from strict DisProt disorder. Direct Start2Fold/HDX and{varphi} -value comparisons are limited in scale but connect the same fragment class to folding-related protection: stability annotations support local structural stabilization that may facilitate folding, whereas folding annotations and transition-state enrichments provide more specific evidence for folding initiation or pathway involvement. Together, these results support a physical-constraint interpretation of local structural conservation, in which reusable compact fragments contribute prominently to local stability and folding-relevant local structure, with folding initiation supported in specific subsets rather than as an exclusive mechanism.

Intrinsically disordered regions (IDRs) of proteins show low sequence conservation, and sequence position alone is a weak predictor of disease risk. Phase-separating IDRs (PS-IDRs) are an exception, showing nearly three times higher pathogenic mutation rates than typical IDRs. Here we determine which sequences within that class show the greatest enrichment of pathogenic missense variants and what local features they share. Using pathogenic mutation rates as an independent biological readout, we isolated a core PS-IDR subclass that maximizes pathogenic enrichment. These sequences are defined less by bulk amino acid content than by a refined sticker-spacer grammar in which aromatic residues are embedded in short glycine-rich motifs, while homotypic charge tracts are avoided. Motifs such as YGG/YGGG, FGG/FGGG, and related patterns are elevated 7- to >200-fold relative to conventional IDRs. Comparison of pathogenic and benign substitutions then shows why genetic variation in IDRs has been confounding: the grammar itself is almost never mutated. Instead, the principal pathogenic targets are glycines directly flanked by non-glycine residues. These findings link a specific local sequence architecture to mutational vulnerability and provide a practical framework for interpreting variants in disordered proteins.

Prokaryotic transcription factors (TFs) lie at the core of antimicrobial resistance, controlling genes that let bacteria survive antibiotic exposure. The AraC/XylS family of TFs is defined by a ~99-residue DNA-binding domain composed of two helix-turn-helix (HTH) motifs. While this two-motif architecture is considered the minimal functional unit, the striking sequence and structural similarity between both HTH motifs raises the question of whether it evolved from a single ancestral HTH domain. Here, we designed two C-terminal truncations of MarA, comprising a single HTH motif, differing by seven-residues (IRSRKMT). Electrophoretic-mobility shift assays reveal that both constructs specifically bind the marbox sequence as reconstituted dimers, while size-exclusion chromatography shows they exist in a monomer-dimer equilibrium in solution. Despite retaining DNA-binding capacity, the truncations diverge functionally: while MarA64 (including IRSRKMT) activates transcription and confers regular erythromycin tolerance, MarA57 (lacking IRSRKMT) yields a transcriptionally inactive complex that suppresses reporter expression below baseline, suggesting competitive promoter occupancy. Molecular dynamics simulations and AlphaFold models suggest that the IRSRKMT extension forms an -helical element stabilizing a transcriptionally productive dimer interface. Conversely, its loss disrupts quaternary assembly, alters DNA bending, and misaligns RNA polymerase-contacting residues. Furthermore, free dimers explore non-productive conformations, suggesting that functional dimerization occurs upon DNA engagement. These findings establish that a single, correctly dimerized HTH domain is sufficient for both DNA binding and transcriptional activation, providing a structural rationale for short AraC/XylS-like proteins and offering a tuneable scaffold for synthetic biology and novel anti-virulence strategies.

Structure-guided mutation design requires relating a proposed substitution to its molecular environment to anticipate its effects. Existing evaluations of large language models (LLMs) in protein engineering emphasize sequence-based prediction or tool-integrated workflows, leaving unclear whether LLMs themselves can infer mutation effects from structural evidence without dedicated predictors. We evaluate physical intuition-qualitative reasoning that connects structural observations with molecular interaction principles-using a benchmark that tests the same substitution in the same protein across different binding partners, with predictions based on local atomic coordinates and no dedicated mutation-effect predictors. In the tested comparisons, the best-performing LLM achieved group accuracy comparable to the evaluated energy predictors and Biomni, an LLM-driven tool workflow, while the methods differed in their prediction patterns. Most evaluated LLMs achieved higher group accuracy for larger affinity improvements. Structural interventions support selective dependence on mutation-site and partner information, while assessable structural claims largely agree with the supplied coordinates. These findings support direct LLM structural reasoning as a basis for developing rational mutation-design tools that connect molecular observations with partner-specific effects.

Membrane proteins play crucial roles in cellular signaling, transport, and pharmacological regulation, yet their structural and functional characterization remains challenging due to experimental limitations. Molecular dynamics (MD) simulations have become indispensable for probing membrane protein behavior at atomic resolution; however, executing these simulations at scale remains a significant bottleneck. Existing tools excel at system preparation for individual cases, but none offer a complete, high-throughput pipeline spanning embedding, simulation, and analysis across multiple membrane compositions, and rarely integrate modern structure prediction and molecular docking frameworks. Here, we present GalaxyMemMD, a fully automated, open-source Galaxy framework that provides a direct, scalable alternative to existing preparation-only tools. GalaxyMemMD integrates every stage membrane embedding, system preparation, MD execution, and downstream analysis into a single reproducible pipeline. Leveraging Galaxy's HPC-ready job scheduling, GalaxyMemMD natively supports high-throughput parallel simulations across multiple membrane compositions and protein variants, including AlphaFold-derived structural inputs and downstream molecular docking workflows, without repeated manual setup. We validate GalaxyMemMD across six structurally diverse membrane proteins four GPCRs, one ion channel, and one beta-barrel demonstrating consistent system preparation, while the benchmark analysis shows stable embeddings, and reproducible trajectory-level production workflow. Across these benchmarks, GalaxyMemMD matches the setup quality of established tools, therefore serves as both a practical alternative and a capability extension for the membrane protein simulation community.

Recent advances in AI- RNA structure prediction have increased the availability of candidate models, but their accuracy remains variable. Developing reliable quality assessment (QA) methods requires datasets that represent contemporary prediction errors across diverse targets and molecular contexts. Here, we present RNA3D-Decoy, a large-scale benchmark dataset comprising 103,549 decoys for 677 experimentally determined targets, including 416 RNA-only structures,117 RNA structures with metal ions, and 144 RNA-protein complexes. Decoys were generated using five biomolecular predictors: AlphaFold 3, ESMFold2, Protenix, Chai-1, and Boltz-2.Each decoy is evaluated against its experimental reference us-ing TM-score, lDDT, and RMSD, with global and local quality annotations where applicable. DockQ scores additionally characterize RNA-protein interface quality. Target grouping incorporates both RNA and protein sequence relationships to support dataset partitioning. Analyses reveal distinct quality distributions across dataset levels and target-dependent differences among predictors, with each predictor contributing the highest-TM-score model for a subset of targets. Broad pooled score distributions also coexist with limited within-target score variation, particularly for RNA-protein complexes, emphasizing the importance of target-level characterization. By combining AI-generated decoys, standardized quality labels, and structured metadata, RNA3D-Decoy provides a resource for developing and evaluating methods for global quality estimation, local error prediction, and candidate-model ranking. The data set and accompanying code are available at: https://github.com/HamiltonChenLab/RNA3D-Decoy.

Components of nuclear pore complexes are broadly classified into two categories: intrinsically disordered FG-repeat nucleoporins such as Nup98, which can undergo liquid-liquid phase separation, and scaffold nucleoporins, which form the NPC's structural framework. The basis for crosstalk of these nucleoporins within NPC and beyond is poorly understood. Here we show that human Nup188, a helical inner-ring scaffold protein, forms condensates both in purified form as well as at endogenous level. This condensate exhibits fusion, dissolved in 1,6-hexanediol and recovered after photobleaching, with dynamics and material properties comparable to those of hNup98 condensates. Moreover, these condensates are not colocalized to annulate lamellae. Our analysis also revealed that hNup188CTD is sufficient to form condensates and MD simulations revealed the key roles of IDR1-3 for condensation. Notably, hNup93 expression along with hNup188 suppressed the condensate formation. Together, these findings indicate that a structured scaffold nucleoporin can adopt a condensate-forming state via its CTD and Nup93 binding can suppress this phenomenon.