Search Results (409)

Background: Mechanosensitive ion channels PIEZO1 and PIEZO2 are key mediators of mechanotransduction, which converts physical forces into cellular signals involved in proprioception, touch, vascular function, and other physiological processes. Mutations in human PIEZO proteins are linked to various diseases, such as hereditary xerocytosis, lymphatic dysplasia, and proprioceptive dysfunction. However, the role of intrinsic disorder in the regulation of these proteins and their susceptibility for disease-associated mutations remains unclear. Methods: We analyzed canonical human PIEZO1 and PIEZO2 protein sequences using machine learning, neural network, and energy-based disorder predictors, together with the prediction of disorder-mediated binding regions, phase separation propensity, interaction networks, evolutionary conservation, clinically annotated human variants, and peptide structural modeling. Results: Both proteins showed moderate intrinsic disorder, with PIEZO2 having slightly greater disorder propensity and higher predicted phase separation potential. Intrinsically disordered regions frequently overlapped binding-prone segments and post-translational modification sites, supporting regulatory functions. Evolutionary comparisons showed strong conservation of PIEZO proteins, while selected disordered regions retained disorder propensity despite greater sequence variability. Disease-causing variants mainly affected the ordered regions of both proteins, whereas disordered regions contained proportionally more benign variants and relatively few pathogenic mutations. The modeling of mutations within disordered hotspots showed altered local conformational tendencies, indicating that some disease variants may disrupt dynamic interaction interfaces rather than global structure. Interaction network analysis linked both proteins to enriched mechanotransduction, ion transport, and cytoskeletal pathways. Conclusions: Overall, our findings identify intrinsic disorder as an underappreciated feature of PIEZO channel biology and provide a framework for interpreting PIEZO-associated channelopathies. PIEZO proteins also perfectly illustrate the proteoform concept, where one gene yields a highly diverse kit of mechanosensitive molecular tools. While humans only have two primary PIEZO genes (PIEZO1 and PIEZO2), the body generates a vast array of functional variations. Full article

SASH1 (SAM [sterile alpha motif] and SH3 [SRC-homology-3] domain-containing protein 1) is a multidomain scaffold implicated in pigmentation, innate immunity, receptor signaling, cytoskeletal dynamics, vascular biology, and tumor suppression. Although genetic and expression studies link SASH1 dysfunction to diverse diseases, a unifying mechanistic framework has remained elusive. Here, we synthesize current knowledge of SASH1 structure, interaction networks, and biological functions across cell types and disease contexts. SASH1 contains an intrinsically disordered SPIDER (SLy Proteins Associated Disordered Region), an SH3 domain, two SAM domains, and multiple linear motifs; together, these elements mediate interactions with EphA8 (ephrin type-A receptor 8), β-arrestin 1, TRAF6 (TNF receptor-associated factor 6), CRKL (CRK-like proto-oncogene), IQGAP1 (IQ-motif-containing GTPase-activating protein 1), cortactin, and TNKS2 (tankyrase-2). We propose that SASH1 functions as a context-dependent multi-docking scaffold that organizes signaling architecture. Its modular domains, intrinsically disordered regions, and dual SAM domains enable flexible, multivalent interactions with partners that can be grouped into three functional modules: receptor regulation, intracellular signaling, and cytoskeletal organization. Notably, many SASH1 partners are themselves scaffold or adaptor proteins, allowing integration into pre-existing networks in a hierarchical ‘scaffold-of-scaffolds’ manner. Through selective partner recruitment, SASH1 links cell-surface receptor inputs to downstream signaling pathways and cytoskeletal remodeling. This model provides a mechanistic framework for how SASH1 drives diverse, cell-type-specific outputs across physiology and disease, while revealing broader principles by which multidomain scaffolds encode cellular behavior. Full article

Classical Major Histocompatibility Complex Class I (MHC-I) molecules are traditionally viewed as stable peptide-presenting structures expressed on the surface of all nucleated cells. Their expression by professional antigen-presenting dendritic cells (DCs) enables CD8+ T-cell activation, differentiation, and immune surveillance. However, accumulating evidence indicates that cell-surface MHC-I molecules exist in three major conformational states: (1) β2m-associated, peptide-loaded conformers that originate in the endoplasmic reticulum and pass through the Golgi apparatus after binding proteasome-generated cytosolic peptides (hereafter referred to as closed conformers); (2) β2m-free, peptide-empty conformers that arise following β2m dissociation from closed conformers either at the plasma membrane or after internalization and recycling (hereafter referred to as open conformers); and (3) β2m-associated, peptide-empty conformers that represent an intermediate state between closed and open conformers. Here, we propose a conceptual framework, supported by computational predictors of intrinsically disordered regions, in which transitions between closed and open MHC-I conformers are coupled to intracellular regulatory processes, including post-translational modifications of conserved motifs, intracellular trafficking, and signaling. Although direct experimental evidence linking these processes remains limited, we integrate independent observations into a working model that may guide future investigations into MHC-I-mediated cell–cell communication in both immune and non-immune contexts, in health and disease. For clarity, in this article we define “open conformers” as structurally competent, β2m-free, and peptide-deficient MHC-I molecules. Full article

Phosphatidate phosphatase (PAP) governs a critical branchpoint in glycerolipid synthesis by catalyzing the Mg²⁺-dependent dephosphorylation of phosphatidate (PA) to diacylglycerol (DAG), thereby controlling the partitioning of lipid flux between membrane phospholipid synthesis and triacylglycerol (TAG) storage. While the structure, regulation, and function of ScPah1 have been extensively characterized in the non-oleaginous yeast Saccharomyces cerevisiae, far less is known about its ortholog in the oleaginous yeast Yarrowia lipolytica. This review provides a comparative analysis of Pah1 between the two yeasts, encompassing domain architecture, phosphorylation-dependent regulation, enzymatic characterization, and genetic and multi-omics studies. ScPah1 and YlPah1 share a conserved HAD-like catalytic core but diverge substantially in their regulatory domains: YlPah1 features compressed intrinsically disordered regions, an attenuated regulation of phosphorylation (RP) domain, and a massively expanded acidic tail. Unlike ScPah1, which is hyperphosphorylated and cytosolically sequestered during growth, YlPah1 maintains membrane association and increasing protein levels throughout growth. Deletion of PAH1 in Y. lipolytica produces a moderate reduction in TAG levels with evidence of metabolic redundancy, contrasting with the near-complete TAG loss observed in S. cerevisiae. Total PAP activity in Y. lipolytica peaks during exponential growth and does not correlate temporally with TAG accumulation, a dissociation attributable to the contributions of non-Pah1 PAP enzymes. Whether the Nem1–Spo7 homologs in Y. lipolytica form a functional phosphatase complex and the individual contributions of all PAP-encoding genes to lipid homeostasis remain important unresolved questions. Full article

The cerebellum is traditionally considered a structure responsible for motor control, but it is also involved in auditory perception, vocalization, speech, memory, emotional control, and social cognition. Due to its high intrinsic synaptic plasticity and complex connectivity with other brain regions, it is of potential interest for monitoring adaptive responses under various physiological and pathological conditions to capture global brain dynamics. Nevertheless, the use of electrocerebellography (ECeG) to detect changes in cerebellar electrical activity is limited, and a systematic evaluation of ECeG data to inform future research directions is lacking. This review summarizes recent ECeG research to explore the contribution of this time-honored method to deciphering the cerebellum’s spatial and temporal dynamics in health and disease. ECeG studies from the past three decades examining the slow and fast adaptive responses of the cerebellum in different cerebellar layers during sleep, anesthesia, brain injury, epilepsy, neurodegenerative diseases, and neuropsychiatric disorders are compiled from the PubMed, Scopus, and Google Scholar databases and discussed accordingly. It can be concluded that, despite certain limitations, ECeG is a practical, valuable, and reliable technique for detecting and predicting the complex spatial and temporal features of cerebellar electrical activity. Full article

SARS-CoV-2 nucleocapsid protein (N protein) binds nucleic acids and packages viral RNA. DNA aptamers that specifically bind the N protein have been used in antigen-based COVID-19 detection and have potential clinical applications for preventing SARS-CoV-2 infection. However, the complex structures of the N protein with DNA aptamers and the mechanisms by which aptamers recognize the N protein remain unclear. Here, we report the NMR-derived complex structure of the N-terminal domain of the N protein (N-NTD) with a 58 nt DNA aptamer, A48. The complex structure reveals a distinct topology with a large contact area between A48 and N-NTD. The N-terminal intrinsically disordered region (IDR) of N-NTD forms close contact with A48, primarily stabilized by hydrophilic interactions. Deletion of the N-terminal IDR or substitution of positively charged arginine residues with negatively charged glutamate residues in the IDR region substantially reduced the binding affinity for A48. Because most previously determined N protein structures were obtained using constructs lacking the N-terminal IDR, this study reveals a topology of the N protein-nucleic acid complex and highlights the importance of the N-terminal IDR in nucleic acid binding. Full article

Emerging viral variants can affect both commercial insect production and wild insect populations, highlighting the need to identify molecular features associated with viral host range. TdNV-Korea, isolated from the Korean rhinoceros beetle Allomyrina dichotoma (syn. Trypoxylus dichotomus), represents a Korean isolate within the Oryctes rhinoceros nudivirus (OrNV) lineage associated with infection of a non-Oryctes scarab host. To define candidate features associated with host-range variation, we compared the sequence and predicted structural properties of viral entry factors across OrNV-related isolates using sequence analysis, structural modeling, and electrostatic surface analysis. The major capsid protein VP39 was highly conserved and served as a comparative baseline, whereas the per os infectivity factors GP106 and GP126 showed greater divergence despite their expected constraints during oral entry. GP106 retained an invariant chitin-binding domain, with substitutions restricted to a peripheral C-terminal region, whereas GP126 concentrated most substitutions within a predicted disordered interdomain segment associated with a localized electrostatic shift on a candidate host-interaction surface. Because functional assays were not performed, these findings should be interpreted as a hypothesis-generating model in which two entry factors follow contrasting modes of sequence change. GP126, and secondarily, the GP106 C-terminal region are prioritized for future experimental validation of nudivirus host-range determinants. Full article

Disc-associated cervical spondylomyelopathy (DA-CSM) is a clinically relevant disorder of the canine cervical spine frequently requiring surgical stabilization, with implant subsidence remaining a common complication. This study aimed to evaluate subchondral bone mineral density (sBMD) distribution in the C6–C7 vertebral motion unit of DA-CSM-affected dogs and to compare these findings with a previously established cohort of clinically unaffected dogs. Computed tomography osteoabsorptiometry (CT-OAM) was applied to eight affected specimens, and sBMD was analyzed across predefined annulus fibrosus (AF) and nucleus pulposus (NP) regions, including detailed topographic subdivisions. Statistical comparisons were performed using paired and independent t-tests with correction for multiple testing, while the topographic pattern of bone density minima and maxima was compared using Chi-squared testings. DA-CSM-affected vertebral endplates demonstrated a consistent and significant reduction in overall sBMD compared to controls (p < 0.0001), affecting both AF and NP regions as well as all topographic subdivisions. Despite this global decrease, the characteristic spatial distribution pattern was not significant different between affected and unaffected vertebrae, with higher sBMD values in peripheral AF regions and lower values in central and centro-dorsal NP regions. These findings indicate that DA-CSM is associated with a generalized reduction in subchondral bone density without alteration of the intrinsic load-adapted distribution pattern. The persistence of structurally weak central regions, combined with reduced overall bone quality, may contribute to the risk of implant subsidence. Consideration of both global and regional sBMD characteristics may therefore be relevant for optimizing implant design and surgical strategies in canine cervical spinal distraction and stabilization. Full article

Autophagy is a carefully regulated catabolic process that utilizes assemblies of specific sets of macromolecules operating at multiple stages of the pathway. Discoveries in recent years show that autophagy markedly relies on liquid-liquid phase separation (LLPS). Here, we present parameters that indicate the plasticity of autophagy proteins and their probability to undergo LLPS in macroautophagy and microautophagy. We show that microautophagy is an extremely LLPS-friendly pathway. Several mechanisms involving proteins in the autophagy machinery that drive LLPS on various types of membranes to regulate this process or that undergo LLPS as autophagic cargo are described in detail. We also summarize the factors that modulate the LLPS potential of autophagy proteins. A high probability of autophagy-related proteins to undergo spontaneous LLPS shown here can direct future research on the role of protein droplets in autophagy. Full article

The spatial organization of the eukaryotic nucleus plays a pivotal role in regulating pre-mRNA splicing; however, the underlying principles governing this organization remain incompletely understood. Recent advances in imaging and sequencing technologies have revealed that splicing regulation is orchestrated across multiple hierarchical levels, from nanoscale protein–RNA interactions to large-scale nuclear architecture. Intrinsically disordered regions (IDRs) in RNA-binding proteins (RBPs) mediate multivalent interactions that drive liquid–liquid phase separation, leading to the formation of dynamic biomolecular condensates, such as nuclear speckles, paraspeckles, and nuclear stress bodies (nSBs). These structures act as functional hubs that modulate RNA processing efficiency and respond to cellular stress. In addition, emerging evidence highlights nucleus-wide RBP meshworks that spatially organize co-transcriptional splicing through dynamic RNA-dependent interactions. The interplay between these condensates and meshworks forms a spatially organized network that fine-tunes the efficiency and fidelity of pre-mRNA splicing. Collectively, this review presents a unified model in which phase separation and higher-order nuclear architecture coordinately regulate transcriptomic output in space and time. Full article

The pathological mechanism of autism spectrum disorder (ASD) exhibits dual heterogeneity: abnormal local energy metabolism and brain-wide high-order topological failure. To synergistically characterize these complex signals captured by advanced neuroimaging sensors, we propose the Quantum-Enhanced Graph Convolutional Wide Residual Network (QG-WRN), a modality-specific, decoupled parallel dual-stream architecture. In the classical branch, to accurately capture the spatial distribution of local metabolic abnormalities, we employ a wide residual network (WRN) to extract amplitude of low-frequency fluctuation (ALFF) features, leveraging its expanded feature channels to effectively mine regional neurodynamic properties. Furthermore, to overcome the representational bottlenecks of classical linear operators in parsing hidden, long-range network connections, we introduce quantum computing, exploiting its exponentially expansive state space and intrinsic low-parameter regularization mechanism. Guided by these properties, the quantum branch utilizes a variational quantum graph convolutional (QGCN) module—featuring a trainable circular encoding strategy and a hardware-efficient 4-qubit configuration—with a 2-layer nested message passing structure to process the functional connectivity (FC) matrix, harnessing quantum interference in Hilbert space to parse complex topology while effectively mitigating overfitting on small-sample medical data. A unified training scheme achieves full-dimensional fusion of node activity and topology. Achieving 68.49% accuracy, our method outperforms 10 classic and recent new baselines, providing a powerful computational intelligence tool for sensor-based ASD clinical diagnosis. Furthermore, interpretability analysis successfully maps core disease hubs to standard AAL116 atlas coordinates, providing a powerful tool for computationally aided ASD diagnosis. Full article

ATP-binding cassette (ABC) transporters are one of the largest superfamilies of membrane proteins, but little is known about the structural and evolutionary features of their non-domain regions. To clarify the diversity of these non-canonical regions across evolutionary lineages, we performed an analysis of intrinsically disordered regions, site-specific selection and predicted post-translational modification (PTM) sites among five architectural classes involving 1581 prokaryotic and eukaryotic sequences. Linker and flanking regions were more disordered than transmembrane and nucleotide-binding domains in all architectures. Disorder fraction was significantly different between region types after phylogenetic correction (Pagel’s λ ≈ 0.97). Predicted PTM sites are enriched in disordered non-domain segments, with N-linked glycosylation and phosphoserine showing the strongest positive enrichment. A total of 140 sites satisfied a tiered conservation criterion (MusiteDeep score ≥ 0.5; cross-species conservancy ≥ 30%), including 40 high-confidence or moderate-confidence sites (conservancy ≥ 50%) as well as novel phosphotyrosine candidates in half transporters and NBD-only proteins. Site-specific selection analyses showed pervasive purifying selection across domain cores and architecture-dependent enrichment of episodic positive selection in non-domain regions, with significant non-domain enrichment in full reverse and half forward transporters (Fisher’s exact, BH-adjusted p < 0.05). In summary, these findings establish that non-canonical regions of ABC transporters are evolutionarily dynamic and contain conserved predicted modification sites, supporting the idea that these regions are evolutionary dynamic segments that deserve experimental characterization as candidate regulatory interfaces. Full article

Ubiquitin-specific protease 7 (USP7/HAUSP) is one of the most studied deubiquitinating enzymes and plays a crucial role in regulating numerous cellular processes, making it a promising therapeutic target. In the nucleus, USP7 partially colocalizes with PML nuclear bodies (PML-NB)—multifunctional membraneless organelles involved in post-translational modifications and protein complexes assembly. The molecular basis and functional significance of this association remain uncharacterized. In this study, comparison of USP7 and PML interactomes revealed a significant overlap of 166 shared proteins. Functional enrichment analysis showed that USP7 and PML may operate within a common molecular context related to transcriptional regulation, chromatin remodeling, and DNA damage responses. Furthermore, these processes are also linked to cellular senescence and human aging (CellAge and GenAge databases). Focused analysis of overlaps between the USP7 interactome and core PML-NB proteins identified 61 proteins forming a dense “small-world” network. Most are prone to liquid–liquid phase separation, are intrinsically disordered, and serve as substrates for SUMOylation or ubiquitination. These findings not only expand our understanding of the molecular functions of USP7 but also highlight PML-NB as an important cellular context for investigating mechanisms associated with USP7 activity. Full article

Background/Objectives: SHP2 (PTPN11) is a key regulator of RAS/MAPK signaling and a well-validated target in cancer and developmental disorders. Designing ligands for its catalytic site is challenging due to the pocket’s intrinsic flexibility and the presence of conserved structural water molecules critical for ligand recognition, which limits traditional discovery approaches. This study aimed to systematically identify and prioritize novel SHP2-binding candidates using a computational strategy that accounts for these challenges. Methods: An integrative computational workflow was applied, combining water-aware docking, large-scale virtual screening of 714,409 compounds, MM/GBSA binding free-energy analysis, AI-driven chemical space modeling using ChemBERTa, and microsecond-scale molecular dynamics (MD) simulations. The high-resolution catalytic PTP domain of SHP2 structure was analyzed to identify conserved water molecules (W711, W716, W726, W776) essential for reproducing the crystallographic binding mode of the reference ligand 3LU. Candidates were prioritized based on docking scores, physicochemical criteria, structural inspection, MM/GBSA energetic profiles, and occupancy of distinct chemical space regions. Results: Seven compounds were selected. SwissADME analysis confirmed favorable drug-likeness and GI absorption, with no BBB permeation. ChemBERTa embeddings revealed substantial structural novelty relative to known SHP2 inhibitors. 1 μs molecular dynamics simulations suggested stable binding of compound 4 (2-(3-methyl-2,6-dioxopurin-7-yl)acetate) and persistent interactions with the conserved water network. MM/GBSA evaluation subsequently highlighted its energetically coherent profile. Conclusions: The workflow prioritizes compound 4 as a promising and structurally innovative SHP2-binding candidate. This integrative strategy provides a generalizable approach for targeting proteins with flexible pockets, critical water networks, and limited scaffold diversity, offering a roadmap for challenging computational ligand-prioritization projects. Full article

Background/Objectives: Alzheimer’s disease (AD) is an irreversible neurodegenerative disorder that imposes a profound burden on global public health. While resting-state functional magnetic resonance imaging (rs-fMRI)-based dynamic functional connectivity (dFC) analysis has demonstrated promise in capturing time-varying brain network abnormalities, existing deep learning methods suffer from three fundamental limitations: (1) an inability to model temporal dependencies across dynamic connectivity windows, (2) reliance on post hoc black-box explainability tools, and (3) misalignment between feature learning and classification objectives. Methods: To address these challenges, we propose MambaKAN, an end-to-end interpretable framework integrating a Variational Autoencoder (VAE), a Selective State Space Model (Mamba), and a Kolmogorov–Arnold Network (KAN). The VAE encodes each dFC snapshot into a compact latent representation, preserving nonlinear connectivity patterns. The Mamba encoder captures long-range temporal dynamics across the sequence of latent representations via input-selective state transitions. The KAN classifier provides intrinsic interpretability through learnable B-spline activation functions, enabling direct visualization of how latent features influence diagnostic decisions without post-hoc approximation. The entire pipeline is trained end-to-end with a joint loss function that aligns feature learning with classification. Results: Evaluated on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset across five classification tasks (CN vs. AD, CN vs. EMCI, EMCI vs. LMCI, LMCI vs. AD, and four-class), MambaKAN achieves accuracies of 95.1%, 89.8%, 84.0%, 86.7%, and 70.5%, respectively, outperforming strong baselines including LSTM, Transformer, and MLP-based variants. Conclusions: Comprehensive ablation studies confirm the indispensable contribution of each module, and the three-layer interpretability analysis reveals key temporal patterns and brain regions associated with AD progression. Full article