Search Results (52)

The SARS-CoV-2 JN.1 subvariant has attracted attention due to the accumulation of mutations in the Spike (S) glycoprotein, particularly within the receptor-binding domain (RBD), contributing to the structural heterogeneity of the Spike protein. However, the extent to which conformational dynamics influence ligand-recognition patterns across functional Spike states remains insufficiently characterized. In this study, we applied a hierarchical computational framework combining homology modeling, molecular dynamics simulations, and molecular docking to determine whether conformational sampling modifies the location, accessibility, and recurrence of ligand-interaction regions in the JN.1 Spike protein. Closed, semi-closed, and open conformations were modeled and subjected to triplicate simulations, including an initial 100 ns phase followed by extended 200 ns simulations. Representative conformations were obtained by trajectory clustering and used for docking analyses. Two flavonoids, hesperitin-7-O-rutinoside (H7R) and flavanone-7-O-glucoside (F7G), were employed as structural probes to assess how ligand interaction patterns vary across conformational states. Comparative analyses revealed that conformational sampling modifies the location, accessibility and spatial distribution of ligand-interaction regions while generating distinct docking poses and recurrent interaction patterns not fully captured by static structural models. These findings highlight the importance of dynamics-informed structural ensembles for docking analyses in flexible viral proteins. Rather than predicting absolute binding affinities, this study provides an exploratory computational framework for evaluating ligand-recognition behavior in structurally dynamic viral systems. Full article

The herpes simplex virus 1 (HSV-1) US3 is a multifunctional serine/threonine kinase that promotes HSV-1 replication and spread. But its role and the mechanisms by which US3 regulates actin cytoskeletal remodeling remain poorly defined. We combined flow cytometry, confocal microscopy, immunoprecipitation-mass spectrometry (IP-MS), protein complex mapping, and machine learning to characterize US3-mediated F-actin dynamics. Flow cytometry and confocal microscopy showed that wild-type HSV-1 induces significant F-actin remodeling, while the ΔUS3 mutant displays F-actin levels comparable to uninfected cells, identifying US3 as a key regulator. IP-MS identified 47 high-confidence US3 interactors enriched in conserved actin regulatory complexes, including Arp2/3 nucleation machinery, formin-associated assemblies, cofilin severing complexes, and Rho-family GTPase modules. Mapping interactors to the CORUM database revealed clustering within actin nucleation, polymerization, and severing complexes, indicating that US3 operates through organized cellular machines. Machine-learning classifiers trained on label-independent mass-spectrometry features were used to prioritize interactors resembling known actin regulators; under protein-group-aware cross-validation, logistic regression performed best (average precision 0.24; ROC-AUC 0.66), and the analysis was interpreted as prioritization rather than de novo discovery. Pharmacological inhibition of Arp2/3 and formin pathways significantly attenuated US3-dependent F-actin remodeling, supporting the functional involvement of these pathways. Together, these findings are consistent with an inferred hierarchical axis in which US3 modulates Rho GTPase signaling and cofilin activation to promote F-actin disassembly, coordinating cytoskeletal remodeling required for efficient viral egress and spread. 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

Background: Titanium implant osseointegration is hierarchically governed by surface properties directing protein adsorption, cell recognition, immune modulation, and bone formation. Photofunctionalization creates ultrahydrophilic surfaces by removing hydrocarbons. To integrate it with 3D-printed architectures requires systematic synthesis. Problem: The classical static view of osseointegration obscures its dynamic, multiscale nature. How photofunctionalization-induced ultrahydrophilicity modulates the surface–protein–cell–bone interface as a continuous, hierarchical system remains unclear. Scope: This review synthesizes evidence on how photofunctionalized ultrahydrophilic titanium surfaces control protein adsorption, integrin-mediated mechanotransduction, immune responses, and in vivo osseointegration, with an emphasis on 3D-printed porous architectures. Conclusions: Photofunctionalization enhances protein adsorption, preserves bioactive conformation, and stabilizes protein layers, selectively engaging osteogenic integrins and amplifying FAK–Src/YAP–TAZ signaling. In 3D-printed implants, ultrahydrophilicity enables capillary-driven fluid infiltration and uniform bone ingrowth. Through this review, knowledge gaps—in surface aging and limited in situ characterization—are identified, and an interface-informed design integrating surface chemistry, architecture, and biological timing is proposed. Full article

Renal-resident macrophages (RMs) are essential regulators of kidney homeostasis and repair, yet the mechanisms governing RM niche regeneration after acute depletion remain poorly defined. To overcome these limitations, we have developed an inducible human CD59- intermedilysin (hCD59-ILY) ablation system, enabling rapid, specific, and reversible depletion of targeted macrophage populations, and subsequent replenishment of RMs, followed by longitudinal scRNA-seq analysis of kidneys at baseline and days 1, 3, and 7 post-ablation. RM ablation triggered a rapid and sustained upregulation of Cx3cl1, predominantly in proximal tubular epithelial cells (PTC1/PTC2), establishing a persistent chemotactic niche signal that coincided with macrophage repopulation. Regenerating RMs transitioned from inflammatory/stress-associated states toward metabolically active and proliferative phenotypes enriched in glycolysis, oxidative phosphorylation, MYC, and cell-cycle programs, with attenuation of canonical inflammatory pathways. Cell–cell communication analysis revealed an early burst of intercellular signaling at day 1, followed by progressive normalization, with fibronectin (Fn1), osteopontin (Spp1), chemokine (Ccl), and amyloid precursor protein (App) axes emerging as key mediators of niche restoration. Transcriptional network analysis identified a conserved regulatory module (Tfe3, Mitf, Hif1a, Myc, Gabpa, Rcor1) coordinating macrophage differentiation and regenerative programming, linking metabolic adaptation to lineage reconstitution. Sub-clustering revealed five dynamically shifting RM subsets with distinct inflammatory, remodeling, proliferative, and surveillance states, reflecting a hierarchical regeneration process. Functional validation using clodronate-mediated depletion in Secreted Phosphoprotein 1 (Spp1) (Opn)-deficient mice demonstrated impaired macrophage repopulation, establishing osteopontin as a critical regulator of RM regeneration. Together, these data define a coordinated epithelial–immune circuit in which Cx3cl1-driven chemotaxis, Spp1-dependent signaling, and a core transcriptional network orchestrate macrophage niche reconstitution and kidney repair following acute immune cell ablation. Full article

Metastasis remains a major cause of cancer mortality, making reliable primary–metastatic state prediction from somatic genomic alterations clinically important yet technically difficult. We present TF-GateNet, a biologically constrained neural network that combines TF-aware feature integration based on TRRUST and DoRothEA TF–gene regulatory priors with sample-specific dynamic gating on a Reactome-defined hierarchical sparse backbone. The model was evaluated on multi-center prostate and breast-cancer cohorts using mutation and copy-number features across 10 repeated runs on a fixed 80/10/10 split, together with independent prostate external validation, and was compared with biologically informed neural-network baselines (P-NET, BKGNet-Pathway, and BKGNet-Protein), a dense feed-forward neural network (FNN), and conventional machine-learning baselines (LR, SVM, RF, DT, and XGBoost). On prostate, TF-GateNet achieved the best internal performance (AUROC 0.954 ± 0.005; AUPRC 0.925 ± 0.007) and the best combined external performance (AUROC 0.952 ± 0.009; AUPRC 0.898 ± 0.018). On breast, TF-GateNet achieved the strongest internal ranking performance, reaching AUROC 0.893 ± 0.004 and AUPRC 0.835 ± 0.006. Ablation analysis indicated that TF-aware integration accounted for the larger prostate gain, whereas within the TF-GateNet family on breast, both TF-aware integration and dynamic gating contributed positively. Interpretability analysis further supported a cross-level route from TF-related genomic perturbation cues to genes, pathways, and phenotype-associated predictions. These results position TF-GateNet as a biologically grounded and interpretable framework for primary–metastatic state prediction, with the strongest overall evidence in prostate cancer and favorable internal evidence in breast cancer. Full article

Background/Objectives: Osteoporosis remains a clinically important metabolic bone disorder with limited bone-forming therapeutic options. SET domain bifurcated protein 1 (SETDB1) is involved in osteogenic epigenetic regulation, but small-molecule discovery guided by SETDB1-associated structural regions remains limited. This study aimed to identify a candidate compound with in silico relevance to a SETDB1-associated ligand-bound pocket and assess its association with early osteogenic readouts. Methods: A computational–experimental workflow was used, including hierarchical molecular docking, MM-GBSA rescoring, ADMET-based prioritization, redocking validation, molecular dynamics simulations, and preliminary in vitro evaluation in MC3T3-E1 cells. Compound 271 (C271) was selected based on structure-based screening results and predicted developability-related properties. Cytocompatibility, alkaline phosphatase (ALP) activity and staining, selected molecular markers, and SETDB1–H3 molecular dynamics behavior were evaluated. Results: Redocking reproduced the reference binding mode, and molecular dynamics simulations indicated that C271 maintained a relatively persistent conformation around the predicted SETDB1-associated pocket. Comparative SETDB1–H3 simulations showed altered H3 dynamics and SETDB1–H3 contact patterns in the C271-containing system. In cell-based assays, C271 showed no appreciable cytotoxicity within the tested concentration range and was associated with increased ALP activity and staining. C271 treatment was accompanied by higher global H3K9me3 and Runx2 levels, whereas SETDB1 protein abundance remained largely unchanged. Conclusions: C271 was identified as a computationally prioritized SETDB1-related candidate compound associated with early osteogenic-associated cellular responses. The evidence supports computational plausibility and cell-level association, but does not establish direct SETDB1 engagement, SETDB1 enzymatic modulation, SETDB1-dependent causality, or late-stage osteogenic maturation/mineralization. Given the single-compound evaluation, further target-engagement, enzymatic, and functional studies are needed. Full article

Background: Acetification is a complex process driven by acetic acid bacteria (AAB), in which high ethanol and acidity levels require strong microbial metabolic adaptation. Although the microbiota involved in vinegar production has been described, the functional mechanisms that enable these bacteria to maintain metabolic activity remain poorly understood. In this study, the functional dynamics of AAB during Verdejo vinegar acetification were analyzed using a quantitative metaproteomic approach. Methods: Acetification was performed in submerged culture under semi-continuous conditions, and samples were collected at four stages of the cycle (S1–S4). Results: LC-MS/MS analysis led to the identification of 1626 proteins, of which 1409 were assigned to the Acetobacteraceae family. Komagataeibacter europaeus was the dominant species (73.7%). Hierarchical clustering revealed four protein abundance patterns, and differential analysis identified 350 proteins with increased abundance and 169 with decreased abundance, with the greatest changes observed between S1 and S4. Functional annotation and protein–protein interaction analyses indicated that the main metabolic adaptations involve pathways related to energy metabolism, amino acid biosynthesis, membrane-associated functions, cellular homeostasis, and acid stress response. Conclusions: Overall, the results show that K. europaeus concentrates most of the metabolic activity during acetification and that proteome reorganization reflects key molecular strategies for adaptation and survival under high-acidity conditions. Full article

The cytoskeleton fulfills many essential roles that are necessary for cell function. Perhaps the most important of these roles is the formation of the mitotic spindle. The mitotic spindle is a complex and dynamic structure made up mainly of microtubules and numerous microtubule-associated proteins (MAPs), but the mechanisms behind its creation and regulation are not fully characterized. Recent research has focused on the link between liquid–liquid phase separation (LLPS) of MAPs and these microtubule organizations. Here, we focus on the protein regulator of cytokinesis 1 (PRC1), a spindle midzone-associated anti-parallel microtubule crosslinker. PRC1 is known to undergo LLPS to form condensed droplets without the need for additional crowders. Using confocal fluorescence microscopy and different constructs of PRC1, we investigate the ability of PRC1’s structural domains to form droplets and hierarchically organize microtubule tactoids. We find that the removal of PRC1’s unstructured C-terminal tail does not inhibit its ability to form droplets or microtubule tactoids in vitro. Removing part of PRC1’s N-terminal rod domain inhibits but does not completely suppress droplet formation. Full article

The continued evolution of SARS-CoV-2 has enabled an escape from most monoclonal antibodies, yet a subset of broadly neutralizing antibodies targeting three newly identified super-conserved RBD epitopes—SCORE-A, SCORE-B, and SCORE-C—retains remarkable activity against even the most recent JN.1-derived sublineages. Here, we employed an integrated computational framework combining conformational dynamics, mutational scanning, MM-GBSA binding energetics, and frustration profiling to dissect the molecular mechanisms by which XGI antibodies achieve broad neutralization and resistance to immune escape. Structural analysis revealed that all three SCORE epitopes share a common architecture: a highly conserved, minimally frustrated core that provides stable anchoring, flanked by peripheral regions that accommodate antibody-specific variations. Conformational dynamics showed that SCORE-A antibodies (XGI-183) rigidify the lateral epitope while leaving the RBM partially mobile; SCORE-B antibodies (XGI-198, XGI-203) clamp the RBM apex, directly blocking ACE2; and SCORE-C antibodies (XGI-171) allosterically loosen the RBM loop, impairing receptor engagement indirectly. Mutational scanning identified a hierarchical hotspot organization where primary hotspots (e.g., K356, T500, Y380, T385) are evolutionarily constrained and minimally frustrated, while secondary hotspots (e.g., V503, Y508, S383) are neutrally frustrated and represent the principal sites of immune-driven mutations. MM-GBSA decomposition revealed that van der Waals-driven hydrophobic packing dominates binding, with electrostatic interactions providing auxiliary stabilization. Critically, frustration analysis demonstrated that immune escape hotspots reside precisely in zones of neutral frustration—“energetic playgrounds” that permit mutational exploration without destabilizing the RBD—while minimally frustrated cores are evolutionarily locked. The comparative analysis of conformational versus mutational frustration distributions revealed a unifying principle: aligned neutral frustration yields permissive, escape-prone interfaces; decoupling enables the targeting of constrained cores; and the convergence of minimal frustration in both distributions creates invulnerable interfaces. These findings establish that broad neutralization arises not from ultra-high-affinity anchors but from strategic energy distribution across rigid, evolutionarily informed interfaces, providing a roadmap for designing next-generation therapeutics that target the invulnerable cores of viral surface proteins. Full article

Qualitative analysis of biochemical reaction systems reveals fundamental system-level properties that are independent of precise kinetic parameters, often context-dependent, or experimentally inaccessible. By focusing on structural and topological features—such as conservation relations, feedback loops, and pathway interconnections—qualitative analysis identifies invariant behaviors, robustness mechanisms, and potential failure modes inherent to the signaling network. In this study, we use Petri nets as a formal modeling framework to conduct qualitative analysis of the integrated MAPK and PI3K/Akt signaling network. By exploiting structural properties including place invariants, transition invariants, and siphons, the analysis establishes a direct correspondence between the Petri net structure and biologically meaningful conservation laws, signaling modules, and characteristic dynamic behaviors. The results demonstrate that the proposed model is structurally consistent, biologically plausible, and modular. Minimal semi-positive place invariants confirm mass conservation, indicating that proteins and enzymes circulate within closed molecular pools. Minimal semi-positive transition invariants identify canonical kinase–phosphatase cycles underlying sustained and reversible signaling. Hierarchical decomposition reveals a modular organization reducible to reusable enzymatic motifs, reflecting biological reuse across cascades and supporting scalability. Additionally, the identification of sixteen siphons that are also traps highlights persistent subsystems that ensure continuous regulator availability, confirming the robustness and dynamic sustainability of the integrated network. Full article

Abscisic acid (ABA) is a major phytohormone regulating plant growth and stress responses. Subclass III SnRK2 kinases and clade A type 2C protein phosphatases (PP2Cs) are core components of ABA signaling. Despite advances from phosphoproteomics, major gaps remain, particularly in mapping PP2C dephosphorylation targets and SnRK2-dependent phosphorylation dynamics under non-stress conditions. Here, we performed large-scale LC–MS/MS phosphoproteomic analyses using the subclass III SnRK2 triple mutant srk2dei and the constitutively active PP2C mutant abi1–1C, with and without ABA treatment in Arabidopsis thaliana. We identified 2757 and 2886 differentially regulated phosphopeptides in srk2dei and abi1–1C, respectively. Beyond known ABA signaling components, these datasets revealed numerous previously uncharacterized candidate proteins involved in metabolism, membrane transport, transcription, and cytoskeletal regulation. Integrative analysis uncovered a core set of candidate proteins oppositely regulated by SnRK2-mediated phosphorylation and ABI1-mediated dephosphorylation, defining a coordinated hierarchical network. These results indicate that the SnRK2–PP2C module functions not only in stress-induced ABA responses but also as a central regulator of phosphorylation homeostasis under basal conditions. This study provides a systematic framework for the global SnRK2–PP2C phosphorylation network and reframes ABA signaling as a dynamic homeostatic system. Full article

Anthocyanins are naturally occurring flavonoid pigments widely distributed in plants and are recognized for their antioxidant and anti-inflammatory activities. However, the molecular mechanisms underlying their potential immunomodulatory effects remain poorly characterized, particularly regarding their direct interactions with key signaling cytokines. In this study, a set of selected anthocyanins was investigated using a hierarchical computational workflow targeting three major pro-inflammatory cytokines: interleukin-2 (IL-2), interleukin-17 (IL-17), and tumor necrosis factor-α (TNF-α). Molecular docking analyses identified primulin and antirrhinin as the most favorable binders, forming stabilizing hydrogen bonds and hydrophobic interactions within predicted cytokine interaction interfaces. To further assess the stability of these complexes, molecular dynamics simulations were performed under near-physiological conditions. Trajectory analyses demonstrated stable ligand–protein interactions and persistent intermolecular contacts throughout the 100 ns simulation period. These findings provide molecular-level insights into anthocyanin–cytokine interactions and highlight their potential relevance for modulating inflammatory signaling pathways. Full article

Meat quality serves as a pivotal determinant of consumer purchasing behavior and of the economic viability of the livestock industry; as such, research into its regulatory mechanisms is of critical significance for the development of modern agriculture. Traditional investigations into meat quality have predominantly centered on sensory and physicochemical assessments of ultimate phenotypic traits, thereby facing inherent limitations in systematically deciphering the intricate molecular regulatory networks underlying meat quality formation. By contrast, an integrated analysis of the transcriptome and metabolome effectively connects the cascade of “gene transcription—metabolic regulation—phenotypic determination,” which has emerged as a core methodological paradigm in contemporary research on the molecular mechanisms governing meat quality. This review systematically delineates the evolutionary trajectory and principal technological frameworks of meat quality evaluation systems, with a focused synthesis of recent advances achieved through combined transcriptomic and metabolomic analyses in the field of meat quality regulation. The scope of this review encompasses core transcriptional regulatory networks associated with meat quality attributes, pivotal metabolic pathways, signal transduction mechanisms, and protein degradation dynamics. Furthermore, the regulatory impacts exerted by genetic variation among breeds, nutritional modulation, rearing environments, and stress responses on meat quality characteristics are comprehensively elucidated. Integrative analysis reveals that combined transcriptome–metabolome approaches transcend the inherent limitations of single-omics investigations, systematically unraveling the hierarchical regulatory mechanisms governing fundamental meat quality traits, such as muscle fiber type differentiation, postmortem glycolytic progression, intramuscular fat deposition, and flavor compound accumulation. Such integrative strategies have facilitated the identification of functional genes and metabolic biomarkers with potential utility for the early prediction of meat quality outcomes. Concurrently, this review acknowledges persistent challenges confronting the field, including the absence of standardized protocols for multi-omics data integration, insufficient functional causal validation, and a discernible disconnect between research discoveries and practical industrial implementation. Building upon this comprehensive assessment, prospective directions for future multi-omics research in meat quality are proposed, accompanied by the formulation of an integrated end-to-end improvement framework spanning fundamental research, technological innovation, and industrial application. Collectively, this review provides a systematic theoretical foundation for the in-depth elucidation of mechanisms that determine meat quality and the precision-oriented regulation of quality-determining traits in livestock production practices, thereby offering substantial scientific guidance for quality improvement initiatives within the animal husbandry sector. Full article

Gluten proteins are key components in wheat flour that determine the formation of dough and the quality of flour-based products. Upon hydration and mixing, gluten proteins undergo complex structural transformations to form a gluten network, exhibiting a hierarchical multi-scale structure spanning molecular, aggregate, and network scales. Due to the extreme complexity of gluten proteins, accurately characterizing their multi-scale structures remains challenging, requiring the combined application of multiple techniques, which are still relatively limited and thus warrant further exploration. Therefore, this review presents the principles, operational details, and result presentations of current techniques at different structural scales, including electrophoresis, high-performance liquid chromatography, proteomics, Fourier transform infrared spectroscopy, and Fourier transform Raman spectroscopy at the molecular scale; size-exclusion chromatography, asymmetrical flow field-flow fractionation, dynamic light scattering, multi-angle light scattering, differential refractive index, and ultraviolet absorbance at the aggregate scale; and confocal laser scanning microscopy, scanning electron microscopy, confocal Raman microscopy, and two-photon excitation microscopy at the network scale, among others. It further compares the advantages and disadvantages of similar techniques, facilitating their scenario-based selective utilization. Finally, it outlines the ongoing challenges and future perspectives for the development and application of techniques for the multi-scale structural characterization of gluten proteins. Full article