Helical motifs are ubiquitous in macromolecular systems at the nanometer to microns length scales. At the micron length scales, the formation of helical structures can be expected to be independent of the specific molecular chemical bonds and steric interactions, and instead be driven by relatively weak intermolecular forces. Emergence of helical order needs coordinated organization over long distances in polymeric macromolecules. We establish a generic mechanism to obtain spontaneous helicity by inducing screened Coulomb interactions between monomers in a semiflexible heteropolymer. In an experimental setup, change in solvent conditions locally can lead to different polymeric segments to attain charges of differing polarities and magnitudes. As we elucidate in this study using a coarse-grained bead spring model of a semiflexible polymer, this in turn can lead to spontaneous emergence of transient helical structures along the chain contour for a range of Debye-lengths. These transient helices can be made long-lived when they are subjected to weak geometric confinement to restrict the relaxation of the helical conformations. We have avoided using torsional potentials to obtain helical structures especially because emergence of torsional forces are unexpected at the micron length scales.

Super-resolution fluorescence imaging enables visualization of subcellular structures and molecular interactions at the nanoscale, but its broader application has been hindered by long-standing limitations in current protein tagging systems, including rapid photobleaching, tag-induced artifacts, poor post-fixation labeling efficiency, and restricted multiplexing capability. Here, we present FLEXTAG (Fluorescent Labeling for Exchangeable, X-resilient Tagging in Advanced Generic Nanoscopy), a comprehensive protein labeling system comprising three orthogonal, ultrasmall (12-18 kDa), and self-renewable protein tags that collectively overcome these major limitations of existing tagging systems, enabling optimized multi-color super-resolution imaging. Through continuous exchange of organic fluorophores, FLEXTAG supports extended durations of high-resolution imaging in both live and fixed cells with minimal photobleaching. It is compatible with major super-resolution modalities, such as SIM, STED, STORM, and PAINT, and is applicable to a wide range of subcellular targets. To further address fixation-induced labeling inefficiency and background fluorescence, we developed an innovative protection-based fixation method and chemical blocking strategies that significantly preserve tag accessibility and enhance signal-to-noise ratio, improvements that are broadly applicable to other protein tagging systems. Altogether, FLEXTAG enables long-term tracking of dynamic behaviors and interactions of subcellular targets, as well as mapping of nanoscale protein organizations and cellular architecture, advancing both basic research and translational applications in cell biology.

Synthesis, crystal structure elucidation, and molecular interaction studies of a guanidinium naphthoate adduct via Hirshfeld and docking analyses

Protein misfolding and aggregation represent key pathological mechanisms in neurodegenerative and systemic amyloid disorders, yet disease-modifying therapeutic strategies remain limited. In recent years, plant-derived nanomaterials have attracted increasing attention as multifunctional platforms capable of interacting with misfolded proteins and modulating aggregation-related pathways. This review examines the evolution of research between 2015 and 2025 on plant-derived nanomaterials—including green-synthesized metallic nanoparticles, plant extracellular vesicles, and phytochemical-based nano-delivery systems—in the context of protein misfolding disorders. The available literature was analyzed to identify principal mechanisms of action, experimental models, and emerging therapeutic perspectives. Current evidence suggests that these nanomaterials may influence protein aggregation through direct molecular interactions, modulation of oxidative stress and neuroinflammatory responses, and enhancement of cellular protein clearance processes. However, the field remains characterized by methodological heterogeneity, limited standardization, and insufficient translational validation. By synthesizing recent developments, this review highlights key research trends, mechanistic gaps, and future directions necessary for advancing plant-derived nanomaterials toward biomedical applications targeting protein misfolding diseases.

Planar cell polarity represents a fundamental mechanism by which cells within epithelial sheets align their orientation, enabling coordinated tissue morphogenesis and function. Disruption of PCP leads to developmental defects and disease, highlighting the importance of understanding its establishment and maintenance. While experimental studies have identified key protein molecules that drive PCP, mathematical and computational modeling have become indispensable in connecting molecular interactions to tissue-level outcomes. Over the last couple of decades, diverse approaches, such as agent-based models, Cellular Potts frameworks, Petri nets, continuum theories, and phenomenological models, have been developed to capture distinct aspects of PCP dynamics. These frameworks allow systematic exploration of nonlinear feedback, intracellular and intercellular signaling, and the influence of geometry and mechanics, and noise on polarization. This review summarizes these mathematical and computational developments in PCP modeling, emphasizing methodological assumptions, insights gained, and open challenges. By bridging experiment and theory, PCP modeling advances both mechanistic understanding and predictive capacity for tissue-scale organization.

ABSTRACT The rising demand for functional low-calorie ingredients with improved powder stability has increased interest in soluble dietary fibers (SDFs) as alternatives to conventional maltodextrins. These fibers differ in molecular structure and water interaction, influencing their ability to form stable amorphous matrices during spray drying. However, direct comparative evaluations of their intrinsic physicochemical and thermal properties remain limited. This study compared commercial Orafti® inulin (inulin), TIC PRETESTED® GUM ARABIC FT POWDER (gum arabic), Nutriose®FB 06 (nutriose), and STA-LITE®III Polydextrose (polydextrose) to elucidate their structure – function relationships as standalone glass formers. Each fiber was characterized for moisture content, water activity, solubility, hygroscopicity, morphology (field emission scanning electron microscopy (FE-SEM), particle size distribution (PSD), universal attenuated total reflectance-fourier transform infrared spectroscopy (UATR-FTIR), X-ray Diffraction (X-RD), water sorption isotherm WSI , and differential scanning calorimetry (DSC). All fibers exhibited very high solubility > 99 % , with inulin achieving 100 ± 0.00 % . Gum arabic showed the highest moisture content 7.22 ± 0.001 % but the lowest water activity 0.167 ± 0.008 , while polydextrose recorded the highest a W 0.335 ± 0.01 . Hygroscopicity ranged from 0.000063 g H 2 O g − 1 solid 24 h − 1 (inulin) to 0.000085 g H 2 O g − 1 solid 24 h − 1 (gum arabic). The Guggenheim – Anderson – de Boer (GAB) model accurately described sorption data R 2 > 0.90 , revealing differences in monolayer moisture 0.062 − 0.175 and multilayer adsorption. Gum arabic and nutriose exhibited higher glass transition temperatures 124.19 ± 1.00 deg C − 102.19 ± 1.00 deg C , respectivley , indicating greater resistance to plasticization, whereas inulin showed lowest T g 43.52 ± 1.00 deg C due to its semi-crystalline structure. Overall, synthetic resistant dextrins (gum arabic and nutriose) provided the most balanced performance in solubility, hygroscopic stability, and thermal resistance, supporting their potential use as sustainable glass formers in spray-dried food systems with extended shelf life

Structural characterization and the role of EPR spectroscopy for protein-polymer conjugates.

Noncanonical amino acids (NCAAs) have emerged as essential building blocks in protein engineering and peptide drug development owing to their advantages in enhancing metabolic stability, membrane permeability, and resistance to proteolytic degradation. Accurate construction of 3D protein structures containing NCAAs is crucial for elucidating their functions, understanding molecular interactions, and enabling rational design. However, integrating NCAAs into state-of-the-art protein structure prediction frameworks─such as AlphaFold3─often results in chirality violations, steric clashes, and local geometric distortions. These issues likely reflect limited parametrization of nonstandard residues within current models. To address these challenges, we expanded the AMBER force field covering 139 NCAAs, and we developed an enhanced Amber-relax protocol named HighRelax. Unlike conventional workflows that are restricted to linear peptides composed of canonical amino acids, HighRelax is compatible with complex systems containing NCAAs and cyclic peptides and can be seamlessly integrated with structures generated by state-of-the-art models such as AlphaFold3. Our results demonstrate that HighRelax effectively reduces steric clashes, restores residue chirality, and improves overall structural quality. This method provides a general postprocessing strategy for refining NCAA-containing structures, facilitating their applications in molecular simulation, peptide drug design, and protein engineering.

Molecular interaction of pristine and photoaged polylactic acid microplastics with extracellular polymeric substances from Microcystisaeruginosa.

Atomistic molecular dynamics (MD) simulations coupled with potential of mean force (PMF) calculations were employed to investigate the interactions between PVC polymer chains containing 6-20 repeating units and various plasticizers, with the goal of identifying potential replacements for the toxic plasticizer di(2-ethylhexyl)phthalate (DEHP) used in blood bags. The selected plasticizers belong to various chemical families, such as orthophthalates, citrates, adipates, and the terephthalate DEHT. Both the polymer and the plasticizers lack ionizable groups, and their interactions are primarily governed by van der Waals and electrostatic forces. A model correlating PMF profiles with interaction forces was developed and validated across polyvinyl chloride (PVC) polymers of different lengths and all investigated plasticizers. This model provides insight into how structural variations in plasticizers influence their respective PMF values. The study ranks the investigated plasticizers based on binding affinity, identifying TOTM (tris(2-ethylhexyl) trimellitate, TEHTM), BTHC (butyryl trihexyl citrate, Citroflex B-6), ATHC (acetyl trihexyl citrate, Citroflex A-6, CA-6), and DEHT (bis(2-ethylhexyl)terephthalate, DOTP/DEHTP) as promising alternatives for further investigation. This comprehensive study encompasses PVC polymers of four different lengths and 14 plasticizers, with all data averaged over 30 independent simulations. The approach provides a deeper understanding of molecular interactions, enabling the tailoring of polymer-plasticizer systems for diverse applications, including extractables and leachables, with relevance spanning materials science to biomedical engineering, and also serves as a basis for developing coarse-grained simulation protocols. Overall, this study provides valuable insights for designing safer and more efficient plasticizer substitutes and is well supported by other studies.

This research investigates the molecular mechanisms of benzyl butyl phthalate (BBP) in atopic dermatitis (AD) using network toxicology and molecular dynamics simulation. The environmental toxicity of BBP was systematically predicted and assessed using ADMETlab and ProTox-II. Structural information on BBP was obtained from PubChem, and potential targets were identified using STITCH and CHEMBL. AD-related target genes were retrieved from OMIM and GeneCards. A PPI network was constructed using STRING and Cytoscape to identify key targets. GO and KEGG pathway analyses were conducted to characterize the biological functions and signaling pathways associated with the targets. Molecular docking of BBP with core targets was performed using CB-Dock2. Finally, 100 ns molecular dynamics simulations of BBP-core target complexes were conducted using Gromacs. A total of 119 potential AD-related targets were identified, with six core targets (AKT1, CASP3, KRAS, SRC, EGFR, TNF) highlighted through PPI network analysis. GO and KEGG analyses demonstrated the involvement of these targets in BP, CC, MF, and signaling pathways, with a notable focus on the PI3K-Akt signaling pathway. Molecular docking analysis revealed strong binding affinities between BBP and the core targets, while molecular dynamics simulations confirmed stable interactions between BBP and AKT1, CASP3, and KRAS. This study systematically identifies key targets and molecular mechanisms underlying BBP-induced AD by integrating network toxicology, molecular docking, and molecular dynamics simulations. The findings establish a hierarchical framework linking chemical exposure, molecular interactions, and pathological phenotypes, providing insights into the toxic mechanisms of environmental pollutants from a molecular dynamics perspective.

Abstract This study presents the swelling, thermodynamic and viscoelastic properties of double‐network hydrogel composites based on polyacrylamide (PAAm) and natural polysaccharide: gellan or xanthan. Hydrogels were synthesized by radical polymerization of acrylamide in water solutions of polysaccharides of 0.2%, 0.4%, 0.6%, 0.8% and 1.0% concentration by weight. Molecular interactions between polymers and water and between polymers were estimated using a thermodynamic approach based on water vapor sorption and microcalorimetry. It was found that both gellan and xanthan had higher thermodynamic compatibility with water than PAAm. The enthalpy of the PAAm–polysaccharide interaction was found to be negative for all compositions. The minimal value for the PAAm–gellan blend was −10.3 ± 1.1 J g −1 and for PAAm–xanthan blend it was −7.3 ± 0.9 J g −1 . In the mechanical analysis, cylindrical gel samples with a diameter of 10 mm and a height of 10 mm were subjected to sinusoidal compressive mechanical deformations to determine the values of storage modulus, loss modulus and shift angle. Gradual increase in the polysaccharide concentration in the composite was accompanied by a significant increase of the mechanical parameters but to different extents for gellan‐ and xanthan‐based gels. Thus, at 0.01 Hz the storage modulus increased from 10.2 ± 1.9 kPa for single‐network PAAm gel to 15.5 ± 0.4 for double‐network PAAm/gellan composite and to 24.2 ± 2.4 kPa for PAAm/xanthan composite with 0.6% of polysaccharide in both cases. Possible interconnections between the thermodynamic and mechanical data are discussed. It is concluded that double‐network PAAm/gellan composites are a more suitable material for designing soft tissue biomimetics than PAAm/xanthan composites. © 2026 Society of Chemical Industry.

The bITEM project carried out at the Natural History Museum Vienna (NHMW) and the Vienna Institute for Archaeological Science (VIAS) of the University of Vienna explores new ways of digitally documenting and disseminating museum objects, their contexts and biographies. With the aim of enhancing access and interpretation, the project addresses challenges of presenting complex histories of museum objects beyond physical displays. Using an interdisciplinary approach, bITEM combines methods and concepts such as 3D scanning and material semiotics with CIDOC CRM and the open-source database system OpenAtlas. The project focuses on five diverse case studies from the NHMW's collection, offering insights into how these objects’ spatial, social, and chronological contexts can be mapped and presented more holistically. The resulting openly accessible web application ( bitem.at ) provides interactive tools, 3D models, timelines, and network graphs. The study demonstrates the effectiveness of combining traditional research methods and archival holdings with advanced digital tools to document and visualise cultural as well as natural heritage objects in novel ways. This approach enhances public access while also serving as a valuable research data resource, establishing a model for future projects in digital humanities and cultural heritage preservation that could select and instrumentalise parts of these tools according to their own prerequisites and requirements. Thus the bITEM project highlights the potential for interdisciplinary, digital approaches to enrich the understanding and accessibility of museum objects in general.

Proteins in complex with small-molecule ligands represent the core of structure-based drug discovery. However, three-dimensional representations are absent from most deep-learning-based generative models. Here, we present a graph-based generative modeling technology that encodes explicit 3D protein-ligand contacts within a relational graph architecture and evaluate its behavior using the dopamine D2 receptor (DD2R) as a model system. The models combine a conditional variational autoencoder that allows for activity-specific molecule generation with putative contact generation that provides predictions of molecular interactions within the target-binding pocket. We show that molecules generated with our 3D procedure are more compatible with the DD2R-binding pocket than those produced by a comparable ligand-based 2D generative method, as measured by docking scores, expected stereochemistry, and recoverability in commercial chemical databases. Predicted protein-ligand contacts were found to be among the highest-ranked docking poses with a high recovery rate. Overall, this work shows how the structural context of a protein target can enhance the generation of small molecules within a realistic binding environment.

Complex diseases such as cancer are characterized by their intricate etiology, arising from several molecular mechanisms that span multiple omic layers. To obtain insights on disease subtypes, associated biomarkers, and improve prognostic modeling, it is essential to integrate and interpret multi-omics data in a biologically meaningful way. We introduce Remics , a redescription-based framework for multi-omics integration inspired by higher-order statistical representations. Remics leverages higher-order cumulants to identify redescriptions, which are sets of multi-omics features that jointly capture equivalent biological variation across modalities. These feature groups are further analyzed through network representations, multi-omics risk scoring, and biomarker discovery to reveal molecular interactions underlying disease mechanisms. We applied Remics on simulated data as well as multi-omics data of six different cancer types from The Cancer Genome Atlas. We demonstrate that redescription-based integration uncovers functionally coherent cross-omics feature associations and compare them with state-of-the-art approaches. Our results highlight the potential of higher-order multi-omics statistical analysis to advance precision medicine through improved interpretability and discovery of novel molecular relationships.

Molecular interactions between therapeutic antibodies and neonatal Fc receptor (FcRn) are major contributors to the long serum half-life of antibodies. Therefore, the in vitro affinity of IgG for FcRn is an important indicator of in vivo pharmacokinetic properties. However, the molecular basis of IgG-FcRn interactions is not fully understood from experimental and structural perspectives. Affinity evaluation using surface plasmon resonance is difficult. The molecular mechanism by which domains other than Fc or surface charges affect FcRn binding remains unclear. In this study, we developed an engineered FcRn-immobilized column for affinity chromatography. We analyzed various types of antibodies to link physicochemical characteristics and FcRn affinity. Furthermore, analysis using charge-engineered mutants indicated that the lateral surface of L chain also affects the FcRn affinity. Finally, we presented a structural model of the IgG-FcRn complex to discuss the molecular mechanism of how the charges at L chain affect the FcRn affinity.

The upper atmospheric microwave sounding channels data are important for atmospheric data assimilation and retrieval. However, radiative transfer simulation accuracy is constrained by the precise characterization of the Zeeman splitting effect. This study investigates key influencing factors in upper-atmospheric microwave radiance simulations, focusing on the geomagnetic field parameters and the Zeeman splitting absorption coefficients. A three-dimensional (3D) atmosphere-magnetic coupling dataset is constructed using the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) version 2.0 Level 2A atmospheric profiles and the International Geomagnetic Reference Field (IGRF-13) as input for the microwave Line-by-Line (LBL) model. Observations from Special Sensor Microwave Imager/Sounder (SSMIS) channels 19 and 20 are used to quantitatively compare the effects of 2D and 3D geomagnetic fields on simulations and evaluate the impact of updated Zeeman splitting coefficients. Quantitative analysis reveals that the average vertical attenuation rate of geomagnetic field strength between 50 and 0.001 hPa is 2.98%, and using 3D magnetic field parameters improves the observation and simulation bias (O-B) for SSMIS channels 19 and 20 by approximately 3.67% and 3.52%, respectively. The updated microwave LBL model, incorporating molecular self-spin interactions and higher-order Zeeman effects, reduces the mean absolute error (MAE) and root mean square error (RMSE) of the SSMIS channel 20 by approximately 2.7% and 2.25%, respectively. Experimental results indicate that the 7+ line within a 2 MHz frequency shift is sensitive to moderate magnetic field strength (0.35–0.55 Gauss), while the 1− line is sensitive to strong magnetic fields (0.5–0.7 Gauss). This study demonstrates that optimizing geomagnetic field representation and Zeeman splitting coefficients can improve upper atmospheric microwave radiance simulation accuracy by detailed comparison with observations.

Essential oils as biopesticides: contact toxicity, volatile profiling, and molecular target interaction in Caryedon serratus

Osteoarthritis (OA) is a degenerative joint disease, which is accompanied by chronic pain and functional impairment, especially among the elderly population. Transdermal drug delivery offers a non-invasive option for managing OA. Our study assesses the relative effectiveness and safety of transdermal Buprenorphine compared to Diclofenac patches in the treatment of knee OA. A randomized controlled trial was performed in 152 patients with radiographically confirmed Grade I/II knee OA and with an age of 50 years and above. The participants were divided into two groups: Group A (transdermal buprenorphine) and Group B (transdermal diclofenac) as the treatment options to be used within 4 weeks. The Numeric Rating Scale (NRS), Western Ontario and McMaster Universities Arthritis Index (WOMAC), and Lequesne Index were used to measure pain intensity, functional status, and disease severity, respectively. Network pharmacology analysis was also used to examine additional interactions such as safety, treatment compliance and molecular interactions. Both treatments reduced pain significantly as well as improved functional outcomes. Nevertheless, buprenorphine had a higher clinical efficacy with higher reductions in NRS scores (7.72 to 2.81 vs. 7.68 to 3.23), WOMAC total scores (71.5 to 31.8 vs. 74.0 to 45.6), and Lequesne Index values (17.4, to 5.87 vs. 17.3, to 8.42) than diclofenac. Network pharmacology analysis revealed that buprenorphine modulates 25 genes related to OA, while diclofenac affects 20 genes, suggesting that Buprenorphine may have a wider range of benefits. Both treatments demonstrated excellent tolerability. Transdermal buprenorphine was found to have better short-term analgesic and functional advantages than transdermal diclofenac in early-stage knee OA. Its high tolerability, once-weekly topography and broad-spectrum interactions with its molecular targets justify its possible use in the treatment of a discrete group of patients, specifically older healthcare individuals or those intolerant to NSAIDs.

Prion diseases are fatal neurodegenerative disorders characterized by profound neuronal damage. Despite evidence supporting a neuroprotective role for β-synuclein (β-syn) in neurodegeneration, its potential functions and mechanisms in prion disease have not been elucidated. To investigate the role of β-syn, we systematically analyzed its alterations in the central nervous system of several prion-infected rodent models and cell models. A series of biochemical, cellular, and immunofluorescence assays were conducted to explore the relationship between β-syn and protein kinase B (Akt) signaling and between β-syn and prion protein (PrP), and its neuroprotective role in prion disease. Student’s t-test was used for statistics. At the terminal stage of prion disease, β-syn and Akt exhibited a parallel and remarkable decrease in rodent brains, contrasting with the slight but significant increase observed at early to middle stages. Dual-stained immunofluorescence assays confirmed that β-syn is localized within NeuN-positive neurons. Further structural and functional analyses revealed a high-affinity molecular interaction between β-syn and Akt, with the N-terminal region of β-syn being essential for binding to Akt1. In a cell model of PrP aggregation, β-syn overexpression suppressed cytochrome c-induced apoptosis, which was demonstrated by decreased levels of cleaved caspase-3. Notably, this anti-apoptotic effect was partially abolished upon Akt knockdown, indicating a dependence on Akt signaling. Moreover, colocalization of β-syn and PrP was observed in rodent brains. Consistently, in cellular models of prion infection and PrP aggregation, β-syn overexpression not only reduced PrP levels but also ameliorated its aberrant histological distribution. Our findings demonstrate that the anti-apoptotic activity of β-syn, mediated via Akt signaling, is severely lost during prion infection, thereby suggesting a mechanism of intrinsic neuronal vulnerability and revealing a novel therapeutic strategy.