Search Results (113)

Murunskite (K₂FeCu₃S₄) is a layered sulfosalt chalcogenide that occupies a unique position between the cuprate and iron pnictide families: it shares electronic characteristics with the former and adopts the crystal structure of the latter. Despite a completely random distribution of magnetic Fe within a nonmagnetic Cu matrix, murunskite exhibits a well-defined quarter-zone antiferromagnetic transition at 97 K and complete orbital order below 30 K. These findings reveal the unexpected emergence of long-range order in a high-entropy-like environment. This inherent robustness to site disorder in a layered structure makes murunskite a paradigmatic system for further studies. Here, we investigate doping strategies in murunskite to assess how its electronic and magnetic properties can be tuned. Using melt-growth techniques, we achieve substitutions at the magnetic metal site (Fe), spacer cation (K), and sulfur ligand (S), which significantly influence transport and magnetic properties. In addition, we use ionic-liquid gating on the parent compound and observe a gate-dependent suppression of resistivity, confirming the potential for electrostatic control over transport. Our results demonstrate the chemical and electronic plasticity of murunskite, offering a valuable platform for co-engineering disorder, magnetism, and transport, and opening avenues to explore quantum phenomena in correlated and high-entropy materials. Full article

Organic mixed ionic–electronic conductors (OMIECs) are pivotal for bioelectronics; however, the microscopic origins of doping-dependent charge transport remain elusive. In this study, we established a multi-scale computational framework to quantify the distinct intramolecular electronic coupling ($H_{ab}$) distributions in systems with 25% and 75% doping levels. Our protocol employs automated quantum chemical calculations to exhaustively identify intrinsic local minima, ensuring thermodynamically stable initial conformations. Subsequent Molecular Dynamics (MD) simulations characterize the equilibration timescales and counter-ion dispersion behaviors. The simulation results reveal that the 75% doped system exhibits significantly stronger counter-ion confinement and a distinct electrostatic landscape compared to the 25% system. Finally, hybrid QM/MM calculations integrated with Constrained Density Functional Theory (CDFT) were utilized to evaluate $H_{ab}$ within these specific environments. The computed coupling distributions show a clear correlation with local electrostatic fluctuations induced by differing counter-ion arrangements. These findings indicate that doping-induced environmental disorder is a critical factor modulating intramolecular transport efficiency, providing a theoretical basis for optimizing OMIEC performance through electrostatic engineering. Full article

Biological membranes are dynamic, information-rich platforms whose structural and functional properties are dictated by lipid composition rather than acting as passive barriers. Recent advances in lipidomics have revealed that variations in lipid headgroups, acyl-chain length and saturation, sn-positional architecture, and oxidative modifications profoundly influence membrane mechanics, lateral organization, and protein–lipid interactions. These features collectively regulate fundamental cellular processes, including signaling, trafficking, curvature generation, and transbilayer asymmetry. In parallel, a wide range of pathological conditions—including cancer, metabolic disorders, neurodegeneration, and inflammatory diseases—are increasingly associated with coordinated lipid remodeling that reshapes membrane material properties and electrostatic landscapes. In this review, we integrate biophysical principles with lipidomics-based evidence to elucidate how lipid chemical diversity translates into membrane-level behavior. We discuss the roles of major membrane lipid classes, the functional consequences of acyl-chain and sn-positional remodeling, and the biological significance of lipid asymmetry and lateral heterogeneity. Particular attention is given to disease-associated lipid reprogramming and extracellular vesicle lipidomes as functional extensions of cellular membranes. Finally, we examine key analytical barriers in modern lipidomics and outline strategies required to connect lipid structural information with biological function. Together, this framework highlights membrane lipid architecture as a central determinant of cellular physiology and a promising axis for mechanistic insight and translational biomarker discovery. Full article

Tau proteins are microtubule-associated proteins that regulate axonal structure, dynamics, and transport, and their dysregulation underlies several neurodegenerative diseases. The MAPT gene produces multiple tau isoforms through alternative splicing, including the high-molecular-weight isoform known as Big tau, which contains an insert of the large 4a exon of approximately 250 amino acids. Big tau is predominantly expressed in neurons of the peripheral nervous system (PNS), cranial motor nuclei, and select neurons of the central nervous system (CNS) such as the cerebellum and brainstem. Developmental expression studies indicate a switch from low-molecular-weight isoforms of tau to Big tau during axonal maturation, suggesting that Big tau optimizes cytoskeletal dynamics to accommodate long axonal projections. Comparative sequence and biophysical analyses show that the exon-4a insert is highly acidic, intrinsically disordered, and evolutionarily conserved in its length but not its primary sequence, implying a structural role. Emerging modeling and in vitro assays suggest that the extended projection domain provided by the exon-4a insert spatially and electrostatically shields the aggregation-prone PHF6 and PHF6* motifs in tau’s microtubule-binding domain, thereby reducing β-sheet driven aggregation. This mechanism may explain why tauopathies that involve aggregation of tau have little effect on the PNS and specific regions of the CNS such as the cerebellum, where Big tau predominates. Transcriptomic and proteomic data further suggest that alternative Big tau variants, including 4a-L, are expressed in certain cancerous tissues, indicating broader roles in cytoskeletal remodeling beyond neurons. Despite its putative anti-aggregation properties, the physiological regulation, interaction partners, and in vivo mechanisms of Big tau remain poorly defined. This review summarizes what is known about Big tau and what is missing toward a better understanding of how expansion via inclusion of exon 4a modifies tau’s structural and functional properties. Our purpose is to inspire future studies that could lead to novel therapeutic strategies to mitigate tau aggregation in neurodegenerative diseases. Full article

Designing the high-performance polyimides (PIs) for the biomimetic structures, which are used in extreme conditions, remains greatly challenging, due to the conflict between processability and thermal stability. Here, we report a series of silicon–alkyne-functionalized diamine-based polyimides that exhibit remarkable processability and thermal stability. The incorporation of bulky siloxy groups disrupts chain packing and increases free volume, enabling excellent solubility in polar solvents, while the rigid fluorene core enhances chain stiffness. DFT calculations confirm twisted molecular geometries (Si bond angle ≈ 103°, dihedral angle ≈ 89°) which weak π–π stacking, while heterogeneous electrostatic potentials enable favorable noncovalent interactions (e.g., C–F···H–C), promoting solvent diffusion. After thermal curing, the obtained product shows a high decomposition temperature (T_d5% = 560 °C), char yield of 72.0% at 800 °C, and glass transition temperature (T_g) of 354.6 °C. Meanwhile, locally planar fluorene units retain inherent thermal stabilization benefits through constrained rotational mobility. These results demonstrate a spatially decoupled siloxy–alkyne design that synergistically enhances molecular flexibility, disorder, and electronic stability, offering a molecular strategy for tailoring PI-based matrices to meet the demands of emerging biomimetic architectures and other high-performance composites operating under severe thermal loads. Full article

Aggregates of misfolded α-synuclein proteins are key markers of Parkinson’s disease. The protein α-synuclein (aSyn) is an intrinsically disordered protein (IDP) and therefore lacks a single stable 3D structure, instead sampling multiple conformations in solution. It is primarily located in presynaptic terminals and is thought to help regulate synaptic vesicle trafficking and neurotransmitter release. ASyn proteins have three domains: an N-terminal domain, a hydrophobic non-amyloid-β component (NAC) core implicated in aggregation, and a proline-rich C-terminal domain. Asyn proteins with truncated C-terminal domains are known to be prone to aggregation and suggest that understanding domain–domain interactions in aSyn monomers could help elucidate the role of the flanking domains in modulating protein structure. To this end, we used Gaussian accelerated molecular dynamics (GAMD) to simulate wild-type (WT), N-terminal truncated (ΔN), C-terminal truncated (ΔC), and isolated NAC domain (isoNAC) aSyn protein variants. Using clustering and contact analysis, we found that removal of the N-terminal domain led to increased contacts between NAC and C-terminal domains and the formation of inter-domain β-sheets. Removal of either flanking domain also resulted in increased compactness of every domain. We also found that the contacts between flanking domains in the WT protein result in an electrostatic potential (ESP) that may lead to favorable interactions with anionic lipid membranes. Removal of the C-terminal domain disrupts the ESP in a way that could result in over-stabilized protein–membrane interactions. These results suggest that cooperation between the flanking domains may modulate the protein’s structure in a way that helps maintain elongation and creates an ESP that may aid favorable interactions with the membrane. Full article

Background/Objectives: Janus kinase 2 (JAK2) is a pivotal signaling protein implicated in various hematological malignancies and inflammatory disorders, making it a compelling target for therapeutic intervention. Methods: In this study, we employed an integrative computational approach combining ligand-based screening, pharmacophore modeling, molecular docking, molecular dynamics (MD) simulations, and MM/PBSA free energy calculations to identify JAK2 inhibitors from the ChEMBL database. A comprehensive virtual screening of over 1,900,000 compounds was conducted using Tanimoto similarity and a validated pharmacophore model, resulting in the identification of 39 structurally promising candidates. Docking analyses prioritized compounds with favorable interaction energies, while MD simulations over 100 ns assessed the dynamic behavior and binding stability of top hits. Results: Four compounds, CHEMBL4169802, CHEMBL4162254, CHEMBL4286867, and CHEMBL2208033, exhibited consistently superior performance, forming stable hydrogen bonds, favorable RMSD profiles (≤0.5 nm), and strong binding interactions, including salt bridges. Notably, the binding free energies revealed ΔG values as low as −29.91 kcal/mol, surpassing that of the reference inhibitor, momelotinib (−24.17 kcal/mol). Conclusions: Among these, CHEMBL4169802 emerged as the most promising candidate due to its synergistic electrostatic and hydrophobic interactions. Collectively, our results highlight these compounds as probable, JAK2-selective inhibitors with strong potential for further biological validation and optimization. Full article

Acne Vulgaris is a chronic inflammatory skin disorder driven by a combination of microbial colonization, immune dysregulation, and disruption of the epidermal barrier. Although isotretinoin remains the most effective treatment, the molecular mechanisms underlying its anti-inflammatory effects are incompletely understood. This study integrates transcriptomic meta-analysis and computational drug screening to identify novel therapeutic targets and candidate compounds for acne management. Three publicly available GEO datasets (GSE6475, GSE10433, GSE11792) were analyzed to identify differentially expressed genes (DEGs) associated with isotretinoin response. Among these, Spectrin beta, non-erythrocytic 1 (SPTBN1) and Signal-induced proliferation-associated 1-like protein 1 (SIPA1L1) emerged as consistently regulated genes with known roles in cytoskeletal organization and immune signaling, respectively. To assess the druggability of these targets, molecular docking was conducted using gentamicin and natural compounds derived from Cymbopogon winterianus, including citronellol, citral, citronellal, and geraniol. Gentamicin demonstrated the strongest binding affinity to SIPA1L1 (−8.6 kcal/mol) and SPTBN1 (−5.9 kcal/mol), forming multiple hydrogen bonds and hydrophobic contacts. Subsequent 100 ns molecular dynamics (MD) simulations confirmed the stability of the gentamicin–protein complexes, as evidenced by favorable RMSD, RMSF, and energy profiles. Interaction energy decomposition revealed strong contributions from electrostatic and van der Waals forces. These findings highlight the potential of gentamicin, and possibly structurally related natural compounds, as modulators of host inflammatory pathways implicated in acne. The study further underscores the utility of integrating transcriptomics, molecular docking, and MD simulation for early-phase therapeutic discovery targeting inflammation and barrier dysfunction in dermatological diseases. Full article

The development of advanced drug delivery systems is essential for improving therapeutic efficacy, particularly in the treatment of neurodegenerative disorders such as Alzheimer’s disease. This study investigates zinc-modified mordenite zeolite (MR-ZN) as a novel platform for the controlled delivery of donepezil (DPZ), a cholinesterase inhibitor. Natural mordenite was modified with zinc, enhancing its surface area from 62.1 to 85.4 m²/g and improving its adsorption properties. Donepezil was successfully loaded at two doses (10 mg and 23 mg), achieving high loading efficiencies of 95% and 94%, respectively. Adsorption kinetics followed a pseudo-second-order model (R² > 0.99), indicating that chemisorption predominates through coordination between DPZ functional groups and Zn²⁺ sites, while complementary physisorption via hydrogen bonding and van der Waals interactions also contributes to molecular stabilization within the zeolite framework. In vitro release studies under simulated gastrointestinal conditions demonstrated sustained and pH-responsive release profile with 80% and 82% of donepezil released after 24 h for 10 mg and 23 mg formulations, respectively. Density Functional Theory (DFT) calculations revealed favorable adsorption energy (−26.4 kJ/mol), while Bader and Electron Localization Function (ELF) analyses confirmed hydrogen bonding and electrostatic interactions without compromising the zeolite framework. These findings validate MR-ZN as structurally stable, efficient, cost-effective and biocompatible matrix for oral drug delivery. The combination of experimental data and theoretical modeling supports its potential to improve bioavailability and therapeutic performance in neurodegenerative treatment. Full article

Dopamine D2-like receptors, including D2, D3, and D4, are members of the aminergic G protein-coupled receptor (GPCR) family and are targets for neurological disorders. The development of subtype selective ligands is important for enhanced therapeutics and reduced side effects; however, it is challenging to design and develop selective ligands owing to the high degree of sequence homology among D2-like subtypes. To gain insight into the structural basis of subtype selectivity of piperazinylalkyl pyrazole/isoxazole analogs for D2-like dopamine receptors, we carried out 3D quantitative structure–activity relationship (3D-QSAR) and molecular docking studies. The 3D-QSAR models for the D2, D3, and D4 subtypes showed robust correlation coefficients (r²) of 0.960, 0.912, and 0.946, as well as reliable predictive values (Q²) of 0.511, 0.808, and 0.560, respectively. Contour map analysis revealed key structural determinants for ligand activity, highlighting the distinct steric and electrostatic requirements for each subtype. These findings were further rationalized by molecular docking studies, which confirmed that interactions with non-conserved residues modulate binding affinity. Crucially, our analysis identified a critical structural basis for D4 subtype selectivity. This selectivity is attributed to a spatial constraint within the hydrophobic pocket formed by TMs 3, 5, and 6. This constraint restricts the orientation of bulky substituents on the 4-phenylpiperazine moiety. These findings provide actionable structural insights for the rational design of next-generation subtype-selective antagonists for D2-like dopamine receptors. Full article

Inherited retinal dystrophies (IRDs) are clinically and genetically heterogeneous disorders. Most IRDs follow a monogenic inheritance pattern. However, an increasing number of unresolved cases suggest the possible contribution of oligogenic or digenic mechanisms. Here, we report two ultra-rare missense variants—AIPL1 R302L and BBS2 P134R—that co-segregate with early-onset nonsyndromic retinal degeneration in affected individuals from a non-consanguineous family. We performed a multi-level computational investigation to assess whether these variants may act through a convergent pathogenic mechanism. Using AlphaFold2-predicted structures, we modeled both wild-type and mutant proteins, introduced point mutations, and performed energy minimization and validation. FoldX, DynaMut2, and DUET all predicted destabilizing effects at the variant sites, corroborated by local disruption of secondary structure and altered surface electrostatics. Comparative docking (via HDOCK and ClusPro) identified a putative interaction interface between the TPR domain of AIPL1 and the β-sheet face of BBS2. This interface was destabilized in the double-mutant model. At the systems level, transcriptomic profiling confirmed co-expression of AIPL1 and BBS2 in human retina and fetal eye, while functional enrichment analysis highlighted overlapping involvement in ciliary and proteostasis pathways. Network propagation suggested that the two proteins may converge on shared interactors relevant to photoreceptor maintenance. Collectively, these in silico results provide structural and systems-level support for a candidate digenic mechanism involving AIPL1 and BBS2. While experimental validation remains necessary, our study proposes a testable mechanistic hypothesis and underscores the value of computational approaches in uncovering complex genetic contributions to IRDs. Full article

Solvents represent the quiet majority in biomolecular systems, yet modeling their influence with both speed and ri:gor remains a central challenge. This study maps the state of the art in implicit solvent theory and practice, spanning classical continuum electrostatics (PB/GB; DelPhi, APBS), modern nonpolar and cavity/dispersion treatments, and quantum–continuum models (PCM, COSMO/COSMO-RS, SMx/SMD). We highlight where these methods excel and where they falter, namely, around ion specificity, heterogeneous interfaces, entropic effects, and parameter sensitivity. We then spotlight two fast-moving frontiers that raise both accuracy and throughput: machine learning-augmented approaches that serve as PB-accurate surrogates, learn solvent-averaged potentials for MD, or supply residual corrections to GB/PB baselines, and quantum-centric workflows that couple continuum solvation methods, such as IEF-PCM, to sampling on real quantum hardware, pointing toward realistic solution-phase electronic structures at emerging scales. Applications across protein–ligand binding, nucleic acids, and intrinsically disordered proteins illustrate how implicit models enable rapid hypothesis testing, large design sweeps, and long-time sampling. Our perspective argues for hybridization as a best practice, meaning continuum cores refined by improved physics, such as multipolar water, ML correctors with uncertainty quantification and active learning, and quantum–continuum modules for chemically demanding steps. Full article

Grain boundaries are among the most influential structural features that control the charge transport in polycrystalline organic semiconductors. Acting as both charge trapping sites and electrostatic barriers, they disrupt molecular packing and introduce energetic disorder, thereby limiting carrier mobility, increasing threshold voltage, and degrading the stability of organic thin-film transistors (OTFTs). This review presents a detailed discussion of grain boundary formation, their impact on charge transport, and experimental strategies for engineering their structure and distribution across several high-mobility small-molecule semiconductors, including pentacene, TIPS pentacene, diF-TES-ADT, and rubrene. We explore grain boundary engineering approaches through solvent design, polymer additives, and external alignment methods that modulate crystallization dynamics and domain morphology. Then various case studies are discussed to demonstrate that optimized processing can yield larger, well-aligned grains with reduced boundary effects, leading to great mobility enhancements and improved device stability. By offering insights from structural characterization, device physics, and materials processing, this review outlines key directions for grain boundary control, which is essential for advancing the performance and stability of organic electronic devices. Full article

Intrinsically disordered regions (IDRs), defined as protein segments lacking stable tertiary structures, are ubiquitously present in the human proteome and enriched with disease-associated mutations. IDRs harbor molecular recognition features (MoRFs) and post-translational modification sites (e.g., phosphorylation), enabling dynamic intermolecular interactions through conformational plasticity. Furthermore, IDRs drive liquid–liquid phase separation (LLPS) of biomacromolecules via multivalent interactions such as electrostatic attraction and pi–pi interactions, generating biomolecular condensates that are essential throughout the cellular lifecycle. These condensates separate intracellular space, forming a physical barrier to avoid interference between other molecules, thereby improving reaction specificity and efficiency. As a dynamically equilibrated process, LLPS formation and maintenance are regulated by multiple factors, endowing the condensates with rapid responsiveness to environmental cues and functional versatility in modulating diverse signaling cascades. Consequently, disruption of LLPS homeostasis can derail its associated biological processes, ultimately contributing to disease pathogenesis. Moreover, precisely because liquid–liquid phase separation (LLPS) is co-regulated by multiple factors, it may provide novel insights into the pathogenic mechanisms of disorders such as autism spectrum disorder (ASD), which result from the cumulative effects of multiple etiological factors. Full article

The performance of electrochemical (bio)sensors is fundamentally determined by the precise engineering of interfacial layers that govern (bio)analyte–surface interactions. However, elucidating structure–function relationships remains challenging due to the complex architecture of modern sensors and the irregular nanoscale morphology of many high-performance materials. In this study, we present a strategy for designing custom functional interfaces as well-defined platforms for probing interfacial processes. Focusing on epinephrine (EP) detection as an important representative of catecholamines, we compare the interfacial behavior of two carboxy-functionalized electrodes—grafted with either para-aminobenzoic acid (PAB) or 3,4,5-tricarboxybenzenediazonium (ATA)—against atomically flat highly oriented pyrolytic graphite (HOPG) as a control. While both modifiers introduce carboxyl groups, PAB forms disordered multilayers that inhibit surface responsiveness, whereas ATA yields an ultrathin monolayer with accessible COOH groups. Electrochemical analysis reveals that ATA-HOPG significantly enhances EP detection at sub-micromolar levels, facilitated by electrostatic interactions between surface-bound COO⁻ and protonated EP and its redox products. These results demonstrate that nanoscale control of diazonium grafting is crucial for optimizing bioanalyte recognition. More broadly, this work highlights how molecular-level surface engineering on high-quality carbon substrates can serve as a test-bed platform for the rational design of advanced electrochemical sensing interfaces. Full article