Search Results (282)

This study presents a comprehensive bibliometric analysis of research on 2xxx series aluminum–copper (Al–Cu) alloys published between 2020 and 2025. A complete analysis of 4380 documents from 747 sources indexed in Scopus reveals sustained research growth, with publications rising from 603 in 2020 to 948 in 2025 at a compound annual growth rate of 9.5%. China dominates global output, contributing 35.7% of publications with Central South University as the leading institution (548 articles). However, China’s international collaboration rate (12.2%) remains notably lower than Western counterparts such as the United Kingdom (62.5%) and Canada (53.2%). Core journals including the Journal of Alloys and Compounds, Materials Science and Engineering: A, and Journal of Materials Research and Technology collectively account for 11.4% of total publications, conforming to Bradford’s Law concentration patterns. Keyword co-occurrence analysis revealed five distinct thematic clusters centered on microstructure–property relationships, friction stir welding and joining technologies, corrosion mechanisms, Al–Cu–Li aerospace alloys, and additive manufacturing. While life cycle modeling (K = 5993; tm = 2022.84) indicates the field is approaching maturity, by identifying emerging frontiers such as machine learning-assisted alloy design, sustainable processing routes, and multi-material joining for electric vehicles, this study offers researchers a quantitative roadmap of the Al–Cu alloy knowledge landscape and highlights strategic opportunities for future investigation. Full article

The eukaryotic translation initiation factor 4E (eIF4E) family plays a dual role in plants, regulating cap-dependent protein synthesis and mediating susceptibility to viruses in the family Potyviridae. In cowpea (Vigna unguiculata (L.) Walp.), an economically important legume cultivated worldwide, the structural determinants of these isoforms remain largely unexplored. This study characterizes the genomic organization, evolutionary history, and conformational dynamics of eIF4E, eIF(iso)4E, and nCBP in cowpea using a multi-omics approach. Genome mining identified three paralogous genes located on chromosomes 4, 6, and 7, showing high synteny with Phaseolus vulgaris. Phylogenetic analysis confirmed nCBP as the ancestral Class I lineage, distinct from the Class II eIF4E and eIF(iso)4E clades. Theoretical models for the isoforms were generated and subsequently validated by molecular dynamics simulations, revealing that while all isoforms preserve the canonical tertiary architecture and an electropositive cap-binding pocket, eIF(iso)4E exhibits superior structural compactness and hydrogen-bond stability. These biophysical features highlight their role as a stable anchor for viral VPg proteins. By elucidating the atomic-level landscape of these factors, we provide a robust structural framework to guide allele mining and genome-editing strategies aiming to engineer virus-resistant cowpea cultivars without compromising agronomic performance. Full article

Sustainable spatial development requires land-use allocation that aligns with reflects the environment’s biophysical capacity. However, rapid urbanization and agricultural expansion often result to spatial mismatches between land utilization and land capability, the reby increasing environmental degradation and disaster vulnerability. East Java Province, one of Indonesia’s most densely populated regions, has experienced significant land-use transformation driven by demographic pressure and economic development. This study aims to evaluate the environmental carrying capacity by assessing the spatial compatibility among land capability, existing land use, and the Provincial Spatial Plan (RTRWP) using a Geographic Information System (GIS)-based analytical approach. Land capability was determined based on key biophysical parameters, including slope gradient, soil texture, drainage conditions, erosion susceptibility, effective soil depth, and flood hazard. Spatial overlay analysis was employed to identify areas of conformity and mismatch between land capability and both current and planned land uses. The results indicate that only approximately 52% of the provincial area is utilised in accordance with its land capability. In comparison, the remaining 48% exhibits varying degrees of spatial mismatch. Erosion is identified as the dominant limiting factor, affecting more than 43% of the region, particularly in mountainous and hilly landscapes. Furthermore, over 60% of East Java falls within Land Capability Classes III–VII, indicating moderate to severe environmental constraints on limitations intensive land use. High levels of spatial mismatch are concentrated in the southern upland districts—such as Pacitan, Trenggalek, southern Malang, and Lumajang, which are highly susceptible to landslides, as well as in the northern lowland corridor, including the Surabaya–Gresik–Sidoarjo metropolitan region, which faces a significantly flood risk. These findings suggest that land-use practices exceeding environmental carrying capacity substantially amplify disaster risk. Therefore, integrating land capability assessment into spatial planning and zoning regulations is essential and for promoting ecosystem-based disaster risk reduction and achieving sustainable spatial development in East Java Province. Full article

The present work set out to examine the antidiabetic capacity of Abelmoschus esculentus (okra) fruit extract through a combined experimental and computational framework. Enzyme inhibition assays were carried out against four metabolic targets, and IC₅₀ values stood at 7.66 ± 0.31 mg/mL for alpha-glucosidase, 5.21 ± 0.18 mg/mL for alpha-amylase, 2.11 ± 0.15 microg/mL for DPP-4, and 9.17 ± 0.54 mg/mL for pancreatic lipase. The extract showed moderate-to-weak activity relative to standard inhibitors acarbose, sitagliptin, and orlistat. Sixteen drug-like phytochemicals obtained from the IMPPAT 2.0 database were docked against the crystal structures of all four tested enzymes (PDB: 8CB1, 5E0F, 2ONC, 1LPB). Alpha-Carotene, Vitamin E, and Spiraeoside emerged as the top-ranked compounds across all targets, with alpha-Carotene recording the strongest binding affinity of −11.1 kcal/mol against pancreatic lipase, which was 4.2 kcal/mol more negative than the positive control orlistat (−6.9 kcal/mol). PLIP-based interaction profiling mapped out hydrogen bonds, hydrophobic contacts, pi-stacking, and salt bridges at the atomic level. Absorption, distribution, metabolism, and excretion (ADME) and toxicity screening of alpha-Carotene returned a favourable pharmacokinetic profile with predicted LD₅₀ of 1510 mg/kg (Class 4) and inactivity across most toxicity endpoints. A 100 ns molecular dynamics simulation of the pancreatic lipase-alpha–Carotene complex, alongside the orlistat control, showed stable root mean square deviation (RMSD) (0.15–0.22 nm), a consistent Rg (~1.97 nm), and sustained hydrogen bonding throughout the trajectory. Free-energy landscape analysis revealed a well-defined single energy basin for alpha-Carotene, suggesting a thermodynamically stable binding conformation. These findings lay the molecular basis for using okra phytochemicals as adjunctive agents in diabetes management, though in vivo validation remains necessary. Full article

Allosteric modulation has emerged as a powerful strategy for achieving superior selectivity and safety in drug discovery and protein function regulation. Unlike highly conserved orthosteric sites, allosteric pockets are structurally diverse and less evolutionarily constrained, making them particularly suitable for modulation by designed miniproteins. Miniproteins can provide extended binding interfaces and high affinity for shallow, dynamic, or cryptic regulatory surfaces that are often inaccessible to small molecules. Recent advances in artificial intelligence (AI) are transforming this field through deep learning-based structure prediction and generative modeling. These AI-driven approaches enable the identification of allosteric hotspots, characterization of conformational ensembles, and de novo design of structured miniprotein binders. They are rapidly expanding the landscape for designing selective modulators across diverse allosteric targets, including GPCRs, receptor tyrosine kinases, nuclear receptors, ion channels, and other protein–protein interaction systems. This review summarizes state-of-the-art AI-driven computational methodologies for designing miniproteins as potential allosteric modulators and discusses their current challenges and future opportunities in allosteric drug discovery. Full article

In this study, we investigated the genomic basis of key body measurement and weight traits in Iraqi Awassi sheep using a multi-locus genome-wide association approach. A total of 315 yearling animals were phenotyped for body length, chest depth, heart girth, withers height, and body weight, and genotyped using the Ovine 50K SNP BeadChip. Genome-wide association analyses were performed within the BLUPmrMLM framework to improve the detection of loci with moderate-to-small effects. Significant associations were identified using an LOD-based threshold (LOD ≥ 5), followed by positional annotation of nearby genes and functional enrichment analyses to infer their potential biological relevance. Multiple genomic regions were associated with the evaluated traits. Among the most biologically plausible candidate genes were DST and CFAP299 for body length, ADAMTS8 for chest depth, ZFPM1 and OST4 for heart girth, CPEB2 for body weight, and ITGBL1, RBMS3, and THSD7B for withers height. Functional enrichment analyses indicated the involvement of pathways related to integrin-mediated signaling, focal adhesion and integrin complexes, extracellular matrix organization, and post-transcriptional regulation, suggesting coordinated effects of cell–matrix interactions and gene-expression regulation on body size and conformation. Overall, these findings refine the genomic landscape underlying body weight and morphometric variation in Awassi sheep and provide a focused set of loci for future validation and possible application in marker-assisted and genomic selection programs. Full article

The human metapneumovirus (HMPV) Fusion (F) glycoprotein is a high-priority target for “fusion-locking” agents that stabilize its metastable prefusion state. While monomeric catechins like EGCG are known antivirals, the molecular basis for the superior activity of structurally complex dimeric catechins remains poorly understood. We employed an advanced biophysical workflow, integrating 100 ns all-atom molecular dynamics (MD), free energy landscape (FEL) analysis, and MM/GBSA thermodynamic integration to decode the Structure–Dynamics Relationship (SDR) of 210 Camellia sinensis (Green tea) phytochemicals. The results reveal a “Galloylation-Driven Anchoring” mechanism: the galloyl moiety of prodelphinidin A2 3′-gallate provides critical electrostatic complementarity to the Asp325-Asp336 acidic ridge. FEL analysis quantitatively demonstrates that this anchoring leads to pronounced stabilization of the F protein in a deep, kinetically favored global minimum (ΔG = 9.357 kJ/mol), effectively raising the energy barrier for the fusogenic conformational shift. This study provides a comparative and mechanistically informed computational proof-of-concept for the use of dimeric natural scaffolds as precision fusion-locking agents, offering a roadmap for experimental biophysical validation. In this workflow, molecular docking was employed exclusively as a qualitative structure-based filtering step, while all quantitative conclusions regarding stabilization and binding energetics were derived from post-docking MD, FEL, and MM/GBSA analyses. Full article

Biocompatible thin films are essential for advancing biomedical devices, as they enhance integration with biological tissues, improve device longevity, and reduce complications. The rapid evolution of both medical needs and materials science has led to a diverse array of deposition techniques, each offering unique advantages and challenges for tailoring surface properties without compromising the bulk characteristics of implants and sensors. While laser-based methods—such as pulsed laser deposition (PLD) and Matrix-Assisted Pulsed Laser Evaporation (MAPLE)—are renowned for their precision, ability to preserve complex material stoichiometry, and suitability for low-temperature processing, the broader landscape includes several other important approaches. Physical Vapor Deposition (PVD) techniques, including magnetron sputtering and pulsed electron deposition, are widely used for their ability to create uniform, adherent coatings with controlled thickness and composition, making them suitable for both hard and soft biomedical substrates. Chemical Vapor Deposition (CVD) and its plasma-enhanced variant (PECVD) offer conformal coatings and excellent control over film chemistry, which is particularly valuable for functional polymer and ceramic films. Other methods, such as sol–gel processing, ion beam deposition, and electrophoretic deposition, provide additional flexibility in terms of coating composition, adhesion, and processing temperature, allowing for the fabrication of films with tailored mechanical, chemical, and biological properties. Despite these advances, the field faces ongoing challenges in optimizing film properties for specific clinical applications, ensuring reproducibility, and scaling up production for widespread use. The necessity of this review lies in its comprehensive comparison of laser-based techniques with alternative deposition methods, providing critical insights into their respective strengths, limitations, and suitability for different biomedical scenarios. By synthesizing recent developments and highlighting current gaps, this review aims to guide researchers and clinicians in selecting the most appropriate thin-film deposition strategies to meet the evolving demands of next-generation biomedical devices. Full article

Nme1Cas9 is an encouraging genome-editing tool with high fidelity and compactness, but its applications are limited by poor catalytic efficiency compared with SpyCas9. Understanding the dynamic activation mechanism of the HNH nuclease domain is the key to breaking the kinetic bottleneck. Here, we integrated Steered Molecular Dynamics (SMD) with the Traveling-Salesman-based automated Path Searching (TAPS) algorithm to reconstruct the atomic-level activation landscape of the L1-HNH module. The simulations suggest a complex “Lifting-Rearrangement-Sliding” pathway, revealing the critical role of a “Backbone Sliding” conformation; in this step, the HNH domain rotates across the R-loop surface. A thermodynamic analysis using free energy decomposition by MM/PBSA indicates that the intrinsic instability of the wild-type HNH/R-loop interface constitutes the predominant energetic barrier. Hyperactive variants (S593Q/W596K and S593Q/W596R) can overcome this barrier by substantially increasing binding affinity to the R-loop through a “Geometry–Electrostatics Synergism”: S593Q improves interfacial proximity, whereas W596K/R acts as an “Electrostatic Anchor.” The results of unbiased MD simulations demonstrate that strengthened interfacial interactions effectively promote spontaneous conformational drift toward the activated state. This computational study proposes a novel in silico model for “Dynamic Interface Engineering” in which reinforcing transient interfacial contacts during conformational sliding can be an effective strategy in developing high-efficiency CRISPR-Cas effectors. 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

Background/Objectives: The tumor suppressor gene TP53 is one of the most frequently mutated genes in human cancers, with alterations predominantly affecting its DNA-binding domain (DBD). However, the mutational landscape and functional consequences of TP53 variants remain poorly characterized in African populations. This study aimed to characterize mutations in exons 5–6 of TP53 in oral cavity cancer (OCC), prostate cancer (PC), and breast cancer (BC) in a Senegalese population, and to assess their structural effects, functional consequences, and impact on protein–protein interactions with BCL-2. Methods: Seventy-eight archived tumor DNA samples from Senegalese patients with OCC, PC, and BC were analyzed. Variants were annotated using COSMIC and dbSNP databases. Functional impact was evaluated with PolyPhen-2. Structural stability changes ($\Delta \Delta G$) were predicted using FoldX, conformational dynamics ($\Delta \Delta S_{vib}$) were assessed with ENCoM, and effects on the p53–BCL-2 interaction were analyzed using DDMut-PPI. Statistical analyses were also performed. Results: BC exhibited the highest TP53 mutation frequency, whereas OCC showed greater mutational diversity. Exon-level analysis revealed a significant enrichment of exon 6 mutations in BC. Structural analyses indicated that exon 5 mutations across all cancers and mutations in OCC were predominantly destabilizing and associated with loss-of-function effects. In contrast, recurrent exon 6 mutations in PC and BC, particularly V217L and V218M, were predicted to stabilize the p53 structure. Conformational dynamics differences between exons were significant only in PC. All analyzed mutations were predicted to stabilize the p53–BCL-2 interaction. Conclusions: This integrative in silico study identified cancer and exon-specific TP53 mutation patterns in a Senegalese population, highlighting exon 6 as a context-dependent hotspot with potential oncogenic implication in PC and BC. Despite its computational nature, the study provides valuable insights that merit further investigation. Full article

Background/Objectives: Breast cancer remains a leading cause of cancer-related mortality in women, with therapeutic resistance frequently arising from tumor heterogeneity and an immunosuppressive tumor immune microenvironment (TIME). While Cynomorium songaricum Rupr. (CS) has been used traditionally in Chinese medicine and exhibits preliminary anti-tumor activity, its bioactive constituents and precise mechanisms against breast cancer remain to be elucidated. Methods: The chemical constituents of CS were systematically profiled using ultra-high-performance liquid chromatography coupled with Q Exactive Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap MS/MS). Network pharmacology and functional enrichment analyses were performed to identify immuno-related targets and pathways, followed by molecular docking to prioritize component–target pairs. Molecular dynamics (MD) simulations were conducted to validate the stability of a representative docked complex and to characterize binding stability, interaction persistence, molecular mechanics/(Poisson–Boltzmann) surface area (MM/(P)BSA) energetics, and principal component analysis (PCA)-based conformational landscapes. Results: We identified 1100 compounds, of which 84 satisfied the in silico drug-likeness criteria, including 12 phenylpropanoids, 4 terpenes, 35 flavonoids, 2 quinones, 1 phenol, 3 alkaloids, and other phytochemicals. Network pharmacology analysis revealed 776 overlapping targets associated with both breast cancer and immune regulation. Functional enrichment analysis underscored significant involvement in immune-related pathways, and molecular docking studies supported high-affinity interactions between the components and their targets. MD analyses further supported a stable bound ensemble for the representative SRC–Tomentogenin complex during the equilibrated window, with persistent pocket occupancy, consistent interaction signatures, favorable MM/(P)BSA binding energetics, and a concentrated low-energy basin on the PCA-based free energy landscape. Conclusions: These findings elucidate the chemical basis of CS and uncover its immunomodulatory mechanism against breast cancer, offering a foundation for developing CS-based immunotherapeutic strategies and supporting multi-target drug discovery from traditional medicines. Full article

Human metapneumovirus genotype B (HMPV-B) is an important respiratory pathogen, requiring detailed elucidation of the evolutionary and antigenic features of its fusion (F) gene. Using 500 sequences collected between 1982 and 2024, we investigated the molecular evolution, phylodynamics, and structural epitope landscape of the HMPV-B F gene. Time-scaled phylogeny dated the divergence of sublineages B1 and B2 to around 1937, and Bayesian Skyline Plot analysis showed that these sublineages exhibited distinct demographic trajectories over time. The F gene evolved at a rate of 1.01 × 10⁻³ substitutions/site/year; however, amino acid variation remained limited, consistent with pervasive purifying selection, with 39% of codons under strong negative selection and little consensus evidence for positive selection. Conformational B-cell epitope prediction demonstrated a high degree of conservation across neutralizing antibody binding regions (sites Ø and I–V), and amino acid substitutions occurring within these sites were not predicted to substantially alter epitope architecture. Together, these findings indicate that the HMPV-B F gene evolves under strong evolutionary constraint while maintaining stable antigenic features, supporting the potential for antibody-based strategies that target neutralizing antibody binding regions of the F protein. Full article

Synucleinopathies, including Parkinson’s disease (PD), are neurodegenerative disorders characterized by aberrant aggregation of α-synuclein (α-syn), a presynaptic protein with an intrinsic disorder nature. The transition of soluble monomers into oligomeric and fibrillar species represents a key molecular event driving neuronal dysfunction and neurodegeneration. Emerging evidence suggests that nutraceuticals, bioactive compounds derived from dietary sources, can modulate α-syn aggregation at multiple conformational stages. Polyphenols, alkaloids, ginsenosides, and food-derived peptides interfere with α-syn structure and assembly, suppressing the formation of toxic oligomer species and promoting the clearance of misfolded assemblies. Despite this potential, clinical translational of nutraceuticals is currently limited by poor systemic bioavailability and restricted central nervous system penetration due to blood–brain barrier constraints, which have largely confined research to preclinical studies. In this context, this review summarizes current knowledge of nutraceutical interventions targeting the conformational landscape of α-syn and highlighting both direct and indirect molecular mechanisms with involved in aggregation-prone species. Furthermore, we critically examine key challenges related to bioavailability and clinical translation, focusing on advanced delivery systems and precision-based approaches to enhance neuroprotective efficacy and support the potential of nutraceuticals as novel or adjunctive therapeutic strategies for PD. Full article

Wee1-like protein kinase 2 (WEE2) is an oocyte-specific kinase that regulates meiotic arrest and fertilization. Its largely restricted expression in female germ cells and absence in somatic tissues make it a highly selective target for reproductive health interventions. Despite its central role in human fertility, no clinically approved WEE2 modulator is available. In this study, we employed an integrated in silico approach that combines structure-based virtual screening, molecular dynamics (MD) simulations, and MM-PBSA free-energy calculations to identify repurposed drug candidates with potential WEE2 inhibitory activity. Screening of ~3800 DrugBank compounds against the WEE2 catalytic domain yielded ten high-affinity hits, from which Midostaurin and Nilotinib emerged as the most mechanistically relevant based on kinase-targeting properties and pharmacological profiles. Docking analyses revealed strong binding affinities (−11.5 and −11.3 kcal/mol) and interaction fingerprints highly similar to the reference inhibitor MK1775, including key contacts with hinge-region residues Val220, Tyr291, and Cys292. All-atom MD simulations for 300 ns demonstrated that both compounds induce stable protein–ligand complexes with minimal conformational drift, decreased residual flexibility, preserved compactness, and stable intramolecular hydrogen-bond networks. Principal component and free-energy landscape analyses further indicate restricted conformational sampling of WEE2 upon ligand binding, supporting ligand-induced stabilization of the catalytic domain. MM-PBSA calculations confirmed favorable binding free energies for Midostaurin (−18.78 ± 2.23 kJ/mol) and Nilotinib (−17.47 ± 2.95 kJ/mol), exceeding that of MK1775. To increase the translational prioritization of candidate hits, we place our structure-based pipeline in the context of modern machine learning (ML) and deep learning (DL)-enabled virtual screening workflows. ML/DL rescoring and graph-based molecular property predictors can rapidly re-rank docking hits and estimate absorption, distribution, metabolism, excretion, and toxicity (ADMET) liabilities before in vitro evaluation. Full article