Search Results (194)

Polyethylene terephthalate (PET) is one of the most widely used synthetic plastics and a major contributor to global plastic pollution because of its high resistance to degradation. Enzymatic degradation by PET hydrolases (PETase) has emerged as a sustainable strategy for PET recycling; however, the limited thermostability of wild-type PETase restricts its industrial application. To elucidate the molecular basis underlying the different thermal behaviors of PET hydrolases, long-timescale molecular dynamics simulations were performed on WT-PETase, FAST-PETase, and the thermostable cutinase variant LCC-ICCG at 30 °C, 50 °C, and 70 °C. Comparative analyses integrating structural stability, residue flexibility, rigidity networks, free energy landscapes, and neural relational inference models revealed that FAST-PETase and LCC-ICCG exhibited enhanced conformational stability and reduced structural flexibility compared with WT-PETase, particularly under elevated temperatures. The improved thermostability was associated with more compact free energy landscapes, strengthened residue interaction networks, and better preservation of the catalytic architecture during thermal perturbation. These results suggest that an optimal balance between structural rigidity and conformational flexibility is critical for maintaining enzyme stability at elevated temperatures. Overall, this study provides molecular-level insights into the structural determinants of PETase thermostability and offers a theoretical framework for the rational engineering of efficient and heat-resistant plastic-degrading enzymes. Full article

Landscape structures generate significant life-cycle embodied carbon due to material redundancy and low structural efficiency. While topology optimization provides a scientific basis for material reduction, its resulting free-form surfaces and complex joints often hinder manufacturing and on-site assembly. This study introduces the Design for Manufacture and Assembly (DfMA) method to address these challenges, using landscape benches, pavilions, and bridges in the Beijing Olympic Forest Park as case studies. After data collection, we performed topology optimization via Autodesk Fusion and applied DfMA principles to simplify complex topological forms into standardized, modular structural systems. Life-cycle embodied carbon emissions were then compared across initial, topology-optimized, and DfMA-simplified designs. The results indicate that while topology optimization reduces material usage by 19–85%, it may increase total carbon emissions, especially in complex metal structures, due to higher construction energy demands and recycling difficulties. In contrast, DfMA simplification significantly improves manufacturing feasibility, cutting total carbon emissions by 33–64% compared to initial designs. The material production phase exhibited the most prominent carbon reduction, contributing an average of 60% to total emission savings. Ultimately, this study highlights that topology optimization alone is not universally carbon-reducing, and it requires DfMA-oriented simplification to achieve reliable low-carbon outcomes. Full article

Background: The development of multitarget drugs capable of simultaneously inhibiting SARS-CoV-2 proteases—3CL^pro and PL^pro—may enhance therapeutic efficacy against COVID-19. Given the historical use of Traditional Chinese Medicine (TCM) in the management of respiratory diseases, phenylethanoid glycosides (PGs) represent an attractive and chemically diverse natural product scaffold for the discovery of antiviral agents. Objectives: This study aimed to identify promising candidates within this class capable of simultaneously inhibiting both target proteases. Methods: The PG structures described in the literature between 1950 and 2020 were gathered and curated to construct a dedicated database, which was subsequently subjected to virtual screening. In silico ADMETox predictions and 2D ligand–protein interaction analyses were then employed to evaluate the identified hit PGs. Ligand stability within the binding sites of the proteases was further assessed using free energy landscape (FEL) and MM/GBSA calculations, while enzymatic inhibition of the commercial PG was evaluated via FRET assays. Results: Virtual screening identified 22 PGs with multitarget potential, predominantly sourced from Asia, followed by the Americas and Europe. The hit compound magnoloside I is found in Magnolia officinalis, a species widely used in TCM for respiratory conditions and officially prescribed during the COVID-19 pandemic. A second hit, calceolarioside B, inhibited more than 90% of the enzymatic activity of both proteases in the FRET assay. Conclusions: Together, these findings highlight phenylethanoid glycosides as promising scaffolds for dual protease inhibition. Full article

The nature of non-Arrhenius kinetics of protein unfolding is investigated in this study. Free-energy profiles along the reaction coordinate of protein unfolding are built in a wide temperature interval. These profiles reveal the temperature-dependent contribution of the intermediate assigned to be the dry molten globule (DMG) state, stabilized by the entropy gain provided by the loose framework of extended hydrogen bonds. The revealed DMG state with a loose pseudo-secondary structure of protein provides a funnel-shaped free-energy landscape, which is a central point of the folding mechanism, rationalizing Levinthal’s paradox. The rate constants of the elementary steps of the unfolding process are calculated according to Transition State Theory. The strong temperature dependence of the Arrhenius parameters for the rate constants of the elementary steps of the unfolding process, and the negative activation energy of the folding process are explained. The main factor influencing the non-Arrhenius behavior of the rate constants is the strong temperature-dependent shift in the location of the DMG and Transition State along the reaction coordinate. The Arrhenius plot for the calculated rate constant for heat denaturation of the protein in a wide temperature range (270–600 K) is built. Its “convex” shape and the sharp drop in the values of the Arrhenius parameters at high temperatures are in very good agreement with the experimentally observed dependencies. Full article

In November 2024, a highly mutated descendant of the Omicron BA.3 subvariant, designated BA.3.2, emerged in South Africa carrying 39 spike mutations, two large N-terminal domain (NTD) deletions and a novel four-amino acid insertion. A key feature of BA.3.2 is extensive NTD remodeling, including a major deletion spanning residues 135–148 affecting the β-hairpin region and contributing to the loss of most of the N1 loop. This study compares the evolutionary dynamics and structural features of BA.3.2 with BA.3. Phylodynamic analyses show that BA.3 underwent early demographic stability followed by a decline in genetic diversity, consistent with limited circulation, whereas BA.3.2 displays recent emergence and a progressive reduction in effective population size without rapid expansion. Selection analyses indicate BA.3 evolution is mainly driven by changes in the receptor-binding domain, while BA.3.2 shows dispersed signals across spike regions, including codon 1162. Structural and molecular dynamic analyses reveal increased flexibility and a broader conformational landscape in the BA.3.2 NTD, driven by the deletion and resulting loss of stabilizing interactions. Overall, BA.3.2 follows a distinct evolutionary trajectory characterized by antigenic remodeling of the spike NTD, underlining the need for continued surveillance of emerging SARS-CoV-2 descendant lineages. Full article

Background/Objectives: The EGFR T790M mutation drives lung cancer resistance by sterically hindering inhibitors and restoring ATP affinity. As C797S mutations render covalent inhibitors obsolete, novel non-covalent strategies are critical. This study identifies inhibitors that redefine the mutant methionine sulfur as a primary stabilizing anchor rather than a liability. Methods: A generative AI framework (DrugEx) sampled 100,000 molecules, prioritized via QSAR classification (ROC-AUC: 0.91 ± 0.01) and Applicability Domain (AD) mapping. The workflow was de-risked through retrospective benchmarking against the DUD-E database (35,590 molecules), achieving a 1% Enrichment Factor of 5.19. Lead candidates underwent 100 ns all-atom molecular dynamics (MD) simulations. Mechanistic stability was quantified via Free Energy Landscape (FEL) analysis and ensemble-averaged MM-GBSA binding free energy calculations. Results: Candidate 106 demonstrated exceptional mutation tolerance by redistributing interactions toward the Met790 sulfur atom. MD analysis confirmed potency is dictated by successful recruitment of the thioether environment, locking the complex within a narrow thermodynamic basin. Candidate 106 maintained stable binding (−11.0 kcal/mol) corroborated by an equipotent MM-GBSA ΔG_bind of −50.51 kcal/mol in the mutant system, driven by persistent π-sulfur contacts (85% occupancy). Conclusions: These results indicates that potential T790M resistance bypass is achievable by exploiting the gatekeeper methionine’s electronic environment. This modeled mutation-aware framework provides a candidate non-covalent strategy to be validated in future wet-lab campaigns. Full article

The escalating crisis of herbicide-resistant weeds threatens global wheat production. While key mutations are well-documented in weeds, the principles governing their interactions in wheat remain largely unknown. Here, we first developed a novel wheat germplasm carrying the acetolactate synthase (TaALS) Ser-627-Asn (S627N) mutation via ethyl methanesulfonate (EMS) mutagenesis. We then employed a computational design strategy to explore its synergy with the prevalent Trp-548-Leu (W548L) mutation—a combination not yet reported in nature. Integrated molecular dynamics (MD) simulations and free energy landscape analysis revealed that the in silico W548L/S627N double mutant triggers synergistic global destabilization of the herbicide–enzyme complex. Binding affinity progressively weakened from wild-type (−25.54 ± 2.05 kcal/mol) to the double mutant (−18.13 ± 2.76 kcal/mol), driven by a polarity inversion at the Arg-347 anchor. Comparative transcriptomic profiling of the S627N germplasm confirmed the absence of deleterious metabolic feedback in the branched-chain amino acid biosynthesis pathway. This work exemplifies a paradigm shift from mimicking natural variation to predictive crop design via multiplex gene editing. Full article

The laminin-derived nonapeptide CDPGYIGSR contains the bioactive YIGSR motif, historically associated with inhibition of tumor cell adhesion, invasion, angiogenesis, and laminin-receptor-mediated cell responses. Although these activities have often been attributed to the 37/67 kDa laminin receptor/RPSA axis, the molecular identity and organization of the laminin-binding receptor system remain debated. This uncertainty makes it essential to define the intrinsic conformational preferences of CDPGYIGSR in solution before assigning a unique receptor-bound structure. In this study, temperature replica-exchange molecular dynamics (T-REMD) simulations in explicit solvent are employed to characterize the solution conformational ensemble of CDPGYIGSR. Free energy landscape analysis, clustering, and structural descriptors reveal a predominant compact bend-like backbone arrangement, together with alternative low-lying conformational states within a heterogeneous ensemble. Rather than assuming a single bioactive conformation, the conformational ensemble is analyzed in terms of structural features that are consistent with available NMR observations and reported structure–activity relationships. Importantly, the most populated conformations in solution do not necessarily correspond to the bioactive state upon receptor binding. Instead, a subset of conformations sharing common structural motifs, including a central backbone bend and specific residue exposure patterns, may represent states compatible with receptor recognition. These results provide an ensemble-based structural framework that connects simulation-derived conformational motifs with available NMR observations and structure–activity data, supporting a recognition-compatible ensemble model in which compact preorganized states may contribute to receptor binding. Full article

We introduce a single dimensionless landscape function $J_{\mathrm{chem}}\left(\rho \right)=cosh(\rho ln\phi )-1$, with $\phi =(1+\sqrt{5})/2$, defined on the noble gas-centred coordinate $\rho =d/L_p\in [0,1)$, and show that it organizes four central within-period atomic observables, first ionization energy ${\mathrm{IE}}_1$, electron affinity $\mathrm{EA}$, Mulliken electronegativity ${\chi }_M$, and Pearson chemical hardness $\eta$, on a single periodic-table axis. The outward step $\Delta J_{\mathrm{chem}}^{+}$ delivers ${\mathrm{IE}}_1$, the inward gap $\Delta J_{\mathrm{chem}}^{-}=J_{\mathrm{chem}}\left(1\right)-J_{\mathrm{chem}}\left(\rho \right)$ delivers $\mathrm{EA}$ and $\eta$, and ${\chi }_M$ follows from Mulliken’s identity. Benchmarked against NIST and Pearson tabulated atomic data, the framework reproduces the within-period ${\mathrm{IE}}_1$ envelope across periods 2–6 and localizes every upward deviation on the textbook anomaly sites $\{p^3,d^5,f^7,s^2,d^{10}\}$; it yields two parameter-free golden ratio ionization-energy identities (${\phi }^{1/4}$ on heavy noble gas pairs and ${\phi }^2$ on halogen/alkali pairs, agreeing with data to MAD $\approx 1\%$ and $\approx 5\%$); and it provides single-parameter analytical fits for $\mathrm{EA}$ (MAE $0.3$–$0.4$ eV), Pearson hardness $\eta$, and Mulliken ${\chi }_M$ ($R^2=0.73$ on a 15-atom 4-class benchmark). By assembling four periodic-table observables under one golden ratio cosh coordinate, the construction provides a compact analytical reference against which relativistic and shell-anomaly corrections can be quantified. Full article

Voltage-gated sodium channels are central to electrical excitability, and Nav1.7 is a major therapeutic target implicated in pain disorders and sensory signaling. Within the channel pore, permeating Na⁺ ions experience dynamically fluctuating hydration and coordination environments that may influence local ion–protein interactions. Identifying chemically distinct coordination states from molecular dynamics (MD) simulations is an important prerequisite for future higher-level electronic structure investigations. In this study, we present a reproducible workflow for identifying and classifying Na⁺ hydration–coordination microstates in the Nav1.7 pore using explicit-solvent molecular dynamics simulations. A geometrically defined pore region was used to quantify pore hydration and Na⁺ inner-shell coordination based on a 3.2 Å Na–O distance criterion. Na⁺ configurations were classified according to ligand identity into water-only (W), mixed protein–water (PW), and protein-only (P) microstates. Analysis of a 2 ns proof-of-principle simulation revealed a persistently hydrated pore environment, with Na⁺ coordination dominated by water-rich states and a smaller but distinct population of protein-contact configurations. These observations demonstrate that local coordination environments are chemically heterogeneous and cannot be fully described by hydration number alone. Representative structures from each microstate class were extracted to provide candidate configurations for future quantum mechanical, Quantum Mechanics/Molecular Mechanics (QM/MM), or density functional theory investigations of ion–ligand interactions in confined pore environments. The present work establishes a transparent and reproducible microstate-selection framework and does not report quantum mechanical energies, free-energy landscapes, or converged microstate populations. More broadly, the workflow provides a practical strategy for reducing complex MD ensembles into chemically interpretable coordination states suitable for subsequent higher-level analysis. Full article

Background: Helicobacter pylori is a globally prevalent gastric pathogen associated with chronic gastritis, peptic ulcer disease, and gastric adenocarcinoma. Its persistence within the gastric niche is strongly linked to biofilm formation, contributing to immune evasion and antibiotic therapy resistance. Methodology: In the present study, we investigated the antibiofilm potential of capsaicin, a natural phytochemical derived from Capsicum species, against H. pylori using experimental and computational approaches. Results: Capsaicin treatment significantly reduced biofilm biomass (up to 75.66 ± 4.00%), metabolic activity (up to 61.23 ± 6.88%), and cell surface hydrophobicity in a dose-dependent manner. Microscopic analyses revealed disrupted biofilm architecture and diminished extracellular polymeric substance at higher concentrations. Molecular docking analysis revealed that capsaicin interacts with target H. pylori proteins (GTP cyclohydrolase II, α-carbonic anhydrase, and urease) through stable hydrogen bonds and hydrophobic contacts. Molecular dynamics simulations further supported the stability of these complexes and demonstrated reduced structural fluctuations upon ligand binding. Free energy landscape analysis suggested ligand-induced conformational alterations in α-carbonic anhydrase, indicating possible structural effects associated with capsaicin interaction. Conclusions: Overall, the findings provide insight into the antibiofilm activity of capsaicin against H. pylori and highlight its potential as a natural adjunct strategy for combating biofilm-associated persistence and antimicrobial resistance. Full article

Lauric acid is a characteristic component of Litsea cubeba seed oil, but FatB thioesterase candidates with predicted structural compatibility for C12 acyl-substrate accommodation remain insufficiently defined. In this study, seed oil content and fatty acid composition were examined during L. cubeba seed development. The fatty acid profile shifted from a C18:2-rich pattern at the early stage to a C12:0-dominated composition at later stages, providing the biochemical context for FatB candidate prioritization. Three FatB-like candidates were retrieved from a de novo seed transcriptome assembly and named LcFatB1, LcFatB2, and LcFatB3. Phylogenetic analysis, conserved motif comparison, sequence alignment, and homology modeling showed that LcFatB1 and LcFatB2 retained more complete FatB-like sequence and structural features than LcFatB3. S-dodecanoyl-4′-phosphopantetheine was used as a C12 acyl-4′-phosphopantetheine surrogate for molecular docking. Docking analysis indicated that LcFatB1 and LcFatB2 formed more interpretable C12-bound poses than LcFatB3. Subsequent 150 ns molecular dynamics simulations, free energy landscape analysis, residue–ligand interaction profiling, and catalytic tunnel analysis further distinguished the two main candidates. Compared with LcFatB2, LcFatB1 maintained a lower-displacement C12-bound state, a more compact contact environment involving Tyr116, Ser125, and Asn278, and a main tunnel with higher throughput and shorter length in the representative global-minimum conformation. LcFatB2 also retained the C12 surrogate but stabilized it in a distinct rearranged binding environment. These results support LcFatB1 as the strongest structurally prioritized FatB candidate among the three transcriptome-derived proteins, while LcFatB2 remains a plausible FatB-like candidate with a distinct C12-bound state. This prioritization provides computational structural clues for future biochemical testing but should not be interpreted as direct functional confirmation of FatB activity in vivo. Full article

Type 1 diabetes (T1D) is driven by autoreactive CD4⁺ T-cell responses to pancreatic beta cell antigens presented by disease-associated human leucocyte antigen (HLA) class II molecules. However, the molecular mechanisms by which subtle antigenic modifications promote pathogenic immunity remain incompletely defined. Recent immunopeptidomic studies have identified a cysteine-to-serine substitution at position 19 of the insulin B chain, referred to as InsC19S, as a microenvironment-driven neoepitope that can be presented by HLA class II molecules, including HLA-DQ8, and is recognized by diabetogenic CD4⁺ T cells. In this study we explore potential structural and thermodynamic mechanisms that may contribute to the enhanced immunogenicity associated with this single-amino-acid modification. Using molecular dynamics simulations combined with coarse-grained free-energy-perturbation analyses, we compared HLA DQ8 complexes bound to wild-type (WT) insulin and InsC19S peptides. The InsC19S variant is predicted in simulations to exhibit enhanced binding stability, characterized by increased hydrogen bond occupancy, reduced peptide conformational mobility, and a more favorable binding free energy. In addition, the modified peptide is predicted to induce peptide-dependent conformational adjustments within the HLA-DQ8 peptide-binding groove, resulting in expansion of the conformational landscape and stabilization of distinct low-energy states that are not accessed by the WT complex. Principal component analysis and free-energy landscape mapping suggest that this mutation may promote altered collective motions within HLA DQ8 that are consistent with enhanced peptide major histocompatibility complex (MHC) persistence and optimized antigen presentation geometry. Together, these computational observations suggest a structural framework that may help explain the preferential presentation and pathogenic recognition of InsC19S reported in experimental studies. These findings provide a molecular-level framework that may help link microenvironment-driven insulin neoepitope formation to altered peptide–MHC stability and conformational dynamics in HLA-DQ8. Full article

Hyperoxaluria Type 1 (PH1) is a rare autosomal recessive metabolic disorder caused by mutations in the AGXT gene, leading to impaired glyoxylate metabolism and excessive oxalate accumulation, resulting in nephrolithiasis, nephrocalcinosis, and end-stage renal disease. As a rare and often neglected disease, PH1 poses a significant challenge to modern healthcare systems due to its progressive nature and limited therapeutic options. In this study, an integrated in silico approach was employed to identify pathogenic single-nucleotide polymorphisms (SNPs) and evaluate potential therapeutic candidates. Computational analyses using ConSurf, Align-GVGD, INPS-MD, CUPSAT, and iStable identified G161C and Y260C as highly deleterious variants affecting protein stability. Virtual screening, followed by ADME and toxicity assessments, identified Tauroursodeoxycholic acid (TUDCA) as a promising candidate with favorable pharmacokinetic and safety profiles. Molecular docking revealed that TUDCA exhibited higher binding affinity than the reference drug pyridoxine across native and SNP variants of AGXT proteins. Molecular dynamics simulations (300 ns) demonstrated enhanced structural stability of TUDCA-bound complexes, indicated by reduced RMSD and RMSF, improved compactness, and sustained hydrogen bonding. Furthermore, free energy landscape (FEL) and dynamic cross-correlation matrix (DCCM) analyses confirmed improved conformational stability and coordinated residue motions in SNP variant structures. Overall, these findings suggest that TUDCA may effectively stabilize structural alterations induced by pathogenic AGXT variants, highlighting its potential as a precision medicine-based therapeutic strategy for PH1. Full article

In today’s energy landscape, defined by the growing demand for sustainable energy generation technologies and the parallel need to advance internal combustion engine (ICE) architectures toward cleaner and more efficient solutions, the adoption of Free-Piston Linear Generator (FPLG) engines emerges as a highly promising approach. This innovative system enables the direct conversion of combustion-induced piston motion into electrical energy, eliminating the need for traditional crankshaft and connecting rod mechanisms. The FPLG concept facilitates efficient utilization of a broad spectrum of fuels—including methane, ethanol, LPG, gasoline, biodiesel, and hydrogen—by supporting variable compression ratio operation. This feature enhances operational flexibility and fuel adaptability, positioning the technology as a viable candidate for future energy transition scenarios. The absence of rotating mechanical components significantly reduces frictional losses, contributing to an overall increase in system efficiency. To accurately characterize and optimize engine performance, an extensive series of one-dimensional (1D) numerical simulations was performed under both free and controlled operating conditions. The resulting data enabled the development of semi-empirical models capable of predicting the dynamic behavior of the engine across a wide range of working scenarios. Finally, through a detailed parametric analysis, the optimal operating conditions were identified to maximize both net electric efficiency and electrical power output. These findings provide a solid ground for the design and implementation of FPLG engine systems in advanced power generation applications. Full article