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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continually undergoes mutation, leading to variants with altered pathogenicity and transmissibility. The Omicron variant (B.1.1.529), first identified in South Africa in 2021, has become the dominant strain worldwide. It harbors approximately 50 mutations compared to the original strain, with 15 located in the receptor-binding domain (RBD) of the spike protein that facilitates viral entry via binding to the human angiotensin-converting enzyme 2 (ACE2) receptor. How do these mutated residues modulate the intermolecular interactions and binding affinity between the RBD and ACE2? This is a question of great theoretical importance and practical implication. In this study, we employed quantum chemical calculations at the B2PLYP-D3/def2-TZVP level of theory to investigate the molecular determinants governing Omicron’s ACE2 interaction. Comparative analysis of the Omicron and wild-type RBD–ACE2 interfaces revealed that mutations including S477N, Q493R, Q498R, and N501Y enhance binding through the formation of bifurcated hydrogen bonds, π–π stacking, and cation–π interactions. These favorable interactions counterbalance such destabilizing mutations as K417N, G446S, G496S, and Y505H, which disrupt salt bridges and hydrogen bonds. Additionally, allosteric effects improve the contributions of non-mutated residues (notably A475, Y453, and F486) via structural realignment and novel hydrogen bonding with ACE2 residues such as S19, leading to an overall increase in the electrostatic and π-system interaction energy. In conclusion, our findings provide a mechanistic basis for Omicron’s increased infectivity and offer valuable insights for the development of targeted antiviral therapies. Moreover, from a methodological perspective, we directly calculated mutation-induced binding energy changes at the residue level using advanced quantum chemical methods rather than relying on the indirect decomposition schemes typical of molecular dynamics-based free energy analyses. The strong correlation between calculated energy differences and experimental deep mutational scanning (DMS) data underscores the robustness of the theoretical framework in predicting the effects of RBD mutations on ACE2 binding affinity. This demonstrates the potential of quantum chemical methods as predictive tools for studying mutation-induced changes in protein–protein interactions and guiding rational therapeutic design. Full article

In the degradation of poly(ethylene terephthalate) (PET), mono(2-hydroxyethyl) terephthalate (MHET) hydrolase (IsMHETase) plays a crucial role in the complete degradation of PET. Although IsMHETase was discovered concurrently with IsPETase, its structural and functional properties are not well understood. To enhance the thermal stability of IsMHETase, we selected six homologous proteins that share the closest evolutionary relationship for structure-based protein rational design, all exhibiting over 60% amino acid sequence identity with IsMHETase. Using FireProt, PROSS, and Consensus analysis, we identified the key mutation sites of IsMHETase. Sequence and structural analyses indicate that, among these seven proteins, all amino acids within 5 Å of the substrate-binding site are identical, with the exception of Ser131 and Phe415. Additionally, the amino acids within a 4 Å range of the catalytic triad are nearly identical. Through integrated free energy calculations, phylogenetic tree analysis, sequence analysis, and conservation analysis, we have identified a variant with four key mutations (termed IsMHETase-M1: N156G, T159V, E110A, A493P) that exhibits improved thermal stability. The selection of mutations during the protein modification process often requires considerable time. Our predictions have established a foundation for the rational design of IsMHETase and its homologous proteins. Full article

Background/Objectives: In this study, we investigated the free-living nutritional intake of older people with type 2 diabetes (T2D) and examined the relationship between nutritional intake and skeletal muscle mass. Methods: Subjects aged 65 years or older with T2D who visited the Kansai Electric Power Hospital between 2015 and 2017 and had not yet received nutritional guidance or intervention at our hospital comprised the study group. Nutritional intake (energy, protein, lipid, and carbohydrate intake) was calculated from a 3-day dietary diary by the participants, and the relationship between nutritional intake and the skeletal muscle index (SMI) was retrospectively investigated. Results: In total, 91 subjects were recruited (53 males and 38 females, aged 70.3 ± 5.5 years). The energy and protein intakes were 28.7 ± 6.1 kcal/kg/day and 1.2 ± 0.3 g/kg/day, respectively. A significant positive correlation was found between the SMI and energy and protein intake (p < 0.001). Multiple regression analysis with the SMI as the dependent variable and age, gender, protein intake, lipid intake, and carbohydrate intake as the independent variables revealed protein intake to be an independent determinant of the SMI. Conclusions: In older people with T2D, the energy and protein intakes are likely to be lower than the recommended levels. Appropriate interventions for protein intake and energy intake are recommended to prevent loss of muscle mass in Japanese older people with type 2 diabetes. Full article

Bioplastics are adopted to replace fossil-based plastics because they are microplastic-free and self-degradable without releasing greenhouse gasses. Despite having many benefits, the main applications of bioplastics are packaging and kitchenware. Moreover, the utilization of bioplastics in electronic applications is still underexplored. Consequently, the development of bioplastics for electronic applications, especially heterojunctions, is essential. Here, we report a novel molybdenum disulfide (MoS₂)/cobalt oxide (Co₃O₄) heterojunction based on bioplastic semiconductors, with agar as a matrix. This work also exposes the effect of carrier concentration on the mechanism of an energy band. Using the density of state in three dimensions, Anderson’s rule, and the Fermi energy level calculated by carrier concentration, we find that the energy gaps of the MoS₂/Co₃O₄ heterojunction at various concentrations almost match the energy gap evaluated by Tauc’s relation. Additionally, leveraging the MoS₂/Co₃O₄ heterojunction as a photodetector, the optimized device indicates an ideality factor of 1.59, a response time of 127 ms, and a recovery time of 115 ms. Our work not only represents a significant step towards using bioplastics in electronic applications but also reveals the mechanism of the energy band affected by carrier concentration. Full article

Chitooligosaccharides (COSs) are a class of functional carbohydrates with significant application prospects in food and medicine. Chitosanase CsnMY002 from the GH46 family has been used to prepare COS with controlled degrees of polymerization. To enhance the industrial applicability of CsnMY002, molecular dynamics (MD) simulations were applied to investigate the structure–property relationship. Guided by the simulation results, the beneficial mutants were screened through a synergistic strategy using a residue-folding free energy calculation and consensus sequence analysis. Iterative combinations constructed the mutant Mut6 (A49G/K70A/S84A/N89G/D199R/N221G) with significantly improved thermal stability, which had a half-life (t_1/2 value) at 55 °C and 75 °C that was 1.80 and 1.62 times higher than that of the wild type, respectively. A highly active mutant, Mut2, was created, exhibiting a 1.52 times catalytic efficiency of the wild type. An MD simulation analysis of the mutants suggested that the improved enzymatic properties were highly correlated with changes in the dynamic behaviours of the enzyme structure. This study generated more suitable CsnMY002 variants for COS production and provided a comprehensive strategy for the optimization of other industrial enzymes with application potential. Full article

The investigation of melanogenesis and tyrosinase inhibitors is essential for developing safe and effective natural compounds to treat pigmentation disorders. This study aimed to evaluate the effects of maculosin, a cyclic dipeptide composed of tyrosine and proline, on melanin production and tyrosinase activity using the B16F10 melanoma cell model, while elucidating its mechanism of action through molecular docking and molecular dynamics (MD) simulations. Experimental results demonstrated that maculosin inhibited intracellular melanin content and tyrosinase activity in a concentration-dependent manner in B16F10 melanoma cells. Molecular docking analyses revealed that maculosin exhibited high binding affinities with mushroom tyrosinase (mTYR), tyrosinase-related protein 1 (TYRP1), and Bacillus megaterium tyrosinase (BmTYR) with binding energies of −7.7, −6.8, and −7.5 kcal/mol, respectively. Furthermore, MD simulations confirmed the structural stability and dynamic flexibility of maculosin–protein complexes, as indicated by RMSD, RMSF, Rg, SASA, hydrogen bond interactions, PCA, and DCCM analyses. Binding free energy calculations using the MM/PBSA method showed that maculosin exhibited binding energies of −28.76 kcal/mol with mTYR and −22.23 kcal/mol with TYRP1, outperforming standard co-crystal inhibitors such as tropolone (−12.47 kcal/mol) and kojic acid (−12.73 kcal/mol). Critical residues, including VAL-283 and HIS-263 in mTYR and HIS-381, GLY-389, and THR-391 in TYRP1, were identified as key contributors to maculosin binding, corroborating molecular docking findings and displaying strong correlations in DCCM analyses. Collectively, these results suggest that maculosin is a highly promising candidate for the treatment of pigmentation disorders, offering significant inhibitory effects on melanogenesis and tyrosinase activity. Full article

We present a theoretical study of forward-angle Delbrück scattering of light by the Coulomb field of a target nucleus. Special attention is paid to the Coulomb corrections, which take into account the interaction of the emerging virtual electron–positron pairs with the nucleus to higher orders of $\alpha Z$. We compare the results from three different computation methods: the direct all-order evaluation of the Delbrück amplitude, the computation from the pair production cross section with the optical theorem and the low-energy limit. We find that the values obtained from the optical theorem are in very good agreement with the all-order calculations and can be used as benchmark data. Moreover, both methods agree with the low-energy limit for photon energies $\omega <<m_e{c}^2$ when correctly accounting for the bound–free pair production cross section in the optical theorem calculations, and the discrepancy found in the literature originates from neglecting this contribution. Full article

Apoptosis signal-regulating kinase 1 (ASK1), a key component of the mitogen-activated protein kinase (MAPK) cascades, has been identified as a promising therapeutic target owing to its critical role in signal transduction pathways. In this study, we proposed novel pyridin-2-yl urea inhibitors exhibiting favorable physicochemical properties. The potency of these compounds was validated through in vitro protein bioassays. The inhibition (IC₅₀) of compound 2 was 1.55 ± 0.27 nM, which was comparable to the known clinical inhibitor, Selonsertib. To further optimize the hit compounds, two possible binding modes were initially predicted by molecular docking. Absolute binding free energy (BFE) calculations based on molecular dynamics simulations further discriminated the binding modes, presenting good tendency with bioassay results. This strategy, underpinned by BFE calculations, has the great potential to expedite the drug discovery process in the targeting of ASK1 kinase. Full article

The rapid evolution of SARS-CoV-2 has led to the emergence of variants with increased immune evasion capabilities, posing significant challenges to antibody-based therapeutics and vaccines. In this study, we conducted a comprehensive structural and energetic analysis of SARS-CoV-2 spike receptor-binding domain (RBD) complexes with neutralizing antibodies from four distinct groups (A–D), including group A LY-CoV016, group B AZD8895 and REGN10933, group C LY-CoV555, and group D antibodies AZD1061, REGN10987, and LY-CoV1404. Using coarse-grained simplified simulation models, rapid energy-based mutational scanning, and rigorous MM-GBSA binding free energy calculations, we elucidated the molecular mechanisms of antibody binding and escape mechanisms, identified key binding hotspots, and explored the evolutionary strategies employed by the virus to evade neutralization. The residue-based decomposition analysis revealed energetic mechanisms and thermodynamic factors underlying the effect of mutations on antibody binding. The results demonstrate excellent qualitative agreement between the predicted binding hotspots and the latest experiments on antibody escape. These findings provide valuable insights into the molecular determinants of antibody binding and viral escape, highlighting the importance of targeting conserved epitopes and leveraging combination therapies to mitigate the risk of immune evasion. Full article

Background: Malaria remains a global health crisis, with the World Health Organization (WHO) reporting 241 million cases and 627,000 deaths worldwide in 2020, predominantly affecting Sub-Saharan Africa. The region accounted for 95% of cases and 96% of deaths, reflecting the immense challenges in malaria prevention and treatment. Plasmodium falciparum Schizont Egress Antigen-1 (PfSEA-1) is crucial in facilitating immune evasion and promoting the sequestration of infected red blood cells (RBCs), contributing to severe malaria symptoms, including cerebral malaria, and necessitates the urgent identification of novel or repurposed drugs targeting PfSEA1. Methods: The protein structure of PfSEA-1 (UniProt ID: A0A143ZXM2) was modelled in three dimensions, prepared, and subjected to a 50 ns molecular dynamics (MD) simulation to achieve a stable structure. The equilibrated structure was minimised for molecular docking against the DrugBank compound library. Docking analysis identified potential inhibitors, including Alparabinos, Dihycid, Ambenzyne, Amiflupipquamine, Ametchomine, and Chlobenethyzenol, with docking scores ranging from −8.107 to −4.481 kcal/mol. Advanced analyses such as interaction fingerprints, density functional theory (DFT), and pharmacokinetics evaluations were conducted. Finally, a 100 ns MD simulation in the NPT ensemble was performed to assess the stability of protein–ligand complexes, with binding free energy and total energy calculations derived from the simulation trajectories. Results and Discussion: The identified compounds exhibited satisfactory pharmacokinetic profiles and binding interactions with PfSEA-1. The MD simulations demonstrated overall stability, with minor fluctuations in some instances. Key intermolecular interactions were observed, supporting the binding stability of the identified compounds. Binding free energy calculations confirmed favourable interactions, underscoring their potential as therapeutic agents against Plasmodium falciparum. While the in silico results are promising, experimental validation is essential to confirm their efficacy and safety for clinical use. Conclusion: These findings highlight PfSEA-1 as a promising antimalarial target and identify potential inhibitors with strong binding affinities and favourable pharmacokinetics. While the computational results are encouraging, further in vitro and in vivo validation is necessary to confirm their therapeutic potential and facilitate future drug development. Full article

The modification of catalytic activity through the use of metallic promoters is a key strategy for optimizing performance, as electronic factors play a crucial role in regulating catalytic behavior. This study explores the electronic factors behind the adsorption of glycerol (Gly) on bimetallic nickel-based compounds (${\mathrm{Ni}}_3\mathrm{X}$) using density functional theory (DFT) calculations; incorporating Mn, Fe, Co, Cu, and Zn as promoters effectively tunes the d-band center of these systems, directly influencing their magnetic, adsorption, and catalytic properties. A good correlation between the calculated glycerol adsorption energy and the d-band filling of the studied bimetallic surfaces was identified. Interestingly, this correlation can be rationalized using the celebrated Newns–Anderson model based on the calculated d-band fillings and centers of the systems under study. Additionally, the adsorption energies and relative stability of other electro-oxidation intermediates toward dihydroxyacetone (DHA) were calculated. Notably, the ${\mathrm{Ni}}_3\mathrm{Co}$ and ${\mathrm{Ni}}_3\mathrm{Cu}$ systems exhibit an optimal balance between glycerol adsorption and DHA desorption, making them promising candidates for glycerol electro-oxidation. These theoretical insights address fundamental aspects of developing glycerol valorization processes and advancing alcohol electro-oxidation technologies in fuel cells with noble-metal-free catalysts. Full article

The discovery and development of new pharmaceutical drugs is a costly, time-consuming, and highly manual process, with significant challenges in ensuring drug bioavailability at target sites. Computational techniques are highly employed in drug design, particularly to predict the pharmacokinetic properties of molecules. One major kinetic challenge in central nervous system drug development is the permeation through the blood–brain barrier (BBB). Several different computational techniques are used to evaluate both BBB permeability and target delivery. Methods such as quantitative structure–activity relationships, machine learning models, molecular dynamics simulations, end-point free energy calculations, or transporter models have pros and cons for drug development, all contributing to a better understanding of a specific characteristic. Additionally, the design (assisted or not by computers) of prodrug and nanoparticle-based drug delivery systems can enhance BBB permeability by leveraging enzymatic activation and transporter-mediated uptake. Neuroactive peptide computational development is also a relevant field in drug design, since biopharmaceuticals are on the edge of drug discovery. By integrating these computational and formulation-based strategies, researchers can enhance the rational design of BBB-permeable drugs while minimizing off-target effects. This review is valuable for understanding BBB selectivity principles and the latest in silico and nanotechnological approaches for improving CNS drug delivery. Full article

Voice onset is the sequence of events between the first detectable movement of the vocal folds (VFs) and the stable vibration of the vocal folds. It is considered a critical phase of phonation, and the different modalities of voice onset and their distinctive characteristics are analysed. Oscillation of the VFs can start from either a closed glottis with no airflow or an open glottis with airflow. The objective of this article is to provide a comprehensive survey of this transient phenomenon, from a biomechanical point of view, in normal modal (i.e., nonpathological) conditions of vocal emission. This synthetic overview mainly relies upon a number of recent experimental studies, all based on in vivo physiological measurements, and using a common, original and consistent methodology which combines high-speed imaging, sound analysis, electro-, photo-, flow- and ultrasound glottography. In this way, the two basic parameters—the instantaneous glottal area and the airflow—can be measured, and the instantaneous intraglottal pressure can be automatically calculated from the combined records, which gives a detailed insight, both qualitative and quantitative, into the onset phenomenon. The similarity of the methodology enables a link to be made with the biomechanics of sustained phonation. Essential is the temporal relationship between the glottal area and intraglottal pressure. The three key findings are (1) From the initial onset cycles onwards, the intraglottal pressure signal leads that of the opening signal, as in sustained voicing, which is the basic condition for an energy transfer from the lung pressure to the VF tissue. (2) This phase lead is primarily due to the skewing of the airflow curve to the right with respect to the glottal area curve, a consequence of the compressibility of air and the inertance of the vocal tract. (3) In case of a soft, physiological onset, the glottis shows a spindle-shaped configuration just before the oscillation begins. Using the same parameters (airflow, glottal area, intraglottal pressure), the mechanism of triggering the oscillation can be explained by the intraglottal aerodynamic condition. From the first cycles on, the VFs oscillate on either side of a paramedian axis. The amplitude of these free oscillations increases progressively before the first contact on the midline. Whether the first movement is lateral or medial cannot be defined. Moreover, this comprehensive synthesis of onset biomechanics and the links it creates sheds new light on comparable phenomena at the level of sound attack in wind instruments, as well as phenomena such as the production of intervals in the sung voice. Full article

Peusner’s network thermodynamics (PNT) is an important way of describing processes in nonequilibrium thermodynamics. PNT allows energy transport and conversion processes in membrane systems to be described. This conversion concerns internal energy transformation into free and dissipated energies linked with the membrane transport of solutes. A transformation of the Kedem–Katchalsky (K-K) equations into the R variant of Kedem–Katchalsky–Peusner (K-K-P) equations was developed for the transport of binary electrolytic solutions through a membrane. The procedure was verified for a system in which a membrane Ultra Flo 145 Dialyser separated aqueous NaCl solutions. Peusner coefficients were calculated by the transformation of the K-K coefficients. Next, the coupling coefficients of the membrane processes and energy fluxes for electrolyte solutions transported through the membrane were calculated based on the Peusner coefficients. The efficiency of energy conversion in the membrane transport processes was estimated, and this coefficient increased nonlinearly with the increase in the solute concentration in the membrane. In addition, the energy fluxes as functions of ionic current density for constant solute fluxes were also investigated for membrane transport processes in the Ultra Flo 145 Dialyser membrane. Full article

Mg₇₂Zn₂₇Pt₁ and Mg₇₂Zn₂₇Cu₁ metallic glasses were produced using a melt-spinner. Their crystallization kinetics were investigated during annealing with five heating rates using DSC. Amorphous Mg₇₂Zn₂₇Pt₁ crystallized in the form of one and Mg₇₂Zn₂₇Cu₁ crystallized in the form of two exothermic crystallization peaks. It was noticed that the glass transition, the onset crystallization and the crystallization peak temperatures were strongly heating-rate-dependent. The addition of Pt and Cu increased the stability compared to that of binary Mg-Zn glass, and especially so with Pt, due to its higher melting point and different atom size to those of Mg and Zn. The activation energies were calculated using six model-free methods: the Kissinger, Ozawa–Flynn–Wall, Boswell, Tang, Augis–Bennett and Gao–Wang methods. The Augis–Bennett and Gao–Wang methods allow for the calculation of only the activation energy at the crystallization peak but they are the only ones that consider $T_x$ or $dx/dT$. For Mg₇₂Zn₂₇Pt₁, the calculated values fluctuate in the ranges 114.60–117.99 kJ/mol, 102.46–105.98 kJ/mol and 71.16–98.62 kJ/mol for $E_g$, $E_x$ and $E_p$, respectively, whereas, for Mg₇₂Zn₂₇Cu₁, the calculated values are in the ranges of 98.51–101.77 kJ/mol, 95.15–98.51 kJ/mol and 55.15–93.34 kJ/mol for $E_g$, $E_x$ and $E_p$, respectively. Both alloys are meta-stable in the amorphous state and crystallization occurs spontaneously. The Kissinger, Ozawa–Flynn–Wall, Tang and Boswell methods give similar values for the activation energy. The Gao–Wang method significantly underestimates values compared to other methods. The Augis–Bennett method shows much lower values for the local activation energy. Considering the ease of their formulas, best convergence and widespread use in the literature, the Kissinger and Ozawa–Flynn–Wall methods will work very well for any comparison. Full article