Search Results (576)

The ATP-binding cassette transport protein Pdr5p is known to play a role in multidrug resistance in Saccharomyces cerevisiae by effluxing structurally diverse xenobiotics; yet the physicochemical determinants of substrate recognition remain poorly defined. To address this, density functional theory (DFT) calculations at the B3LYP-D3BJ/def2-SVP level were combined with machine learning to derive a predictive model of substrate recognition using a curated dataset of 66 compounds spanning 9 functional categories. A hybrid support vector machine (SVM) classifier achieved 96.3% accuracy (95% CI: 81.0–99.9%, Clopper–Pearson exact) in discriminating substrates from non-substrates under leave-one-out cross-validation. Feature importance analysis identified lipophilicity (LogP, F-score = 37.5) as the dominant descriptor, suggesting that membrane partitioning constitutes the initial recognition step. The HOMO–LUMO gap contributed secondarily (F-score = 12.4). Substrates were further distinguished by high frontier orbital focalization, with frontier orbital spread of 1.8–2.6%, compared to 4.18–7.22% for non-substrates. Notably, a model trained exclusively on Pdr5p data achieved 87% prediction accuracy when applied without retraining to the human P-glycoprotein (ABCB1) dataset, suggesting conserved physicochemical principles of substrate recognition across evolutionarily distant ABC transporters. These findings provide a quantum chemical framework for understanding and potentially predicting MDR transporter substrate specificity. Full article

Total cross-sections for the single electron impact ionization of deoxyribose (C₅H₁₀O₄), Uridine (C₉H₁₂N₂O₆), Thymidine (C₁₀H₁₄N₂O₅), Cytidine (C₉H₁₃N₃O₅), Adenosine (C₁₀H₁₃N₄O₄), and Guanosine (C₁₀H₁₃N₅O₅) have been calculated using the binary-encounter-Bethe model from the first ionization threshold up to 4 keV. Electronic structure calculations of the studied targets have been performed at the Hartree–Fock (H-F) level using quantum chemical methods, including the outer valence Green function (OVGF) method, in order to obtain all the necessary physical input parameters for the BEB method. The possibility and feasibility of estimating the ionization cross-sections of larger DNA building blocks, such as nucleosides, based on the sum of the ionization cross-sections of DNA bases and simple sugar analogs, such as $\alpha$-tetrahydrofurfuryl alcohol or deoxyribose, are also discussed. Full article

This study aims to investigate the performance and mechanism of N′-[(E)-phenylmethylidene] furan-2-carbohydrazide (FNH), a hydrazone Schiff base, as a corrosion inhibitor for carbon steel in 1.0 M HCl. The research was conducted by coupling electrochemical testing (Tafel analysis and Impedance spectroscopy) with surface characterization (SEM and AFM) and advanced computational tools, including quantum-chemical modeling and classical molecular dynamics (MD) simulations. Tafel analysis revealed that FNH acts as a mixed-type inhibitor, concurrently slowing iron oxidation and hydrogen reduction. Impedance data showed that the Faradaic resistance grew monotonically with FNH dosage, reaching 95% protection at 1 × 10⁻⁴ M. Fitting the results to the Langmuir model indicated a joint physical–chemical anchoring pathway, further confirmed by SEM/AFM inspection which disclosed a uniform organic deposit. Quantum-chemical modeling revealed that protonated species broaden the molecule’s capacity for bidirectional electron exchange, while MD simulations on the Fe (110) slab confirmed a flat-lying geometry that maximizes heteroatom–metal contact. The consistency between laboratory observables and atomic-scale predictions provides a detailed, mechanism-oriented picture of how this organic protective layer curtails acid corrosion. Full article

In this article, the different types of self-coagulation discovered in the fluid simulations of inductively coupled plasma (abbreviated as ICP) at both the electronegative and electropositive cases are presented. Among these, the electronegative plasma sources include Ar/O₂, Ar/Cl₂, and Ar/SF₆, and the electropositive plasma source is the inertial argon plasma itself. The fluid simulation versions are not the same. Concretely, the Comsol software version 5.4 is used to simulate the Ar/O₂, Ar/Cl₂, Ar/SF₆, and the pure argon ICPs, and the self-written code of the fluid model is used to simulate the pure argon ICP as well, but in a different framework of fluid design. The types of self-coagulation refined from these fluid simulations are the physically ambi-polar self-coagulation of ions, the chemically ambi-polar self-coagulation of ions, the mono-polar self-coagulation of electrons, and the non-polar self-coagulation of argon metastable atoms. These self-coagulations are based on mass and founded through the Comsol fluid simulations, and moreover, the self-coagulation of thermal energy of electrons is founded through the self-written fluid code simulation. Based on the self-coagulations of mass and energy, together with the accompanying discharge hierarchy, we hypothesize (1) the correlation of ambi-polar self-coagulation and diffusion, (2) the mean of using the Schrodinger equation to describe the quasi-particle of anions given by self-coagulation in a certain potential barrier, (3) the analogy of the $\beta$ and ${\beta }^{+}$ decay and the asymmetry given by two types of ICP source simulation, (4) the picture of spin orientations of neutrino and anti-neutrino, and (5) the model for photon sustainment. The self-coagulation behavior is seen to be general and the interdisciplinary works of plasma physics with quantum mechanics, particle physics, nuclear physics, and optics are helpful for us to better understand the mass and energy general dynamics. Full article

Understanding the atomic-scale mechanisms of coal pyrolysis is essential for efficient coal utilization and carbon-neutral energy strategies, yet conventional computational approaches often struggle to balance between the high accuracy of quantum-chemical calculations and the efficiency of reactive force fields. To overcome this limitation, we proposed a multiscale computational framework integrating high-throughput density functional theory (DFT) calculations, ReaxFF-based configuration sampling, YARP reaction enumeration, and DPA3-based machine learning potentials (MLPs). Two coal-specific MLPs, DPA3-coal and DPA3-coal@dftb, were constructed and systematically benchmarked on both small molecular systems and larger C20–30 coal fragments extracted from MD simulations. DPA3-coal@dftb model demonstrated significantly improved accuracy over ReaxFF in predicting energies and atomic forces while maintaining good transferability. To balance computational efficiency and accuracy in large-scale simulations, the DPA3-coal model was employed to perform accelerated reactive molecular dynamics simulations of a Solomon-type bituminous coal molecule from 1600 to 2600 K. The simulations revealed temperature-dependent evolution of coke, tar, and gas products, including secondary condensation and deep-cracking processes at elevated temperatures. Higher-level DFT calculations further confirmed the thermodynamic consistency of key reaction pathways involving radical formation, H-transfer, recombination, and CO generation, indicating that coal-specific MLPs provide an effective atomistic tool for investigating mechanistic trends in coal pyrolysis. Full article

Aromatic compounds are abundant in urban and industrial environments and potentially serve as one of the primary precursors for new particle formation (NPF). Pi-pi stacking is a distinctive weak interaction observed between aromatic compounds. Aromatic oxygenated organic molecules (AOOM) are key products of atmospheric oxidation of aromatic compounds; however, the role of pi-pi stacking in their involvement in atmospheric new particle formation (NPF) remains unclear. This study used quantum chemical calculations to reveal the nucleation mechanism of AOOM through pi-pi stacking and hydrogen bonding. The results indicate that the contribution of pi-pi stacking to nucleation in aromatic compounds is primarily determined by the stacking area. For aromatic hydrocarbons with 1–2 phenyl groups, the Gibbs free energy (ΔG) of dimolecular clusters formed solely by pi-pi stacking is positive. In contrast, for polycyclic aromatic hydrocarbons with three or more phenyl groups, the ΔG of these clusters decreases significantly and becomes negative. Single-phenyl AOOM primarily participates in the NPF process through hydrogen bonding with sulfuric acid molecules. In this work, an explanation is provided for observations and laboratory findings of the appearance of aromatic-ring-retaining species in nanoparticles. The discovery of pi-pi stacking also completes the variety of atmospheric nucleation weak interactions. The oxidation and nucleation mechanisms of aromatic compounds should be reassessed, considering the effects of pi-pi stacking, especially polycyclic aromatic hydrocarbons. These findings have important implications for sustainable urban air-quality management. By clarifying the role of pi-pi stacking, particularly in polycyclic aromatic hydrocarbons, this study may improve predictions of new particle formation, refine secondary organic aerosol modeling, and inform targeted emission-control policies to protect public health and mitigate climate impacts. Full article

Context/Objective: Fungi of the genus Tolypocladium are known for their diverse metabolic capabilities and medicinal potential. Indole diterpenoids (IDTs) represent a structurally unique class of fungal metabolites. Beyond their established roles as mycotoxins, these compounds have recently shown promise for neuroprotective effects. The objective of this study was to isolate and characterize novel IDTs from Tolypocladium album DWS131 and evaluate their neuroprotective activities and underlying mechanisms. Methods: IDTs were isolated through comprehensive chromatographic techniques. Their structures were elucidated using HRESIMS data, 1D/2D NMR spectra, and quantum chemical calculations. Neuroprotective effects were evaluated using glutamate (Glu)-induced R28 cells in vitro and N-methyl-D-aspartic acid-induced mouse models in vivo. A total of 48 mice were utilized for in vivo evaluations, divided into two separate experimental cohorts. In each cohort, mice were randomly assigned to four groups (n = 6 per group). Post-intravitreal injection, retinal survival and visual function were assessed via Brn3a-stained flat-mounts, H&E staining, f-VEP, f-ERG, and OptoDrum. Mechanisms involving the SLC7A11/GPX4/ACSL4 axis were investigated by Western blotting and immunofluorescence. Results: Seven previously undescribed paxilline-type IDTs, tolypindoles A–G (1–7), and two known analogues (8–9) were identified. Compounds 8 and 9 exhibited significant neuroprotection closely associated with the attenuation of oxidative stress and the modulation of ferroptosis-related pathways in Glu-induced R28 cells. In vivo, they preserved retinal ganglion cells, maintained retinal structure, and protected visual function, with compound 8 demonstrating superior efficacy. Mechanistic investigations revealed that both compounds modulate the SLC7A11/GPX4/ACSL4 signaling axis. Conclusions: This study expands the chemical diversity of T. album DWS131. Compounds 8 and 9, characterized by isopentenyl moieties, highlight a promising therapeutic potential for retinal neurodegenerative diseases such as glaucoma. Full article

The identification of the chemical species responsible for the anomalous near-ultraviolet (UV) opacity in the Venusian cloud for “unknown absorber” remains a paramount challenge in planetary science. This study presents a comprehensive quantum chemical investigation into a broad suite of candidate molecules, including isomers of thiosulfeno (S₂O₂), the hydroxysulfonyl radical (HSO₃), disulfur monoxide (S₂O), disulfur dichloride (S₂Cl₂), iron(III) chloride (FeCl₃), phosphine (PH₃), and structural isomers of polysulfur oxides (S₃O). Utilizing Time-Dependent Density Functional Theory (TD-DFT) at the CAM-B3LYP/def2-TZVPP level of theory, we systematically mapped electronic transitions across three distinct environmental phases: gas-phase (without solvent), supercritical CO₂, and concentrated H₂SO₄ aerosols. To establish confidence in the predicted results, our TD-DFT approach was rigorously benchmarked against high-level theoretical methods (CCSD(T), EOM-CCSD, and MRCI+Q) from recent literature. All these electronic transitions were modeled via the Solvation Model based on Density (SMD). Our results demonstrate a profound topological and environmental dependence on spectral signatures. Among the candidates, trans-OSSO (t-OSSO) emerged as the most viable near-UV absorber candidate, exhibiting a highly allowed π → π* transition at 379.37 nm (f = 0.1140) in H₂SO₄, providing a near-perfect alignment with the observed 365 nm planetary albedo drop. Conversely, the polysulfur oxide cis-S₃O was acknowledged as a primary visible-light chromophore, with an intense absorption at 436.31 nm (f = 0.1280) responsible for the characteristic yellow tint of the planet. Additionally, the photochemically maintained SSCl₂ isomer was identified as a critical broadband near-UV absorber. Species such as S₂O and planar S₃O were found to function as critical mid-UV shields (270–300 nm). This work establishes a multi-chromophore model of the Venusian atmosphere, where a chemically stratified network of sulfur-oxygen chains and chlorine-sulfur reservoirs, tuned by the acidic aerosol matrix, collectively governs radiative balance and atmospheric super-rotation of the planet. Furthermore, to account for massive continuum tailing into the visible region (>400 nm), we employed a semi-classical Reflection Principle approach to model 1D vibronic broadening. This analysis revealed that while standard solvent effects induce minor solvatochromic shifts, ground-state structural fluxionality in the OSSO isomers drives intense, symmetry-allowed transitions deep into the visible spectrum, an effect absent in structurally constrained or rigid control species. Full article

In this study, the synthesis of a series of alkaloid analogs—isoxazole and isothiazole esters of 2-substituted 3-oxoindoline-4-carboxylic acid was performed. The target derivatives were obtained by the carbodiimide method. It was established that the studied esters have low cytotoxicity and are able to enhance the effect of the anticancer drug carboplatin, taken in low doses (0.5–5 μM), by up to 30%. Quantum chemical modeling of the obtained compounds and their conjugates with carboplatin was carried out to analyze the relationship between various calculated parameters and the observed biological effects. Full article

This paper presents the electrochemical behavior of stainless steel 304 (SS304), a material often utilized in the wine industry, in the presence of varying concentrations of ascorbic acid (AcAS), introduced in a neutral solution (Na₂SO₄ 0.25 M + 12% (v/v) EtOH). The experimental part of this paper included potentiodynamic polarization and chronoamperometry techniques to evaluate the influence of ascorbic acid on the corrosion processes in the test solutions. Electrochemical impedance spectroscopy (EIS) has been used to investigate the charge transfer at the interface and the formation of a protective film in the absence and presence of AcAS. The Tafel method was employed to determine the kinetic parameters of the corrosion process studied. Additionally, several models of adsorption isotherms were applied to describe the interactions between AcAS and the stainless steel surface, with the Freundlich and Dubinin–Radushkevich isotherms demonstrating the most robust correlation, based on the R² correlation coefficients. Quantum chemical calculations (DFT) were also performed to clarify the molecular mechanism via which AcAS functions as an eco-friendly corrosion inhibitor in winemaking-related environments. Full article

Background: Triple-negative breast cancer (TNBC) remains among the most aggressive and therapeutically unresponsive subtypes due to the absence of ER, PR, and HER2 targets. Casein Kinase II (CK2), a pleiotropic serine/threonine kinase overexpressed in TNBC, represents a compelling target for rational drug design. Methods: Here, we present an AI-integrated benchmarking framework combining virtual drug discovery, molecular dynamics simulations, machine learning-driven QSAR modeling, and quantum-mechanical electronic structure analysis to identify potent CK2 inhibitors from natural product chemical space. Results: A validated XP docking protocol (ROC–AUC = 0.748) screened ~480,000 compounds, yielding seven hits, with superior binding to the reference inhibitor CX-4945. Among these, Anastatin B, 3,4,8,9,10-pentahydroxy-dibenzo-[b,d]pyran-6-one, Rhein, and aloe emodin acetate exhibited highly favorable docking scores (−11.6 to −13.1 kcal mol⁻¹) and stable 200 ns binding dynamics, reflected by RMSD ≤ 2 Å and compact Rg trajectories. MM-PBSA/MM-GBSA analyses confirmed robust thermodynamic stability, while DFT-derived HOMO–LUMO gaps (3.8–4.3 eV) suggested optimal electronic reactivity for kinase inhibition. Machine learning QSAR models demonstrated strong predictive performance, with the best stacking models achieving test R² ≈ 0.69 and consistent cross-validation performance (CV R² ≈ 0.66–0.69), supporting reliable prediction of pIC₅₀ values and prioritization of top-ranked scaffolds. Conclusions: Collectively, this integrative framework bridges AI-based learning and biophysical validation, establishing a reproducible paradigm for de novo CK2 inhibitor discovery in TNBC. Full article

The efficient capture of chlorinated volatile organic compounds (Cl-VOCs) represents a significant challenge in environmental protection and sustainable chemical engineering. In this study, a functional deep eutectic solvent (DES) composed of tetrabutylphosphonium bromide ([P₄₄₄₄][Br]) and levulinic acid (LEV) at a 1:2 molar ratio was prepared, and its absorption performance toward two typical Cl-VOCs, namely dichloromethane (DCM) and chloroform (TCM), was evaluated using this DES as a recyclable absorbent. Based on COSMO-SAC model predictions and experimental validation, the [P₄₄₄₄][Br]-LEV (1:2) system was identified as the preferred candidate. Under mild conditions (10 °C, N₂ flow rate of 100 mL/min), the saturated absorption capacities of this DES reached 1521.71 mg/g and 1620.30 mg/g for DCM and TCM, respectively. The absorbent exhibited favorable regeneration stability over five consecutive absorption–desorption cycles, retaining over 90% of its initial absorption efficiency. Mechanistic studies, including proton nuclear magnetic resonance (¹H NMR), Fourier-transform infrared spectroscopy (FT-IR), DSC (Differential Scanning Calorimetry), TGA (Thermogravimetric Analysis) and quantum chemical calculations, including electrostatic potential (ESP), independent gradient model (IGM), and reduced density gradient (RDG), demonstrated that the absorption process was dominated by physical interactions such as hydrogen bonding and van der Waals forces, with no chemical reactions involved. At the laboratory scale, this DES system showed excellent Cl-VOCs absorption performance, providing a useful reference for the rational design of high-efficiency VOC absorbents. Full article

Since their initial discovery in 2003, carbon quantum dots (CDs) have attracted significant attention due to their unique optical properties and potential biomedical applications. This review critically examines the past 20 years of research on CDs, with a particular focus on cytotoxicity studies from the last decade. CDs, typically less than 10 nm in size, have been synthesized from various organic and inorganic precursors using multiple methods, including hydrothermal, microwave, and chemical reduction techniques. Their properties can be finely tuned by modifying synthesis parameters and incorporating dopants. The preliminary studies on the biological effects of CDs were published in 2013, highlighting their antibacterial properties and low toxicity in certain contexts. Subsequent research has explored their bioactivity, including their application in drug delivery, bioimaging, and photothermal therapy. However, the cytotoxicity of CDs remains a critical area of investigation. Further studies have demonstrated that surface functional groups, charge, concentration, and size significantly influence their interaction with biological systems. For instance, CDs with positive surface charges exhibit higher cellular uptake and greater cytotoxicity compared to their negatively charged counterparts. In vivo studies utilizing animal models such as zebrafish, mice, and planarians have provided valuable insights into the potential toxicological impacts of CDs. The results indicate that while CDs generally exhibit low toxicity at certain concentrations, high doses can lead to adverse effects, including oxidative stress, organ damage, and disrupted cellular functions. Notably, the route of administration (oral, intravenous, or intraperitoneal) also affects the observed toxicity profiles. The goal of this review is to integrate the results of various studies to provide a balanced perspective on the potential risks and benefits of CDs, guiding future research and applications in nanomedicine. This review underscores the necessity for standardized and comprehensive toxicological evaluations of CDs to fully understand their safety and efficacy for biomedical applications. Full article

In this study, the applicability of achiral column chromatography—including both medium-pressure liquid chromatography (MPLC) and classical gravity-driven techniques—was evaluated as a laboratory method for enantiomeric enrichment of scalemic (non-racemic) samples of axially chiral compounds. As model substrates, 3-(ortho-substituted-phenyl)quinazolin-4-one derivatives were employed. The results confirmed that self-disproportionation of enantiomers (SDE), occurring during column chromatography (SDEvCC), enabled the efficient isolation of enantiomerically pure fractions, with MPLC demonstrating particularly high effectiveness. Additionally, the parameters governing gravity-driven column chromatography were systematically optimized, with particular attention to variables such as eluent type and concentration, stationary phase composition, sample preparation protocol, and solvent purity. Furthermore, leveraging known crystallographic data and quantum chemical calculations based on Density Functional Theory (DFT), a molecular association mechanism was proposed to elucidate the physicochemical basis of the SDE phenomenon. Full article

This study investigates the antioxidant and anticorrosive properties of Mentha pulegium L. essential oil (MP EO) as a sustainable and eco-friendly alternative to synthetic oxidation inhibitors. The antioxidant activity of MP EO was evaluated using the ferric reducing antioxidant power (FRAP) assay, which demonstrated a strong electron-donating capacity and effective reduction of ferric ions, indicating promising antioxidant potential. The anticorrosive performance was assessed on mild steel in 0.5 M H₂SO₄ using potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). The results showed inhibition efficiencies of up to 75.8% at a concentration of 2 g/L. Molecular docking simulations revealed favorable binding interactions between the key oil components (pulegone and menthone) and the ROS-generating enzyme model (PDB ID: 2CDU), providing complementary mechanistic insight into their potential role in oxidative stress modulation. Additionally, quantum chemical calculations highlighted electronic properties favoring adsorption on metallic surfaces. Surface morphology analysis using SEM/EDX confirmed the formation of a protective film on steel in the presence of MP EO. These combined findings position Mentha pulegium essential oil as a potent, biodegradable candidate for both antioxidant applications and corrosion prevention in acidic environments. Full article