The Journal of Physical Chemistry B最新文献

Aquaporin-4 (AQP4)is an integral membrane protein channel specificfor water molecules. It is highly polarized in the endfeet of astrocytesin the central nervous system where it allows water–ion homeostasis.AQP4 has two N-terminal isoforms: M1 (long) and M23 (short). Bothisoforms retain their function but differ in their N-terminal lengths,which regulate AQP4 aggregation size. There are also long and shortisoforms at the C-terminus. The long form has a 29-amino-acid extension(AQP4ex) that interacts with α-syntrophin, a component of thedystrophin-associated protein complex (DAPC). This interaction anchorsAQP4 to the perivascularastrocyte endfeet through the DAPC, therebymaintaining its polarized localization at the blood–brain barrier.This study uses peptides with the sequence of the extended regionto demonstrate a strong interaction with α-syntrophin, boundto a glass surface via maleimide-PEG silane chemistry. It was observedthat substituting alanine for threonine, four amino acids from theC-terminus, eliminates binding, and an alanine scan shows that thelast six amino acids at the C-terminus also play a crucial role. Kineticstudies using time-lapse single-molecule fluorescence imaging wereused to determine the Gibbs free energy of activation for both forwardand reverse rates (ΔG^‡) usingan Eyring analysis. Equilibrium constants (K_eq) were measured between 15 and 37 °C, and standard-statethermodynamic free energies (ΔG°), enthalpies(ΔH°), and entropies (ΔS°) were determined using a van’t Hoff analysis. It wasfound that forward rates ranged from 4.5 × 10⁴ to1.0 × 10⁵ M^–1 s^–1 depending on peptide length, with ΔG^‡_forward = 45–46 kJ mol^–1. Reverse rates ranged from 11.6 to 21.1 s^–1 dependingon peptide length, with ΔG^‡_reverse = 65.2–67.0 kJ mol^–1.Using a vant’ Hoff analysis, the overall standard-state freeenergies were between −19 and −22 kJ mol^–1. The work also describes how dynamic single-molecule imaging canbe used to determine kinetic and thermodynamic properties.

In this study, molecular dynamics simulations combinedwith Ramanspectroscopic characterization were employed to investigate the localcoordination environments, oxygen coordination states, polyhedralconnectivity, and network polymerization characteristics in binaryAl₂O₃–Y₂O₃ glasseswithin the composition range of 60–75 mol % Al₂O₃. Comprehensive analysis of the radial distribution function,coordination number distribution, and angular distribution functionhas been used to characterize the short-range ordered structures ofAl–O and Y–O and to elucidate the distribution characteristicsof aluminum–oxygen structure units such as [AlO₄], [AlO₅], and [AlO₆]. Furthermore, the evolutionof corner-sharing and edge-sharing behaviors, revealed by bond-anglevariations, has been identified. Distributions of oxygen species and Q_i species further revealed the evolution ofglass network connectivity with composition variation. Deconvolutionof Raman spectra in the high-wavenumber region enabled the quantitativeanalysis of microstructure species. This study provided a comprehensiveunderstanding of the structure evolution in Al-rich binary Al₂O₃–Y₂O₃ glasses, establishinga theoretical foundation for the rational network design.

Investigations ofG protein-coupled receptors (GPCRs)interactionswith nonvisual arrestins in living cells are essential to understandingthe complex molecular mechanisms of GPCR-based signaling. Quantitativeanalysis of these interactions remains challenging in live cells,particularly when attempting to repeatedly image distinct cellularregions with high precision. Here, we describe the implementationof an optical imaging stabilization approach that integrates the recentlydeveloped Focal Readjustment for Enhanced Vertical Resolution (FREVR)technology into a multiphoton microscope, enabling high-precisionalternation between image-forming sample planes with <20 nanometerrepeatability and stability over time. Using this setup, we monitoredthe dynamic recruitment of arrestin-2 (Arr2) to the plasma membraneof HEK-293 cells expressing muscarinic acetylcholine M₂ receptors (M₂R) by alternately imaging distinct planesof interest, the basolateral membrane and a membrane cross-section.Following stimulation of M₂R by agonist ligand, we observeda pronounced redistribution of cytoplasmic Arr2 toward the plasmamembrane in both cellular cross sections and at the basolateral membrane.This method enables direct comparison of receptor and arrestin dynamicsacross regions of individual cells with very high precision, eliminatingthe need for averaging over numerous cells in order to denoise biologicallyrelevant signals, and thereby capturing physiological cell-to-cellvariability with accuracy.

Protein adsorption at solid–liquid interfacesplays a crucialrole in many biological and technological processes, including thedesign of biomaterials, biosensor performance, and biocatalysis. Understandinghow proteins interact with surfaces is essential for controlling biofouling,optimizing medical implants, and engineering functional interfaces.Despite its significance, predicting adsorption behavior from molecular-levelinteractions remains challenging. In this work, we performed moleculardynamics simulations using umbrella sampling to sample the two-dimensionalfree-energy surface of bovine serum albumin adsorption on the anionicadsorbent Q Sepharose FF. By combining molecular dynamics simulationswith enhanced free energy sampling techniques, we systematically exploredthe orientations and positions of the protein near the surface. Noconformational changes were observed within the examined time scales.We obtained a comprehensive free-energy map that captures the adsorptionbehavior across the entire protein surface. This approach providesaccess to the adsorption free energy while accounting for contributionsfrom all possible adsorption sites and orientations. The resultinglandscape offers a detailed molecular-level understanding of how proteinsinteract with surfaces.

Althoughphotodynamic therapy (PDT) has emerged as apromisingtreatment for unresectable cholangiocarcinoma, the hypoxic tumor microenvironmentseverely limits oxygen-dependent Type II photochemical processes,resulting in insufficient reactive oxygen species (ROS) generationand compromised therapeutic outcomes. Therefore, developing Type Iphotosensitizers (PSs) with optimized excited-state dynamics and efficienthypoxia-tolerant ROS generation is critical for improving PDT efficacyunder hypoxic conditions. Herein, we developed three hemicyanine-basedType I PSs (HCy1–3) and systematically investigatedthe relationship between molecular structure, TICT-mediated excited-staterelaxation, and ROS generation behavior. By modulating the electron-donatingcapability of donor moieties, the TICT characteristics of the hemicyaninescaffold were precisely tuned, thereby regulating the competitionbetween nonradiative decay and ROS-generating pathways. Among them, HCy3 exhibited enhanced excited-state utilization and thehighest Type I ROS generation efficiency under both normoxic and hypoxicconditions. Furthermore, HCy3 efficiently accumulatedin mitochondria and induced mitochondrial dysfunction, leading tosuperior photodynamic cytotoxicity against cholangiocarcinoma cellsunder hypoxia compared with the clinically used PS HiPorfin. The therapeuticpotential of HCy3 was further validated in cholangiocarcinomaorganoids. This study establishes a structure–photophysics-photochemistrycorrelation between TICT regulation and Type I ROS generation, providinga mechanistic strategy for designing high-performance hypoxia-tolerantPSs for PDT.

Optical basicity measurements provide a basis for determiningtherelative chlorobasicity of a given molten salt composition. This studyuses Bi³⁺ as a spectroscopic probe to investigate opticalbasicity across three binary molten chloride systems (LiCl-KCl, MgCl₂–KCl, and ZnCl₂–KCl) through in situUV–vis spectroscopy measurements of the ¹S₀→³P₁ transition. LiCl-KCl systems exhibitthe highest optical basicity with minimal compositional dependence,while both divalent systems show stronger, yet nonlinear, dependencethat is reminiscent of acid–base titration curves. The influenceof cation electronegativity and polarizing power (Li⁺ <Mg²⁺ < Zn²⁺) directly reflects the basicitycurves, with ZnCl₂–KCl displaying the steepest gradientsand lowest basicity values. Nonlinear dependencies in divalent systemsindicate formation of chloride-bridged network structures with coordinationstates dictated by the amount of KCl in a salt composition, whichwas further investigated and validated by molecular dynamics simulationsof polymeric structures formed in ZnCl₂ and MgCl₂-based salts using machine learning force fields. The temperaturedependence of chlorobasicity in terms of optical basicity was investigated,and a loose, positive correlation between the two was revealed. Thesefindings establish Bi³⁺ as a sensitive probe for understandingelectronic environments in molten chloride systems and provide insightsfor predicting the chemical behavior of molten salts for use in high-temperatureenvironments.

Reactive nitrogenspecies (RNSs) are key contributors to plasma-liquidprocesses and play a critical role in the chemistry of plasma-activatedwater (PAW). Despite their importance, their molecular-level behaviorin aqueous environments is still not well understood, largely dueto the absence of reliable reactive force fields. In this study, anew ReaxFF parameter set, ReaxFF_CHONx-2026, is developedand systematically assessed for modeling nitrogen- and oxygen-containingreactive species under both gas-phase and aqueous conditions relevantto plasma systems. The parameter set is optimized using density functionaltheory (DFT) reference data for representative NO_x reaction pathways and integrated with an existing aqueous/biomolecularReaxFF framework to enable reactive molecular dynamics simulationsin water. Its performance is validated through a range of structural,thermodynamic, and dynamic properties including radial distributionfunctions, potential energy profiles, and diffusion coefficients.The results demonstrate strong agreement with DFT calculations andpreviously reported data, particularly in describing N–O bondbreaking and solvation behavior. As a case study, the interactionof peroxynitrite (ONOO^–) with water is investigatedusing reactive molecular dynamics, where atomic charges are dynamicallydetermined via the ReaxFF charge equilibration method. The simulationsshow protonation leading to ONOOH formation, pronounced site-specificsolvation around oxygen atoms, and preferential cleavage of the peroxideO–O bond. Analysis of diffusion further indicates that thepredicted transport properties of RNS are consistent with the availabledata, supporting the reliability of the developed force field. Overall,ReaxFF_CHONx-2026 offers a robust framework for large-scaleatomistic simulations of PAW and reactive nitrogen chemistry.

The understanding of mutual solubilitiesin H₂-containingsystems is the foundation for improving H₂-related processes.This study demonstrates that Gibbs ensemble Monte Carlo simulationssuccessfully predict the mutual solubility of hydrogen-alkane systemsover a wide range of conditions (323.2–462.5 K, 1.7–20.3MPa) with the optimal corrections to the combination rules. We foundthat the solubility of decane and hexadecane in H₂ increasesby 2–3.3 times with an increasing number of methyl groups inthe alkane (branching). Notably, a decrease in the solubility parameterand an increase in alkane–H₂ interactions are thekey mechanisms responsible for the enhanced solubility in H₂. This study enables the prediction of mutual solubility for a varietyof hydrogen–alkane systems and reveals that introducing methylgroups is an effective strategy for enhancing the solubility of compoundsin H₂ (termed H₂-philicity).

Systems in which the free energydensity is nonuniformin spaceare familiar; the surface tension of a water droplet and the surfaceenergy of a solid are good examples. Some such cases can be treatedwith prior theory, notably inhomogeneous solvation theory (IST), butIST is applicable only to liquids. Despite this limitation, IST hasproven useful as a guide to the design of ligands to bind a targetedprotein, based on the idea that ligands that displace high free energywater will tend to bind more tightly, other things being equal. Here,we present Generalized Thermodynamic Mapping (GTM) theory, a moregeneral theory that is applicable to the entirety of a biomolecularor other chemical system, and which thus may provide additional guidancefor molecular design. For example, it might highlight parts of a ligandwhose local free energy rises on binding, thus suggesting where modificationscould improve affinity. Starting from classical statistical thermodynamics,we derive structural decompositions that assign energy and entropyto individual atoms or to larger chemical components, such as aminoacid residues, and spatial decompositions that define continuouslyvarying thermodynamic densities throughout the system. The potentialenergy is decomposed via the multibody expansion, and the entropyvia the mutual information expansion. The resulting thermodynamicdensities satisfy key desiderata: their spatial integrals yield thecorrect total thermodynamic quantities, the densities vanish wherethe atomic number density is zero, and all entropy terms above firstorder go to zero in the absence of correlation. The entropy decompositionin GTM theory is closely related to that of IST, but it is simpler,largely because it expresses the entropy in terms of normalized probabilitydensity functions instead of nonnormalized correlation functions.We show that GTM theory is formally exact for any number of particles, N, whereas IST is not. The unified framework presented hereenables thermodynamic mapping of solute and solvent alike and is expectedto support a range of applications, including in structure-based drugdesign, protein design, the analysis of allostery, and materials science.The use of GTM theory to gain insight into protein-ligand bindingis illustrated here with an initial case study.

The Zn²⁺ coordination shell in ZnCl₂-basedbattery electrolytes is far more dynamic than its time-averaged structuresuggests. Using a machine-learning force field (MACE) fine-tuned withdensity functional theory data, we simulate nanosecond-scale moleculardynamics of a ZnCl₂:urea:H₂O deep eutectic electrolyteacross 300–400 K, a time regime inaccessible to ab initio methods and poorly captured by classical force fields.The Zn²⁺ first coordination shell is tetrahedral and compositionallymixed with chloride ions, urea, and water contributing comparableshares. This overall occupancy remains essentially constant with temperature,masking markedly asymmetric underlying kinetics. Residence-time analysisreveals that chloride is essentially nonexchanging on the nanosecondtime scale, while water and urea exchange continuously, with residencetimes an order of magnitude shorter and activation energies of 12.5and 16.2 kJ/mol, respectively. Potential of mean force and speciationanalyses identify ZnCl₂ as the dominant solute speciesand show that ligand substitution proceeds predominantly through anassociative pathway. Self-diffusion coefficients and activation energiesfor all four constituent species further establish a mobility hierarchyconsistent with this coordination picture. Together, these resultsprovide a molecular-level rationale for the transport behavior ofZnCl₂-based electrolytes and a general framework for understandingion speciation and lability in coordinating eutectic battery electrolytes.