The Journal of Physical Chemistry B最新文献

Nanosized dispersions of the bicontinuous cubic phase (cubosomes) are emerging carriers for drug delivery. These particles possess well-defined internal structures composed of highly-curved lipid bilayers that can accommodate significant drug payloads. Although cubosomes present promising potential for drug delivery, their physicochemical properties and interactions with cell membranes have not yet been fully understood. To clarify the interactions of the cubosomes with cell membranes, we investigated the changes in the structural and cubic membranes of monoolein (MO) cubosomes when mixed with model cell membranes at different phase states using time-resolved small-angle X-ray scattering (TR-SAXS), cryogenic transmission electron microscopy (cryo-TEM), and fluorescence spectroscopy. TR-SAXS results showed that the cubosomes gradually transitioned from the Im3m phase to the lamellar phase after interacting with the liposomes. The time of the structural change of the cubic phase to the lamellar phase was influenced by the fluidity of the liposome bilayers. Mixing the cubosomes with fluid membrane liposomes required less time to transition to the lamellar phase and vice versa. Cryo-TEM images showed that the well-defined internal structure of the cubosomes disappeared, leaving behind lamellar vesicles after the interaction, further confirming the TR-SAXS results. Laurdan fluorescence probe was used to assess the membrane polarity changes occurring to both the cubosomes and liposomes during the interaction. Examination of the normalized fluorescence intensity of the probed cubosomes showed decreasing intensity, followed by a recovery of intensity, which could indicate the disintegration of the cubic membrane and the formation of a mixed membrane. Also, the kinetics of the disintegration of the cubic phase did not seem to be influenced by the composition of the liposomes, which was in line with the normalized SAXS intensity results. Assessing the generalized polarization (GP₃₄₀) values of the cubosomes and liposomes after mixing revealed that the fluidity and membrane hydration states of the cubosomes and liposomes transitioned to resemble their counterpart, confirming the exchange of material between the particles. Over time, the hydration states of the cubosomes and liposomes equilibrated toward an intermediate state between the two. The time needed to reach the final intermediate state was influenced by the membrane fluidity and hydration of the liposomes, more particularly the difference in GP₃₄₀ values and their membrane phase state. These results highlight the importance of examination of the cubic membrane conditions, such as membrane polarity, and their implications on the changes in the cubic structure during the interaction with liposomal membranes.

Salts readily alter the physical properties of intrinsically disordered proteins (IDPs) rich in charged residues. Using a coarse-grained IDP model and computer simulations, we investigated how salts affect the heterogeneous conformational ensemble and segment-level structures of the IDP prothymosin-α, classified as a polyelectrolyte. We show that clusters of conformations with distinct structural features are present within the conformational ensemble of prothymosin-α by projecting it onto a two-dimensional latent space with the aid of autoencoders. Although prothymosin-α is inherently disordered, there are preferred transitions between these clusters of conformations. Changing the salt concentration led to the formation of new conformational clusters or/and the disappearance of existing conformational clusters, contributing to changes in IDP properties. Shuffling the Skopelitian domain (C-terminal sequence) of prothymosin-α, known for its anticancer activity, resulted in a different conformational cluster, indicating that clusters with specific structures are related to a particular IDP function. The multiple conformational clusters with distinct structural features could be correlated to different IDP functions, and salts aid or inhibit these functions by modulating the population of conformations in the clusters.

Intrinsically disordered proteins (IDPs) are macromolecules, which in contrast to well-folded proteins explore a large number of conformationally heterogeneous states. In this work, we investigate the conformational space of the disordered protein β-casein using Hamiltonian replica exchange atomistic molecular dynamics (MD) simulations in explicit water. The energy landscape contains a global minimum along with two shallow funnels. Employing static polymeric scaling laws separately for individual funnels, we find that they cannot be described by the same polymeric scaling exponent. Around the global minimum, the conformations are globular, whereas in the vicinity of local minima, we recover coil-like scaling. To elucidate the implications of structural diversity on equilibrium dynamics, we initiated standard MD simulations in the NVT ensemble with representative conformations from each funnel. Global and internal motions for different classes of trajectories show heterogeneous dynamics with globule to coil-like signatures. Thus, IDPs can behave as entirely different polymers in different regions of the conformational space.

Acedan (ADN) and its derivatives are versatile dyes known for their donor-acceptor properties that can be fine-tuned for numerous spectroscopic applications. Currently, they are widely used as fluorescent probes for labeling biomolecules and cellular organelles. This study examines the newly discovered multifunctionality of three ADN chromophores, amplifying their application perspectives. We employ TD-DFT methods to guide, discuss, and support experimental research. Furthermore, by utilizing nonlinear optical (NLO) techniques such as the Maker fringes method to evaluate third harmonic generation (THG) and all-optical switching (optical Kerr effect, OKE), we show that ADN derivatives exhibit remarkable NLO properties. Specifically, in THG experiments, ADN1, ADN2, and ADN3 reveal signals approximately 2.5, 2.0, and 12.0 times stronger, respectively, than the reference material (silica). Additionally, the OKE experiment confirms ADNs' photoinduced birefringence. Examined acedanes can also exhibit polychromatic fluorescence and energy transfer between individual components in two- and three-dye arrangements. Consequently, this comprehensive study offers valuable insights for applications, such as light-emitting diodes, sensors, projectors, and displays.

Understanding the interfacial mechanical behavior of graphene-polymer nanocomposites is of great significance to achieve a balance between high strength and high toughness. Grafting polymer chains onto the surface of graphene can effectively improve the dispersibility of graphene in the polymer matrix and alter the interfacial mechanical properties between graphene and the polymer matrix. In this work, we conduct coarse-grained molecular dynamics simulations to systematically study the interfacial mechanical properties between the polymer-grafted graphene and the polymer matrix. By performing normal and shear separation tests, the influences of separation velocity, graft chain length, grafting density, and matrix cross-linking density on the interfacial mechanical properties are comprehensively investigated. Results indicate that compared with pristine graphene, grafting polymer chains onto the surface of graphene can significantly enhance the fracture toughness of the graphene-polymer interface system at the expense of weakening strength. The use of medium-length graft chains and low grafting density helps to find a balance between high strength and high toughness, achieving optimal design of high-performance nanocomposites. In addition, during high-velocity separation, an increase in matrix cross-linking density is beneficial to improve the interfacial cohesive and shear strength but has no significant effect on interfacial fracture toughness. This study sheds new light on the interface design of graphene-polymer nanocomposites with desired performance.

Interfacial systems with spherical symmetry are ubiquitous in nature and the accurate estimation of local self-diffusion coefficients in these systems is crucial to our understanding of processes such as the partitioning of atmospheric species to aerosol droplets and water transport across cell membranes. In this work, we extend a method originally developed to estimate local diffusion coefficients in systems with flat interfaces to the spherically symmetric case. Specifically, we derive an analytical solution to the linearized Smoluchowski equation in spherical coordinates and utilize molecular dynamics simulations to obtain a parameter required to estimate the local self-diffusion coefficient from the solution. We demonstrate that the derived solution is indeed accurate by comparing it to the numerical solution and also validate that the assumptions under which our solution was derived are not too stringent. We further validate our solution by computing the local diffusion coefficients at different radial positions in bulk SPC/E water and comparing the results to the overall diffusion coefficient obtained from Einstein's mean squared displacement method. Finally, we apply the method to an SPC/E water droplet suspended in its own vapor. We observe that the diffusion coefficient increases from the center of the droplet toward the interface, a result in line with previous results reported for flat interfaces.

The information engine extracts work from a single heat bath using mutual information obtained during the operation cycle. This study investigates the influence of potential shaping in a Brownian information engine (BIE) in harnessing the information from thermal fluctuations. We designed a BIE by considering an overdamped Brownian particle inside a confined potential and introducing an appropriate symmetric feedback cycle. We find that the upper bound of the extractable work for a BIE with a monostable centrosymmetric confining potential, with a stable state at the potential center, depends on the bath temperature and the convexity of the confinement. A concave confinement is more efficient than a convex one for an information-energy exchange. For a bistable confinement with an unstable center and two symmetric stable basins, one can find an engine-to-refrigeration transition beyond a certain barrier height related to the energy difference between the energy barrier and the stable basins. Finally, we use the concavity-induced gain in information harnessing to device a BIE in the presence of a multistable potential that can harvest even more energy than monostable confinement.

Block copolymers of amphiphilic nature represent a distinctive class of macromolecules that have been extensively studied due to their intriguing surface-active properties. Their ability to reduce interfacial tension and create disperse phases, such as emulsions, has made them crucial in industries that rely on the interfacial effects of these molecules. Experimental and computational studies have reported the effects of changing various properties associated with the polymeric chains including stiffness, molecular weight, and other structural attributes. In this work, extensive molecular simulations were performed to understand how the sequence of an AB multiblock copolymer impacts the interfacial tension between two immiscible liquids. To efficiently explore a range of surface concentration values and four different block copolymer sequences, a coarse-grained model was employed. Simulation results indicate that at a fixed composition, block sequence has a strong effect on the rate of interfacial tension reduction as polymer surface concentration increases. Of all studied sequences, the alternating sequence was able to greatly reduce the interfacial tension at low surface concentrations, whereas pentablock and triblock sequences were able to reduce it even more than the alternating sequence, but it required a higher polymer surface concentration to achieve this. To correlate polymer conformations with interfacial effects, several structural descriptors were computed to quantify the conformations adopted by the macromolecules at the interface.

Hemoglobin (Hb)-based oxygen carriers (HBOCs) are a potential solution to the growing shortage in the worldwide blood supply. Recent developments in HBOC design have shown that Polyethylene glycol surface-conjugated liposome-encapsulated Hb (PEG-LEH) has shown promising results in mimicking the oxygen uptake and release of human red blood cells. This study aims to use atomistic simulations to investigate the mechanical properties, gas-exchange properties, and pH responsiveness of a novel HBOC which introduces a pH-sensitive molecule (KC1003) to the phospholipid membrane to regulate the uptake and release of oxygen based on pH. Mechanical properties of KC1003 in a phospholipid membrane show that it is a stable phospholipid membrane, with slight structural differences from increasing the concentration of KC1003, where an increased concentration slightly increases lipid disorder. Gas diffusion through the membrane was not limited by the addition of KC1003, and the gas diffusion values were similar to those of red blood cells. Furthermore, the membrane proved to be pH responsive, allowing for the binding and release of 2,3-DPG (2,3-Diphosphoglyceric Acid) at high and low pHs, respectively. These results collectively show that the membrane is mechanically stable at physiological conditions at a molecular scale, allows for proper gas diffusion through the phospholipid membrane, and can act as a pH-sensitive lipid membrane that the concentration of KC1003 can modify. Collectively, these results can be used for tuning of the membrane of an HBOC to mimic the physiological oxygen intake and release of a red blood cell.

The interaction between water and solid surfaces is an active area of research, and the interaction can be generally defined as hydrophobic or hydrophilic depending on the level of wetting of the surface. This wetting level can be modified, among other methods, by applying coatings, which often modify the chemistry of the surface. With the increase in available computing power and computational algorithms, methods to develop new materials and coatings have shifted from being heavily experimental to including more theoretical approaches. In this work, we use a range of experimental and computational features to develop a supervised machine learning (ML) model using the XGBoost algorithm that can predict the water contact angle (WCA) on the surface of a range of solid polymers. The mean absolute error (MAE) of the predictions is below 5.0°. Models composed of only computational features were also explored with good results (MAE < 5.0°), suggesting that this approach could be used for the "bottom-up" computational design of new polymers and coatings with specific water contact angles.