The Journal of Physical Chemistry B最新文献

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.

A considerable effort has been expended over the years to tune the properties of ionic liquids (ILs) by designing cations, anions, and pendant groups on the ions. A simple and effective approach to altering the properties of ILs is formulating IL–IL mixtures. However, the measurements and properties of such mixtures lag considerably behind those of pure ILs. From a molecular simulation point of view, binary IL mixtures have been investigated using charge distributions of pure ILs, which implicitly assumes that the ions of different polarizability do not influence the local electronic environment due to changing concentrations. To understand this effect, molecular dynamics (MD) simulations were conducted for a series of IL–IL mixtures containing the common cation 1-ethyl-3-methylimidazolium [C₂mim] varying the composition of various combinations of anions (tetrafluoroborate [BF₄] and dicyanamide [DCA], [BF₄] and bis(trifluoromethanesulfonyl)imide [NTF₂], [BF₄] and trifluoromethanesulfonate [TFO], and [TFO] and [NTF₂]). The effect of changing the electronic environment was evaluated by deriving partial charges using density functional theory (DFT) calculations in the condensed phase. It was observed that the overall charge on the cation and anion was a function of the cation–anion pairings for pure ILs. Moreover, the cation charge was found to vary linearly with anionic concentrations. Improved agreement of predicted density and ionic conductivity with experimental values was found for binary IL mixtures with this approach, in comparison to that when a fixed charge model is employed.

Abnormal aggregation of tau protein is pathologically linked to Alzheimer's disease, while the aggregation of the prion-like RNA-binding protein (RBP) CPEB3 is functional and is associated with long-term memory. However, the interaction between these two memory-related proteins has not yet been explored. Our residue-specific NMR relaxation study revealed that the first prion domain of CPEB3 (PRD1) interacts with the ³⁰⁶VQIVYKPVDLSKV³¹⁸ segment of tau and prevents the aggregation of tau-K18. Notably, this interaction is synergistic as it not only inhibits tau-K18 aggregation but also enhances PRD1 fibril formation. We also studied the interaction of different PRD1 subdomains with tau-K18 to elucidate the precise region of PRD1 that inhibits tau-K18 aggregation. This revealed that the PRD1-Q region is responsible for preventing tau-K18 aggregation. Inspired by this, we synthesized a 15 amino acid Poly-Q peptide that inhibits tau-K18 aggregation, suggesting its potential as a small drug-like molecule for Alzheimer's disease therapeutics.

Antimicrobial peptides (AMPs) have important developmental prospects as potential candidates for novel antibiotics. Although many studies have been devoted to the identification of AMPs and the qualitative prediction of their functional activities, few methods address the quantitative prediction of their activity values. In this paper, we propose a regression model called MSCMamba, which fuses multiscale convolutional neural network with Mamba module to accurately predict the activity values of AMPs. AMPs sequences are feature-extracted by multiple encoding methods and fed into a multiscale convolutional network and a Mamba module to capture local and long-range dependent features, respectively. The model fuses these two outputs and predicts the activity values of AMPs through a linear layer. Experimental results show that MSCMamba outperforms the current state-of-the-art methods in several performance metrics, especially with an increase in R² from 0.422 to 0.467, representing a 10.66% improvement. Additionally, we did a series of ablation experiments to verify the validity of each part of the MSCMamba model and the performance enhancement of feature diversification.This study provides a new method for activity prediction of AMPs, which is expected to accelerate the development of novel antibiotics.

Modeling polymer brushes is essential for understanding their complex behavior at surfaces and interfaces, enabling the design of materials with tunable properties. We present a computational protocol to model polymer brushes composed of grafted, brush-like chains of the charged polymer poly(N,N-dimethylaminoethyl methacrylate) (p(DMAEMA)) using an all-atom representation that captures detailed molecular interactions and structural properties. The approach is flexible and non-grid-based and allows for randomized strand configurations and the incorporation of periodic boundary conditions, enabling the construction of asymmetric polymer brush setups. An atactic p(DMAEMA) configuration is demonstrated as an example, though the protocol can be readily adapted to construct other brush-like polymer systems with varying tacticities or compositions, depending on the pH environment. Furthermore, this can be extended to stimuli-responsive materials, which generate conformation or charge upon changes in pH value or other external triggers. Molecular dynamics simulations are then employed to gain insights into the conformational behavior of the grafted p(DMAEMA) brushes and their surrounding aqueous environment, as well as their response to temperature, protonation, and variations in grafting densities, in terms of the solvent-accessible surface area, radius of gyration, and radial distribution functions. This versatile protocol provides a robust tool for simulating and analyzing the properties of diverse polyelectrolyte polymer brush systems and also as composite materials.

Simulating excited-state dynamics or computing spectra for molecules in condensed phases requires sampling the ground state to generate initial conditions. Initial conditions (or snapshots for spectra) are typically produced by QM/MM Boltzmann sampling following MM equilibration or optimization. Given the switch from a MM to a QM/MM potential energy surface, one should discard a set period of time (which we call the "healing time") from the beginning of the QM/MM trajectory. Ideally, the healing time is as short as possible (to avoid unnecessary computational effort), but long enough to equilibrate to the QM/MM ground state distribution. Healing times in previous studies range from tens of femtoseconds to tens of picoseconds, suggesting the need for guidelines to choose a healing time. We examine the effect of healing time on the nonadiabatic dynamics and spectrum of a first-generation Donor-Acceptor Stenhouse Adduct in chloroform. Insufficient healing times skew the branching ratio of ground state products and alter the relaxation time for one pathway. The influence of the healing time on the absorption spectrum is less pronounced, warning that the spectrum is not a sensitive indicator for the quality of a set of initial conditions for dynamics. We demonstrate that a reasonable estimate for the healing time can be obtained by monitoring the solute temperature during the healing trajectory. We suggest that this procedure should become standard practice for determining healing times to generate initial conditions for nonadiabatic QM/MM simulations in large molecules and condensed phases.

Noncovalent interactions, particularly hydrogen bonding, play a pivotal role in determining the structural stability and functional properties of molecules, including bioactive compounds like resveratrol. This study focuses on the hydrogen-bonding behavior and other noncovalent interactions in gas-phase resveratrol-ethanol (EtOH) and resveratrol-methanol (MtOH) complexes, referred to as System 1 and System 2, respectively. These systems were optimized using the ωB97XD functional and cc-pVDZ basis set, providing a detailed picture of their stability and intermolecular interactions. By employing advanced methods such as Domain-Based Local Pair Natural Orbital Coupled Cluster (DLPNO-CCSD)(T) for energy decomposition, natural bond orbital (NBO) for charge analysis, atoms in molecule (AIM) for electron density topology, and noncovalent interaction (NCI) techniques, we decompose interaction energies into meaningful components like electrostatic, dispersion, and exchange-repulsion. The findings indicate that, while hydrogen bonding contributes to the stability of these complexes, London dispersion and other attractive interactions are substantial factors as well. The resveratrol-EtOH and resveratrol-MtOH systems demonstrate a robust electronic environment with significant contributions from various intermolecular forces, underscoring the importance of noncovalent interactions in stabilizing bioactive compounds. This study adds to our understanding of molecular interactions in resveratrol complexes, with potential implications for medicinal chemistry and material science, particularly where solvation effects are critical.

Water is vital to all facets of life and is anomalously behaving in its condensed states, making it continually a substance of interest to researchers. Therefore, attempting to capture its properties via correlations and equations of state is extremely valuable. Liquid water has not been studied as extensively in the low-temperature and high-pressure region as in other regions. Some key applications for correlations in this region are cryopreservation (specifically in certain methods of cryopreservation such as hyperbaric (high-pressure) and isochoric (constant-volume) cryopreservation), deep oceans, hydrospheres, clouds, and precipitation. Although there are not nearly as many models for water at low temperatures and high pressures as there are in other temperature and pressure ranges, there are some models that do currently exist. However, these either do not extend to temperatures and pressures as extreme as the data that exist, or they are complex with large numbers of parameters making them more difficult for application. Herein, we present a new correlation for liquid water valid for the temperature range of 200-300 K (-73-27 °C) and pressure range of 0.1-400 MPa that can analytically calculate volume, isothermal compressibility, isobaric expansivity, constant pressure heat capacity, and speed of sound, using only 17 adjustable parameters. The analytical expressions that we derived, and the fitting method that we used can also be applied to other fluids of interest in the future.

Nanoaperture optical tweezers allow for trapping single proteins and detecting their conformational changes without modifying the protein, i.e., being free from labels or tethers. While past works have used laser heating as a way to vary the local temperature, this does not allow for probing of lower temperature values. Here we investigate the lower temperature dynamics of individual Bovine Serum Albumin (BSA) proteins with the help of a custom Peltier cooling stage. The BSA transitions between the normal (N) and fast (F) states. The normal form of BSA has a maximum occupancy at 21 ± 1 °C, which is interpreted as its maximum stability point for the compact N form with respect to the F form. In this way, it is possible to find the relative thermodynamic parameters of single proteins without requiring any modifications to the intrinsic structure.

In this study, the synergistic behavior of aqueous binary mixtures of 1,2-dimethoxyethane (DME), 2-methoxyethanol (2ME), and ethylene glycol (EG) was investigated using three solvatochromic dyes: coumarin 461 (C461), 4-aminophthalimide (4AP), and para-nitroaniline (pNA) through steady-state UV-visible spectroscopy and fluorescence emission spectroscopy. The absorption maxima of the dyes exhibited extensive bathochromic shifts with varying solvent mixture compositions. In the water-rich region of the mixtures, the absorption maxima displayed significantly larger bathochromic shifts compared with those in pure water. A clear case of synergistic solvation was observed, indicating that the polarity of mixtures exceeds that of pure water. The synergistic effect was pronounced in the water-DME and water-2ME mixtures, while it was weaker in the water-EG mixture. This "hyper-polarity" was analyzed from the molar transition energy variation using a generalized Bosch solvation model. In the water-DME and water-2ME mixtures, the equilibrium constant for synergistic solvation was significantly greater than that for preferential solvation, whereas in the water-EG mixture, the values were comparable. This behavior stemmed from the intermolecular hydrogen bonding between water and cosolvents. The mole fraction of synergistic solvation suggested microheterogeneity around the solute within the mixtures. Notably, the variation in emission maxima of the probes showed no synergistic behavior, implying that solvent reorientation in the excited state disrupts the synergistic effect. IR spectroscopy was also employed to investigate the hydrogen-bonded structures in the binary mixtures. Analytical modeling of -OH and -CH stretching frequency was established, and it revealed that the formation of water-DME and water-2ME hydrogen-bonded aggregates is responsible for the observed synergistic "hyper-polarity" effect.