The Journal of Physical Chemistry B最新文献

Despite the significant understanding of phase separation in proteins with intrinsically disordered regions, a considerable percentage of proteins without such regions also undergo phase separation, presenting an intriguing area for ongoing research across all kingdoms of life. Using a combination of spectroscopic and microscopic techniques, we report here for the first time that a low temperature and low pH can trigger the liquid-liquid phase separation (LLPS) of a parasitic protein, kinetoplastid membrane protein-11 (KMP-11). Electrostatic and hydrophobic forces are found to be essential for the formation and stability of phase-separated protein assemblies. We show further that the increase in the ionic strength beyond a threshold decreases the interchain electrostatic interactions acting between the alternate charged blocks, altering the propensity for phase separation. More interestingly, the addition of cholesterol inhibits LLPS by engaging the cholesterol recognition amino acid consensus (CRAC)-like domains present in the protein. This was further confirmed using a CRAC-deleted mutant with perturbed cholesterol binding, which did not undergo LLPS.

Molten salts are promising candidates in numerous clean energy applications, where knowledge of thermophysical properties and vapor pressure across their operating temperature ranges is critical for safe operations. Due to challenges in evaluating these properties using experimental methods, fast and scalable molecular simulations are essential to complement the experimental data. In this study, we developed machine learning interatomic potentials (MLIP) to study the AlCl₃ molten salt across varied thermodynamic conditions (T = 473-613 K and P = 2.7-23.4 bar), which allowed us to predict temperature-surface tension correlations and liquid-vapor phase diagram from direct simulations of two-phase coexistence in this molten salt. Two MLIP architectures, a Kernel-based potential and neural network interatomic potential (NNIP), were considered to benchmark their performance for AlCl₃ molten salt using experimental structure and density values. The NNIP potential employed in two-phase equilibrium simulations yields the critical temperature and critical density of AlCl₃ that are within 10 K (∼3%) and 0.03 g/cm³ (∼7%) of the reported experimental values. An accurate correlation between temperature and viscosities is obtained as well. In doing so, we report that the inclusion of low-density configurations in their training is critical to more accurately represent the AlCl₃ system across a wide phase-space. The MLIP trained using PBE-D3 functional in the ab initio molecular dynamics (AIMD) simulations (120 atoms) also showed close agreement with experimentally determined molten salt structure comprising Al₂Cl₆ dimers, as validated using Raman spectra and neutron structure factor. The PBE-D3 as well as its trained MLIP showed better liquid density and temperature correlation for AlCl₃ system when compared to several other density functionals explored in this work. Overall, the demonstrated approach to predict temperature correlations for liquid and vapor densities in this study can be employed to screen nuclear reactors-relevant compositions, helping to mitigate safety concerns.

Fermi resonance is a common phenomenon, and a hidden caveat exists in the applications of infrared probes, causing spectral complication and shorter vibrational lifetime. In this work, using the cyanotryptophan (CNTrp) side chain model compound 5-cyanoindole (CN-5CNI), we performed Fourier transform infrared spectroscopy (FTIR) and two-dimensional infrared (2D-IR) spectroscopy on unlabeled ¹²C¹⁴N-5CNI and its isotopically labeled substituents (¹²C¹⁵N-5CNI, ¹³C¹⁴N-5CNI, ¹³C¹⁵N-5CNI) and demonstrated the existence of Fermi resonance in 5CNI. By constructing the Hamiltonian and simulating 2D-IR spectra, we show that the distinct Fermi resonance 2D-IR patterns in various isotope substituents are determined by the quantum mixing consequences at the v = 1 state, as well as the v = 2 state, where the Fermi coupling and anharmonicity play a crucial role. Our work provides important insights into the elusive type of Fermi resonance, where the coupling is much smaller than the anharmonicity, which is termed the weak coupling case.

The retinal Schiff base is a chromophore of significant biological relevance, as it is responsible for capturing sunlight in rhodopsins, which are photoactive proteins found in various living organisms. Additionally, this chromophore is subjected to various mechanical forces in different proteins, which alter its structure and, consequently, its properties. To thoroughly understand the mechanical response limits of the retinal excitation energy, a simple first-order formalism has been developed to quantify the chromophore's optimal mechanical response to applied external forces (on the order of tens of pN). Additionally, the response to larger forces is analyzed by using an algorithm to explore the potential energy surfaces. It can be concluded that the retinal Schiff base exhibits a significant mechanical response and that the optimal forces and displacements involve certain coordinates typically of low frequency, showing differences between the S₁ and T₁ states, as well as between the 11-cis and all-trans isomers. Additionally, the possibility of mechanically modulating the bond length alternation using mechanical forces is ruled out.

We reassess the modeling of amorphous silica bilayers as a 2D classical system whose particles interact with an effective pairwise potential. We show that it is possible to reparametrize the potential developed by Roy, Heyde, and Heuer to quantitatively match the structural details of the experimental samples. We then study the glassy dynamics of the reparametrized model at low temperatures. Using appropriate cage-relative correlation functions, which suppress the effect of Mermin-Wagner fluctuations, we highlight the presence of two well-defined Arrhenius regimes separated by a narrow crossover region, which we connect to the thermodynamic anomalies and changes in the local structure. We find that the bond-orientational order grows steadily below the crossover temperature and is associated with transient crystalline domains of nanometric size. These findings raise fundamental questions about the nature of the glass structure in two dimensions and provide guidelines to interpret the experimental data.

The increased levels of carbon dioxide (CO₂) emissions due to the combustion of fossil fuels and the consequential impact on global climate change have made CO₂ capture, storage, and utilization a significant area of focus for current research. In most electrochemical CO₂ applications, water is used as a proton donor due to its high availability and mobility and use as a polar solvent. Additionally, supercritical CO₂ is a promising avenue for electrochemical applications due to its unique chemical and physical properties. Consequently, understanding the interactions between water and supercritical CO₂ is of great importance for future electrochemical applications. Molecular dynamics (MD) simulation is a powerful tool that enables atomistic-resolution dynamics of molecular systems, which can complement and guide future experimental investigations. This study employed atomistic MD to study the cosolubilities, codiffusivities, and structure of supercritical CO₂ and water systems, with a polarizable water model (SWM4-NDP) and a nonpolarizable CO₂ model (TraPPE). Additionally, ab initio MD simulations were used to better understand how atomistic polarizable/nonpolarizable models compare to explicit modeling of electron densities. The polarizable water model exhibited substantial improvement in water-associated properties. We anticipate the development of a compatible polarizable CO₂ model to yield similar improvement, providing a pathway for realizing novel high-pressure electrochemical systems.

Artificially synthesized DNA holds significant promise in addressing fundamental biochemical questions and driving advancements in biotechnology, genetics, and DNA digital data storage. Rapid and precise electric identification of these artificial DNA strands is crucial for their effective application. Herein, we present a comprehensive investigation into the electric recognition of eight artificial synthesized DNA (xDNA and yDNA) nucleobases using quantum tunneling transport and machine learning (ML) techniques. By embedding these nucleobases within a solid-state nanogap junction, we calculated their fingerprint transmission and current readouts and also analyzed the influence of electronic coupling and molecular orbital delocalization on these properties. The trained ML model achieved a predictive basecalling accuracy of up to 100% for xDNA nucleobases and 99.80% for yDNA transmission readout data sets. ML explainability study revealed that normalized descriptors have a greater impact on nucleobase prediction than the original transmission function, proving more effective in disentangling overlapping artificial DNA nucleobase signals. Quaternary classification results highlighted higher recognition accuracy for xDNA nucleobases than for yDNA nucleobases. Furthermore, precise calling of complementary, purine, and pyrimidine base pair combinations was demonstrated with high sensitivity and an F1 score. Our findings reveal the feasibility of highly sensitive and precise electrical recognition of artificial DNA nucleobases, which can transform genetic research and spur advancements in genetic data storage, synthetic biology, and diagnostics.

Fluid-silica interfaces are ubiquitous in chemistry, occurring in both natural geochemical environments and practical applications ranging from separations to catalysis. Simulations of these interfaces have been, and continue to be, a significant avenue for understanding their behavior. A constraining factor, however, is the availability of accurate force fields. Most simulations use traditional "mixing rules" to determine nonbonded dispersion interactions, an approach that has not been critically examined. Here, we present Lennard-Jones parameters for the interaction of carbon dioxide with silica interfaces that are optimized to reproduce density functional theory (DFT)-based binding energies. The modeling is based on the recently developed silica-DDEC force field, whose atomic charges are consistent with DFT calculations. Standard mixing rules are found to predict weaker CO₂ binding to silica than that obtained from DFT, an effect corrected by the optimized parameters given here. This behavior extends to other silica force fields (Clayff and Gulmen-Thompson), and the present Lennard-Jones parameters improve their performance as well. The effects of improved Lennard-Jones parameters on the structural and dynamical properties of condensed CO₂ in silica slit pores are also examined.

The folding of the guanine repetitive region in the telomere unit into G-quadruplex (G4) by drugs has been suggested as an alternative approach for cancer therapy. Hydroxychloroquine (HCQ) and chloroquine (CQ) are two important drugs in the trial stage for cancer. Both drugs can induce the folding of telomere-guanine-rich sequences into G4 even in the absence of salt. However, the guanine repetitive telomeric sequences are always flanked by other nucleobases at both the terminal (5' or 3') that can affect the drug-induced folding pathways and stability of the G4 significantly. Hence, in this study, the HCQ and CQ drug-induced folding of the guanine repetitive telomeric sequences into G4 and its stability by varying the chemical nature, number, and positions of the flanking nucleobases has been explored using several biophysical techniques and docking studies. It has been found that the drug-induced folding of telomere with single flanking nucleobases is similar to that without flanking nucleobases irrespective of the chemical nature and position of the flanking nucleobase. However, the propensity of the folding and the stability of the telomeric G4 induced by drugs decrease significantly with the increase of the flanking nucleobases more than one of any chemical nature and position. The data suggest that the number of flanking nucleobases rather than their chemical nature and location is a critical factor in the folding of the telomere into G4 induced by both drugs. Further, it has been observed that both drugs mainly interact with the G-tract and thymine of the loop region rather than the flanking nucleobases of the telomeric sequences without or with one flanking nucleobase. In contrast, the flanking nucleobases also participate in the interaction with the HCQ and CQ along with the core guanine repeat telomeric unit in the case of the telomeric sequences with more than one flanking nucleobases. The participation of the flanking nucleobases in the interaction with the HCQ and CQ affects the hydrogen bonding of the positively charged side chain of drugs with G quartet and loop nucleobases of telomere along with the with π···π and C-H···π weak interactions between the quinoline part of the drugs with the core telomeric guanine repeat unit which affects the folding pattern of the telomere sequences with more than one flanking nucleobases into G4.

Liquid-liquid phase transitions play a pivotal role in various scientific disciplines and technological applications, ranging from biology to materials science and geophysics. Understanding the behavior of materials undergoing these transitions provides valuable insights into complex systems and their dynamic properties. This review explores the implications of liquid-liquid phase transitions, particularly focusing on the transition between low-density liquid (LDL) and high-density liquid (HDL) phases. We investigate the thermodynamic, structural, and mechanistic aspects of these transitions, emphasizing their relevance in diverse fields. The creation of dynamic heterogeneities and critical fluctuations during liquid-liquid phase transitions is discussed, highlighting their role in shaping the phase behavior and dynamics of complex fluids. Experimental observations, including the use of dielectric spectroscopy and nonlinear methods, shed light on the intricate nature of these transitions. Our findings suggest a connection between liquid-liquid phase transitions and critical phenomena, with implications for understanding the supercooled state and phase behavior of hydrogen-bonded liquids such as glycerol. Overall, this review underscores the importance of interdisciplinary approaches in unraveling the complexities of liquid-liquid phase behavior and addressing fundamental questions.