The Journal of Physical Chemistry B最新文献

Nucleation is a critical step that determines the assembly pathway and the structure and functions of the peptide assemblies. However, the dynamic evolution of interactions between nucleating agents and peptides, as well as between peptides themselves during the nucleation process, remains elusive. Herein, we show that the heterogeneous nucleating agent carboxymethylcellulose (CMC) can promote the nucleation of Aβ_16-20 (KF) peptide. The Förster resonance energy transfer (FRET) technology was used to unveil the interaction dynamics between the CMC and KF peptide. Initially, CMC enriches KF monomers through weak nondirectional electrostatic interactions. The electrostatic screening reduces the electrostatic repulsion between KF molecules. Subsequently, KF-KF interactions become dominant, leading to the dissociation of KF from the CMC and nucleation. By adjustment of the adding time, dosage, size, and active sites of CMC, the assembly kinetics of KF can be effectively controlled. This study helps gain a deep understanding of the early heterogeneous nucleation process of peptide assembly and provides valuable guidance for the rational design of efficient nucleating agents for peptide assembly toward functional materials.

Lysophospholipids (LPLs) and host defense peptides (HDPs) are naturally occurring membrane-active agents that disrupt key membrane properties, including the hydrocarbon thickness, intrinsic curvature, and molecular packing. Although the membrane activity of these agents has been widely examined separately, their combined effects are largely unexplored. Here, we use experimental and computational tools to investigate how lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE), an LPL of lower positive spontaneous curvature, influence the membrane activity of piscidin 1 (P1), an α-helical HDP from fish. Four membrane systems are probed: 75:25 C16:0-C18:1 PC (POPC)/C16:0-C18:1 phosphoglycerol (POPG), 50:25:25 POPC/POPG/16:0 LPC, 75:25 C16:0-C18:1 PE (POPE)/POPG, and 50:25:25 POPE/POPG/14:0 LPE. Dye leakage, circular dichroism, and NMR experiments demonstrate that while the presence of LPLs alone does not induce leakage-proficient defects, it boosts the permeabilization capability of P1, resulting in an efficacy order of POPC/POPG/16:0 LPC > POPE/POPG/14:0 LPE > POPC/POPG > POPE/POPG. This enhancement occurs without altering the membrane affinity and conformation of P1. Molecular dynamics simulations feature two types of asymmetric membranes to represent the imbalanced ("area stressed") and balanced ("area relaxed") distribution of lipids and peptides in the two leaflets. The simulations capture the membrane thinning effects of P1, LPC, and LPE, and the positive curvature strain imposed by both LPLs is reflected in the lateral pressure profiles. They also reveal a higher number of membrane defects for the P1/LPC than P1/LPE combination, congruent with the permeabilization experiments. Altogether, these results show that P1 and LPLs disrupt membranes in a concerted fashion, with LPC, the more disruptive LPL, boosting the permeabilization of P1 more than LPE. This mechanistic knowledge is relevant to understanding biological processes where multiple membrane-active agents such as HDPs and LPLs are involved.

Despite the remarkable resistance of the nucleic acid phosphodiester backbone to degradation affording genetic stability, the P-O bond must be broken during DNA repair and RNA metabolism, among many other critical cellular processes. Nucleases are powerful enzymes that can enhance the uncatalyzed rate of phosphodiester bond cleavage by up to ∼10¹⁷-fold. Despite the most well accepted hydrolysis mechanism involving two metals (M_A²⁺ to activate a water nucleophile and M_B²⁺ to stabilize the leaving group), experimental evidence suggests that some nucleases can use a single metal to facilitate the chemical step, a controversial concept in the literature. The present perspective uses the case studies of four nucleases (I-PpoI, APE1, and bacterial and human EndoV) to highlight how computational approaches ranging from quantum mechanical (QM) cluster models to molecular dynamics (MD) simulations and combined quantum mechanics-molecular mechanics (QM/MM) calculations can reveal the atomic level details necessary to understand how a nuclease can use a single metal to facilitate this difficult chemistry. The representative nucleases showcase how different amino acid residues (e.g., histidine, aspartate) can fulfill the role of the first metal (M_A²⁺) in the two-metal-mediated mechanisms. Nevertheless, differences in active site architectures afford diversity in the single-metal-mediated mechanism in terms of the metal-substrate coordination, the role of the metal, and the identities of the general acid and base. The greater understanding of the catalytic mechanisms of nucleases obtained from the body of work reviewed can be used to further explore the progression of diseases associated with nuclease (mis)activity and the development of novel nuclease applications such as disease diagnostics, gene engineering, and therapeutics.

The homotrimeric SARS-CoV-2 spike protein enables viral infection by undergoing a large conformational transition, which facilitates the fusion of the viral envelope with the host cell membrane. The spike protein is anchored to the SARS-CoV-2 envelope by its transmembrane domain (TMD), composed of three TM helices, each contributed by one of the protomers of spike. Although the TMD is known to be important for viral fusion, whether it is a passive anchor of the spike or actively promotes fusion remains unknown. Specifically, it is unclear if the TMD and its dynamics facilitate the prefusion to postfusion conformational transition of the spike. Here, we computationally study the dynamics and self-assembly of the SARS-CoV-2 spike TMD in homogeneous POPC and cholesterol containing membranes. Atomistic simulations of a long TM helix-containing protomer segment show that the membrane-embedded segment bobs, tilts and gains and loses helicity, locally thinning the membrane. Coarse-grained multimerization simulations using representative TM helix structures from the atomistic simulations exhibit diverse trimer populations whose architecture depends on the structure of the TM helix protomer. While a symmetric conformation reflects the symmetry of the resting spike, an asymmetric TMD conformation could promote membrane fusion through the stabilization of a fusion intermediate. Together, our simulations demonstrate that the sequence and length of the SARS-CoV-2 spike TM segment make it inherently dynamic, that trimerization does not abrogate these dynamics and that the various observed TMD conformations may enable viral fusion.

Machine learning methods have been important in the study of phase transitions. Unsupervised methods are particularly attractive because they do not require prior knowledge of the existence of a phase transition. In this work we focus on the constant magnetization Ising model in two (2D) and three (3D) dimensions. While there have been many studies using machine learning for the critical behavior of these systems, we are not aware of any studies for the phase diagram at off-critical magnetizations below the critical temperature. Previous work has used the raw spins as the input feature. We show that a more robust input feature is the local affinity, where the value of the feature at each site is determined by the spin and its neighbors. When coupled with a variational autoencoder, the method is able to predict the phase behavior of the 2D and 3D Ising models (including the critical exponent β) in quantitative agreement with conventional simulations. The choice of activation functions in the autoencoder is crucial, and this requires physical insight into the nature of the phase transition. The method is general and can be applied to any lattice or off-lattice system.

Changes in water-protein interactions are crucial for proteins to achieve functional and nonfunctional conformations during structural transitions by modulating local stability. Amyloid-like protein aggregates in deteriorating neurons are hallmarks of neurodegenerative disorders. These aggregates form through significant structural changes, transitioning from functional native conformations to supramolecular cross-β-sheet structures via misfolded and oligomeric intermediates in a multistep process. However, the site-specific dynamics of water molecules from the native to misfolded conformations and further to oligomeric and compact amyloid structures remain poorly understood. In this study, we used the fluorescence method known as red-edge excitation shift (REES) to investigate the solvation dynamics at specific sites in various equilibrium conformations en route to the misfolding and aggregation of the functional domain of the TDP-43 protein (TDP-43^tRRM). We generated three single tryptophan-single cysteine mutants of TDP-43^tRRM, with the cysteines at different positions and tryptophan at a fixed position. Each sole cysteine was fluorescently labeled and used as a site-specific fluorophore along with the single tryptophan, creating four monitorable sites for REES studies. By investigating the site-specific extent of REES, we developed a residue-specific solvation dynamics map of TDP-43^tRRM during its misfolding and aggregation. Our observations revealed that solvation dynamics progressively became more rigid and heterogeneous to varying extents at different sites during the transition from native to amyloid-like conformations.

Hydrated deep eutectic solvents (DESs) are recognized for their potential in biocatalysis due to their tunability, biocompatibility, greenness, and ability to keep protein stable and active. However, the mechanisms governing enzyme stability and activity in DES remain poorly understood. Herein, using bromelain as the model enzyme and acetamide (0.5)/urea(0.3)/sorbitol(0.2) as the model DES, we provide experimental evidence that modulation of associated water plays a key role in dictating protein stability and activity in hydrated DES. Specifically, rigid associated water at higher DES concentrations (beyond 40% v/v) stabilizes bromelain through entropy but destabilizes it through enthalpy. On the other hand, flexible associated water dynamics at lower DES concentrations result in an opposite thermodynamic outcome. Importantly, the bulk water dynamics cannot explain the stability trend, which emphasizes the critical role of water near the protein surface. Strikingly, associated water dynamics also correlates strongly with bromelain's proteolytic activity. An increasing flexibility of the associated water dynamics leads to the enhancement of the activity. This is the first study to experimentally link associated water dynamics to enzyme behavior in hydrated DES, offering insights that could guide future developments in solvent engineering for enzyme catalysis.

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.

Macrocyclization or stapling is an important strategy for increasing the conformational stability and target-binding affinity of peptides and proteins, especially in therapeutic contexts. Atomistic simulations of such stapled peptides and proteins could help rationalize existing experimental data and provide predictive tools for the design of new stapled peptides and proteins. Standard approaches exist for incorporating nonstandard amino acids and functional groups into the force fields required for MD simulations and have been used in the context of stapling for more than a decade. However, enthusiasm for their use has been limited by their time-intensive nature and concerns about whether the resulting simulations would be physically realistic. Here, we report the development of force field parameters for two unnatural triazole staples, which we have incorporated into implicit-solvent parallel temperature replica-exchange molecular dynamics simulations of several stapled coiled-coil variants and their nonstapled counterparts. We used these simulations to calculate melting temperatures (T_m) of each variant along with the impact of stapling on the conformational stability of each variant relative to its nonstapled counterpart (ΔΔG). Trends among these simulated T_m and ΔΔG values closely match those observed in previous experiments, suggesting that the parameters we developed for these staples are sufficiently realistic to be useful in predicting the impact of stapling on the protein/peptide conformational stability in other contexts.

Introduction of non-DLVO forces by nonionic surfactants brings about fascinating changes in the phase behavior of silica nanosuspensions. We show here that alterations in the interaction and wetting properties of negatively charged silica nanoparticles (Ludox® LS) in the presence of polyethylene oxide-polypropylene oxide-polyethylene oxide-based triblock copolymers called Pluronics lead to the formation of stable o/w Pickering emulsions and interparticle attraction-induced thermoresponsive liquid-liquid phase separations. The results make interesting comparisons with those reported for Ludox® TM nanosuspensions comprising larger silica nanoparticles. Association of these nanosystems with Pluronics occurs through their surface silanol groups. LS nanoparticles with a higher surface-to-volume ratio thus need a higher amount of Pluronics for the onset of interparticle attraction as compared to their TM counterparts. Small-angle X-ray scattering studies reveal that unlike TM nanosuspensions, LS nanosuspensions form Pickering emulsions with the ordering of both Pluronic-coated and bare nanoparticles at the oil-water interface. This could arise due to steric limitations in accommodating large Pluronic molecules between smaller LS nanoparticles, with highly curved surfaces, in closed-packed configurations. Small angle neutron scattering studies show clear signatures of the onset of thermoresponsive intermicellar attraction in these systems as a function of temperature and Pluronic concentration, induced solely by the modulation of non-DLVO steric and hydrophobic interactions, not reported hitherto in charged nanosuspensions. The results give insights into the roles of hydrophilic-lipophilic balance of surfactants and size of silica nanoparticles in determining the phase behaviors of silica-surfactant nanocomposite systems.