The Journal of Physical Chemistry B最新文献

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder, marked by the accumulation of amyloid-β (Aβ) plaques in the brain, excessive tau protein phosphorylation, and cholinergic neuron degeneration. In this work, a library of computationally designed peptides based on the Aβ₄₂ recognition sequence KLVFF has been generated, which is further evaluated for its ability to effectively attenuate Aβ₄₂ fibrillation. Notably, molecular mechanics Poisson–Boltzmann surface area analysis identified three new peptides, RPPWF (ΔG_binding = −58.08 ± 9.02 kcal/mol), RPPWY (ΔG_binding = −46.13 ± 3.62 kcal/mol), and KPPWW (ΔG_binding = −44.27 ± 4.08 kcal/mol), displaying significantly higher binding affinity to the Aβ₄₂ monomer (Aβ₄₂m) compared to KLVFF (ΔG_binding = −38.70 ± 17.17 kcal/mol). Importantly, among the designed peptides, RPPWF induces the helix conformation in Aβ₄₂m to the maximum extent and prevents the conformational transitions in Aβ₄₂m to aggregation-competent β-sheet structures. Furthermore, the thioflavin T (ThT) fluorescence assay depicted no self-fibrillation of RPPWF and a maximum inhibitory effect among the synthesized peptides (IC₅₀ = 8.90 ± 0.98 μM) against Aβ₄₂ fibrillation, consistent with the computational results. Notably, DLS and TEM analyses confirmed the RPPWF-induced modulation in Aβ₄₂ fibrillation. RPPWF efficiently rescued PC12 cells from Aβ₄₂ aggregate-induced neurotoxicity by notably enhancing cell viability to 89.6% as compared to 42.2% (Aβ₄₂ alone). Remarkably, this study highlights the synergistic effect of multiple substitutions (K → R, L → P, V → P, and F → W) in the amyloidogenic KLVFF sequence of Aβ₄₂ and depicts the importance of arginine, proline, and tryptophan residues in the RPPWF sequence in affording an efficient new potent inhibitor, RPPWF, of Aβ₄₂ fibrillation. Furthermore, RPPWF has the potential for conjugation or further modifications to afford more effective and clinically relevant multifunctional agents against Aβ₄₂ fibrillation in AD.

α-Synuclein (α-Syn) is an intrinsically disordered protein (IDP) whose aggregation into fibrils is implicated in Parkinson’s disease (PD). While benign α-Syn aggregation frequently occurs, off-target aggregates are implicated in disease progression. Although most mechanisms of toxic α-Syn aggregate formation are unknown, high concentrations of salt ions have been shown to systematically result in faster aggregation. Previous work suggests that salt slows water in the hydration shell of α-Syn, promoting intermolecular interactions. Here, we use polarizable molecular dynamics (MD) to investigate the interactions between α-Syn and water in response to an increased NaCl concentration. While we also find that the water in the hydration shell of the nonamyloid-β component (NAC) domain slows down with increasing salt concentration, the water in the hydration shell of the N- and C-terminal domains accelerates. The segments of the N- and C-terminal domains that show faster water diffusion kinetics corroborate with truncation experiment results. Overall, our work suggests that α-Syn aggregation is related to partial salt-induced dehydration of the N- and C-terminal domains.

In the present work, a structural model for the protein–protein interface of bone marrow stromal cell antigen 2 (BST-2) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) open reading frame 7a (ORF7a) is predicted using multiscale molecular dynamic simulations. Coarse-grained simulations enabled broad conformational sampling, and all-atom simulations refined the resulting structures. A machine learning-based clustering analysis was applied to the simulation ensemble to categorize the dominant heterodimeric conformations that captured the principal interaction geometries. Across these dominant conformations, BST-2 and ORF7a form a tightly packed transmembrane core stabilized by complementary hydrophobic and polar interactions. The cytoplasmic region contributes additional anchoring through recurrent hydrogen bonds, salt bridges, and cation–π interactions between BST-2’s N-terminal residues and ORF7a’s short cytoplasmic extending stabilization beyond the TM interface. On the other hand, the extracellular interface is reinforced by an overlapping dense network of polar and aromatic contacts. Central hubs such as N49, D55, E62, R64, N65, and H93 engage multiple ORF7a partners (R25, K32, R76, K85, and E95), creating a robust and redundant interaction architecture. Our simulations indicate that ORF7a disrupts BST-2 homodimerization through transmembrane domain competition, extracellular interface hijacking, and cytoplasmic tail anchoring. This not only destabilizes tetherin’s canonical dimer but also creates a robust heterodimeric BST-2–ORF7a complex. Functionally, this structural reorganization undermines BST-2’s ability to cross-link budding virions at the cell surface, thereby antagonizing its antiviral tethering function. Overall, our model provides structural insight into the molecular mechanism underlying the ORF7a-mediated antagonism.

Sulfonylureas are hypoglycemic agents used in type 2 diabetes mellitus, although their low water solubility implies high therapeutic doses. Inclusion complexes with β-cyclodextrin (β-CD), a cyclic oligosaccharide featuring a hydrophobic interior and hydrophilic exterior, offer a supramolecular polymer capable of encapsulating drugs, improving solubility and stability. We explore how substituent size and interaction type influence the stability of β-CD complexes with p-toluenesulfonylurea, tolbutamide, and tolazamide. Using molecular dynamics simulations, clustering analysis, and quantum chemistry calculations at the M06-2X-D3/ACP-6-31G(d) + SMD level of theory, we identified the most stable binding modes. Boltzmann populations of complexes revealed a single dominant conformation for p-toluenesulfonylurea (∼97%), two major coexisting conformations for tolbutamide (75/25%), and two near-equal conformations for tolazamide (56/43%). Predominant conformations adopted by guest molecules are in line with experimental reports. Binding free energies, determined via molecular mechanics Poisson–Boltzmann surface area analysis, for p-toluensulfonylurea, tolbutamide and tolazamide in β-CD inclusion complexes, averaged −10.75, −13.42, and −12.84 kcal mol^–1, respectively. Interaction energies increased with bulkier substituents, though this was partially offset by higher deformation costs. Analyses of ρ(r) showed that stabilization arises from networks of spatially distributed weak interactions rather than from strong directional intermolecular hydrogen bonds. These findings offer a detailed view of β-CD host–guest recognition within a carrier context, guiding the design of β-cyclodextrin-based systems to improve the formulation, stability, and therapeutic effectiveness of drugs in type 2 diabetes mellitus.

The mucosa-associated lymphoid tissue lymphoma-translocation protein 1 (MALT1) is a key protein in the adaptive immune response system in humans. This protein is widely expressed in the human body and is related to nuclear factor-κB (NF-κB) signaling activation in response to T-cell receptors. Due to this, MALT1 is key in the regulation of inflammatory events in a variety of tissues, where its dysregulation is associated with several types of cancer, especially hematological cancers. In this sense, its relevance makes MALT1 a valuable target to treat many diseases, drawing the attention of many researchers with the aim of proposing new MALT1 inhibitors. However, there is a lack of literature describing its complex dynamical behavior and allosteric inhibition, which considerably hampers the computational design of new MALT1 allosteric inhibitors. In that regard, the present work investigated the complex conformational behavior of MALT1 protein during its allosteric inhibition. For this, biased molecular dynamics simulations, sophisticated machine learning techniques such as neural networks, and docking calculations were used. From the performed investigation, it was observed that through allosteric inhibition, Loop 1 and 3 movements were crucial to reduce the catalytic site cavity volume, keeping cysteine unavailable for substrate mimic binding. In addition, statistical information over the explored ensemble showed that the great majority of the inhibited conformations presented an unavailable catalytic cysteine for substrate binding. Hence, the presented results can be used as an objective criterion for the computational proposal of new MALT1 allosteric inhibitors. However, despite mouse MALT1 and human MALT1 presenting 93% homology, the generalization of the findings to human MALT1 protein should be taken with care, and the obtained results apply specifically to the mouse MALT1 construct.

Classical density functional theory (DFT) is the primary method for investigations of inhomogeneous fluids in external fields. It requires the excess Helmholtz free energy functional as input to an Euler–Lagrange equation for the one-body density. A variant of this methodology, the force-DFT, uses instead the Yvon–Born–Green equation to generate density profiles. It is known that the latter are consistent with the virial route to the thermodynamics, while DFT is consistent with the compressibility route. In this work we will show an alternative DFT scheme using the Lovett–Mou–Buff–Wertheim (LMBW) equation to obtain density profiles, that are shown to be also consistent with the compressibility route. However, force-DFT and LMBW DFT can both be implemented using a closure relation on the level of the two-body correlation functions. This is proven to be an advantageous feature, opening the possibility of an optimization scheme in which the structural inconsistency between different routes to the density profile is minimized. (“Structural inconsistency” is a generalization of the notion of thermodynamic inconsistency, familiar from bulk integral equation studies). Numerical results are given for the density profiles of two-dimensional systems of hard-core Yukawa particles with a repulsive or an attractive tail, in planar geometry.

Solvent effects by ionic liquids (ILs) may be assessed by using a complementary supermolecule + dielectric continuum approach. We revisited the carbonation mechanism of epoxide in the [Net₂(HE)₂][Br] ionic liquid and found that the reaction field (RF) effect in the outer sphere of solvation determines the accepted mechanism for the title reaction. This implicit solvent effect appears to be related to the maximum hardness principle (MHP) involving the relative energy/hardness relationship at the transition-state structures: a highly encouraging result, as it suggests that classical reactivity rules could still be applied in the presence of complex ionic environments.

Several mechanistic (thermodynamic) models were developed for folding of the SAM-II riboswitch as a function of SAM and Mg²⁺ ion concentrations. For each model, the parameters were determined from experimental (apparent) binding data, based on the underlying assumptions of the model. The predicted titration curves computed from the different models were compared with the experimental observation of the fraction of the RNA forming a pseudoknot at specific concentrations of the ligands. Strikingly, only one of the six models correctly predicts the experimental findings, unveiling the dominant mechanism of the riboswitch function. More interestingly, the latter mechanism is found to be the most efficient compared to the other possible mechanisms. The study sheds light on the cognate ligand conformational capture mechanism of the SAM-II riboswitch in the presence of specific concentrations of magnesium ions. The presented analytical and thermodynamic framework, as well as the inferred equilibrium constants, provides foundations for making accurate quantitative predictions of the SAM-II riboswitch ensemble populations as a function of SAM and magnesium concentrations. The mechanistic linked equilibria model can be generalized to describe other thermodynamically driven riboswitches and hence facilitate identifying RNA intermediates that can be leveraged for small-molecule drug design.

Grotthuss transfer is responsible for a large increase in the self-diffusion of hydroxide and hydronium ions in aqueous solutions compared to similarly sized ions. Recent advances in machine-learning molecular dynamics have shown some success in capturing this process. In the present work, we show that classical molecular dynamics combined with experimentally measured electrical conductivities can also be used to determine self-diffusion coefficients and the lifetimes of hydroxide and hydronium ions in aqueous KOH, NaOH, and HCl solutions. This was tested and validated across a wide range of concentrations at 25 and 60 °C. The approach relies on augmenting classically computed trajectories with a biased random walk, which together accounts for both vehicular transport and Grotthuss transfer. The concentration and temperature dependence of this random walk are calibrated by comparing simulated electrical conductivities with available experimental electrical conductivity data. The computed self-diffusion coefficients match measurements at infinite dilution and results from machine learning molecular dynamics. Ion lifetimes reported by machine learning and ab initio molecular dynamics studies depend strongly on the precise definition of what constitutes a Grotthuss transfer event. Our approach for calculating ion lifetimes does not have this drawback. We also show that our self-diffusion coefficients and electrical conductivities are insensitive to the precise definition of what constitutes a Grotthuss transfer event.

Coiled-coil peptides incorporating cyclic β-amino acids, such as trans-(1S,2S)-2-aminocyclopentanecarboxylic acid (trans-ACPC), offer a versatile scaffold for engineering foldamers with tailored self-assembly and photophysical properties. Here, we investigate how solvent polarity and hydrogen-bonding capacity modulate two intrinsic features of such foldamers: autofluorescence and supramolecular organization. A series of trans-ACPC–modified and unmodified coiled-coil peptides were synthesized and characterized by circular dichroism (CD), steady-state and time-resolved fluorescence spectroscopy (SSFS and TRFS), transmission electron microscopy (TEM), and attenuated total reflectance─Fourier-transform infrared (ATR-FTIR) in water, ethanol, and acetonitrile. All peptides exhibited label-free fluorescence, with emission maxima and lifetimes varying systematically with the solvent environment and aggregate morphology. Insertion of a trans-ACPC residue rigidified the backbone, reduced solvent sensitivity, and promoted more homogeneous photophysical responses. TEM and distribution-free statistics show solvent-programmed morphologies, with water favoring extended fibrils, ethanol predominantly yielding globular or shorter twisted aggregates, and acetonitrile producing compact, less ordered clusters with intermediate cross sections (H₂O < ACN < EtOH). ATR-FTIR spectra in the amide I/II region reveal solvent-dependent band positions consistent with reorganized hydrogen-bond networks and through-space interactions among backbone carbonyls, supporting the proposed carbonyl-lock contribution to emission. Across solvents, excitation and emission wavelengths follow the expected solvatochromic ordering (most red-shifted in water, blue-shifted in ethanol, and further in acetonitrile), whereas fluorescence lifetimes are broadly similar in water and acetonitrile and shortened in ethanol, indicating only a partial correlation between supramolecular order and decay kinetics. Thus, the external solvent programs intrinsic emissive states by reshaping backbone packing and hydrogen-bond topology rather than introducing new chromophores. These findings establish a structure–solvent–photophysics relationship for cyclic β-amino acid–containing coiled-coils and highlight their potential as intrinsically emissive nanomaterials and optical probes in environments where external labels are undesirable.