Oligomeric forms of the amyloid-β (Aβ) peptide are thought to represent the primary synaptotoxic species underlying the neurodegenerative changes seen in Alzheimer's disease. It has been proposed that the cellular prion protein (PrP) functions as a cell-surface receptor, which binds to Aβ oligomers and transduces their toxic effects. However, the molecular details of the PrP-Aβ interaction remain uncertain. Here, we investigated the effect of PrP on polymerization of Aβ under rigorously controlled conditions in which Aβ converts from a monomeric to a fibrillar state via a series of kinetically defined steps. We demonstrated that PrP specifically inhibited elongation of Aβ fibrils, most likely by binding to the ends of growing fibrils. Surprisingly, this inhibitory effect required the globular C-terminal domain of PrP, which has not been previously implicated in interactions with Aβ. Our results suggest that PrP recognizes structural features common to both Aβ oligomers and fibril ends and that this interaction could contribute to the neurotoxic effect of Aβ aggregates. Additionally, our results identify the C terminus of PrP as a new and potentially more druggable molecular target for treating Alzheimer's disease.

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Normal micelle aggregates of amphiphilic surfactant in aqueous solvent are formed by a process of entropically driven self-assembly. The self-assembly of reverse micelles from amphiphilic surfactant in non-polar solvent in the presence of water is considered to be an enthalpically driven process. While the formation of normal and reverse surfactant micelles has been well characterized in theory and experiment, the nature of dry micelle formation, from amphiphilic surfactant in non-polar solvent in the absence of water, is poorly understood. In this study, a theory of dry reverse micelle formation is developed. Variation in free energy during micelle assembly is derived for the specific case of AOT surfactant in isooctane solvent using atomistic molecular dynamics simulation analyzed using the energy representation method.The existence and thermodynamic stability of dry reverse micelles of limited size are confirmed. The abrupt occurence of monodisperse aggregates is a clear signature a critical micelle concentration, commonly observed in the formation of normal surfactant micelles. The morphology of large dry micelles provides insight into the nature of the thermodynamic driving forces stabilizing the formation of the surfactant aggregates. Overall, this study provides detailed insight into the structure and stability of dry reverse micelles assembly in non-polar solvent.

The authors propose a novel method to evaluate the position-dependent diffusion constant by analyzing unperturbed segments of a trajectory determined by the additional flat-bottom potential. The accuracy of this novel method is first established by studying homogeneous systems, where the reference value can be obtained by the Einstein relation. The applicability of this new method to heterogeneous systems is then demonstrated by studying a hydrophobic solute near a hydrophobic wall. The proposed method is also comprehensively compared with popular conventional methods, whereby the significance of the present method is illustrated. The novel method is powerful and useful for studying kinetics in heterogeneous systems based on molecular dynamics calculations.

Molecular self‐diffusion coefficients underlie various kinetic properties of the liquids involved in chemistry, physics, and pharmaceutics. In this study, 547 self‐diffusion coefficients are calculated based on all‐atom molecular dynamics (MD) simulations of 152 diverse pure liquids at various temperatures employing the OPLS4 force field. The calculated coefficients are compared with experimental data (424 extracted from the literature and 123 newly measured by pulsed‐field gradient nuclear magnetic resonance). The calculations well agree with the experimental values. The determination coefficient and root mean square error between the observed and calculated logarithmic self‐diffusion coefficients of the 547 entries are 0.931 and 0.213, respectively, demonstrating that the MD calculation can be an excellent industrial tool for predicting, for example, molecular transportation in liquids such as the diffusion of active ingredients in biological and pharmaceutical liquids. The self‐diffusion coefficients collected in this study are compiled into a database for broad researches including artificial intelligence calculations.