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Cholesterol has been conjectured to be a modulator of the amyloid cascade, the mechanism that produces the amyloid-β (Aβ) peptides implicated in the onset of Alzheimer's disease. We propose that cholesterol impacts the genesis of Aβ not through direct interaction with proteins in the bilayer, but indirectly by inducing the liquid-ordered phase and accompanying liquid–liquid phase separations, which partition proteins in the amyloid cascade to different lipid domains and ultimately to different endocytotic pathways. We explore the full process of Aβ genesis in the context of liquid-ordered phases induced by cholesterol, including protein partitioning into lipid domains, mechanisms of endocytosis experienced by lipid domains and secretases, and pH-controlled activation of amyloid precursor protein secretases in specific endocytotic environments. Outstanding questions on the essential role of cholesterol in the amyloid cascade are identified for future studies. Expected final online publication date for the Annual Review of Biophysics, Volume 53 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

The equilibrium association of transmembrane proteins plays a fundamental role in membrane protein function and cellular signaling. While the study of the equilibrium binding of single pass transmembrane proteins has received significant attention in experiment and simulation, the accurate assessment of equilibrium association constants remains a challenge to experiment and simulation. In experiment, there remain wide variations in association constants derived from experimental studies of the most widely studied transmembrane proteins. In simulation, state-of-the art methods have failed to adequately sample the thermodynamically relevant structures of the dimer state ensembles using coarse-grained models. In addition, all-atom force fields often fail to accurately assess the relative free energies of the dimer and monomer states. Given the importance of this fundamental biophysical process, it is essential to address these shortcomings. In this work, we establish an effective computational protocol for the calculation of equilibrium association constants for transmembrane homodimer formation. A set of transmembrane protein homodimers, used in the parameterization of the MARTINI v3 force field, are simulated using metadynamics, based on three collective variables. The method is found to be accurate and computationally efficient, providing a standard to be used in the future simulation studies using coarse-grained or all-atom models. 

ABSTRACT Chemical exchange line broadening is an important phenomenon in nuclear magnetic resonance (NMR) spectroscopy, in which a nuclear spin experiences more than one magnetic environment as a result of chemical or conformational changes of a molecule. The dynamic process of chemical exchange strongly affects the sensitivity and resolution of NMR experiments and increasingly provides a powerful probe of the interconversion between chemical and conformational states of proteins, nucleic acids, and other biologic macromolecules. A simple and often used theoretic description of chemical exchange in NMR spectroscopy is based on an idealized 2-state jump model (the random phase or telegraph signal). However, chemical exchange can also be represented as a barrier crossing event that can be modeled by using chemical reaction rate theory. The timescale of crossing is determined by the barrier height, the temperature, and the dissipation modeled as collisional or frictional damping. This tutorial explores the connection between the NMR theory of chemical exchange line broadening and strong collision models for chemical kinetics in statistical mechanics. Theoretic modeling and numeric simulation are used to map the rate of barrier crossing dynamics of a particle on a potential energy surface to the chemical exchange relaxation rate constant. By developing explicit models for the exchange dynamics, the tutorial aims to elucidate the underlying dynamical processes that give rise to the rich phenomenology of chemical exchange observed in NMR spectroscopy. Software for generating and analyzing the numeric simulations is provided in the form of Python and Fortran source codes. 

Lipid-coated noble metal nanoparticles (L-NPs) combine the biomimetic surface properties of a self-assembled lipid membrane with the plasmonic properties of a nanoparticle (NP) core. In this work, we investigate derivatives of cholesterol, which can be found in high concentrations in biological membranes, and other terpenoids, as tunable, synthetic platforms to functionalize L-NPs. Side chains of different length and polarity, with a terminal alkyne group as Raman label, are introduced into cholesterol and betulin frameworks. The synthesized tags are shown to coexist in two conformations in the lipid layer of the L-NPs, identified as “head-out” and “head-in” orientations, whose relative ratio is determined by their interactions with the lipid–water hydrogen-bonding network. The orientational dimorphism of the tags introduces orthogonal functionalities into the NP surface for selective targeting and plasmon-enhanced Raman sensing, which is utilized for the identification and Raman imaging of epidermal growth factor receptor–overexpressing cancer cells.