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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. 

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.