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We report here an experimental-computational study of hydrated TiO2anatase nanoparticles interacting with glycine, where we obtain quantitative agreement of the measured adsorption free energies. Ab initio simulations are performed within the tight binding and density functional theory in combination with enhanced free-energy sampling techniques, which exploit the thermodynamic integration of the unbiased mean forces collected on-the-fly along the molecular dynamics trajectories. The experiments adopt a new and efficient setup for electrochemical impedance spectroscopy measurements based on portable screen-printed gold electrodes, which allows fast and in situ signal assessment. The measured adsorption free energy is −30 kJ/mol (both from experiment and calculation), with preferential interaction of the charged NH3+group which strongly adsorbs on the TiO2bridging oxygens. This highlights the importance of the terminal amino groups in the adsorption mechanism of amino acids on hydrated metal oxides. The excellent agreement between computation and experiment for this amino acid opens the doors to the exploration of the interaction free energies for other moderately complex bionano systems.

Membrane curvature sensing, where the binding free energies of membrane-associated molecules depend on the local membrane curvature, is a key factor to modulate and maintain the shape and organization of cell membranes. However, the microscopic mechanisms are not well understood, partly due to absence of efficient simulation methods. Here, we describe a method to compute the curvature dependence of the binding free energy of a membrane-associated probe molecule that interacts with a buckled membrane, which has been created by lateral compression of a flat bilayer patch. This buckling approach samples a wide range of curvatures in a single simulation, and anisotropic effects can be extracted from the orientation statistics. We develop an efficient and robust algorithm to extract the motion of the probe along the buckled membrane surface, and evaluate its numerical properties by extensive sampling of three coarse-grained model systems: local lipid density in a curved environment for single-component bilayers, curvature preferences of individual lipids in two-component membranes, and curvature sensing by a homotrimeric transmembrane protein. The method can be used to complement experimental data from curvature partition assays and provides additional insight into mesoscopic theories and molecular mechanisms for curvature sensing.