Atomic resolution and coarse-grained simulations of dimyristoylphosphatidylcholine lipid bilayers were analyzed for fluctuations perpendicular to the bilayer using a completely Fourier-based method. We find that the fluctuation spectrum of motions perpendicular to the bilayer can be decomposed into just two parts: 1), a pure undulation spectrum proportional to q(-4) that dominates in the small-q regime; and 2), a molecular density structure factor contribution that dominates in the large-q regime. There is no need for a term proportional to q(-2) that has been postulated for protrusion fluctuations and that appeared to have been necessary to fit the spectrum for intermediate q. We suggest that earlier reports of such a term were due to the artifact of binning and smoothing in real space before obtaining the Fourier spectrum. The observability of an intermediate protrusion regime from the fluctuation spectrum is discussed based on measured and calculated material constants.

Thermal fluctuations of lipid orientation are analyzed to infer the bending rigidity of lipid bilayers directly from molecular simulations. Compared to the traditional analysis of thermal membrane undulations, the proposed method is reliable down to shorter wavelengths and allows for determination of the bending rigidity using smaller simulation boxes. The requisite theoretical arguments behind this analysis are presented and verified by simulations spanning a diverse range of lipid models from the literature.

Adsorption profiles and adsorption free energies were determined for the side chain analogs of the 20 naturally occurring amino acids and a titanium binding peptide on the TiO 2 (100) surface. Microsecond simulations with umbrella sampling and metadynamics were used to sample the free energy barriers associated with desolvation of strongly bound water molecules at the TiO 2 surface. Polar and aromatic side chain analogs that hydrogen bond either to surface waters or directly to the metal oxide surface were found to be the strongest binders. Further, adsorption simulations of a 6-residue titanium binding peptide identified two binding modes on TiO 2 (100). The peptide structure with lowest free energy was shown to be stabilized by a salt bridge between the end termini. A comparison between the free energies of the side chain analogs of the peptide sequence and the peptide itself shows that the free energy contributions are not additive. The simulations emphasize that tightly bound surface waters play a key role for peptide and protein structures when bound to inorganic surfaces in biological environments.

Ab initio molecular dynamics simulations are reported for water-embedded TiO2 surfaces to determine the diffusive and reactive behavior at full hydration. A three-domain model is developed for six surfaces [rutile (110), (100), and (001), and anatase (101), (100), and (001)] which describes waters as “hard” (irreversibly bound to the surface), “soft” (with reduced mobility but orientation freedom near the surface), or “bulk.” The model explains previous experimental data and provides a detailed picture of water diffusion near TiO2 surfaces. Water reactivity is analyzed with a graph-theoretic approach that reveals a number of reaction pathways on TiO2 which occur at full hydration, in addition to direct water splitting. Hydronium (H3O+) is identified to be a key intermediate state, which facilitates water dissociation by proton hopping between intact and dissociated waters near the surfaces. These discoveries significantly improve the understanding of nanoscale water dynamics and reactivity at TiO2 interfaces under ambient conditions.

Atomistic force field parameters were developed for the TiO 2 −water interface by systematic optimization with respect to experimentally determined crystal structures (lattice parameters) and surface thermodynamics (water adsorption enthalpy). Optimized force field parameters were determined for the two cases where TiO 2 was modeled with or without covalent bonding. The nonbonded TiO 2 model can be used to simulate different TiO 2 phases, while the bonded TiO 2 model is particularly useful for simulations of nanosized TiO 2 and biomatter, including protein− surface and nanoparticle−biomembrane simulations. The procedure is easily generalized to parametrize interactions between other inorganic surfaces and biomolecules. ■ INTRODUCTIONBiomolecules interacting with inorganic objects are fundamental in nanobiotechnological applications such as surfaceattached biomolecules for target delivery of drug molecules, 1 protein adsorption to medical implants, 2 protein−nanoparticle interactions 3 and, not least, to understand the molecular mechanisms of nanotoxicity. 4 The contact points between inorganic surfaces and biomatter (the nanobio interface 5 ) can be tracked with experimental techniques like dynamic light scattering (DLS), 6−8 chromatography 9,10 and/or spectroscopy, 11,12 but only by indirect measurements.On the other hand, computer simulations can in principle be used to directly calculate interactions at the nanobio interface, covering system sizes ∼1000 Å and time scales ∼1000 ns. These windows are highly relevant when modeling the nanobio interface, but outside the realm of quantum mechanics. This calls for "classical" models with atomistic or semiatomistic (atoms being grouped into effective interaction centers) representations in computer simulations of nanobio interactions, parametrized to reproduce properties relevant to the nanobio interface. Substantial effort has been invested during the last decades to develop classical molecular models for biomolecules (proteins, lipids, nucleic acids, carbohydrates, etc.), but there has been no comparable endeavor to include inorganic materials into the models. The state of classical models aimed to describe the nanobio interface remains underdeveloped, largely because of the difficulties involved with representing the electronic structure of the inorganic material by interacting point particles. The present work is an attempt to close this modeling gap by developing atomistic force field parameters for the TiO 2 −water interface. We use an automated algorithm that is extended to accept arbitrary experimental data as targets in the parameter fitting. The method can easily be generalized to develop force field parameters for other inorganic surfaces and biomolecules. In an accompanying paper, 13 we use the optimized force field parameters to address the other long-standing problem in nanobio simulationsaccurate sampling of biomolecules near inorganic surfacesand to compute binding free energies of amino acid side chain analogues and a peptide to the TiO 2 surface.T...