Interaction Energies in Complexes of Zn and Amino Acids: A Comparison of Ab Initio and Force Field Based Calculations

Zinc plays important roles in structural stabilization of proteins, enzyme catalysis, and signal transduction. Many Zn binding sites are located at the interface between the protein and the cellular fluid. In aqueous solutions, Zn ions adopt an octahedral coordination, while in proteins zinc can have different coordinations, with a tetrahedral conformation found most frequently. The dynamics of Zn binding to proteins and the formation of complexes that involve Zn are dictated by interactions between Zn and its binding partners. We calculated the interaction energies between Zn and its ligands in complexes that mimic protein binding sites and in Zn complexes of water and one or two amino acid moieties, using quantum mechanics (QM) and molecular mechanics (MM). It was found that MM calculations that neglect or only approximate polarizability did not reproduce even the relative order of the QM interaction energies in these complexes. Interaction energies calculated with the CHARMM-Drude polarizable force field agreed better with the ab initio results, although the deviations between QM and MM were still rather large (40–96 kcal/mol). In order to gain further insight into Zn–ligand interactions, the free energies of interaction were estimated by QM calculations with continuum solvent representation, and we performed energy decomposition analysis calculations to examine the characteristics of the different complexes. The ligand-types were found to have high impact on the relative strength of polarization and electrostatic interactions. Interestingly, ligand–ligand interactions did not play a significant role in the binding of Zn. Finally, analysis of ligand exchange energies suggests that carboxylates could be exchanged with water molecules, which explains the flexibility in Zn binding dynamics. An exchange between carboxylate (Asp/Glu) and imidazole (His) is less likely

Predicting Frequency from the External Chemical Environment: OH Vibrations on Hydrated and Hydroxylated Surfaces

Robust correlation curves are essential to decipher structural information from IR-vibrational spectra. However, for surface-adsorbed water and hydroxides, few such correlations have been presented in the literature. In this paper, OH vibrational frequencies are correlated against 12 structural descriptors representing the quantum mechanical or geometrical environment, focusing on those external to the vibrating molecule. A nonbiased fitting procedure based on Gaussian process regression (GPR) was used alongside simple analytical functional forms. The training data consist of 217 structurally unique OH groups from 38 water/metal oxide interface systems for MgO, CaO and CeO2, all optimized at the DFT level, and the fully anharmonic and uncoupled OH vibrational signatures were calculated. Among our results, we find the following: (i) The intermolecular R(H···O) hydrogen bond distance is particularly strong, indicating the primary cause of the frequency shift. (ii) Similarly, the electric field along the H-bond vector is also a good descriptor. (iii) Highly detailed machine learning descriptors (ACSF, SOAP) are less intuitive but were found to be more capable descriptors. (iv) Combinations of geometric and QM descriptors give the best predictions, supplying complementary information

Investigation of Vibrational Modes and Phonon Density of States in ZnO Quantum Dots

The ability to understand the phonon behavior in small metal oxide nanostructures and their surfaces is of great importance for thermal and microelectronic applications in successively smaller devices. Here the development of phonons in successively larger ZnO wurtzite quantum dots (QDs) is investigated. Raman spectroscopic measurements for particles from 3 to 11 nm reveal that the E₂ Raman active optical phonon at 436 cm^–1 is the first mode to be developed with a systematic increase with particle size. We also find a broad phonon band at 260–340 cm^–1, attributed to surface vibrations. The E₁-LO mode at 585 cm^–1 is the next to be developed while still being strongly suppressed in the confined particles. Other modes found in bulk ZnO are not developed for particles below 11 nm. Results from density functional theory showed an excellent agreement with the experimental molecular vibrations in the zinc acetate precursor and phonon modes in bulk ZnO. To elucidate the vibration behavior and phonon development in the ZnO QDs under nonzero temperature conditions and incorporating surface reconstruction, we performed reactive force field calculations. We show that the experimentally developed phonon modes in the QDs are the ones expected from dynamic theory. In particular, we show that the surface phonon modes in the very outermost surface (5 Å) can explain the observed broad phonon band and give the precise relation between the intensity of the surface and bulk phonons as the particle size increases. Calculations with temperatures between 50K and 1000K also show distinction of temperature effects in the material and that the phonon peaks are not generally shifted when the system is heated and quantum confined but instead reveal a dependence on the symmetry of the phonon mode

Band-Filling Correction Method for Accurate Adsorption Energy Calculations: A Cu/ZnO Case Study

We present a simple method, the “band-filling correction”, to calculate accurate adsorption energies (<i>E</i>_ads) in the low coverage limit from finite-size supercell slab calculations using DFT. We show that it is necessary to use such a correction if charge transfer takes place between the adsorbate and the substrate, resulting in the substrate bands either filling up or becoming depleted. With this correction scheme, we calculate <i>E</i>_ads of an isolated Cu atom adsorbed on the ZnO(101̅0) surface. Without the correction, the calculated <i>E</i>_ads is highly coverage-dependent, even for surface supercells that would typically be considered very large (in the range from 1 nm × 1 nm to 2.5 nm × 2.5 nm). The correction scheme works very well for semilocal functionals, where the corrected <i>E</i>_ads is converged within 0.01 eV for all coverages. The correction scheme also works well for hybrid functionals if a large supercell is used and the exact exchange interaction is screened

CO₂ Hydration Shell Structure and Transformation

The hydration-shell of CO₂ is characterized using Raman multivariate curve resolution (Raman-MCR) spectroscopy combined with <i>ab initio</i> molecular dynamics (AIMD) vibrational density of states simulations, to validate our assignment of the experimentally observed high-frequency OH band to a weak hydrogen bond between water and CO₂. Our results reveal that while the hydration-shell of CO₂ is highly tetrahedral, it is also occasionally disrupted by the presence of entropically stabilized defects associated with the CO₂-water hydrogen bond. Moreover, we find that the hydration-shell of CO₂ undergoes a temperature-dependent structural transformation to a highly disordered (less tetrahedral) structure, reminiscent of the transformation that takes place at higher temperatures around much larger oily molecules. The biological significance of the CO₂ hydration shell structural transformation is suggested by the fact that it takes place near physiological temperatures

Self-Consistent-Charge Density-Functional Tight-Binding (SCC-DFTB) Parameters for Ceria in 0D to 3D

Reducible oxides such as CeO₂ are challenging to describe with standard density-functional theory (DFT) due to the mixed valence states of the cations; they often require the use of non-standard correction schemes, and/or more computationally expensive methods. This adds a new layer of complexity when it comes to the generation of Slater–Koster tables and the corresponding repulsive potentials for self-consistent density-functional based tight-binding (SCC-DFTB) calculations of such materials. In this work, we provide guidelines for how to set up a parametrization scheme for mixed valence oxides within the SCC-DFTB framework, with a focus on reproducing structural and electronic properties as well as redox reaction energies calculated using a reference DFT method. This parametrization procedure was here used to generate parameters for Ce–O systems, with Ce in its +III or +IV formal oxidation states. The generated parameter set is validated by comparison with DFT calculations for various ceria (CeO₂) and reduced ceria (CeO_2–<i>x</i>) systems of different dimensionalities ranging from 0D (nanoparticles) to 3D (bulk). As oxygen vacancy defects in ceria are of crucial importance to many technological applications, special focus is directed toward the capability of describing such defects accurately

Indirect-to-Direct Band Gap Transition of Si Nanosheets: Effect of Biaxial Strain

The effect of biaxial strain on the band structure of two-dimensional silicon nanosheets (Si NSs) with (111), (110), and (001) exposed surfaces was investigated by means of density functional theory calculations. For all the considered Si NSs, an indirect-to-direct band gap transition occurs as the lateral dimensions of Si NSs increase; that is, increasing lateral biaxial strain from compressive to tensile always enhances the direct band gap characteristics. Further analysis revealed the mechanism of the transition which is caused by preferential shifts of the conduction band edge at a specific <i>k</i>-point because of their bond characteristics. Our results explain a photoluminescence result of the (111) Si NSs [U. Kim et al., <i>ACS Nano</i> <b>2011</b>, <i>5</i>, 2176–2181] in terms of the plausible tensile strain imposed in the unoxidized inner layer by surface oxidation

Evolutionary Monte Carlo of QM Properties in Chemical Space: Electrolyte Design

Optimizing a target function over the space of organic molecules is an important problem appearing in many fields of applied science but also a very difficult one due to the vast number of possible molecular systems. We propose an evolutionary Monte Carlo algorithm for solving such problems which is capable of straightforwardly tuning both exploration and exploitation characteristics of an optimization procedure while retaining favorable properties of genetic algorithms. The method, dubbed MOSAiCS (Metropolis Optimization by Sampling Adaptively in Chemical Space), is tested on problems related to optimizing components of battery electrolytes, namely, minimizing solvation energy in water or maximizing dipole moment while enforcing a lower bound on the HOMO–LUMO gap; optimization was carried out over sets of molecular graphs inspired by QM9 and Electrolyte Genome Project (EGP) data sets. MOSAiCS reliably generated molecular candidates with good target quantity values, which were in most cases better than the ones found in QM9 or EGP. While the optimization results presented in this work sometimes required up to 106 QM calculations and were thus feasible only thanks to computationally efficient ab initio approximations of properties of interest, we discuss possible strategies for accelerating MOSAiCS using machine learning approaches