Buried Atoms Research Articles

Visualizing Surface-Subsurface Cu Atom Exchange at the FeO/Pt(111) Surface Induced by CO Adsorption at 150 K.

Structural evolution of solid catalyst surfaces induced by direct exposure to reaction gas has been extensively studied and is well understood. However, whether and how subsurface atomic structures are affected by the reaction atmosphere require further exploration. In this work, our results confirm that Cu clusters supported on FeO/Pt(111) (Cun/FeO/Pt) transform into surface CuCO complexes (CuCO/FeO/Pt) with exposure to CO at 78 K. Surprisingly, Cu clusters on Pt(111) buried under monolayer FeO film (FeO/Cun/Pt) can also transform into surface CuCO complexes on FeO/Pt(111) upon CO adsorption at 150 K. The place exchange of surface and subsurface Cu atoms at the FeO/Pt(111) surface can be mediated by exposing to CO at 150 K and keeping in ultrahigh vacuum at 300 K, alternatively. Calculation results reveal that CO adsorption induces restructuring of the FeO film above the Cu clusters, generating a diffusion channel for Cu atoms to pass through the FeO film and form surface CuCO, while Cu atoms remaining at the FeO-Pt interface are more thermodynamically favored without CO. Our work suggests that buried subsurface atoms may be involved in strong restructuring processes driven by reaction gas, which could strongly influence the catalytic performance.

Development of a Fluctuating Charge Model for Zinc-Containing Metalloproteins.

Metalloproteins widely exist in biology and play important roles in various processes. To accurately simulate metalloprotein systems, modeling polarization and charge transfer effects is vital. The fluctuating charge (FQ) model can efficiently generate atomic charges and simulate the charge transfer effect; it has been developed for a wide range of applications, but few models have been specifically tailored for metalloproteins. In this study, we present a fluctuating charge model specifically for zinc-containing metalloproteins based on the extended charge equilibration (EQeq) scheme. Our model was parametrized to reproduce CM5 charges instead of RESP/CHELPG charges because the former is less dependent on the conformation or basis set, does not suffer from unphysical charges for buried atoms, and is still being able to well reproduce the molecular dipoles. During our study, we found that adding the Pauling-bond-order-like term (referred to as the "+C term" in a previous study) between the zinc ion and ligating atoms significantly improves the model's performance. Although our model was trained for four-coordinated zinc sites only, our results indicated it can well describe the atomic charges in diverse zinc sites. Morever, our model was used to generate partial charges for the metal sites in three different zinc-containing metalloproteins (with four-, five-, and six-coordinated metal sites, respectively). These charges exhibited performance comparable to that of the RESP charges in molecular dynamics (MD) simulations. Additional tests indicated our model could also well reproduce the CM5 charges when geometric changes were involved. Those results indicate that our model can efficiently calculate the atomic charges for metal sites and well simulate the charge transfer effect, which marks an important step toward developing versatile polarizable force fields for metalloproteins.

A study on the approximated angular averaging of distribution functions obtained from the Ornstein–Zernike theory for diatomic solutes consisting of fused Lennard-Jones particles immersed in a Lennard–Jones monatomic solvent

We propose an approximate method to obtain an angular averaged distribution function around an atom of a diatomic solute molecule consisting of fused Lennard–Jones (LJ) particles solvated in an LJ monatomic solvent. Our method employs the Ornstein–Zernike and closure equations for the correlation function between a single-centered solute and solvent by assuming spherical symmetry for the potential interaction. In setting the potential along the radial direction, the interaction between the solvent and solute atom that is covalently bonded to the atom located at the origin is also considered, as is typical in interaction site models. The proposed method accurately describes the angular averaged distribution function between a solvent and a solute atom that is completely buried inside the other atom in the solute, where the term “buried” indicates that the sum of the radius of one atom and the bond length is less than the radius of the other atom. The obtained angular-dependent one-dimensional distribution function is also reasonable for buried solute atoms. Thus, the proposed method is superior to the reference interaction site model (RISM) theory. However, our method failed to correctly describe the distribution function for an unburied atom of the solute, for which the RISM theory would be better than the proposed method. Furthermore, we demonstrated that sigma enlarging bridge (SEB) correction [T. Miyata, Bull. Chem. Soc. Japan, 90 (2017) 1095] is applicable to the proposed method. The combination of the method proposed in this study and SEB correction improves both the first rising region of the angular averaged distribution function and the solvation free energy.

Combining Alchemical Transformation with a Physical Pathway to Accelerate Absolute Binding Free Energy Calculations of Charged Ligands to Enclosed Binding Sites.

We present a new approach to more accurately and efficiently compute the absolute binding free energy for receptor-ligand complexes. Currently, the double decoupling method (DDM) and the potential of mean force method (PMF) are widely used to compute the absolute binding free energy of biomolecular complexes. DDM relies on alchemically decoupling the ligand from its environments, which can be computationally challenging for large ligands and charged ligands because of the large magnitude of the decoupling free energies involved. In contrast, the PMF method uses a physical pathway to directly transfer the ligand from solution to the receptor binding pocket and thus avoids some of the aforementioned problems in DDM. However, the PMF method has its own drawbacks: because of its reliance on a ligand binding/unbinding pathway that is free of steric obstructions from the receptor atoms, the method has difficulty treating ligands with buried atoms. To overcome the limitation in the standard PMF approach and enable buried ligands to be treated, here we develop a new method called AlchemPMF in which steric obstructions along the physical pathway for binding are alchemically removed. We have tested the new approach on two important drug targets involving charged ligands. One is HIV-1 integrase bound to an allosteric inhibitor; the other is the human telomeric DNA G-quadruplex in complex with a natural product protoberberine buried in the binding pocket. For both systems, the new approach leads to more reliable estimates of absolute binding free energies with smaller error bars and closer agreements with experiments compared with those obtained from the existing methods, demonstrating the effectiveness of the new method in overcoming the hysteresis often encountered in PMF binding free energy calculations of such systems. The new approach could also be used to improve the sampling of water equilibration and resolvation of the binding pocket as the ligand is extracted.

Ag surface segregation in nanoporous Au catalysts during CO oxidation

The present study focuses on the modification of surface compositional profiles induced in nanoporous (NP) Au catalysts by the catalytic oxidation of carbon monoxide to carbon dioxide in the presence of oxygen. The phenomenon has deep implications concerning the catalytic behavior of NP Au foams in particular, and more in general for the design of more efficient catalysts. Aimed at gaining deeper insight into the mechanisms governing surface segregation, we exposed NP Au foams containing residual Ag to a mixture of gaseous carbon monoxide and oxygen at different temperature. Structural and surface composition analyses pointed out the concomitant occurrence of both NP Au coarsening and Ag surface segregation processes. Experimental findings suggest for Ag surface segregation a two-stage kinetics. During the initial, rapid coarsening of the NP Au structure, Ag surface segregation is mediated by surface rearrangements, which allow the Ag atoms to reach the surface at anomalously fast rate. As coarsening decelerates, the slower diffusion of buried Ag atoms towards the surface predominates, due to favorable chemical interactions with adsorbed oxygen. This novel mechanism’s understanding can benefit strategic areas of science and technology.

Publisher's Note: Visualizing buried silicon atoms at the Cd-Si(111)- 7×7 interface with localized electrons [Phys. Rev. B 96, 125410 (2017)

Publisher's Note: Visualizing buried silicon atoms at the Cd-Si(111)- <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>7</mml:mn><mml:mo>×</mml:mo><mml:mn>7</mml:mn></mml:mrow></mml:math> interface with localized electrons [Phys. Rev. B 96, 125410 (2017)

Co diffusion in the near-surface region of Cu

We present our experimental and theoretical study on Co diffusion in the first few atomic layers of Cu(001). While the diffusion of Co atoms in Cu(001) is usually expected to be intense at a temperature $T\ensuremath{\ge}800$ K, in the vicinity of the surface, it is already activated at a considerably lower temperature $T\ensuremath{\sim}650$ K whereas the diffusion in the deep bulk region is still inhibited. This intense near-surface diffusion provides an accumulation of Co atoms in the first six atomic layers upon a single stage Co deposition. The details of the near-surface diffusion are studied by analyzing the distribution of the location depth of the buried single Co atoms. The depth of location of single Co atoms is deduced from scanning tunneling microscopy (STM) data. The subsurface Co atoms induce a perturbation of the electron density of states of the surface which is observable as apparent ringlike ripples in the STM images of the atomically flat Cu surface. The depth of location of the buried Co atoms is determined from the diameter of those rings. The largest amount of Co atoms is found to be in the third layer, emphasizing that the near-surface diffusion should be described by diffusion parameters different from those for bulk diffusion. A model that describes the embedding process of Co atoms into Cu(001) layers is developed. The model assumes Co atoms to diffuse via the vacancy and ring-exchange mechanisms. The energy barriers for the interlayer Co diffusion via those mechanisms are calculated using the nudged elastic band method. The model satisfactorily explains the experimental results. Our study reveals that the energy barriers for Co diffusion in the first five atomic layers of Cu(001) are lower than those in the bulk. This defines the region in which Co diffusion should be considered as a near-surface one.

CX, DPX, and PCW: Web Servers for the Visualization of Interior and Protruding Regions of Protein Structures in 3D and 1D.

The CX and DPX web-based servers at http://pongor.itk.ppke.hu/bioinfoservices are dedicated to the analysis of protein 3D structures submitted by the users as Protein Data Bank (PDB) files. CX computes an atomic protrusion index, cx that makes it possible to highlight the protruding atoms within a protein 3D structure. DPX calculates a depth index, dpx for buried atoms, and allows one to visualize the distribution of buried residues. CX and DPX visualize 3D structures colored according to the calculated indices and return PDB files that can be visualized using standard programs. A combined server site, the Protein Core Workbench allows visualization of dpx, cx, solvent-accessible area as well as the number of atomic contacts as 3D plots and 1D sequence plots. Online visualization of the 3D structures and 1D sequence plots are available in all three servers. Mirror sites are available at http://hydra.icgeb.trieste.it/protein/ .

Adapting the semi-explicit assembly solvation model for estimating water-cyclohexane partitioning with the SAMPL5 molecules.

We describe here some tests we made in the SAMPL5 communal event of 'Semi-Explicit Assembly' (SEA), a recent method for computing solvation free energies. We combined the prospective tests of SAMPL5 with followup retrospective calculations, to improve two technical aspects of the field variant of SEA. First, SEA uses an approximate analytical surface around the solute on which a water potential is computed. We have improved and simplified the mathematical model of that surface. Second, some of the solutes in SAMPL5 were large enough to need a way to treat solvating waters interacting with 'buried atoms', i.e. interior atoms of the solute. We improved SEA with a buried-atom correction. We also compare SEA to Thermodynamic Integration molecular dynamics simulations, so that we can sort out force field errors.

Partial Charges in Periodic Systems: Improving Electrostatic Potential (ESP) Fitting via Total Dipole Fluctuations and Multiframe Approaches.

Two major improvements to the state-of-the-art Repeating Electrostatic Potential Extracted Atomic (REPEAT) method, for generating accurate partial charges for molecular simulations of periodic structures, are here developed. The first, D-REPEAT, consists in the simultaneous fit of the electrostatic potential (ESP), together with the total dipole fluctuations (TDF) of the framework. The second, M-REPEAT, allows the fit of multiple ESP configurations at once. When both techniques are fused into one, DM-REPEAT method, the resulting charges become remarkably stable over a large set of fitting regions, giving a robust and physically sound solution to the buried atoms problem. The method capabilities are extensively studied in ZIF-8 framework, and subsequently applied to IRMOF-1 and ITQ-29 crystal structures. To our knowledge, this is the first time that this approach is proposed in the context of periodic systems.

Structure and function of water molecules buried in the protein core.

Although the formation of the apolar core is crucial for protein folding, protein interior is often packed sub-optimally and incorporates water molecules that leave the bulk solvent. On average, one buried water molecules is observed every 20-90 amino acids, depending on the protein dimension and structural class: more buried water molecules are observed in large proteins and less in alpha proteins. >From a structural perspective, it was shown that buried water molecules tend to be as rigid as buried protein atoms, incline to form hydrogen bonds with backbone residues of loops, and often are in contact with other buried water molecules. From a functional perspective, buried water molecules have a stabilizing effect by filling internal cavities and by interacting with polar atoms buried in the protein core and may also act as lubricants to favor loop dynamics. Their exchange kinetics with the bulk solvent is quite variable, ranging from few tens of nanoseconds to few tens of milliseconds.

Genetic algorithm optimization of point charges in force field development: challenges and insights.

Evolutionary methods, such as genetic algorithms (GAs), provide powerful tools for optimization of the force field parameters, especially in the case of simultaneous fitting of the force field terms against extensive reference data. However, GA fitting of the nonbonded interaction parameters that includes point charges has not been explored in the literature, likely due to numerous difficulties with even a simpler problem of the least-squares fitting of the atomic point charges against a reference molecular electrostatic potential (MEP), which often demonstrates an unusually high variation of the fitted charges on buried atoms. Here, we examine the performance of the GA approach for the least-squares MEP point charge fitting, and show that the GA optimizations suffer from a magnified version of the classical buried atom effect, producing highly scattered yet correlated solutions. This effect can be understood in terms of the linearly independent, natural coordinates of the MEP fitting problem defined by the eigenvectors of the least-squares sum Hessian matrix, which are also equivalent to the eigenvectors of the covariance matrix evaluated for the scattered GA solutions. GAs quickly converge with respect to the high-curvature coordinates defined by the eigenvectors related to the leading terms of the multipole expansion, but have difficulty converging with respect to the low-curvature coordinates that mostly depend on the buried atom charges. The performance of the evolutionary techniques dramatically improves when the point charge optimization is performed using the Hessian or covariance matrix eigenvectors, an approach with a significant potential for the evolutionary optimization of the fixed-charge biomolecular force fields.

Expanding the Scope of Density Derived Electrostatic and Chemical Charge Partitioning to Thousands of Atoms.

The density derived electrostatic and chemical (DDEC/c3) method is implemented into the onetep program to compute net atomic charges (NACs), as well as higher-order atomic multipole moments, of molecules, dense solids, nanoclusters, liquids, and biomolecules using linear-scaling density functional theory (DFT) in a distributed memory parallel computing environment. For a >1000 atom model of the oxygenated myoglobin protein, the DDEC/c3 net charge of the adsorbed oxygen molecule is approximately -1e (in agreement with the Weiss model) using a dynamical mean field theory treatment of the iron atom, but much smaller in magnitude when using the generalized gradient approximation. For GaAs semiconducting nanorods, the system dipole moment using the DDEC/c3 NACs is about 5% higher in magnitude than the dipole computed directly from the quantum mechanical electron density distribution, and the DDEC/c3 NACs reproduce the electrostatic potential to within approximately 0.1 V on the nanorod's solvent-accessible surface. As examples of conducting materials, we study (i) a 55-atom Pt cluster with an adsorbed CO molecule and (ii) the dense solids Mo2C and Pd3V. Our results for solid Mo2C and Pd3V confirm the necessity of a constraint enforcing exponentially decaying electron density in the tails of buried atoms.

Specific Non-Local Interactions Are Not Necessary for Recovering Native Protein Dynamics

The elastic network model (ENM) is a widely used method to study native protein dynamics by normal mode analysis (NMA). In ENM we need information about all pairwise distances, and the distance between contacting atoms is restrained to the native value. Therefore ENM requires O(N2) information to realize its dynamics for a protein consisting of N amino acid residues. To see if (or to what extent) such a large amount of specific structural information is required to realize native protein dynamics, here we introduce a novel model based on only O(N) restraints. This model, named the ‘contact number diffusion’ model (CND), includes specific distance restraints for only local (along the amino acid sequence) atom pairs, and semi-specific non-local restraints imposed on each atom, rather than atom pairs. The semi-specific non-local restraints are defined in terms of the non-local contact numbers of atoms. The CND model exhibits the dynamic characteristics comparable to ENM and more correlated with the explicit-solvent molecular dynamics simulation than ENM. Moreover, unrealistic surface fluctuations often observed in ENM were suppressed in CND. On the other hand, in some ligand-bound structures CND showed larger fluctuations of buried protein atoms interacting with the ligand compared to ENM. In addition, fluctuations from CND and ENM show comparable correlations with the experimental B-factor. Although there are some indications of the importance of some specific non-local interactions, the semi-specific non-local interactions are mostly sufficient for reproducing the native protein dynamics.

Deriving Static Atomic Multipoles from the Electrostatic Potential

The description of molecular systems using multipolar electrostatics calls for automated methods to fit the necessary parameters. In this paper, we describe an open-source software package that allows fitting atomic multipoles (MTPs) from the ab initio electrostatic potential by adequate atom typing and judicious assignment of the local axis system. By enabling the simultaneous fit of several molecules and/or conformations, the package addresses issues of parameter transferability and lack of sampling for buried atoms. We illustrate the method by studying a series of small alcohol molecules, as well as various conformations of protonated butylamine.

Atomic-Scale Identification of Individual Lanthanide Dopants in Optical Glass Fiber

Various dopants are added in commercially available optical glass fibers. The specific atomic species and charge state of lanthanide dopants are known to significantly influence the fiber's optical properties. For understanding the role of dopants on the optical properties, atomic-scale identification of the lanthanide dopants in the optical fiber is crucial. Aberration-corrected scanning transmission electron microscopy (STEM) is especially powerful for visualizing individual atoms of heavy elements buried in a matrix composed of light elements. Here, we apply aberration-corrected high-angle annular dark field (HAADF)-STEM to directly visualize individual erbium (Er) dopants buried in the optical glass fiber. Molecular dynamics and image simulations are used to interpret the experimental images and draw quantitative conclusions. The visibility of the buried Er atoms in the amorphous glass is strongly dependent on the defocus and specimen thickness, and only Er atoms in very thin regions can be reliably identified.

Reduced and quenched polarizabilities of interior atoms in molecules

Polarizability is a key molecular property controlling induction and dispersion forces in molecules, and atomic polarizabilities in molecules are widely used elements both in qualitative schemes for understanding molecular interactions and in quantitative methods for modeling them. Unfortunately, experimental probes of local polarizability are not readily available. Here we predict the polarizability of individual atoms and functional groups in a variety of systems, and we draw both general and specific conclusions with broad consequences. We find that the polarizability of the same functional group (e.g., the carbonyl group) can differ substantially, depending on the position of this group in a molecule (e.g., in a protein). More specifically, we find that the polarizability of buried atoms and groups is screened and thereby diminished; thus the outermost atoms and functional groups (for example, those lying closer to the molecular van der Waals surface) are more polarizable than buried ones, even when acted on by the same electric field. These findings mitigate against attributing isolated system behavior to molecular fragments since their polarizability depends on their environment, and the methods used here provide a way to probe molecular polarizability with a finer grain than has previously been possible.

Voronoia4RNA—a database of atomic packing densities of RNA structures and their complexes

Voronoia4RNA (http://proteinformatics.charite.de/voronoia4rna/) is a structural database storing precalculated atomic volumes, atomic packing densities (PDs) and coordinates of internal cavities for currently 1869 RNAs and RNA–protein complexes. Atomic PDs are a measure for van der Waals interactions. Regions of low PD, containing water-sized internal cavities, refer to local structure flexibility or compressibility. RNA molecules build up the skeleton of large molecular machineries such as ribosomes or form smaller flexible structures such as riboswitches. The wealth of structural data on RNAs and their complexes allows setting up representative data sets and analysis of their structural features. We calculated atomic PDs from atomic volumes determined by the Voronoi cell method and internal cavities analytically by Delaunay triangulation. Reference internal PD values were derived from a non-redundant sub-data set of buried atoms. Comparison of internal PD values shows that RNA is more tightly packed than proteins. Finally, the relation between structure size, resolution and internal PD of the Voronoia4RNA entries is discussed. RNA, protein structures and their complexes can be visualized by the Jmol-based viewer Provi. Variations in PD are depicted by a color code. Internal cavities are represented by their molecular boundaries or schematically as balls.

Charge Model 5: An Extension of Hirshfeld Population Analysis for the Accurate Description of Molecular Interactions in Gaseous and Condensed Phases

We propose a novel approach to deriving partial atomic charges from population analysis. The new model, called Charge Model 5 (CM5), yields class IV partial atomic charges by mapping from those obtained by Hirshfeld population analysis of density functional electronic charge distributions. The CM5 model utilizes a single set of parameters derived by fitting to reference values of the gas-phase dipole moments of 614 molecular structures. An additional test set (not included in the CM5 parametrization) contained 107 singly charged ions with nonzero dipole moments, calculated from the accurate electronic charge density, with respect to the center of nuclear charges. The CM5 model is applicable to any charged or uncharged molecule composed of any element of the periodic table in the gas phase or in solution. The CM5 model predicts dipole moments for the tested molecules that are more accurate on average than those from the original Hirshfeld method or from many other popular schemes including atomic polar tensor and Löwdin, Mulliken, and natural population analyses. In addition, the CM5 charge model is essentially independent of a basis set. It can be used with larger basis sets, and thereby this model significantly improves on our previous charge models CMx (x = 1-4 or 4M) and other methods that are prone to basis set sensitivity. CM5 partial atomic charges are less conformationally dependent than those derived from electrostatic potentials. The CM5 model does not suffer from ill conditioning for buried atoms in larger molecules, as electrostatic fitting schemes sometimes do. The CM5 model can be used with any level of electronic structure theory (Hartree-Fock, post-Hartree-Fock, and other wave function correlated methods or density functional theory) as long as an accurate electronic charge distribution and a Hirshfeld analysis can be computed for that level of theory.

Buried Pd slows self-diffusion on Cu(001)

Using low-energy electron microscopy, we determine that self-diffusion of the Cu(001) surface is slowed by the presence of a $c$($2\ifmmode\times\else\texttimes\fi{}2$)-Pd buried surface alloy. We probe surface diffusion using Cu-adatom island-ripening measurements. On alloyed surfaces, the island decay rate decreases monotonically as the Pd concentration is increased up to $\ensuremath{\sim}$0.5 monolayer (ML), where the $2\ifmmode\times\else\texttimes\fi{}2$ buried alloy is Pd saturated. We propose that the Pd slows island ripening by inhibiting the diffusion of surface vacancies across terraces. For dilute alloys ($\ensuremath{\lesssim}$0.2-ML Pd), this conclusion is supported by density-functional theory calculations, which show that surface vacancies migrate more slowly owing to an attraction to isolated buried Pd atoms. The results illustrate a fundamental mechanism by which even a dilute alloy thin-film coating may act to inhibit surface-diffusion-mediated processes, such as electromigration.