Nanometallic glasses: size reduction brings ductility, surface state drives its extent.

We report tensile experiments on Ni80P20 metallic glass samples fabricated via a templated electroplating process and via focused ion beam milling, which differed only in their surface energy states: Ga-ion-irradiated and as-electroplated. Molecular dynamics simulations on similar Ni80Al20 systems corroborate the experimental results, which suggest that the transition from brittle to ductile behavior is driven by sample size, while the extent of ductility is driven by surface state.

Shock response of single crystal and nanocrystalline pentaerythritol tetranitrate: Implications to hotspot formation in energetic materials.

We investigate shock response of single crystal and nanocrystalline pentaerythritol tetranitrate (PETN) with a coarse-grained model and molecular dynamics simulations, as regards mechanical hotspot formation in the absence or presence of grain boundaries (GBs). Single crystals with different orientations, and columnar nanocrystalline PETN with regular hexagonal, irregular hexagonal, and random GB patterns, are subjected to shock loading at different shock strengths. In single crystals, shock-induced plasticity is consistent with resolved shear stress calculations and the steric hindrance model, and this deformation leads to local heating. For regular-shaped hexagonal columnar nanocrystalline PETN, different misorientation angles lead to activation of different/same slip systems, different deformation in individual grains and as a whole, different GB friction, different temperature distributions, and then, different hotspot characteristics. Compared to their regular-shaped hexagonal counterpart, nanocrystalline PETN with irregular hexagonal GB pattern and that with random GBs, show deformation and hotspot features specific to their GBs. Driven by stress concentration, hotspot formation is directly related to GB friction and GB-initiated crystal plasticity, and the exact deformation is dictated by grain orientations and resolved shear stresses. GB friction alone can induce hotspots, but the hotspot temperature can be enhanced if it is coupled with GB-initiated crystal plasticity, and the slip of GB atoms has components out of the GB plane. The magnitude of shearing can correlate well with temperature, but the slip direction of GB atoms relative to GBs may play a critical role. Wave propagation through varying microstructure may also induce differences in stress states (e.g., stress concentrations) and loading rates, and thus, local temperature rise. GB-related friction and plasticity induce local heating or mechanical hotspots, which could be precursors to chemical hotspot formation related to initiation in energetic materials, in the absence of other, likely more effective, means for hotspot formation such as void collapse.

Theoretical chemistry comes alive: full partner with experiment.

During the last decade, advances in computational techniques and in the extraction of chemically useful concepts from electronic wave functions have put theorists into the mainstream of chemistry. Some recent examples of the prediction of spectroscopic quantities and the elucidation of catalytic processes for homogeneous and heterogeneous reactions from theoretical calculations are used to illustrate how theory and experiment are now full partners in chemical research. It is expected that during the next decade the thrust of theoretical chemistry will be to combine the knowledge of fundamental chemical steps and fundamental interactions with advances in chemical dynamics and irreversible statistical mechanics and in computer technology to produce simulations of chemical systems with competing reactions taking place simultaneously at various reaction sites. The promise of such simulation is illustrated by a study of the enzyme thermolysin.

The magnon pairing mechanism of superconductivity in cuprate ceramics.

The magnon pairing mechanism is derived to explain the high-temperature superconductivity of both the La2-xSrxCu(1)O(4) and Y(1)Ba(2)Cu(3)O(7) systems. Critical features include (i) a one- or two-dimensional lattice of linear Cu-O-Cu bonds that contribute to large antiferromagnetic (superexchange) coupling of the Cu(II)(d(9)) orbitals; (ii) holes in the oxygen ppi bands [rather than Cu(III)(d(8))] leading to high mobility hole conduction; and (iii) strong ferromagnetic coupling between oxygen ppi holes and adjacent Cu(II)(d(9)) electrons. The ferromagnetic coupling of the conduction electrons with copper d spins induces the attractive interaction responsible for the superconductivity, leading to triplet-coupled pairs called "tripgems." The disordered Heisenberg lattice of antiferromagnetically coupled copper d spins serves a role analogous to the phonons in a conventional system. This leads to a maximum transition temperature of about 200 K. For La(1.85)Sr(0.15)Cu(1)O(4), the energy gap is in excellent agreement with experiment. For Y(1)Ba(2)Cu(3)O(7), we find that both the CuO sheets and the CuO chains can contribute to the supercurrent.

Electronic structure and valence-bond band structure of cuprate superconducting materials.

From ab initio calculations on various clusters representing the La2-xSrxCu(1)O(4) and Y(1)Ba(2)Cu(3)O(7) classes of high-temperature superconductors, it is shown that (i) all copper sites have a Cu(II)(d(9))oxidation state with one unpaired spin that is coupled antiferromagnetically to the spins of adjacent Cu(II) sites; (ii) oxidation beyond the cupric (Cu(II)) state leads not to Cu(III) but rather to oxidized oxygen atoms, with an oxygen ppi hole bridging two Cu(II) sites; (iii) the oxygen ppihole at these oxidized sites is ferromagnetically coupled to the adjacent Cu(II)d electrons despite the fact that this is opposed by the direct dd exchange; and (iv) the hopping of these oxygen ppi holes (in CuO sheets or chains) from site to site is responsible for the conductivity in these systems (N-electron band structures are reported for the migration of these localized charges).

Benzene forms hydrogen bonds with water.

Fully rotationally resolved spectra of three isotopic species of 1:1 clusters of benzene with water (H(2)O, D(2)O, and HDO) were fit to yield moments of inertia that demonstrate unambiguously that water is positioned above the benzene plane in nearly free internal rotation with both hydrogen atoms pointing toward the pi cloud. Ab initio calculations (MP2 level of electron correlation and 6-31 G(**) basis set with basis set superposition error corrections) predict a binding energy D(e) greater, similar 1.78 kilocalories per mole. In both the experimental and theoretical structures, water is situated nearly 1 angstrom within the van der Waals contacts of the monomers, a clear manifestation of hydrogen bond formation in this simple model of aqueous-pi electron interactions.

Predicting solid-state heats of formation of newly synthesized polynitrogen materials by using quantum mechanical calculations.

We present density functional theory level predictions and analysis of the basic properties of newly synthesized high-nitrogen compounds together with 3,6-bis(2H-tetrazol-5-yl)-1,2,4,5-tetrazine (BTT) and 3,3'-azobis(6-amino-1,2,4,5-tetrazine) (DAAT), for which experimental data are available. The newly synthesized high-nitrogen compounds are based on tricycle fused 1,2,4-triazine and 1,2,4,5-tetrazine heterocycles. In this work, the molecules BTT and DAAT have been studied in order to validate the theoretical approach and to facilitate further progress developments for the molecules of interest. Molecular structural properties are clarified, and IR spectra predictions are provided to help detection of those compounds in the experiment. The energy content of the molecules in the gas phase is evaluated by calculating standard enthalpies of formation, by using a special selection of isodesmic reaction paths. We also include estimates of the condensed-phase heats of formation and heats of sublimation in the framework of the Politzer approach. The obtained properties are consistent with those new high-nitrogen compounds being a promising set of advanced energetic materials.

Tensile Strength of Liquids: Equivalence of Temporal and Spatial Scales in Cavitation.

It is well known that strain rate and size effects are both important in material failure, but the relationships between them are poorly understood. To establish this connection, we carry out molecular dynamics (MD) simulations of cavitation in Lennard-Jones and Cu liquids over a very broad range of size and strain rate. These studies confirm that temporal and spatial scales play equivalent roles in the tensile strengths of these two liquids. Predictions based on smallest-scale MD simulations of Cu for larger temporal and spatial scales are consistent with independent simulations, and comparable to experiments on liquid metals. We analyze these results in terms of classical nucleation theory and show that the equivalence arises from the role of both size and strain rate in the nucleation of a daughter phase. Such equivalence is expected to hold for a wide range of materials and processes and to be useful as a predictive bridging tool in multiscale studies.

First principles prediction of protein folding rates.

Experimental studies have demonstrated that many small, single-domain proteins fold via simple two-state kinetics. We present a first principles approach for predicting these experimentally determined folding rates. Our approach is based on a nucleation-condensation folding mechanism, where the rate-limiting step is a random, diffusive search for the native tertiary topology. To estimate the rates of folding for various proteins via this mechanism, we first determine the probability of randomly sampling a conformation with the native fold topology. Next, we convert these probabilities into folding rates by estimating the rate that a protein samples different topologies during diffusive folding. This topology-sampling rate is calculated using the Einstein diffusion equation in conjunction with an experimentally determined intra-protein diffusion constant. We have applied our prediction method to the 21 topologically distinct small proteins for which two-state rate data is available. For the 18 beta-sheet and mixed alpha-beta native proteins, we predict folding rates within an average factor of 4, even though the experimental rates vary by a factor of approximately 4 x 10(4). Interestingly, the experimental folding rates for the three four-helix bundle proteins are significantly underestimated by this approach, suggesting that proteins with significant helical content may fold by a faster, alternative mechanism. This method can be applied to any protein for which the structure is known and hence can be used to predict the folding rates of many proteins prior to experiment.

Substrate assistance in the mechanism of family 18 chitinases: theoretical studies of potential intermediates and inhibitors.

Based on first principles and molecular mechanics calculations, we conclude that the mechanism of hevamine (a family 18 chitinase) involves an oxazoline ion intermediate stabilized by the neighboring C2' acetamido group. In this intermediate, the acetamido carbonyl oxygen atom forms a covalent bond to C1' of N-acetyl-glucosamine and has a transferred positive charge from the pyranose ring onto the acetamido nitrogen atom, leading to an anchimeric stabilization of 38.1 kcal/mol when docked with hevamine. This double displacement mechanism involving an oxazoline intermediate distinguishes the family 18 chitinase (which have one acidic residue near the active site) from family 19 chitinase and from hen egg-white lysozyme, which have two acidic residues near the active site. The structural and electronic properties of the oxazoline intermediate are similar to the known chitinase inhibitor allosamidin, suggesting that allosamidins act as transition state analogs of an oxazoline intermediate. Structural and electronic features of the oxazoline ion likely to be important in the design of new chitinase inhibitors are discussed.

Building proteins from C alpha coordinates using the dihedral probability grid Monte Carlo method.

Dihedral probability grid Monte Carlo (DPG-MC) is a general-purpose method of conformational sampling that can be applied to many problems in peptide and protein modeling. Here we present the DPG-MC method and apply it to predicting complete protein structures from C alpha coordinates. This is useful in such endeavors as homology modeling, protein structure prediction from lattice simulations, or fitting protein structures to X-ray crystallographic data. It also serves as an example of how DPG-MC can be applied to systems with geometric constraints. The conformational propensities for individual residues are used to guide conformational searches as the protein is built from the amino-terminus to the carboxyl-terminus. Results for a number of proteins show that both the backbone and side chain can be accurately modeled using DPG-MC. Backbone atoms are generally predicted with RMS errors of about 0.5 A (compared to X-ray crystal structure coordinates) and all atoms are predicted to an RMS error of 1.7 A or better.

Prediction of polyelectrolyte polypeptide structures using Monte Carlo conformational search methods with implicit solvation modeling.

Many interesting proteins possess defined sequence stretches containing negatively charged amino acids. At present, experimental methods (X-ray crystallography, NMR) have failed to provide structural data for many of these sequence domains. We have applied the dihedral probability grid-Monte Carlo (DPG-MC) conformational search algorithm to a series of N- and C-capped polyelectrolyte peptides, (Glu)20, (Asp)20, (PSer)20, and (PSer-Asp)10, that represent polyanionic regions in a number of important proteins, such as parathymosin, calsequestrin, the sodium channel protein, and the acidic biomineralization proteins. The atomic charges were estimated from charge equilibration and the valence and van der Waals parameters are from DREIDING. Solvation of the carboxylate and phosphate groups was treated using sodium counterions for each charged side chain (one Na+ for COO-; two Na for CO(PO3)-2) plus a distance-dependent (shielded) dielectric constant, epsilon = epsilon 0 R, to simulate solvent water. The structures of these polyelectrolyte polypeptides were obtained by the DPG-MC conformational search with epsilon 0 = 10, followed by calculation of solvation energies for the lowest energy conformers using the protein dipole-Langevin dipole method of Warshel. These calculations predict a correlation between amino acid sequence and global folded conformational minima: 1. Poly-L-Glu20, our structural benchmark, exhibited a preference for right-handed alpha-helix (47% helicity), which approximates experimental observations of 55-60% helicity in solution. 2. For Asp- and PSer-containing sequences, all conformers exhibited a low preference for right-handed alpha-helix formation (< or = 10%), but a significant percentage (approximately 20% or greater) of beta-strand and beta-turn dihedrals were found in all three sequence cases: (1) Aspn forms supercoil conformers, with a 2:1:1 ratio of beta-turn:beta-strand:alpha-helix dihedral angles; (2) PSer20 features a nearly 1:1 ratio of beta-turn:beta-sheet dihedral preferences, with very little preference for alpha-helical structure, and possesses short regions of strand and turn combinations that give rise to a collapsed bend or hairpin structure; (3) (PSer-Asp)10 features a 3:2:1 ratio of beta-sheet:beta-turn:alpha-helix and gives rise to a superturn or C-shaped structure.

De novo prediction of polypeptide conformations using dihedral probability grid Monte Carlo methodology.

We tested the dihedral probability grid Monte Carlo (DPG-MC) methodology to determine optimal conformations of polypeptides by applying it to predict the low energy ensemble for two peptides whose solution NMR structures are known: integrin receptor peptide (YGRGDSP, Type II beta-turn) and S3 alpha-helical peptide (YMSEDEL KAAEAAFKRHGPT). DPG-MC involves importance sampling, local random stepping in the vicinity of a current local minima, and Metropolis sampling criteria for acceptance or rejection of new structures. Internal coordinate values are based on side-chain-specific dihedral angle probability distributions (from analysis of high-resolution protein crystal structures). Important features of DPG-MC are: (1) Each DPG-MC step selects the torsion angles (phi, psi, chi) from a discrete grid that are then applied directly to the structure. The torsion angle increments can be taken as S = 60, 30, 15, 10, or 5 degrees, depending on the application. (2) DPG-MC utilizes a temperature-dependent probability function (P) in conjunction with Metropolis sampling to accept or reject new structures. For each peptide, we found close agreement with the known structure for the low energy conformational ensemble located with DPG-MC. This suggests that DPG-MC will be useful for predicting conformations of other polypeptides.

Effects of pressure on the structure of metmyoglobin: molecular dynamics predictions for pressure unfolding through a molten globule intermediate.

We investigated the pathway for pressure unfolding of metmyoglobin using molecular dynamics (MD) for a range of pressures (0.1 MPa to 1.2 GPa) and a temperature of 300 K. We find that the unfolding of metmyoglobin proceeds via a two-step mechanism native --> molten globule intermediate --> unfolded, where the molten globule forms at 700 MPa. The simulation describes qualitatively the experimental behavior of metmyoglobin under pressure. We find that unfolding of the alpha-helices follows the sequence of migrating hydrogen bonds (i,i + 4) --> (i,i + 2).

Theoretical studies of oxygen binding.

We discussed the bonding of O2 to hemoglobin using results of ab initio calculations of idealized portions of the Hb molecule. The bond between Fe and O2 is formed by coupling a triplet state (intermediate spin state) of Fe to the triplet ground state of O2 (analogous to the bonding of O to O2 in ozone). The coordination sphere of the Fe reduces the energy separation between the quintet, triplet, and singlet states, making an intermediate spin state accessible for bond formation. This provides the mechanism by which an O2 molecule can easily and reversibly bind to Hb. Neither the diamagnetic (t2g) excited state of Fe nor the excited singlet state of O2 play a role in the formation of the FeO2 bond. We also discussed the role of the Fe intra-atomic exchange terms and show how they serve to store electronic energy upon bond formation. An example was given, illustrating how this stored electronic energy can then be used to drive enzymatic reactions. Metal atoms such as ferrous Fe are capable of existing in several distinct electronic configurations, depending upon the ligands. Our objective here has been to illustrate the different characteristics of these Fe configurations and to indicate why various axial ligands stabilize particular Fe configurations. In addition, we have sketched the type of orbital descriptions arising from theoretical wavefunctions and illustrated how to use these descriptions to predict chemical phenomena.

Direct MD Simulations of Terahertz Absorption and 2D Spectroscopy Applied to Explosive Crystals.

A direct molecular dynamics simulation of the THz spectrum of a molecular crystal is presented. A time-dependent electric field is added to a molecular dynamics simulation of a crystal slab. The absorption spectrum is composed from the energy dissipated calculated from a series of applied pulses characterized by a carrier frequency. The spectrum of crystalline cyclotrimethylenetrinitramine (RDX) and triacetone triperoxide (TATP) were simulated with the ReaxFF force field. The proposed direct method avoids the linear response and harmonic approximations. A multidimensional extension of the spectroscopy is suggested and simulated based on the nonlinear response to a single polarized pulse of radiation in the perpendicular polarization direction.

Computational modeling of structure-function of g protein-coupled receptors with applications for drug design.

G protein-coupled receptors (GPCRs) mediate senses such as odor, taste, vision, and pain in mammals. In addition, important cell recognition and communication processes often involve GPCRs. Many diseases involve malfunction of GPCRs, making them important targets for drug development. Indeed, greater than 50 % of all marketed therapeutics act on those receptors. Unfortunately, the atomic-level structures are only available for rhodopsin, beta2AR, beta1AR, A2A adenosin and opsin. In silico computational methods, employing receptor-based modeling, offer a rational approach in the design of drugs targeting GPCRs. These approaches can be used to understand receptor selectivity and species specificity of drugs that interact with GPCRs. This review gives an overview of current computational approaches to GPCR model building; ligand-receptor interaction for drug design; and molecular mechanism of GPCR activation from simulation.

Quantum Chemical Calculations of the Influence of Anchor-Cum-Spacer Groups on Femtosecond Electron Transfer Times in Dye-Sensitized Semiconductor Nanocrystals.

Electronic properties of dye-sensitized semiconductor nanocrystals, consisting of perylene (Pe) chromophores attached to 2 nm TiO2 nanocrystals via different anchor-cum-spacer groups, have been studied theoretically using density functional theory (DFT) cluster calculations. Approximate effective electronic coupling strengths for the heterogeneous electron-transfer interaction have been extracted from the calculated electronic structures and are used to estimate femtosecond electron-transfer times theoretically. Results are presented for perylenes attached to the TiO2 via formic acid (Pe-COOH), propionic acid (Pe-CH2-CH2-COOH), and acrylic acid (Pe-CH [Formula: see text] CH-COOH). The calculated electron transfer times are between 5 and 10 fs with the formic acid and the conjugated acrylic acid bridges and about 35 fs with the saturated propionic acid bridge. The calculated electron injection times are of the same order of magnitude as the corresponding experimental values and qualitatively follow the experimental trend with respect to the influence of the different substitutions on the injection times.

The pentamer channel stiffening model for drug action on human rhinovirus HRV-1A.

Development of effective drugs against the rhinovirus (HRV) responsible for the common cold remains a challenge because there are over 100 serotypes. This process could be significantly aided by an understanding of the atomistic mechanism by which such drugs work. We suggest that the most effective drugs against HRV-1A act by stiffening the pentamer channel of the viral coat through which the RNA is released, preventing the steps leading to uncoating. Using molecular dynamics methods we tested this Pentamer Channel Stiffening Model (PCSM) by examining the changes in strain energy associated with opening the pentamer channel through which the RNA is released. We find that the PCSM strain correlates well with the effectiveness of the WIN (Sterling-Winthrop) drugs for HRV-1A. To illustrate the use of the PCSM to predict new drugs and to prioritize experimental tests, we tested three modifications of the WIN drugs that are predicted to be nearly as effective (for HRV-1A) as the best current drug.